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Journal articles on the topic 'Data dimension'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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1

Yasmine Aljarallah, Mutasim Alfadhel. "Data Governance Evaluation of the Data Management Office at King Saud University based on the National Data Management Office standards." Journal of Information Systems Engineering and Management 10, no. 10s (2025): 794–805. https://doi.org/10.52783/jisem.v10i10s.1530.

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This study aimed to investigate the implementation of data governance at the Data Management Office of King Saud University by examining the adoption of the strategic plan, implementation mechanisms, and compliance with data governance standards and controls established by the National Data Management Office (NDMO), the national regulatory and reference authority for data management and governance.Using a descriptive-analytical approach, a questionnaire was designed based on three dimensions: the strategic dimension, the executive dimension, and the challenges dimension. The study sample inclu
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Adi Wicaksana, I. Gusti Ngurah, Achmad Nizar Hidayanto, Handini Mekkawati, and Rizha Febriyanti. "DATA QUALITY ASSESSMENT: A CASE STUDY ON ASSET VALUATION COMPARISON DATA." JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) 9, no. 2 (2024): 263–72. http://dx.doi.org/10.33480/jitk.v9i2.5184.

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To realize a data-driven organization, good data quality is needed as a foundation for solving various problems related to data management. The case study used in this research is asset valuation comparison data. The purpose of this research is to define dimensions, measure and analyze data quality on asset valuation comparison data. There are three dimensions used in measuring data quality in this study which are adjusted based on existing regulations at Ministry X, namely accuracy, completeness, and validity. This research uses the stages in the Total Data Quality Management (TDQM) framework
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Zhihui, Ni, Wu Lichun, Wang Ming-hui, Yi Jing, and Zeng Qiang. "The Fractal Dimension of River Length Based on the Observed Data." Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/327297.

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Although the phenomenon that strictly meets the constant dimension fractal form in the nature does not exist, fractal theory provides a new way and means for the study of complex natural phenomena. Therefore, we use some variable dimension fractal analysis methods to study river flow discharge. On the basis of the flood flow corresponding to the waterline length, the river of the overall and partial dimensions are calculated and the relationships between the overall and partial dimensions are discussed. The law of the length in section of Chongqing city of Yangtze River is calibrated by using
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Le Dinh, Thang, Nguyen Anh Khoa Dam, Chan Nam Nguyen, Thi My Hang Vu, and Nguyen Cuong Pham. "From Customer Data to Smart Customer Data: The Smart Data Transformation Process." ITM Web of Conferences 41 (2022): 05002. http://dx.doi.org/10.1051/itmconf/20224105002.

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Nowadays, smart data has emerged as a new trend in creating more business value for enterprises that is defined as the data that is gathered and processed to create new insights to support business decisions. However, the transformation from data into actionable insights is still a real challenge for enterprises. For this reason, this paper presents a smart data transformation process, which aims at transforming customer data into smart customer data in order to offer actionable insights. The purpose of the study is to propose a transformation process that can be used to operate a knowledge st
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Kuffo, Leonardo, Elena Krippner, and Peter Boncz. "PDX: A Data Layout for Vector Similarity Search." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–26. https://doi.org/10.1145/3725333.

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We propose Partition Dimensions Across (PDX), a data layout for vectors (e.g., embeddings) that, similar to PAX [6], stores multiple vectors in one block, using a vertical layout for the dimensions (Figure 1). PDX accelerates exact and approximate similarity search thanks to its dimension-by-dimension search strategy that operates on multiple-vectors-at-a-time in tight loops. It beats SIMD-optimized distance kernels on standard horizontal vector storage (avg 40% faster), only relying on scalar code that gets auto-vectorized. We combined the PDX layout with recent dimension-pruning algorithms A
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Rossi, Rogério, and Kechi Hirama. "Characterizing Big Data Management." Issues in Informing Science and Information Technology 12 (2015): 165–80. http://dx.doi.org/10.28945/2204.

