To see the other types of publications on this topic, follow the link: Information networks Information services Human information processing.
Journal articles on the topic 'Information networks Information services Human information processing'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Information networks Information services Human information processing.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Alwateer, M., S. W. Loke, and A. M. Zuchowicz. "Drone services: issues in drones for location-based services from human-drone interaction to information processing." Journal of Location Based Services 13, no. 2 (January 16, 2019): 94–127. http://dx.doi.org/10.1080/17489725.2018.1564845.
Full text
2
Streimikis, Justas, Liudmila Kortenko, Marina Panova, and Mikhail Voronov. "Development of a smart city information system." E3S Web of Conferences 301 (2021): 05002. http://dx.doi.org/10.1051/e3sconf/202130105002.
Full textAbstract:
This paper is centred around the development of a smart city information system. Smart cities use the framework of information and communications technologies to create, deploy and promote practices that address urban challenges and create, connect and enable sustainable infrastructure. This definition focuses on network deployment, transport, ICT investment, human and social capital to support sustainable community goals and quality of life by involving users of certain technologies and community-based applications in social participation. In this paper, we show that a multi-disciplinary approach is needed to address these issues, combining expertise from distributed systems, software and services engineering, network and data management and processing, crowdsourcing, sensor and update methods, social computing, as well as the collective intelligence.
3
Chen, Huanzhao, and Guohui Tian. "A Computing Model of Selective Attention for Service Robot Based on Spatial Data Fusion." Journal of Robotics 2018 (July 2, 2018): 1–9. http://dx.doi.org/10.1155/2018/5368624.
Full textAbstract:
Robots and humans are facing the same problem: they all need to face a lot of perceptual information and choose valuable information. Before the robots provide services, they need to complete a robust real-time selective attention process in the domestic environment. Visual attention mechanism is an important part of human perception, which enables humans to select the visual focus on the most potential interesting information. It also could dominate the allocation of computing resource. It also could focus human’s attention on valuable objects in the home environment. Therefore we are trying to transfer visual attention selection mechanism to the scene analysis of service robots. This will greatly improve the robot’s efficiency in perception and processing information. We proposed a computing model of selective attention which is biologically inspired by visual attention mechanism, which aims at predicting focus of attention (FOA) in a domestic environment. Both static features and dynamic features are composed in attention selection computing process. Information from sensor networks is transformed and incorporated into the model. FOA is selected based on a winner-take-all (WTA) network and rotated by inhibition of return (IOR) principle. The experimental results showed that this approach is robust to the partial occlusions, scale-change illumination, and variations. The result demonstrates the effectiveness of this approach with available literature on biological evidence. Some specific domestic service tasks are also tailored to this model.
4
Tomašević, Aleksandra, Ranka Stanković, Miloš Utvić, Ivan Obradović, and Božo Kolonja. "Managing mining project documentation using human language technology." Electronic Library 36, no. 6 (December 10, 2018): 993–1009. http://dx.doi.org/10.1108/el-11-2017-0239.
Full textAbstract:
Purpose This paper aims to develop a system, which would enable efficient management and exploitation of documentation in electronic form, related to mining projects, with information retrieval and information extraction (IE) features, using various language resources and natural language processing. Design/methodology/approach The system is designed to integrate textual, lexical, semantic and terminological resources, enabling advanced document search and extraction of information. These resources are integrated with a set of Web services and applications, for different user profiles and use-cases. Findings The use of the system is illustrated by examples demonstrating keyword search supported by Web query expansion services, search based on regular expressions, corpus search based on local grammars, followed by extraction of information based on this search and finally, search with lexical masks using domain and semantic markers. Originality/value The presented system is the first software solution for implementation of human language technology in management of documentation from the mining engineering domain, but it is also applicable to other engineering and non-engineering domains. The system is independent of the type of alphabet (Cyrillic and Latin), which makes it applicable to other languages of the Balkan region related to Serbian, and its support for morphological dictionaries can be applied in most morphologically complex languages, such as Slavic languages. Significant search improvements and the efficiency of IE are based on semantic networks and terminology dictionaries, with the support of local grammars.
5
Wang, Yiming, and Xidan Gong. "Optimization of Data Processing System for Exercise and Fitness Process Based on Internet of Things." Wireless Communications and Mobile Computing 2021 (July 6, 2021): 1–11. http://dx.doi.org/10.1155/2021/7132301.
Full textAbstract:
In the digital network era, people have higher requirements for physical fitness. In the future, physical fitness requires not only good fitness equipment and fitness environment but also more convenient and intelligent health management, service guidance, social entertainment, and other refined fitness services. The innovation of sports and fitness equipment for the digital network era will definitely depend on the development of information technology and network technology. Based on the cutting-edge Internet of Things technology, this thesis focuses on the development and application of a new generation of digital fitness equipment adapted to future development, advocating the new concept of seamless integration of fitness exercise and information services through human-oriented systematic design thinking and providing implementable solutions to realize the science, convenience, and life of public fitness. This thesis uses modern science and technology, especially the Internet of Things (IoT) technology, to fully meet the diversified fitness needs of the fitness crowd as the guide; IoT digital fitness equipment design and application research was newly generated, using a variety of research methods to explore the functional design and application of IoT fitness equipment; the goal is to create a more intelligent and three-dimensional IoT fitness service model in the future. Through the application research of intelligent devices in IoT fitness equipment, the realization of the functions of identity identification, environment perception, and data transmission of IoT fitness equipment is made faster. Intelligent devices can become the interaction channel between fitness service personnel, fitness equipment, and fitness users and also reduce the development cost of IoT fitness equipment. The construction of an IoT fitness cloud service platform and data management system integrates the application of IoT, cloud computing, mobile communication, and other technologies to make IoT fitness service supply remote, real-time, and diversified. While providing convenient and value-added fitness services for fitness people, it also brings sustainable development space for the health service industry.
6
Cai, Chunling, and Chuanyi Chen. "Optimization of Human Resource File Information Decision Support System Based on Cloud Computing." Complexity 2021 (June 4, 2021): 1–12. http://dx.doi.org/10.1155/2021/8919625.
Full textAbstract:
With the rapid development of science and technology era, human resources and knowledge resources have become an important part of the development of enterprises. Therefore, it is very necessary to establish human resources data pool and carry out data mining based on it, so as to extract high quality and high quantity information to provide support for managers’ decision-making. In this study, the human resource archive information decision support system (DSS) is developed for various management and decision-making works by taking advantage of the characteristics of cloud computing, such as large scale, high reliability, versatility, and high expansibility. Based on the analysis of “cloud computing” advantages in resources integration and sharing and so on, on the basis of this system is designed by using the basis of the data acquisition layer, support layer of network services, cloud computing support layer, data standardization conversion layer, system application layer, system layer, decision support layer and so on 7 layer architecture, discusses the features and functions of each layer structure, the working mode and working mode of the Decision Support System (DSS) are introduced in detail. The system makes up for the defects of the traditional archive management, such as the lack of data resources, the inability to realize the isomorphism, and standardized processing of the data from multiple data sources.
7
Molnár, Tünde Lengyel. "Trend Analysis of Technologies Supporting the Availability of Online Content: From Keyword-Based Search to the Semantic Web." Acta Universitatis Sapientiae, Communicatio 7, no. 1 (December 1, 2020): 92–106. http://dx.doi.org/10.2478/auscom-2020-0007.
Full textAbstract:
Abstract The era of Web 1.0 implied the connection of web-based documents via links, which enabled search engines to scan for information and guarantee the search and availability of webpages. Web 2.0 represented the next evolutionary stage. Known as the collaborative web, the emphasis in this case was on the establishment of services and content by the community. Search options were complemented with labelling and frequently undesirable clickstream analysis coupled with push technology-supported information provision. The semantic web is a revolutionary development, which, in addition to processing information by humans, assures the readability of datasets by machines and facilitates communication between devices. In order to promote data and information processing by machines, the semantic web relies on a special ontology allocating the respective meaning to the given data along with relying on the global indexing and naming schemes of the web. Several ontologies emerged with differing basic guidelines while displaying compatibility to the RDF standard ranging from the more semantic description of bibliographical data in libraries to the description of information gained from social networks and human conversations. While Web 3.0 is often used interchangeably with the semantic web, the former one with its intelligent server function exceeds the semantic web. We have to ask ourselves, however, whether we can rely on the accuracy of the obtained data, and we must explore what progress have libraries – expected to increase reliability – made regarding the implementation of semantic data storage.
8
Bansal, Maggi, Inderveer Chana, and Siobhan Clarke. "Enablement of IoT Based Context-Aware Smart Home with Fog Computing." Journal of Cases on Information Technology 19, no. 4 (October 2017): 1–12. http://dx.doi.org/10.4018/jcit.2017100101.
Full textAbstract:
The recent advent of Internet of Things (IoT), has given rise to a plethora of smart verticals- smart homes being one of them. Smart Home is a classic example of IoT, wherein smart appliances connected via home gateways constitute a local home network to assist people in activities of daily life. Smart Home involves IoT-based automation (such as smart lighting, heating, surveillance etc.), remote monitoring and control of smart appliances. Besides automation, human-in-the-loop is a unique characteristic of Smart home to offer personalized services. Understanding the human behavior requires context processing. Thus, enablement of Smart home involves two prominent technologies IoT and context-aware computing. Further, local devices lying in the smart home have the implicit location and situational information, hence fog computing can offer real-time smart home services. In this paper, the authors propose ICON (IoT-based CONtext-aware) framework for context-aware IoT applications such as smart home, further ICON leverages fog-based IoT middleware to perform context-aware processing.