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Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dime
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Ummu Hani’ Hair Zaki, Izyan Izzati Kamsani, Roliana Ibrahim, Norzehan Sakamat, and Eser Kandogan. "Random Dimension Manipulation for Efficient High-Dimensional Data Clustering." Journal of Advanced Research in Applied Sciences and Engineering Technology 51, no. 1 (2024): 129–40. http://dx.doi.org/10.37934/araset.51.1.129140.

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High-dimensional data is collected from various sources, fields, and applications such as medicine, science, business and more to provide helpful information to others. Unfortunately, the complexity of high-dimensional data has made it difficult to interpret and understand. As a result, sophisticated data analysis is required to extract knowledge and information from it. This can be illustrated through a visualization presentation. However, overlap between data can occur during visualization as data increases. Indirectly, it can cause a cluttered visual presentation. As a result, it affects th
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Hu, Yong De, Jing Chang Pan, and Xin Tan. "High-Dimensional Data Dimension Reduction Based on KECA." Applied Mechanics and Materials 303-306 (February 2013): 1101–4. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1101.

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Kernel entropy component analysis (KECA) reveals the original data’s structure by kernel matrix. This structure is related to the Renyi entropy of the data. KECA maintains the invariance of the original data’s structure by keeping the data’s Renyi entropy unchanged. This paper described the original data by several components on the purpose of dimension reduction. Then the KECA was applied in celestial spectra reduction and was compared with Principal Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) by experiments. Experimental results show that the KECA is a good method
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Vlassis, Nikos, Yoichi Motomura, and Ben Kröse. "Supervised Dimension Reduction of Intrinsically Low-Dimensional Data." Neural Computation 14, no. 1 (2002): 191–215. http://dx.doi.org/10.1162/089976602753284491.

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High-dimensional data generated by a system with limited degrees of freedom are often constrained in low-dimensional manifolds in the original space. In this article, we investigate dimension-reduction methods for such intrinsically low-dimensional data through linear projections that preserve the manifold structure of the data. For intrinsically one-dimensional data, this implies projecting to a curve on the plane with as few intersections as possible. We are proposing a supervised projection pursuit method that can be regarded as an extension of the single-index model for nonparametric regre
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Badakhshan Farahabadi, Fazel, Kianoush Fathi Vajargah, and Rahman Farnoosh. "Dimension Reduction Big Data Using Recognition of Data Features Based on Copula Function and Principal Component Analysis." Advances in Mathematical Physics 2021 (July 11, 2021): 1–8. http://dx.doi.org/10.1155/2021/9967368.

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Nowadays, data are generated in the world with high speed; therefore, recognizing features and dimensions reduction of data without losing useful information is of high importance. There are many ways to dimension reduction, including principal component analysis (PCA) method, which is by identifying effective dimensions in an acceptable level, reducing dimension of data. In the usual method of principal component analysis, data are usually normal, or we normalize data; then, the principal component analysis method is used. Many studies have been done on the principal component analysis method
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Vincentia, Audri Senduk, and Rachmawati Dyna. "Control of Service Quality Indicators on Wooden Floor Retail "Flooring Parquete"." International Journal of Management, Accounting and Economics 9, no. 8 (2022): 517–30. https://doi.org/10.5281/zenodo.7028300.

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CV. Ladang Berkat Abadi is a company in Surabaya that has a brand called Flooring Parquete. Flooring Parquete is engaged in wood floor retail. As one of the businesses engaged in services, of course, it requires special attention to the quality of service provided to its customers. This study aims to analyze the control of indicators / dimensions of service quality owned by Flooring Parquete in providing service quality. The five indicators are the dimension of physical evidence, the dimension of reliability, the dimension of responsiveness, the dimension of assurance, and the dimension of emp
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Yan, Loh Guan, Nuryazmin Ahmat Zainuri, and Mohd Zaki Nuawi. "Characterization of Musical Data Signals Resulting from Traditional Musical Instruments Using Fractal Features." Jurnal Kejuruteraan si6, no. 2 (2023): 167–78. http://dx.doi.org/10.17576/jkukm-2023-si6(2)-18.