9
Kholkhunova, O. S. "Librarian in charge of social media: Volunteering or staffing position?" Scientific and Technical Libraries, no. 3 (March 4, 2019): 63–74. http://dx.doi.org/10.33186/1027-3689-2019-3-63-74.
Full textAbstract:
Тhe problems of library services integration into social media are considered. The main activities of the library specialist working in social media are revealed. The opinion is expressed that the library account in social networks has not only a marketing function, but also an educational and service one. The example of applied research "Activities of municipal public libraries in Belgorod region on the grounds" held in 2016, Belgorod state universal scientific library, lists the shortcomings of the mission of the municipal libraries of the region in social networks, among them the lack of system and low frequency, incorrect processing of accounts, poor navigation, insufficient efficiency in answering queries of users and the support of dialogue. It is proved that the insufficient realization of the potential of social networks as a resource for promoting libraries and a platform for full library and information services is due to human resources. It is concluded that the library, the leading representation of the library in social networks, requires an employee at a separate rate for work in social networks.
10
Tan, Rong, Yuan Tao, Wen Si, and Yuan-Yuan Zhang. "Privacy preserving semantic trajectory data publishing for mobile location-based services." Wireless Networks 26, no. 8 (June 15, 2019): 5551–60. http://dx.doi.org/10.1007/s11276-019-02058-8.
Full textAbstract:
Abstract The development of wireless technologies and the popularity of mobile devices is responsible for generating large amounts of trajectory data for moving objects. Trajectory datasets have spatiotemporal features and are a rich information source. The mining of trajectory data can reveal interesting patterns of human activities and behaviors. However, trajectory data can also be exploited to disclose users’ privacy information, e.g., the places they live and work, which could be abused by a malicious user. Therefore, it is very important to protect the users’ privacy before publishing any trajectory data. While most previous research on this subject has only considered the privacy protection of stay points, this paper distinguishes itself by modeling and processing semantic trajectories, which not only contain spatiotemporal data but also involve POI information and the users’ motion modes such as walking, running, driving, etc. Accordingly, in this research, semantic trajectory anonymizing based on the k-anonymity model is proposed that can form sensitive areas that contain k − 1 POI points that are similar to the sensitive points. Then, trajectory ambiguity is executed based on the motion modes, road network topologies and road weights in the sensitive area. Finally, a similarity comparison is performed to obtain the recordable and releasable anonymity trajectory sets. Experimental results show that this method performs efficiently and provides high privacy levels.
11
Kemavuthanon, Kemachart, and Osamu Uchida. "Integrated Question-Answering System for Natural Disaster Domains Based on Social Media Messages Posted at the Time of Disaster." Information 11, no. 9 (September 21, 2020): 456. http://dx.doi.org/10.3390/info11090456.
Full textAbstract:
Natural disasters are events that humans cannot control, and Japan has suffered from many such disasters over its long history. Many of these have caused severe damage to human lives and property. These days, numerous Japanese people have gained considerable experience preparing for disasters and are now striving to predict the effects of disasters using social network services (SNSs) to exchange information in real time. Currently, Twitter is the most popular and powerful SNS tool used for disaster response in Japan because it allows users to exchange and disseminate information quickly. However, since almost all of the Japanese-related content is also written in the Japanese language, which restricts most of its benefits to Japanese people, we feel that it is necessary to create a disaster response system that would help people who do not understand Japanese. Accordingly, this paper presents the framework of a question-answering (QA) system that was developed using a Twitter dataset containing more than nine million tweets compiled during the Osaka North Earthquake that occurred on 18 June 2018. We also studied the structure of the questions posed and developed methods for classifying them into particular categories in order to find answers from the dataset using an ontology, word similarity, keyword frequency, and natural language processing. The experimental results presented herein confirm the accuracy of the answer results generated from our proposed system.
12
Dang, Xiaochao, Xiong Si, Zhanjun Hao, and Yaning Huang. "A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information." Sensors 19, no. 4 (February 20, 2019): 875. http://dx.doi.org/10.3390/s19040875.
Full textAbstract:
With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy.
13
Dedem, Dedi, Welly Sando, and Suci Badri Yana. "Analisis Sistem Informasi Kesehatan Daerah (SIKDA) Generik Di Unit Rekam Medis Puskesmas Langsat Tahun 2020." Photon: Jurnal Sain dan Kesehatan 11, no. 1 (January 10, 2021): 55–62. http://dx.doi.org/10.37859/jp.v11i1.2237.
Full textAbstract:
Regional information system is a term that is used to describe a system consisting of a combination of input such as human resources (brainware), software, information needs format (informware), information technology and communication technology, the process of sending an analysis report recording (entry). the feedback and output data information mechanism that can be accessed together and has adequate quality, regional information system in the Langsat Health Center Medical Record Unit only started in 2017, SIKDA in the medical records unit lacks Human Resources because it does not there is a Medical Record and IT graduate. Obstacles that occur, such as disruption of soft ware and hard ware networks when opened, experience delays, causing delays in the given services. For the Fund itself, there is no special budget provided for the implementation of theregional information system application because it has been allocated by the Health Office. Budget allocation of funds is held only if needed. This type of qualitative research uses interview and observational sheets. The research was conducted in February-September, at Langsat Public Health Center, Pekanbaru City. The research subjects were the Head of Langsat Community Health Center, the Head of the Medical Records Unit, the person in charge of SIKDA, and Operators. Data analysis was used by systematically managing the interview guidelines, then processing the data, data from observations were identified to describe each variable, a summary will be presented in a narrative form. The results of this study indicate that the Generic regional information system in the Medical Records Unit has been running at its maximum, even though there is a lack of calm in Human Resources there are no medical records and IT graduates. Infrastructure is lacking in terms of ginset, Fund Allocation is not a special budget. Must improve Human Resources, Facilities and Infrastructure.
14
Dedem, Dedi, Welly Sando, and Suci Badri Yana. "Analisis Sistem Informasi Kesehatan Daerah (SIKDA) Generik Di Unit Rekam Medis Puskesmas Langsat Tahun 2020." Photon: Jurnal Sain dan Kesehatan 11, no. 1 (January 10, 2021): 55–62. http://dx.doi.org/10.37859/jp.v11i1.2237.
Full textAbstract:
Regional information system is a term that is used to describe a system consisting of a combination of input such as human resources (brainware), software, information needs format (informware), information technology and communication technology, the process of sending an analysis report recording (entry). the feedback and output data information mechanism that can be accessed together and has adequate quality, regional information system in the Langsat Health Center Medical Record Unit only started in 2017, SIKDA in the medical records unit lacks Human Resources because it does not there is a Medical Record and IT graduate. Obstacles that occur, such as disruption of soft ware and hard ware networks when opened, experience delays, causing delays in the given services. For the Fund itself, there is no special budget provided for the implementation of theregional information system application because it has been allocated by the Health Office. Budget allocation of funds is held only if needed. This type of qualitative research uses interview and observational sheets. The research was conducted in February-September, at Langsat Public Health Center, Pekanbaru City. The research subjects were the Head of Langsat Community Health Center, the Head of the Medical Records Unit, the person in charge of SIKDA, and Operators. Data analysis was used by systematically managing the interview guidelines, then processing the data, data from observations were identified to describe each variable, a summary will be presented in a narrative form. The results of this study indicate that the Generic regional information system in the Medical Records Unit has been running at its maximum, even though there is a lack of calm in Human Resources there are no medical records and IT graduates. Infrastructure is lacking in terms of ginset, Fund Allocation is not a special budget. Must improve Human Resources, Facilities and Infrastructure.
15
Vorozhtsova, Nadezhda, Ilya Shushkov, and Sergey Vologdin. "System approach to development of Intellectual Information Mobile System for Electric Power Metering." E3S Web of Conferences 114 (2019): 01004. http://dx.doi.org/10.1051/e3sconf/201911401004.
Full textAbstract:
The relevance of the work lies in the application of universal image processing for further verification of data. The use of pattern recognition makes it possible to quickly identify errors in the manual entry of various information. The object of the research is business processes aimed at detailed monitoring and metering of electric power of IDGC of Center and Volga Region, PJSC, Udmurtenergo branch. Subject of research - the principles of design and practical application of the intellectual system in the enterprise. The aim of the work is to increase the level of reliability of commercial accounting of electricity. Development of the Intellectual Information System for Electric Power Metering (IISEPM) by applying the data collection terminals has been proposed in order to solve the problem of mobile electricity metering. The implementation of IISEPM will reduce commercial losses and improve the observability and controllability of the power grid infrastructure. For enterprises, which activities are aimed at providing services for the electricity transmission to a large number of consumers, it is important to have an accurate idea of the number of the provided services. In the modern conditions, it is possible to automate the process of collecting information, so that in the future it will be possible to verify the received data in a single processing center. Taking readings from metering devices is a necessary monthly procedure. The traditional way is that the consumer writes down the meter readings on paper, and then also manually calculates the amount of energy spent per month. The next step for the consumer is to transfer the readings taken from the power sales company, where employees record the meter readings and then also manually calculates the amount of energy spent per month. The next step for the consumer is to transfer the readings taken from the power sales company, where employees record the meter readings in the database. The user has the right to transfer data remotely by logging into his personal account on the company’s website. The power supply company, having received the consumer’s data, calculates the cost of the electricity consumed at a certain tariff and notifies the consumer about it, sending him a receipt of payment. Automation will reduce the amount of paper media. The human factor will also be excluded, which will increase the accuracy of the calculated energy consumption and, therefore, the inadmissibility of emergency situations will be achieved. Index Terms—convolutional neural network, data collection terminal, information-analytical complex, intelligent information mobile system, mobile energy accounting, pattern recognition, service-oriented architecture, Viola-Jones method.
16
Basha, Shaik Rahamat, M. Surya Bhupal Rao, P. Kiran Kumar Reddy, and G. Ravi Kumar. "Emotional Tweets Analysis on Social Media with Short Text Classification Using Various Machine Learning Techniques." Journal of Computational and Theoretical Nanoscience 17, no. 12 (December 1, 2020): 5477–82. http://dx.doi.org/10.1166/jctn.2020.9442.
Full textAbstract:
Online Social media are a huge source of regular communication since most people in the world today use these services to stay communicating with each other in their modern lives. Today’s research has been implemented on emotion recognition by message. The majority of the research uses a method of machine learning. In order to extract information from the textual text written by human beings, natural language processing (NLP) techniques were used. The emotion of humans may be expressed when reading or writing a message. Human beings are willing, since human life is filled with a variety of emotions, to feel various emotions. This analysis helps us to realize the use of text processing and text mining methods by social media researchers in order to classify key data themes. Our experiments presented that the two main social networks in the world are conducting text-based mining on Facebook and Twitter. In this proposed study, we categorized the human feelings such as joy, fear, love, anger, surprise, sadness and thankfulness and compared our results using various methods of machine learning.
17
Jiang, Dazhi, Zhihui He, Yingqing Lin, Yifei Chen, and Linyan Xu. "An Improved Unsupervised Single-Channel Speech Separation Algorithm for Processing Speech Sensor Signals." Wireless Communications and Mobile Computing 2021 (February 27, 2021): 1–13. http://dx.doi.org/10.1155/2021/6655125.
Full textAbstract:
As network supporting devices and sensors in the Internet of Things are leaping forward, countless real-world data will be generated for human intelligent applications. Speech sensor networks, an important part of the Internet of Things, have numerous application needs. Indeed, the sensor data can further help intelligent applications to provide higher quality services, whereas this data may involve considerable noise data. Accordingly, speech signal processing method should be urgently implemented to acquire low-noise and effective speech data. Blind source separation and enhancement technique refer to one of the representative methods. However, in the unsupervised complex environment, in the only presence of a single-channel signal, many technical challenges are imposed on achieving single-channel and multiperson mixed speech separation. For this reason, this study develops an unsupervised speech separation method CNMF+JADE, i.e., a hybrid method combined with Convolutional Non-Negative Matrix Factorization and Joint Approximative Diagonalization of Eigenmatrix. Moreover, an adaptive wavelet transform-based speech enhancement technique is proposed, capable of adaptively and effectively enhancing the separated speech signal. The proposed method is aimed at yielding a general and efficient speech processing algorithm for the data acquired by speech sensors. As revealed from the experimental results, in the TIMIT speech sources, the proposed method can effectively extract the target speaker from the mixed speech with a tiny training sample. The algorithm is highly general and robust, capable of technically supporting the processing of speech signal acquired by most speech sensors.
18
Yu, Binbin, and Hongtu Li. "Anonymous authentication key agreement scheme with pairing-based cryptography for home-based multi-sensor Internet of Things." International Journal of Distributed Sensor Networks 15, no. 9 (September 2019): 155014771987937. http://dx.doi.org/10.1177/1550147719879379.
Full textAbstract:
Home-based multi-sensor Internet of Things, as a typical application of Internet of Things, interconnects a variety of intelligent sensor devices and appliances to provide intelligent services to individuals in a ubiquitous way. As families become more and more intelligent, complex, and technology-dependent, there is less and less need for human intervention. Recently, many security attacks have shown that Internet home-based Internet of Things have become a vulnerable target, leading to personal privacy problems. For example, eavesdroppers can acquire the identity of specific devices or sensors through public channels, which is not secure, to infer individual public life in the home area network. Authentication is the essential portion of many secure systems processing of verifying and declaring identity. Before providing confidential information, home-based-Internet of Things service authenticates users and devices. The communication and processing capabilities of intelligent devices are limited. Therefore, in home-based Internet of Things, lightweight authentication and key agreement technology are very important to resist known attacks. This article proposes an anonymous authenticated key agreement protocol using pairing-based cryptography. The protocol proposed in this article provides lightweight computation and ensures the security of communication between home-based multi-sensor Internet of Things network and Internet network.
19
Rachman, M. Taufik, Nidya Putri Syahida, and Yana Isnaini. "Implementasi Sistem Informasi Administrasi Dalam Peningkatan Pelayanan Kesehatan Pada Puskesmas Bayan." JIAP (Jurnal Ilmu Administrasi Publik) 6, no. 1 (January 19, 2019): 48. http://dx.doi.org/10.31764/jiap.v6i1.665.
Full textAbstract:
Health center of Bayan is one of the main health center is location in the north of Lombok district. As the performance of systems running in patient care in the health center of Bayan is still not optimal for the data processing is still done use media bookkeeping. Many of the constraints experienced by the health center, including an error in the input, data storage, and can occur double patient files. So that data processing becomes ineffective and inefficient. There are several public and employee perception of the administration of health care information system in health center Bayan. This is the author's interest in conducting research on employee perceptions of the application of information systems administration in the improvement of health services in health center Bayan and in this case the author uses qualitative research methods in which a qualitative study that examines the participants with strategies that are interactive and flexible.
The qualitative research aimed at understanding social phenomena from the perspective of the participants. The results obtained from this study is an information system that is applied to the health center administration Bayan still using a manual system, which means keep using the computer but not connected to a data network local area network ( LAN) and does not use as a database server. From this study it can be concluded that the health care information system in health center Bayan already well underway although there are some deficiencies in the means of infrastructures and human resources.
20
Liu, Xinhua, Yao Zou, Hailan Kuang, and Xiaolin Ma. "Face Image Age Estimation Based on Data Augmentation and Lightweight Convolutional Neural Network." Symmetry 12, no. 1 (January 10, 2020): 146. http://dx.doi.org/10.3390/sym12010146.
Full textAbstract:
Face images contain many important biological characteristics. The research directions of face images mainly include face age estimation, gender judgment, and facial expression recognition. Taking face age estimation as an example, the estimation of face age images through algorithms can be widely used in the fields of biometrics, intelligent monitoring, human-computer interaction, and personalized services. With the rapid development of computer technology, the processing speed of electronic devices has greatly increased, and the storage capacity has been greatly increased, allowing deep learning to dominate the field of artificial intelligence. Traditional age estimation methods first design features manually, then extract features, and perform age estimation. Convolutional neural networks (CNN) in deep learning have incomparable advantages in processing image features. Practice has proven that the accuracy of using convolutional neural networks to estimate the age of face images is far superior to traditional methods. However, as neural networks are designed to be deeper, and networks are becoming larger and more complex, this makes it difficult to deploy models on mobile terminals. Based on a lightweight convolutional neural network, an improved ShuffleNetV2 network based on the mixed attention mechanism (MA-SFV2: Mixed Attention-ShuffleNetV2) is proposed in this paper by transforming the output layer, merging classification and regression age estimation methods, and highlighting important features by preprocessing images and data augmentation methods. The influence of noise vectors such as the environmental information unrelated to faces in the image is reduced, so that the final age estimation accuracy can be comparable to the state-of-the-art.
21
Ru, Lei, Bin Zhang, Jing Duan, Guo Ru, Ashutosh Sharma, Gaurav Dhiman, Gurjot Singh Gaba, Emad Sami Jaha, and Mehedi Masud. "A Detailed Research on Human Health Monitoring System Based on Internet of Things." Wireless Communications and Mobile Computing 2021 (May 14, 2021): 1–9. http://dx.doi.org/10.1155/2021/5592454.
Full textAbstract:
The technological advent in smart sensing devices and the Internet has provided practical solutions in various sectors of networking, public and private sector industries, and government organizations worldwide. This study intends to combine the Internet of Things (IoT) technology with health monitoring to make it personalized and timely through allowing the interconnection between the devices. This work is aimed at exploring various wearable health monitoring modules that people wear to monitor heart rate, blood pressure, pulse, body temperature, and physiological information. The information is acquired using the wireless sensor to create a health monitoring system. The data is integrated using the Internet of Things for processing, connecting, and computing to achieve real-time monitoring. The temperature of three people measured by the temperature thermometer is 36.4, 36.7, and 36.5 (°C), respectively, and the average acquired by the monitoring system of the three people is 36.5, 36.4, and 36.5 (°C), respectively, indicating that the system demonstrated relatively accurate and stable testability. The user’s ECG is displayed clearly and conveniently using the ECG acquisition system. The pulse rate of the three people tested by the system is 78, 78, and 79 (times/min), respectively, similar to the medical pulse meter results. The physiological information acquired using the semantic recognition, matching system, and character matching system is relatively accurate. It concludes that the human health monitoring system based on the Internet of Things can provide people with daily health management, instrumental in heightening health service quality and level.
22
Ali, Md Nawab Yousuf, Md Golam Sarowar, Md Lizur Rahman, Jyotismita Chaki, Nilanjan Dey, and João Manuel R. S. Tavares. "Adam Deep Learning With SOM for Human Sentiment Classification." International Journal of Ambient Computing and Intelligence 10, no. 3 (July 2019): 92–116. http://dx.doi.org/10.4018/ijaci.2019070106.