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Musical instruments are usually distinguished by their sound produced through human perception which may lead to misinterpretation due to auditory perception bias and other disturbances. Therefore, recognition using music signals is carried out to help characterize signals from different musical instruments. Fractal analysis is a mathematical tool used to study complex and irregular patterns in various systems. In this study, fractal analysis was used to study and analyze musical notes signal data from different instruments. The fractal analysis method used is the box counting method. The trad
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Li, Zhizhong, Chien-Chi Chang, Patrick G. Dempsey, Lusha Ouyang, and Jiyang Duan. "Validation of a three-dimensional hand scanning and dimension extraction method with dimension data." Ergonomics 51, no. 11 (2008): 1672–92. http://dx.doi.org/10.1080/00140130802287280.

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Li, Yehua, and Tailen Hsing. "Deciding the dimension of effective dimension reduction space for functional and high-dimensional data." Annals of Statistics 38, no. 5 (2010): 3028–62. http://dx.doi.org/10.1214/10-aos816.

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Lee, Yeon Kyeong, and Taejong Kim. "Analyzing and Reflecting on Generational Issue Changes in K-POP Idol Groups: Focusing on News Big Data." Korean Society of Culture and Convergence 45, no. 10 (2023): 143–62. http://dx.doi.org/10.33645/cnc.2023.10.45.10.143.

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This study aims to identify the major issues in the news big data related to generational idols formed by the growth and development of idols amid the current global spread of K-pop, and to suggest ways to strengthen the competitiveness of the Korean music industry by identifying the major issues that are being formed through the media for each generation of K-pop idols and how they have changed. For this purpose, news big data LDA technique was used as a topic modeling analysis method for 55,660 cases, and as a result of the topic modeling analysis, common issue types of six dimensions were d
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Putri, Angela Suryani, and Roziah Roziah. "Investigating Prospective Teachers’ Competences in Understanding Religious Dimensions in Poetry ‘Perang Pecah Lagi Di Gaza’." Journal of Languages and Language Teaching 12, no. 3 (2024): 1253. http://dx.doi.org/10.33394/jollt.v12i3.11309.

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Religiosity refers to the extent of insight and knowledge one has about their religion, the strength of their belief in carrying out worship and following rules, and the depth of their absorption in their faith. Religiosity can be classified into several dimensions. According to Stark and Glock, these dimensions are divided into five categories: Religious Belief (The Ideological Dimension), Religious Practice (The Ritualistic Dimension), Religious Feeling (The Experiential Dimension), Religious Knowledge (The Intellectual Dimension), and Religious Effect (The Consequential Dimension). This res
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Gabr, Menna Ibrahim, Yehia M. Helmy, and Doaa Saad Elzanfaly. "DATA QUALITY DIMENSIONS, METRICS, AND IMPROVEMENT TECHNIQUES." Future Computing and Informatics Journal 6, no. 1 (2021): 25–44. http://dx.doi.org/10.54623/fue.fcij.6.1.3.

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Achieving high level of data quality is considered one of the most important assets for any small, medium and large size organizations. Data quality is the main hype for both practitioners and researchers who deal with traditional or big data. The level of data quality is measured through several quality dimensions. High percentage of the current studies focus on assessing and applying data quality on traditional data. As we are in the era of big data, the attention should be paid to the tremendous volume of generated and processed data in which 80% of all the generated data is unstructured. H
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Habibie, Khairul, Suhardi Suhardi, and Wardani Muhamad. "Implementation of Data Governance on the Open Government Data Management Platform to Improve Data Quality." IJAIT (International Journal of Applied Information Technology) 7, no. 02 (2023): 92. http://dx.doi.org/10.25124/ijait.v7i02.5979.

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Currently, realizing good governance related to data disclosure in government agencies is an initiative as a manifestation of open government data. However, there are still problems with the quality of published data. As a solution, organizations need to establish policies, strategies, and initiatives for data management activities This paper proposes adding data management activities to the platform to enhance the quality of published data. As for the value of the quality of the data tested using the XYZ district budget, there is an increase in the uniqueness quality dimension from valid DQI
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Wang, Dong, Haipeng Shen, and Young Truong. "Efficient dimension reduction for high-dimensional matrix-valued data." Neurocomputing 190 (May 2016): 25–34. http://dx.doi.org/10.1016/j.neucom.2015.12.096.