Full textAbstract:
Nowadays, with the improvement in communication through social network services, a massive amount of data is being generated from user's perceptions, emotions, posts, comments, reactions, etc., and extracting significant information from those massive data, like sentiment, has become one of the complex and convoluted tasks. On other hand, traditional Natural Language Processing (NLP) approaches are less feasible to be applied and therefore, this research work proposes an approach by integrating unsupervised machine learning (Self-Organizing Map), dimensionality reduction (Principal Component Analysis) and computational classification (Adam Deep Learning) to overcome the problem. Moreover, for further clarification, a comparative study between various well known approaches and the proposed approach was conducted. The proposed approach was also used in different sizes of social network data sets to verify its superior efficient and feasibility, mainly in the case of Big Data. Overall, the experiments and their analysis suggest that the proposed approach is very promissing.
23
De Fazio, Roberto, Massimo De Vittorio, and Paolo Visconti. "Innovative IoT Solutions and Wearable Sensing Systems for Monitoring Human Biophysical Parameters: A Review." Electronics 10, no. 14 (July 12, 2021): 1660. http://dx.doi.org/10.3390/electronics10141660.
Full textAbstract:
Digital and information technologies are heavily pervading several aspects of human activities, improving our life quality. Health systems are undergoing a real technological revolution, radically changing how medical services are provided, thanks to the wide employment of the Internet of Things (IoT) platforms supporting advanced monitoring services and intelligent inferring systems. This paper reports, at first, a comprehensive overview of innovative sensing systems for monitoring biophysical and psychophysical parameters, all suitable for integration with wearable or portable accessories. Wearable devices represent a headstone on which the IoT-based healthcare platforms are based, providing capillary and real-time monitoring of patient’s conditions. Besides, a survey of modern architectures and supported services by IoT platforms for health monitoring is presented, providing useful insights for developing future healthcare systems. All considered architectures employ wearable devices to gather patient parameters and share them with a cloud platform where they are processed to provide real-time feedback. The reported discussion highlights the structural differences between the discussed frameworks, from the point of view of network configuration, data management strategy, feedback modality, etc.
24
Liao, Qing, Haoyu Tan, Wuman Luo, and Ye Ding. "Diverse Mobile System for Location-Based Mobile Data." Wireless Communications and Mobile Computing 2018 (August 1, 2018): 1–17. http://dx.doi.org/10.1155/2018/4217432.
Full textAbstract:
The value of large amount of location-based mobile data has received wide attention in many research fields including human behavior analysis, urban transportation planning, and various location-based services. Nowadays, both scientific and industrial communities are encouraged to collect as much location-based mobile data as possible, which brings two challenges: (1) how to efficiently process the queries of big location-based mobile data and (2) how to reduce the cost of storage services, because it is too expensive to store several exact data replicas for fault-tolerance. So far, several dedicated storage systems have been proposed to address these issues. However, they do not work well when the ranges of queries vary widely. In this work, we design a storage system based on diverse replica scheme which not only can improve the query processing efficiency but also can reduce the cost of storage space. To the best of our knowledge, this is the first work to investigate the data storage and processing in the context of big location-based mobile data. Specifically, we conduct in-depth theoretical and empirical analysis of the trade-offs between different spatial-temporal partitioning and data encoding schemes. Moreover, we propose an effective approach to select an appropriate set of diverse replicas, which is optimized for the expected query loads while conforming to the given storage space budget. The experiment results show that using diverse replicas can significantly improve the overall query performance and the proposed algorithms for the replica selection problem are both effective and efficient.
25
Valarezo Añazco, Edwin, Seung Ju Han, Kangil Kim, Patricio Rivera Lopez, Tae-Seong Kim, and Sangmin Lee. "Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks." Sensors 21, no. 4 (February 17, 2021): 1404. http://dx.doi.org/10.3390/s21041404.
Full textAbstract:
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research produces patchable inertial measurement units (IMUs). In this paper, a hand gesture recognition system using a single patchable six-axis IMU attached at the wrist via recurrent neural networks (RNN) is presented. The IMU comprises IC-based electronic components on a stretchable, adhesive substrate with serpentine-structured interconnections. The proposed patchable IMU with soft form-factors can be worn in close contact with the human body, comfortably adapting to skin deformations. Thus, signal distortion (i.e., motion artifacts) produced for vibration during the motion is minimized. Also, our patchable IMU has a wireless communication (i.e., Bluetooth) module to continuously send the sensed signals to any processing device. Our hand gesture recognition system was evaluated, attaching the proposed patchable six-axis IMU on the right wrist of five people to recognize three hand gestures using two models based on recurrent neural nets. The RNN-based models are trained and validated using a public database. The preliminary results show that our proposed patchable IMU have potential to continuously monitor people’s motions in remote settings for applications in mobile health, human–computer interaction, and control gestures recognition.
26
Zhang, Guangnan, Wang Jing, Hai Tao, Md Arafatur Rahman, Sinan Q. Salih, Ahmed AL-Saffar, and Renrui Zhang. "ADA-SR: Activity detection and analysis using security robots for reliable workplace safety." Work 68, no. 3 (March 26, 2021): 935–43. http://dx.doi.org/10.3233/wor-203427.
Full textAbstract:
BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease. OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process. RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset. CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
27
Budiyanto, Setiyo, Freddy Artadima Silaban, Lukman Medriavin Silalahi, Selamet Kurniawan, Fajar Rahayu I. M., Ucuk Darusalam, and Septi Andryana. "Design and monitoring body temperature and heart rate in humans based on WSN using star topology." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (April 1, 2021): 326. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp326-334.
Full textAbstract:
<span><span>Electronic health (E-health) uses information and communication technology including electronics, telecommunications, computers, and informatics to process various types of medical information, to carry out clinical services (diagnosis or therapy). Health is the most important asset in human life, therefore maintaining health is a top priority and serious attention needed. Heart rate and body temperature are vital signs that the hospital routinely checks for clinical signs and are useful for strengthening the diagnosis of a disease. In this research monitoring heart rate and body temperature with the wireless sensor network (WSN) method that uses <span>NodeMCU 1.0 as a controller module and wireless as communication between nodes, the wireless network used in this research Wi-Fi network. As a data taker, a DS18b20 temperature sensor and a heart rate sensor (pulse sensor) are needed, which will be displayed by the ThingSpeak web and smartphones. From the test results, the success rate of the system in detecting heart rates is 97.17%. Whereas in detecting body temperature the success rate of the system is 99.28%. For data transmission, the system can send data smoothly at a maximum distance of 15 meters with a barrier.</span></span></span>
28
Kumar, Abhinav, Sanjay Kumar Singh, K. Lakshmanan, Sonal Saxena, and Sameer Shrivastava. "A Novel Cloud-Assisted Secure Deep Feature Classification Framework for Cancer Histopathology Images." ACM Transactions on Internet Technology 21, no. 2 (June 2021): 1–22. http://dx.doi.org/10.1145/3424221.
Full textAbstract:
The advancements in the Internet of Things (IoT) and cloud services have enabled the availability of smart e-healthcare services in a distant and distributed environment. However, this has also raised major privacy and efficiency concerns that need to be addressed. While sharing clinical data across the cloud that often consists of sensitive patient-related information, privacy is a major challenge. Adequate protection of patients’ privacy helps to increase public trust in medical research. Additionally, DL-based models are complex, and in a cloud-based approach, efficient data processing in such models is complicated. To address these challenges, we propose an efficient and secure cancer diagnostic framework for histopathological image classification by utilizing both differential privacy and secure multi-party computation. For efficient computation, instead of performing the whole operation on the cloud, we decouple the layers into two modules: one for feature extraction using the VGGNet module at the user side and the remaining layers for private prediction over the cloud. The efficacy of the framework is validated on two datasets composed of histopathological images of the canine mammary tumor and human breast cancer. The application of differential privacy preserving to the proposed model makes the model secure and capable of preserving the privacy of sensitive data from any adversary, without significantly compromising the model accuracy. Extensive experiments show that the proposed model efficiently achieves the trade-off between privacy and model performance.
29
Jamil, Faisal, Muhammad Azhar Iqbal, Rashid Amin, and DoHyeun Kim. "Adaptive Thermal-Aware Routing Protocol for Wireless Body Area Network." Electronics 8, no. 1 (January 1, 2019): 47. http://dx.doi.org/10.3390/electronics8010047.
Full textAbstract:
The recent advancement in information technology and evolving of the (IoT) shifted the traditional medical approach to patient-oriented approach (e.g., Telemedicine/Telemonitoring). IoT permits several services including sensing, processing and communicating information with physical and bio-medical constraints. Wireless Body Area Network (WBAN) handles the issues pertaining to the medical purposes in the form of sensor nodes and connected network. The WBAN takes human physiological data as an input to subsequently monitor the patient conditions that are transferred to other IoT components for analysis. Such monitoring and analysis demand a cohesive routing approach to ensure the safe and in-time transfer of data. The temperature rise of bio-medical sensor nodes makes the entire routing operation very crucial because the temperature of implanted nodes rises and ultimately damages body tissues. This needs dispersion in data transmission among different nodes by opting various available routes while avoiding temperature rise. In this paper, we present Adaptive Thermal-Aware Routing algorithm for WBAN. The ATAR is designed to overcome the temperature rise issue of implanted bio-medical sensors nodes. The new protocol is based on Multi-Ring Routing approach to find an alternative route in the case of increasing temperature. The simulation results indicate that proposed protocol is more efficient in terms of temperature rise and throughput than existing approaches.
30
Kumar, Hareesh. "Involvement of Cloud Computing and IoT in the Field of Health Care." March 2021 3, no. 1 (January 15, 2021): 1–13. http://dx.doi.org/10.36548/jtcsst.2021.1.001.