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Cao, Wen, Wenhao Liu, Xiaochong Tong, et al. "A Management Method of Multi-Granularity Dimensions for Spatiotemporal Data." ISPRS International Journal of Geo-Information 12, no. 4 (2023): 148. http://dx.doi.org/10.3390/ijgi12040148.

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To understand the complex phenomena in social space and monitor the dynamic changes in people’s tracks, we need more cross-scale data. However, when we retrieve data, we often ignore the impact of multi-scale, resulting in incomplete results. To solve this problem, we proposed a management method of multi-granularity dimensions for spatiotemporal data. This method systematically described dimension granularity and the fuzzy caused by dimension granularity, and used multi-scale integer coding technology to organize and manage multi-granularity dimensions, and realized the integrity of the data
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Liu, Chunting, Shanshan Wang, and Guozhu Jia. "Exploring E-Commerce Big Data and Customer-Perceived Value: An Empirical Study on Chinese Online Customers." Sustainability 12, no. 20 (2020): 8649. http://dx.doi.org/10.3390/su12208649.

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The purpose of this study is to make good use of the massive amount of online user comment data to explore and analyze the dimensions of customer-perceived value and the importance of each dimension, given the background of China’s huge e-commerce market. We compiled a web crawler program to collect online comment data from online reviews. The crawled data were pre-processed and content analysis were performed. A customer-perceived value dictionary was constructed based on the extraction of frequent terms, literature review, and expert opinions. We re-identified the dimensions of customer-perc
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Aris, Muhammad, Murdjani Kamaluddin, and Muhammad Masri. "PENGARUH DIMENSI KUALITAS PELAYANAN TERHADAP KEPUASAN MASYARAKAT PADA PROSES PEMBUATAN SIM DI SATLANTAS SATUAN PENYELENGGARA ADMINISTRASI SIM (SATPAS) POLRES KENDARI." Jurnal Manajemen, Bisnis dan Organisasi (JUMBO) 4, no. 3 (2021): 121. http://dx.doi.org/10.33772/jumbo.v4i3.16678.

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The purpose of this study was to determine the effect; 1) Simultaneously the dimensions of service quality consisting of tangibles, reliability, responsiveness, assurance, on community satisfaction. 2) partially the tangible dimension to community satisfaction. 3) partially the dimension of reliability to community satisfaction. 4) partially the dimensions of responsiveness to community satisfaction. 5) partially the dimension of assurance to community satisfaction. 6) partially the dimension of empathy to community satisfaction. The research design used is quantitative research. The data used
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Jiang, Qing Chao. "The Research of High-Dimensional Big Data Dimension Reduction Strategy." Applied Mechanics and Materials 710 (January 2015): 121–26. http://dx.doi.org/10.4028/www.scientific.net/amm.710.121.

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With the increase of data dimension, many low dimensional mining algorithms cannot get satisfactory results. With the increase of data dimension, it can produce a large amount of redundant information; this information will greatly reduce the efficiency of mining, increasing the complexity of the mining algorithm. Feature selection is an efficient way to solve the problem; it can remove a lot of irrelevant and redundant features. In this paper, on the basis of Lars algorithm applying differential evolution thought to the extraction of feature subset, puts forward a new method of feature select
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Wang, Hu. "Clustering statistical method of high dimensional sparse data based on fuzzy data." Journal of Physics: Conference Series 2791, no. 1 (2024): 012060. http://dx.doi.org/10.1088/1742-6596/2791/1/012060.

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Abstract Developing effective clustering and statistical methods for high-dimensional sparse data presents unique challenges compared to traditional low-dimensional data. To address this, a novel approach is proposed, leveraging fuzzy data principles to enhance the clustering and statistical performance of high-dimensional sparse datasets. The method builds upon the fuzzy C-means clustering algorithm, introducing key modifications for better suitability to high-dimensional sparse data. One crucial enhancement involves tackling the local optimization problem by optimizing the initial clustering
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He, Qing, Xiurong Zhao, and Zhongzhi Shi. "Classification based on dimension transposition for high dimension data." Soft Computing 11, no. 4 (2006): 329–34. http://dx.doi.org/10.1007/s00500-006-0085-3.