Full textAbstract:
The rapid growth of the Internet of Things (IoT) and cloud computing is finding is a big part of our lifestyle, planning to upgrade personal satisfaction by partnering with various shrewd gadgets, innovations, and applications. Generally, the fields of IoT and cloud computing considers the mechanization of everything around the world. Presently scientists have discovered that there is a reasonably big utilization of IoT and cloud in the field of the health care industry. In between the panoply of uses empowered by the Internet of Things (IoT), brilliant and associated health care services play a significant role. The arrangement of network sensors, either exhausted on the body or incorporated into our living environment which makes the processing of information demonstrative of our physical and emotional well-being. Such data can achieve a positive disruptive shift in the human services, collected consistently, totaled, and adequately mined. This study exhibits the significance of the Internet of Things and Cloud in the field of the Healthcare Industry.
31
Lee, Chee Wei, and Stuart Madnick. "Cybersafety Approach to Cybersecurity Analysis and Mitigation for Mobility-as-a-Service and Internet of Vehicles." Electronics 10, no. 10 (May 20, 2021): 1220. http://dx.doi.org/10.3390/electronics10101220.
Full textAbstract:
Urban mobility is in the midst of a revolution, driven by the convergence of technologies such as artificial intelligence, on-demand ride services, and Internet-connected and self-driving vehicles. Technological advancements often lead to new hazards. Coupled with the increased levels of automation and connectivity in the new generation of autonomous vehicles, cybersecurity is emerging as a key threat affecting these vehicles. Traditional hazard analysis methods treat safety and security in isolation and are limited in their ability to account for interactions among organizational, sociotechnical, human, and technical components. In response to these challenges, the cybersafety method, based on System Theoretic Process Analysis (STPA and STPA-Sec), was developed to meet the growing need to holistically analyze complex sociotechnical systems. We applied cybersafety to coanalyze safety and security hazards, as well as identify mitigation requirements. The results were compared with another promising method known as Combined Harm Analysis of Safety and Security for Information Systems (CHASSIS). Both methods were applied to the Mobility-as-a-Service (MaaS) and Internet of Vehicles (IoV) use cases, focusing on over-the-air software updates feature. Overall, cybersafety identified additional hazards and more effective requirements compared to CHASSIS. In particular, cybersafety demonstrated the ability to identify hazards due to unsafe/unsecure interactions among sociotechnical components. This research also suggested using CHASSIS methods for information lifecycle analysis to complement and generate additional considerations for cybersafety. Finally, results from both methods were backtested against a past cyber hack on a vehicular system, and we found that recommendations from cybersafety were likely to mitigate the risks of the incident.
32
Alexeev, V. M., L. A. Baranov, M. A. Kulagin, and V. G. Sidorenko. "Building Architecture of Intelligent Control System for Urban Rail Transit System." World of Transport and Transportation 19, no. 1 (September 8, 2021): 18–46. http://dx.doi.org/10.30932/1992-3252-2021-19-1-18-46.
Full textAbstract:
The increase in the volume of passenger transportation in megalopolises and large urban agglomerations is efficiently provided by the integration of urban public transit systems and city railways. Traffic management under those conditions requires creating intelligent centralised multi-level traffic control systems that implement the required indicators of quality, comfort, and traffic safety regarding passenger transportation. Besides, modern control systems contribute to traction power saving, are foundation and integral part of the systems of digitalisation of urban transit and the cities. Building systems solving the traffic planning and control tasks is implemented using algorithms based on the methods of artificial intelligence, principles of hierarchically structured centralised systems, opportunities provided by Big Data technology. Under those conditions it is necessary to consider growing requirements towards software as well as theoretical design and practical implementation of network organisation.This article discusses designing architecture and shaping requirements for developed applications and their integration with databases to create a centralised intelligent control system for the urban rail transit system (CICS URTS). The article proposes the original architecture of the network, routing of information flows and software of CICS URTS. The routing design is based on a fully connected network. This allows to significantly increase the network bandwidth and meet the requirements regarding information protection, since information flows are formed based on the same type of protocols, which prevents emergence of covert transmission channels. The implementation of the core using full connectivity allows, according to the tags of information flows, to pre-form the routes for exchange of information between servers and applications deployed in CICS URTS. The use of encrypted tags of information flows makes it much more difficult to carry out attacks and organise collection of information about the network structure.Platforms for development of intelligent control systems (ICS), which include CICS URTS, high computing power, data storage capacity and new frameworks are becoming more available for researchers and developers and allow rapid development of ICS. The article discusses the issues of interaction of applications with databases through a combination of several approaches used in the field of Big Data, substantiates combination of Internet of Things (IoT) methodology and microservice architecture. This combination will make it possible to single out business processes in the system and form streaming data processing requiring operational analysis by a human, which is shown by relevant examples.Thus, the objective of the article is to formalise the principles of organising data exchange between CICS URTS and automated control systems (ACS) of railway companies (in our case, using the example of JSC Russian Railways), URTS services providers, and city government bodies, implement the developed approaches into the architecture of CICS URTS and formalise principles of organisation of microservice architecture of CICS URTS software. The main research methods are graph theory, Big Data and IoT methods.
33
Buzova, N. V. "Artificial Intelligence and the Use of Databases as Related Rights Objects." Lex Russica, no. 8 (August 25, 2020): 62–69. http://dx.doi.org/10.17803/1729-5920.2020.165.8.062-069.
Full textAbstract:
The development of digital technologies and creation of high-tech services constitute one of the directions of strategic development of Russia. Modern technologies are already capable of searching, systematizing and analyzing large data amounts within a short period of time. But the state sets additional tasks: to process and synthesize speech, to prepare analytical materials for making complex decisions, to perform tasks at the level of results achieved by a human being, to train and even automatically self-learn and eventually create a “strong” artificial intelligence. Adopted legal acts and legal acts under consideration define the main objectives, tasks and expected results to be achieved through the application of artificial intelligence technology in the immediate period. However, the application of artificial intelligence technology raises additional questions related to the creation of new technical solutions and works and the application of the protected results of intellectual activity, exclusive rights to which belong to third parties. The search for data for further analysis is carried out, inter alia, in databases that are objects of related rights, limited access to which is provided through information and telecommunications Internet network. In this regard, the lawfulness of such search and processing of information from protected databases requires clarification. The paper gives examples of judicial practice that show the difficulty of establishing and proving the fact of using materials from databases accessed through high-tech services. The paper also identifies the risks of violation of the rights and legitimate interests of third parties whose personal data are posted in databases that can be accessed via the Internet.
34
Olenev, Valentin. "Analysis of requirements for modern spacecraft onboard network protocols." Information and Control Systems, no. 1 (March 3, 2021): 8–16. http://dx.doi.org/10.31799/1684-8853-2021-1-8-16.
Full textAbstract:
Introduction: New technologies are replacing the onboard space networks based on bus topologies. One of these technologies is SpaceWire. New communication protocols are being developed, expanding SpaceWire functionality. The protocol developers should provide all the required technical characteristics for data transmission and processing. Purpose: Analysis of the existing requirements for communication protocols, and development of consolidated set of requirements that will take into account the modern requests of the space industry. Results: The analysis of the existing demands on communication protocols resulted in a set of consolidated requirements for the physical-network layers’ protocols and the transport layer protocols. The requirements cover the speed, latencies, transmission distance, transmitted information amount, fault detection functionality, time synchronization between the devices, quality of service, main user data types, and data transfer modes at the transport level. The existing SpaceWire protocols are defined as a special class of protocols, possessing unique characteristics. Practical relevance: The performed analysis can simplify the implementation of new onboard communication protocols and provide a required level of technique for new generation spacecraft.
35
Lynn, Christopher W., Lia Papadopoulos, Ari E. Kahn, and Danielle S. Bassett. "Human information processing in complex networks." Nature Physics 16, no. 9 (June 15, 2020): 965–73. http://dx.doi.org/10.1038/s41567-020-0924-7.
Full text
36
Pászto, Vít, and Alena Vondráková. "Mobility Community Reports data: Geovisual analytics and cartographic synthesis of behaviour changes due to COVID-19 pandemic in Europe." Abstracts of the ICA 2 (October 8, 2020): 1–2. http://dx.doi.org/10.5194/ica-abs-2-13-2020.