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Fernández-Domínguez, Juan Carlos, Isabel Escobio-Prieto, Albert Sesé-Abad, Rafael Jiménez-López, Natalia Romero-Franco, and Ángel Oliva-Pascual-Vaca. "Health Sciences—Evidence Based Practice Questionnaire (HS-EBP): Normative Data and Differential Profiles in Spanish Osteopathic Professionals." International Journal of Environmental Research and Public Health 17, no. 22 (2020): 8454. http://dx.doi.org/10.3390/ijerph17228454.

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The main goal of this study was to obtain normative data of the scores of the Health-Sciences Evidence Based Practice (HS-EBP) questionnaire, and to analyse evidence-based practice (EBP) among potential clusters of osteopathy professionals in Spain. An online descriptive cross-sectional study has been applied. A total number of 443 Spanish practicing osteopaths answered a survey including the 5 dimensions of the HS-EBP questionnaire and sociodemographic, training, and practice variables using the “LimeSurvey” online platform. Results point out that the median scores for each five HS-EBP questi
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Sadeli, Annisa Fajriyati, and Indira Irawati. "Awareness of Personal Data Protection Law in concern to literacy." Jurnal Kajian Informasi & Perpustakaan 11, no. 2 (2023): 241. http://dx.doi.org/10.24198/jkip.v11i2.47526.

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Understanding privacy literacy can help everyone treat their personal data shared on online platforms. Data protection starts from the idea that individuals have the right to information about themselves. There must be efforts to prevent misuse; hence, it makes digital literacy important. This research aimed to measure students' understanding of the importance of protecting personal data in the PDP Law based on the categories of knowledge, attitudes, and behavior. The research used quantitative methods with an analytical survey approach. Data analysis techniques used the Analytical Hierarchy P
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Barry, Christine A. "Choosing Qualitative Data Analysis Software: Atlas/ti and Nudist Compared." Sociological Research Online 3, no. 3 (1998): 16–28. http://dx.doi.org/10.5153/sro.178.

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Choosing between Nudist and Atlas/ti, the main qualitative data analysis software packages can be difficult. To assist researchers in making this choice, I have conceptualised their differences along two dimensions, related to the qualities of the software and of the research project. The software dimension is structural design, and the project dimension is complexity. Software structure is dichotomised between structured, sequential, verbal versus visual, spatial, interconnected modes of operation. Projects are dichotomised between homogeneous sample, short timeframe, single data-type, single
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Auladi, Ahmad Yusron, Dwi Rukmini, and Djoko Sutopo. "The Implementation of Cultural Dimensions in The “Bahasa Inggris” English Textbook for Eleventh Graders." English Education Journal 9, no. 1 (2018): 107–13. http://dx.doi.org/10.15294/eej.v9i1.27938.

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This study aims at explaining the implementation of the cultural dimensions in the textbook. There are four cultural dimensions analysed in this research, they are product, practice, perspective, and person (Moran, 2001). Product dimension refers to goods and services. Practice dimension refers to how the member of culture manipulates the product. Perspective dimension refers to perceptions, beliefs, and attitudes. Person dimension refers to the personal experience and story of the cultural members. This study applied descriptive qualitative research with interactive data analysis, consisting
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Wang, Tong, Wenan Tan, and Jianxin Xue. "A Data Mining Method For Improving the Prediction Of Bioinformatics Data." Journal of Physics: Conference Series 2137, no. 1 (2021): 012067. http://dx.doi.org/10.1088/1742-6596/2137/1/012067.

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Abstract The composition of proteins nearly correlated with its function. Therefore, it is very ungently important to discuss a method that can automatically forecast protein structure. The fusion encoding method of PseAA and DC was adopted to describe the protein features. Using this encoding method to express protein sequences will produce higher dimensional feature vectors. This paper uses the algorithm of predigesting the characteristic dimension of proteins. By extracting significant feature vectors from the primitive feature vectors, eigenvectors with high dimensions are changed to eigen
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Zhang, Hongjun, Youliang Zhang, and Rui Zhang. "Dimension-Specific Efficiency Measurement Using Data Envelopment Analysis." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/247248.