Full textAbstract:
Abstract. It was probably more valuable to use user-generated data from location services than ever before during the COVID-19 pandemic. The newly emerged situation caused by the disease’s rapid spread found most of the European countries not ready in many aspects. From the geospatial point of view, it was a tremendous lack of open-data about people’s behaviour. Many public and private services were closed as a preventive measure to slow down COVID-19 spread, which caused an unprecedented change in citizens’ mobility and overall behaviour. It is not possible to acquire such information using traditional ways of data collection (e.g. surveys and questionnaires), or it would be extremely expensive and time-consuming. In order to obtain information about people’s change in behaviour, location-based data from mobile phone users could be used. Although individual user-generated data are highly sensitive, they could be aggregated (e.g. for higher administrative units) and thus anonymised; while still possessing valuable insight into the behaviour change. This contribution deals with COVID-19 Community Mobility Reports dataset released in early April 2020 by Google (available at https://www.google.com/covid19/mobility), which offers unique information about a change of human activities due to the pandemic. This data is in principle very similar to data from mobile operators; however, more accurate, because the location of the device is determined also by connection to Wi-Fi networks and especially via GPS – besides nearby BTS stations. Information carried by the data gives the average decline in population activity in spatial resolution, either only for the entire country or for the country and its main regions. The data is constantly being updated, but Google provides no information on the date of future dissemination of data. Behavioural changes as such are monitored in six categories according to the location of the activity, which was determined by Google as useful for maintaining social distancing or from the point of view of the availability of basic services. The categories are as follows – a) residential, b) transit stations, c) retail and recreation, d) grocery and pharmacy, e) parks, and f) workplaces. Key information is the percentage decrease or increase in the number of individuals present compared to the usual state of affairs (baseline – 3 January to 6 February 2020) in these six fundamental localities. We analysed and visualized data during the peak of the pandemic (from 5 March to 11 April 2020) by processing the average value from that period. In total, 567 European regions with six pieces of information on activity in the above categories was analyzed and visualized. First, we displayed average values in given categories in separate maps, which allowed us to understand a spatial pattern of data. This procedure is relatively common step in the data visual analytics process. We present resulting maps in the contribution of the conference.From the analytical part, we applied a cluster analysis, which served as the processing input for the cartographical synthesis. Methodologically, we created a typology based on the results of cluster analysis as multiple variables can be analyzed simultaneously to provide groups of types of regions with common properties. The k-medoid method was chosen for processing data on human activity type due to its lower sensitivity to outliers. By calculating auxiliary numerical statistics (Pseudo F-index, gap statistics, silhouette method) and after expert assessment, we chose to analyse and display results into five categories (Figure 1), although the optimum number of clusters was originally determined to be two, which was cartographically senseless. This also gives readers a finer breakdown of European regions, which more appropriately shows the diversity/similarity of individual types of regions; especially in the case of areas adjacent to the countries most severely afflicted by COVID-19 - for example Portugal, southern Austria, Slovenia, and others.Besides analytical processing of data (e.g. geovisual and cluster analysis), we also explored a more advance cartographic approach. Cartographic synthesis methods allow the visualization of various types of data with qualitative and quantitative resolution. Therefore, the synthetic processing of the above-mentioned data has been implemented. During the pandemic, a lot of maps were created that are cartographically incorrect, as well as a lot of maps that are cartographically correct. In most cases, however, it was only a simple visualization of the amount of positive-tested people or any other dealing issues in the form of analytical maps. Thus, synthetic maps can provide a new perspective on the issue and can be useful in unconventionally providing information about Covid-19 pandemic. We show how this dataset can be utilised in terms of cartographic synthesis in form of a regional typology in order to reveal the spatial pattern of such change in citizens‘ behaviour.The resulting typology categorizes the relevant administrative units into five clusters (types) in the space defined by the change in behaviour. These clusters can also be named according to the impact of the COVID-19 pandemic on behaviour of citizens: 1) moderate – regions with a relatively small change in population activity. For this type, it must especially be emphasized that this involves a mild impact of the pandemic compared to other types and that COVID-19 and related restrictions have had a visible effect on human behaviour in these regions as well; 2) substantial (secondary activities) – regions with a generally statistically average change in population activity with a more significant change in secondary activities (Grocery and Pharmacy, Parks); 3) substantial (main activities) – regions with a generally statistically average change in population activity with a more significant change in main activities (Residential, Transit Stations, Workplaces); 4) significant – regions with a statistically significant change in behaviour (values in the fourth quartile outside the range of the box graph); 5) extreme – regions with an unprecedented change in behaviour in outliers or near their borders.Five types of regions were identified according to the impact of COVID-19 and related restrictions - from the type moderately impacted by COVID-19 (e.g. Sweden, Latvia, Hungary), to those impacted by the pandemic in a substantial (Ireland, regions of Greece, the Czech Republic, Norway, Switzerland), significant (e.g. regions of France, Belgium, Austria, Slovenia, Portugal), and extreme manner (Spain, Italy, and the Paris region). As a conclusion, The current global situation clearly shows that positional and individual data can also be useful in the case of pandemics or any other situations involving the safety and health of the population. The use of Google Location data proves to be valuable in analysis and evaluation of citizens’ behaviour during any pandemic crisis, though, in this case, aggregated into higher territorial units.
37
Huang, Chao, and Shah Nazir. "Analyzing and Evaluating Smart Cities for IoT Based on Use Cases Using the Analytic Network Process." Mobile Information Systems 2021 (February 22, 2021): 1–13. http://dx.doi.org/10.1155/2021/6674479.
Full textAbstract:
With the passage of time, the world population is growing. Proper utilization of resources and other devices is tremendously playing an important role to easily examine, manage, and control the resources of the Internet of Things (IoT) in the smart city. Research in the field of IoT has revolutionized the services mostly in smart cities. In the smart city, the applications of IoT are utilized without human involvement. Diverse IoT devices are connected with each other and communicate for different tasks. With the existence of a huge number of IoT devices in the forthcoming years, the chances of privacy breach and information leakage are increasing. Billions of devices connected on IoT producing huge volume of data bound to cloud for processing, management, and storage. Sending of whole data to the cloud might create risk of security and privacy. Various needs of the smart city should be considered for both urgent and effective solutions to support requirements of the growing population. On the other side of rising technology, the IoT evolution has massively produced diverse research directions for the smart city. Keeping in view the use cases of the smart city, the proposed study presents the analytic network process (ANP) for evaluating smart cities. The approach of ANP works well in the situation of complexity, and vagueness exists among the available alternatives. The experimental results of the planned approach show that the approach is effective for evaluating the smart cities for IoT based on the use cases.
38
Wang, Yikang, Jiangnan Zhang, Hairui Zhao, Mengjie Liu, Shiyi Chen, Jian Kuang, and Xiaoji Niu. "Spatial Structure-Related Sensory Landmarks Recognition Based on Long Short-Term Memory Algorithm." Micromachines 12, no. 7 (June 30, 2021): 781. http://dx.doi.org/10.3390/mi12070781.
Full textAbstract:
Indoor localization is the basis for most Location-Based Services (LBS), including consumptions, health care, public security, and augmented reality. Sensory landmarks related to the indoor spatial structures (such as escalators, stairs, and corners) do not rely on active signal transmitting devices and have fixed positions, which can be used as the absolute positioning information to improve the performance of indoor localization effectively without extra cost. Specific motion patterns are presented when users pass these architectural structures, which can be captured by mobile built-in sensors, including accelerometers, gyroscopes, and magnetometers, to achieve the recognition of structure-related sensory landmarks. Therefore, the recognition of these landmarks can draw on the mature methods of Human Activity Recognition (HAR) with improvements. To this end, we improved a Long Short-Term Memory (LSTM) neural network to recognize different kinds of spatial structure-related sensory landmarks. Labels of structural sensory landmarks were proposed, and data processing methods (including interpolation, filter, and window length) were used and compared to achieve the highest recognition accuracy of 99.6%.
39
Wang, Ke, Xuejing Li, Jianhua Yang, Jun Wu, and Ruifeng Li. "Temporal action detection based on two-stream You Only Look Once network for elderly care service robot." International Journal of Advanced Robotic Systems 18, no. 4 (July 1, 2021): 172988142110383. http://dx.doi.org/10.1177/17298814211038342.
Full textAbstract:
Human action segmentation and recognition from the continuous untrimmed sensor data stream is a challenging issue known as temporal action detection. This article provides a two-stream You Only Look Once-based network method, which fuses video and skeleton streams captured by a Kinect sensor, and our data encoding method is used to turn the spatiotemporal temporal action detection into a one-dimensional object detection problem in constantly augmented feature space. The proposed approach extracts spatial–temporal three-dimensional convolutional neural network features from video stream and view-invariant features from skeleton stream, respectively. Furthermore, these two streams are encoded into three-dimensional feature spaces, which are represented as red, green, and blue images for subsequent network input. We proposed the two-stream You Only Look Once-based networks which are capable of fusing video and skeleton information by using the processing pipeline to provide two fusion strategies, boxes-fusion or layers-fusion. We test the temporal action detection performance of two-stream You Only Look Once network based on our data set High-Speed Interplanetary Tug/Cocoon Vehicles-v1, which contains seven activities in the home environment and achieve a particularly high mean average precision. We also test our model on the public data set PKU-MMD that contains 51 activities, and our method also has a good performance on this data set. To prove that our method can work efficiently on robots, we transplanted it to the robotic platform and an online fall down detection experiment.
40
Et. al., Vaishali Fulmal,. "The Implementation of Question Answer System Using Deep Learning." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 1S (April 11, 2021): 176–82. http://dx.doi.org/10.17762/turcomat.v12i1s.1604.
Full textAbstract:
Question-answer systems are referred to as advanced systems that can be used to provide answers to the questions which are asked by the user. The typical problem in natural language processing is automatic question-answering. The question-answering is aiming at designing systems that can automatically answer a question, in the same way as a human can find answers to questions. Community question answering (CQA) services are becoming popular over the past few years. It allows the members of the community to post as well as answer the questions. It helps users to get information from a comprehensive set of questions that are well answered. In the proposed system, a deep learning-based model is used for the automatic answering of the user’s questions. First, the questions from the dataset are embedded. The deep neural network is trained to find the similarity between questions. The best answer for each question is found as the one with the highest similarity score. The purpose of the proposed system is to design a model that helps to get the answer of a question automatically. The proposed system uses a hierarchical clustering algorithm for clustering the questions.
41
Savitskaya, Tatiana E. "Paradigm Shift: Libraries in the Context of Digital Humanities (Foreign Experience)." Observatory of Culture 15, no. 5 (December 14, 2018): 532–41. http://dx.doi.org/10.25281/2072-3156-2018-15-5-532-541.