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Data envelopment analysis (DEA) is a powerful tool for evaluating and improving the performance of a set of decision-making units (DMUs). Empirically, there are usually many DMUs exhibiting “efficient” status in multi-input multioutput situations. However, it is not appropriate to assert that all efficient DMUs have equivalent performances. Actually, a DMU can be evaluated to be efficient as long as it performs best in a single dimension. This paper argues that an efficient DMU of a particular input-output proportion has its own specialty and may also perform poorly in some dimensions. Two DEA
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Malekzadeh, Mohammad, Richard Clegg, Andrea Cavallaro, and Hamed Haddadi. "DANA." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (2021): 1–27. http://dx.doi.org/10.1145/3478074.

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Motion sensors embedded in wearable and mobile devices allow for dynamic selection of sensor streams and sampling rates, enabling several applications, such as power management and data-sharing control. While deep neural networks (DNNs) achieve competitive accuracy in sensor data classification, DNN architectures generally process incoming data from a fixed set of sensors with a fixed sampling rate, and changes in the dimensions of their inputs cause considerable accuracy loss, unnecessary computations, or failure in operation. To address these limitations, we introduce a dimension-adaptive po
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Han, Xue, Yue Zhang, and Sheng Gao. "Research on Multidimensional Power Big Data Clustering Algorithm Based on Graph Mode." Journal of Advanced Computational Intelligence and Intelligent Informatics 29, no. 2 (2025): 358–64. https://doi.org/10.20965/jaciii.2025.p0358.

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Power system data possess many characteristics and indicators, having certain high dimensions and redundant information, which can easily increase the calculation and storage overhead. To reduce the dimension of power data, eliminate redundant information, and reduce the delay time, a data clustering algorithm is proposed. Firstly, an algorithm based on PCA and kernel local Fisher identification is used to reduce the dimension of large multidimensional samples and enhance the accuracy of subsequent clustering. Thereafter, the redundant data are processed after dimension reduction is processed
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G. Gupta, Uma, and Ashok Gupta. "Vision: A Missing Key Dimension in the 5V Big Data Framework." Journal of International Business Research and Marketing 1, no. 3 (2015): 40–47. http://dx.doi.org/10.18775/jibrm.1849-8558.2015.13.3005.

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If Big Data is to deliver on its big promises, a well-articulated vision must be developed in a collaborative way and effectively communicated to all key stakeholders. Without a guiding technology vision, the promise and benefits of Big Data will become elusive and lost to many organizations. The literature on Big Data frequently refers to the 5Vs of Big Data (Volume, Variety, Velocity, Veracity and Value). Based on a strategic framework, this paper adds another dimension to this important and widely used framework, namely Vision, and elaborates on the critical role of vision and its relations
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Erawati, Gusti Ayu Putu Sintha Arma, I. Wayan Widiana, and I. Gusti Ngurah Japa. "Elementary School Teachers’ Problems in Online Learning during the Pandemic." International Journal of Elementary Education 5, no. 4 (2021): 562. http://dx.doi.org/10.23887/ijee.v5i4.39233.

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COVID-19 pandemic has caused chaos in various field such as economic, social, tourism and many more. One of the fields that affected to it is in the field of education. The government requires schools in Indonesia to carry out online learning activities from home. This policy certainly raises various problems not only for students but also for teacher, many teachers faced problems during the online learning. This research was conducted to find out the problems experienced by elementary school teachers in online learning during the pandemic. The method of research carried out by the researchers
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Einbeck, Jochen, Zakiah Kalantan, and Uwe Kruger. "Practical Considerations on Nonparametric Methods for Estimating Intrinsic Dimensions of Nonlinear Data Structures." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 09 (2019): 2058010. http://dx.doi.org/10.1142/s0218001420580100.