Full textAbstract:
The article analyzes the new status of Western libraries within the framework of Digital Humanities (DH), a volumetric trend coupled with a radical change in the existing scientific paradigm. The concept of DH, connected with the use of the methods of computer-aided text analysis, processing of large data sets, digital mapping and 3D modeling in historical, linguistic and cultural studies, affected libraries in the whole range of their inherent functions: custodians of cultural heritage, providers of scientific communication, and centers for knowledge organization and dissemination.The article aims to compensate the lack of publications, existing in Russian library science, both on the conceptual grounds and the practice of productive cooperation of libraries and DH-projects. The author reveals the content of the cardinal reform of the essence of library work under the auspices of digital science (e-science), associated with the growing complexity of the information environment, the large amounts of heterogeneous data, the interactive potential of modern information and communication technologies, and the personalization of user interfaces. The article classifies the types of cooperation between libraries and DH-projects, reducible to three main models: service, laboratory and network. The range of services provided by libraries to DH-project developers is analyzed: from initial consulting, access to electronic storage infrastructure, management of digital projects, finding grants and applying for them, to promotion, marketing and professional computer assistance.The article presents positive examples of library rebranding as a place for avant-garde scientific research, synergy of methods and research strategies for exact and human sciences. The list of responsibilities of library DH-centers is considered: building digital collections for scientific or educational purposes; creating tools for databases identification, formation, and analysis; management of research process, support of websites, digital publication and storage of research results; organization of training in the field of DH, creation of lecture courses and programs, organization of seminars and conferences, cooperation with similar structural units of other institutions.
42
Chen, Pei-Fu, Ssu-Ming Wang, Wei-Chih Liao, Lu-Cheng Kuo, Kuan-Chih Chen, Yu-Cheng Lin, Chi-Yu Yang, Chi-Hao Chiu, Shu-Chih Chang, and Feipei Lai. "Automatic ICD-10 Coding and Training System: Deep Neural Network Based on Supervised Learning." JMIR Medical Informatics 9, no. 8 (August 31, 2021): e23230. http://dx.doi.org/10.2196/23230.
Full textAbstract:
Background The International Classification of Diseases (ICD) code is widely used as the reference in medical system and billing purposes. However, classifying diseases into ICD codes still mainly relies on humans reading a large amount of written material as the basis for coding. Coding is both laborious and time-consuming. Since the conversion of ICD-9 to ICD-10, the coding task became much more complicated, and deep learning– and natural language processing–related approaches have been studied to assist disease coders. Objective This paper aims at constructing a deep learning model for ICD-10 coding, where the model is meant to automatically determine the corresponding diagnosis and procedure codes based solely on free-text medical notes to improve accuracy and reduce human effort. Methods We used diagnosis records of the National Taiwan University Hospital as resources and apply natural language processing techniques, including global vectors, word to vectors, embeddings from language models, bidirectional encoder representations from transformers, and single head attention recurrent neural network, on the deep neural network architecture to implement ICD-10 auto-coding. Besides, we introduced the attention mechanism into the classification model to extract the keywords from diagnoses and visualize the coding reference for training freshmen in ICD-10. Sixty discharge notes were randomly selected to examine the change in the F1-score and the coding time by coders before and after using our model. Results In experiments on the medical data set of National Taiwan University Hospital, our prediction results revealed F1-scores of 0.715 and 0.618 for the ICD-10 Clinical Modification code and Procedure Coding System code, respectively, with a bidirectional encoder representations from transformers embedding approach in the Gated Recurrent Unit classification model. The well-trained models were applied on the ICD-10 web service for coding and training to ICD-10 users. With this service, coders can code with the F1-score significantly increased from a median of 0.832 to 0.922 (P<.05), but not in a reduced interval. Conclusions The proposed model significantly improved the F1-score but did not decrease the time consumed in coding by disease coders.
43
Khrupovych, Svitlana, and Tetiana Borysova. "Using of an artificial intelligence in the marketing analysis of unstructured data." Marketing and Digital Technologies 5, no. 1 (March 14, 2021): 17–26. http://dx.doi.org/10.15276/mdt.5.1.2021.2.
Full textAbstract:
The aim of the article. The aim of the article is to find effective ways to use an artificial intelligence in the marketing analysis of unstructured data. This will allow us to highlight the benefits of using big data in marketing. To develop end-to-end analytics, it is necessary to develop a scheme of aggregation of personalized information about the client. Analyses results. It is established that the accumulated information in marketing contains a huge potential for new knowledge and can provide many new opportunities for decision-making. Unstructured data is described as information that does not have a predefined data model, or is poorly organized and structured. This data can be obtained from video content, e-mails, images, social media posts, PDF files. The article proposes systematization of unstructured data in accordance with content sources. Unstructured data analysis will allow us to model a portrait of the target consumer; study and analyze loyal consumer demands through automated content analysis of social networks; to influence consumer behavior through personalized communication content; set up personalized advertising appeals; effectively forecast production costs for the creation of new products and the withdrawal from the market of those, that are not in demand; generate and retain the target audience. Artificial intelligence technology makes unstructured data an extremely valuable resource for marketing analytics to their automated processing. It is noted that the biggest advantage of using unstructured data in marketing is that artificial intelligence can analyze texts by scanning emails and processing documents by word processors. Data mining through smart machine algorithms also allows marketers to see hidden patterns and identify associations of events, sequences of events and the correlation between them. The tools of practice of the individualized approach in marketing which work on the basis of big data are highlighted. Contextual advertising, which with the help of artificial intelligence algorithms itself "guesses" that the potential customer is looking for, having only keywords from the given parameters. Chatbots are ready to answer standardized questions round-the-clock. Using this artificial intelligence program helps reduce marketing costs, optimize customer service time, and increase conversions. It is investigated that the world practice of marketing analytics in big data processing is based on a powerful and free Microsoft Power BI platform. It is noted that the introduction of such end-to-end analytics through the integration of all data sources, can significantly increase profitability. A business process model of unstructured data analytics based on the Microsoft Power BI platform is proposed. Among the basic benefits that we can get from the use of artificial intelligence in the analysis of unstructured data in order to personalize content, is the formation of a portrait of each client. This data, combined with specialized analytical information processing software, enables marketers to move from understanding the customer-consumer to the customer-person. Conclusions and directions for further research. The research conducted in the field of using artificial intelligence algorithms for the practical direction of marketing analysis of unstructured data, indicates to us that we can better target proposals for individual consumers. In summary, we note that cognitive technologies and analytical platforms based on artificial intelligence allow us to understand the visual image and text through machine learning. This process can only be ensured by creating a partnership between the human consumer and the computer systems of various business areas. Replacing routine work with a machine algorithm of artificial intelligence will allow the cognitive system to use unstructured data to improve marketing analytics in the context of personalizing content for each consumer. Keywords: marketing analysis, unstructured data, artificial intelligence, information, cognitive system.
44
CHRISTOPHE, BENOIT. "MANAGING MASSIVE DATA OF THE INTERNET OF THINGS THROUGH COOPERATIVE SEMANTIC NODES." International Journal of Semantic Computing 06, no. 04 (December 2012): 389–408. http://dx.doi.org/10.1142/s1793351x12400120.
Full textAbstract:
The Internet of Things refers to extending the Internet to physical entities of interest (EoI) to humans (e.g., a table, a room or another human being) sensed as a set of properties that can be observed, measured, accessed or triggered by devices such as actuators, sensors or other smart components. In this vision, the IoT foresees novel types of applications dynamically finding the associations between devices and EoIs around a common feature of interest (e.g., temperature of a room) to provide meaningful information as well as rich services to users about the things they are interested in. Growing interest in providing sensors and actuators has led to billions of services or data offered through different platforms, some of them wrapped with semantic descriptions to realize aforementioned associations through accurate search processes. However, due to the ubiquitous aspect of the IoT and the potential mobility of the devices that enable it, a centralized approach does not allow designing scalable processes to efficiently search and manage these associations or the devices and EoIs that compose them. As location seems to be an important parameter when searching the IoT, we believe that designing a framework composed of geographically distributed nodes with local reasoning capabilities is a much more scalable approach to realize the IoT vision. We describe our approach of such a vision by creating a federated network composed of such nodes that declare their location based on a formal model. In this vision, each node is capable of processing semantic descriptions of devices or EoIs to share deduced associations with other peers that are selected based on their location nearness.
45
Lynn, Christopher W., Lia Papadopoulos, Ari E. Kahn, and Danielle S. Bassett. "Author Correction: Human information processing in complex networks." Nature Physics 16, no. 12 (July 7, 2020): 1238. http://dx.doi.org/10.1038/s41567-020-0985-7.
Full text
46
Ramtohul, Arvind, and Kavi Kumar Khedo. "Mobile Positioning Techniques and Systems: A Comprehensive Review." Mobile Information Systems 2020 (September 16, 2020): 1–18. http://dx.doi.org/10.1155/2020/3708521.
Full textAbstract:
The recent developments in mobile positioning technologies and the increasing demands of ubiquitous computing have significantly contributed to sophisticated positioning applications and services. Position information represents a core element in the human-centred activities, assisting in visualising complex environments effectively and providing a representational coordinate for localisation, tracking, and navigation purposes. The emergence of smartphones has accelerated the development of cutting-edge positioning-based systems since they are contained to have more processing, memory, and battery power. Similarly, mobile devices are now equipped with new sensory capabilities, wireless communications, and localisation technologies. This has quadrupled towards new advances on positioning techniques, enhancing the existing ones and brought more value to positioning-based systems. Research studies in positioning techniques have progressed in different directions, and no work has categorised and assessed the various advancements in this area. Accuracy and precision are the two challenging aspects that are crucial to the proper functioning of a positioning system. In practice, there is not a single positioning technique that could be appropriate for different situations. Most of the survey papers have focussed on carrying out their review on conventional positioning techniques. The common positioning technique uses simple technologies and is applied to a single type of environment. Hybrid techniques are the next generation of positioning technique that is supporting the real and com plex environment. This paper presents a comprehensive review on the mobile positioning techniques and systems. A total of 21 positioning systems published between the years 2012 and 2018 in the top 5 most popular indexed databases are reviewed. The positioning techniques are identified and streamlined through a methodical process, and the selected ones are reviewed using derived parameters. This paper provides a significant review of the current state of the mobile positioning techniques and outlines the research issues that require more investigation.