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This paper develops readily applicable methods for estimating the intrinsic dimension of multivariate datasets. The proposed methods, which make use of theoretical properties of the empirical distribution functions of (pairwise or pointwise) distances, build on the existing concepts of (i) correlation dimensions and (ii) charting manifolds that are contrasted with (iii) a maximum likelihood technique and (iv) other recently proposed geometric methods including MiND and IDEA. This comparison relies on application studies involving simulated examples, a recorded dataset from a glucose processing
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Kumra, Sona. "Data Modeling Techniques for Data Warehouse." International Journal of Advance Research and Innovation 5, no. 2 (2017): 51–53. http://dx.doi.org/10.51976/ijari.521709.

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The conceptual Entity-Relationship (ER) diagrams are extensively used for database design in relational database environment, which emphasized on day-to-day operations. Multidimensional (MD) data modelling, on the other hand, is crucial in data warehouse design, which targeted for managerial decision support. It supports decision making by allowing users to drill-down for a more detailed information, roll-up to view summarized information, slice and dice a dimension for a selection of a specific item of interest and pivot to re-orientate the view of MD data. When designing a MD model regardles
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Zhang, Tonglin, and Baijian Yang. "Dimension reduction for big data." Statistics and Its Interface 11, no. 2 (2018): 295–306. http://dx.doi.org/10.4310/sii.2018.v11.n2.a7.

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Zhang, Wei, Minghua Han, Zishu He, and Huiyong Li. "Data‐dependent reduced‐dimension STAP." IET Radar, Sonar & Navigation 13, no. 8 (2019): 1287–94. http://dx.doi.org/10.1049/iet-rsn.2018.5473.

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Mohan, T. R. Krishna, J. Subba Rao, and R. Ramaswamy. "Dimension Analysis of Climatic Data." Journal of Climate 2, no. 9 (1989): 1047–57. http://dx.doi.org/10.1175/1520-0442(1989)002<1047:daocd>2.0.co;2.

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Kantz, Holger, and Thomas Schreiber. "Dimension estimates and physiological data." Chaos: An Interdisciplinary Journal of Nonlinear Science 5, no. 1 (1995): 143–54. http://dx.doi.org/10.1063/1.166096.

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Kurniadi, Elika, Vina Amalia Suganda, and Bunda Harini. "THE PEDAGOGICAL CONTENT KNOWLEDGE DIMENSIONS OF MATHEMATICS TEACHER IN MATHEMATICS MODELING LEARNING." Prima: Jurnal Pendidikan Matematika 6, no. 2 (2022): 90. http://dx.doi.org/10.31000/prima.v6i2.5381.

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This study aims to explain the dimensions of pedagogical content knowledge of mathematics teachers in learning mathematical modeling. Four dimensions of teacher pedagogical content knowledge for mathematical modeling: (1) Dimension of mathematical modeling theory, (2) Dimension of cognitive, (3) Dimension of learning, and (4) dimension of evaluation. The data collection is observation and interview. Based on the basic assumptions about the impact of teaching on learning, teacher competence will result in quality teaching and quality student learning. Therefore, all of dimensions should be incl
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Hadi, R. R. Hanny Advenia, I. Putu Sudana, and Yohanes Kristianto. "PENGEMASAN PAKET WISATA KEBUGARAN DI DESA SAYAN, KECAMATAN UBUD, KABUPATEN GIANYAR." Jurnal IPTA 11, no. 1 (2023): 23. http://dx.doi.org/10.24843/ipta.2023.v11.i01.p04.

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Wellness and village tourism are one of the travel trends that can be done during the pandemic. To increase interest in this tour, the activities are packaged in an attractive manner, in this study referring to the thematic packaging of fitness tour packages. This research was conducted to determine the potential of wellness tourism in Sayan Village, which was then packaged thematically to become a fitness tour package. The package of this tour package can then be used as a tourism product in Sayan Village. Data collection techniques used in this study, namely observation, in-depth interviews,
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Purwaningtias, Fitri, Muhamad Ariandi, and Maria Ulfa. "Visualisasi Data Kriminal Wilayah Polres Musi Banyuasin." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 1 (2023): 193–202. https://doi.org/10.25126/jtiik.2023105658.