47
Çeloaliaj, Merisa. "GENERAL REGULATION ON PERSONAL DATA PROTECTION. CERTAIN ASPECTS OF THE GDPR'S IMPACT ON LEGAL ENTITIES IN THE REPUBLIC OF ALBANIA." Knowledge International Journal 34, no. 5 (October 4, 2019): 1487–90. http://dx.doi.org/10.35120/kij34051487m.
Full textAbstract:
Actuality, recent, has made us witnesses of rapid technological developments, as part of the globalization process, which inevitably affect to our lives.Technological developments facilitate our day-to-day life starting from the most common aspects and advancing at the speed of light to more complex processes that the human mind would not have been able to solve in the same space of time and with the same resources utilized. Free movement, downloading different apps on our smartphones, shopping online or the registering on social networks are just some of the activities that each of us performs daily, often without being aware of what brings these activities together is actually an action, which is legally called "processing of personal data of the individual".Often with the help of technology, private companies and public authorities collect personal information from clients, services receivers or ordinary citizens and they use it to an unprecedented extent in the pursuit of their activities and goals. The protection of personal data of individuals is in fact a fundamental right, which is sanctioned by a legislation of particular importance in international and domestic law.Even in the Albanian legal order, the right to protection of personal data is sanctioned by a specific legal corpus. In the context of the particular importance of the sensitivity that personal data bears, the European Union has adopted the GDPR, an improved act that reinforces the level of protection of the individual against bureaucracy and rapid technological developments.This modest paper focuses on the impact of this regulation in Albania on public and private legal entities that collect and process personal data.How will the GDPR affect, as an act focusing on respect for private and family life, housing and communications, personal data protection, free thought, conscience and religion, freedom of expression and information, freedom to perform business, the right to effective protection and fair trial in terms of cultural, religious and linguistic diversity, decision-making and activity of various entities in the Republic of Albania?The structure of this paper includes in the introductory section a brief history of the relevant legal acts, goes on to explain some specific terms and addresses important aspects of the impact on legal entities of the latest European Union regulation in the field of protection of personal data.
48
Caputo, Richard K. "Book Review: Information and Referral Networks: Doorways to Human Services." Families in Society: The Journal of Contemporary Social Services 71, no. 5 (May 1990): 315–17. http://dx.doi.org/10.1177/104438949007100515.
Full text
49
Delazari, Luciene Stamato, Leonardo Ercolin Filho, and Ana Luiza Stamato Delazari Skroch. "UFPR CampusMap: a laboratory for a Smart City developments." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-57-2019.
Full textAbstract:
<p><strong>Abstract.</strong> A Smart City is based on intelligent exchanges of information that flow between its many different subsystems. This flow of information is analyzed and translated into citizen and commercial services. The city will act on this information flow to make its wider ecosystem more resource-efficient and sustainable. The information exchange is based on a smart governance operating framework designed to make cities sustainable.</p><p>The public administration needs updated and reliable geospatial data which depicts the urban environment. These data can be obtained through smart devices (smartphones, e.g.), human agents (collaborative mapping) and remote sensing technologies, such as UAV (Unnamed Aerial Vehicles). According to some authors, there are four dimensions in a Smart City. The first dimension concerns the application of a wide range of electronic and digital technologies to create a cyber, digital, wired, informational or knowledge-based city; the second is the use of information technology to transform life and work; the third is to embed ICT (Information and Communication Technology) in the city infrastructure; the fourth is to bring ICT and people together to enhance innovation, learning, and knowledge. Analyzing these dimensions, it is possible to say that in all of them the geospatial information is crucial, otherwise, none of them are possible. Considering these aspects, this research intends to use the Smart City concept as a methodological approach using the UFPR (Federal University of Parana) as a target to develop a case study.</p><p>The UFPR has 26 campus in different cities of the Paraná State, south of Brazil. Its structure has 14 institutes. It comprises 11 million square meters of area, 500,000 square meters of constructed area and 316 buildings. There are more than 6,300 employees (staff and administration), 50,000 undergraduate students and 10,000 graduate students. Besides these figures, there are external people who need access to the UFPR facilities, such as deliveries, service providers and the community in general.</p><p>The lack of knowledge about the space and its characteristics has a direct impact on issues such as resources management (human and material), campi infrastructure (outside and inside of the buildings), security and other activities which can be supported using an updated geospatial database. In 2014, the UFPR CampusMap project was started with the indoor mapping as the main goal. However, the base map of the campus was needed in order to support the indoor mapping, the available one was produced in 2000. Thereafter, the campus Centro Politécnico (located in the city of Curitiba) is being used as a case study to develop methodologies to create a geospatial database which will allows to different users the knowledge and management of the space.</p><p>According to Gruen (2013), a Smart City must have spatial intelligence. Moreover, it is necessary the establishment of a database, in particular, a geospatial database. The knowledge of the space where the events happen is a key element in this context. This author also states that to achieve this objective are necessary the following items:</p> <ul><li>Automatic or semi-automated Digital Surface Models (DSM) generation from satellite, aerial and terrestrialimages and/or LiDAR data;</li><li>Further development of the semi-automated techniques onto a higher level of automation; </li><li>Integrated automated and semi-automated processing of LiDAR point clouds and images, both from aerial andterrestrial platforms; </li><li>Streamlining the processing pipeline for UAV image data projects; </li><li>Set-up of GIS with 3D/4D capabilities; </li><li>Change detection and databases updating; </li><li>Handling of dynamic and semantic aspects of city modeling and simulation. This leads to 4D city models; </li><li>LBS (Location Based Services) system investigations (PDAs, mobiles); and </li><li>Establishment of a powerful visualization and interaction platform.</li></ul><p>Some of these aspects are being addressed in this research. The first one is the integration of indoor/outdoor data to helps the space management and provides a tool for navigation between the spaces. The base map was updated through a stereo mapping compilation from images collected using a UAV Phantom 4 from DJI (https://www.dji.com/phantom-4). The use of this technology for data acquisition is not only faster but also cheaper compared to the traditional photogrammetric method. Besides the quality of the images (in this case a GSD – Ground Sample Distance – of 2,5 cm), it can be use in urban areas as a rapid response in emergency situations.</p><p> To georreferencing the image block, it was used 50 control points collected by GNSS (Global Navigation Satellite System) and the software Agisoft Photoscan (http://www.agisoft.com/) to perform the bundle block adjustment with self-calibration. After the processing, the exterior orientation parameters of image block and the tridimensional coordinates of each tie point were calculated simultaneously with the determination of the interior orientation parameters: focal length (f), principal point coordinates (x0, y0), radial symmetric (k1, k2, k3) and decentering distortion coefficients (p1, p2).</p><p> In the mapping production step, the features were extracted through stereo mapping compilation accordingly the standards defined by the Brazilian Mapping Agency. The several layers were edited in GIS software (QGIS) and then the topology was built. Afterward, it was created a spatial database using Postgre/PostGIS. Also, the dense point cloud was generated using SfM (Structure from Motion) algorithms to allow to generate the digital surface model and orthomosaics.</p><p> Meanwhile, a website using HTML5+CSS3&reg; and JavaScript&reg; technologies was developed to publish the results and the first applications. (www.campusmap.ufpr.br). The architecture of this application uses JavaScript&reg;, LeafLet, PgRouting library (to calculate the routes between interest points), files in GeoJson format and custom applications. The indoor database comprises the data about the interior of the buildings and provides to the user some functionalities such as: search for rooms, laboratories, and buildings; routes between points (inside and outside the buildings), floor change. Also, some web applications were developed in order to demonstrate the capabilities of the use of geospatial information in an environment very similar to a city and its problems, e.g. parking management, security, logistics, resources inventory, among others. It was developed a mobile application to provide the indoor user positioning through Wi-Fi (Wireless Fidelity) networks. This, combined with the indoor mapping, will allow the users to navigate in real time inside the buildings. Using the data from the point cloud and the CityGML standard it was developed a 3D model of some buildings. An application to inform crime occurrences (such as robbery, assaults) was also developed so these occurrences can be mapped, and the administration can increase the security of the campus.</p><ol type="a"> <li>Design an interface with functionalities to integrate all applications which are being presented in individual Webpages;</li><li>Develop a visualization tool for 3D models using CityGML;</li><li>Evaluate the potential of UAV images for different applications in urban scenarios;</li><li>Develop an interface for collaborative database update.</li><li>Expand the database to other campus of UFPR and develop new functionalities to different users;</li></ol><p> The “smart city” concept allows to develop an optimized system that use geospatial data to understand the complexity of the urban environments. The use of the geospatial data can improve efficiency and security to manage urban aspects like infrastructure, building and public spaces, natural environment, urban services, health and education. Also, this concept can give a support to the city management agents during the design, realization and evaluation of the urban projects.</p><p>In the present project, we believe these are the first steps to build a connected environment and apply the “smart city” concept into the university administration to make the sustainable use of resources and could suit as an example to some existing problems in public administrations.</p>
50
Macpherson, Karen. "An information processing model of undergraduate electronic database information retrieval." Journal of the American Society for Information Science and Technology 55, no. 4 (2004): 333–47. http://dx.doi.org/10.1002/asi.10385.
Full text