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Tahanan kriminal di wilayah Polres Musi Banyuasin merupakan tahanan yang memiliki catatan kriminalisasi dibidang narkoba, terorisme/separatisme, lalu lintas, kriminal khusus dan kriminal umum. Banyaknya kasus dan data tentang kriminalisasi yang ada di Polres Musi Banyuasin pada tahun 2019-2020 yaitu 652 kasus yang mana data tersebut diolah dengan menggunakan Word begitu juga laporannya yang hanya dipisahkan berdasarkan kasus saja. Karena banyaknya data yang bisa menyebabkan redudansi data ataupun laporan yang bisa terlambat untuk diberikan ke Kapolres MuBa sehingga diperlukan sebuah sistem Bus
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Irwin, Robert D., and Daniel L. Weber. "Factors Influencing the Perceived Urgency of Auditory Stimuli." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 4 (1998): 419–23. http://dx.doi.org/10.1177/154193129804200404.

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The interaction among two spectral and two temporal dimensions that contribute to urgency was investigated by conducting a discrimination experiment. Discrimination performance for each dimension was evaluated when a second dimension (i.e., dimension not being discriminated) was subject to no variation, correlated variation, and uncorrelated variability. For the pair of spectral dimensions and the pair of temporal dimensions, variation on the second dimension produces facilitation in the correlated condition and interference in the uncorrelated condition. No influence occurs for other pairings
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Dashee Dughaim, Alaa, Arezoo Aghaei Chadegani, Mohammed Sameer Deherieb Al Robaaiy, and Mohammad Alimoradi. "Proposing a Model of Sustainability Reporting Dimensions for Manufacturing and Non-Manufacturing Firms Listed on the Stock Exchange." Digital Transformation and Administration Innovation 2, no. 2 (2024): 49–58. https://doi.org/10.61838/dtai.2.2.6.

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The issue of sustainability reporting, due to its significant importance and its impact on enhancing performance and societal development, has become a prominent and noteworthy subject in academic research. The aim of this study is to identify the dimensions of sustainability reporting among manufacturing and non-manufacturing companies listed on the stock exchange. This research is categorized as a fundamental study in terms of purpose and outcome, as a qualitative study in terms of execution process, and as a descriptive study in terms of analysis. For data collection, the interview tool was
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Yoon, Hyunjin. "Progression-Preserving Dimension Reduction for High-Dimensional Sensor Data Visualization." ETRI Journal 35, no. 5 (2013): 911–14. http://dx.doi.org/10.4218/etrij.13.0212.0468.

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da Silva, Renato R. O., Paulo E. Rauber, and Alexandru C. Telea. "Beyond the Third Dimension: Visualizing High-Dimensional Data with Projections." Computing in Science & Engineering 18, no. 5 (2016): 98–107. http://dx.doi.org/10.1109/mcse.2016.90.

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Miswari, Miswari. "RAGAM DIMENSI PEMBELAJARAN ILMU PENDIDIKAN AGAMA ISLAM." SYAIKHONA: Jurnal Magister Pendidikan Agama Islam 2, no. 2 (2024): 87–113. https://doi.org/10.59166/syaikhona.v2i2.235.

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Education is an important element in human life that requires serious treatment in various dimensions, namely the outer and inner dimensions. The birth dimension requires extensive and detailed techniques and handling. The inner dimension requires in-depth philosophical study. This article discusses various dimensions in the study of Islamic religious education in higher education. The success of implementing Islamic religious education is largely determined by the outer and inner dimensions. The inner dimension includes the formation of a foundation for understanding humans and their knowledg
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Liu, Li. "Research on the application of urban air quality prediction and prediction model under the background of big data." SHS Web of Conferences 145 (2022): 01027. http://dx.doi.org/10.1051/shsconf/202214501027.

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In the previous research on air quality prediction, the research on the problem is usually one-sided, and many problems are solved from a single time dimension. In the research of this problem, this paper starts from the time dimension and the space dimension respectively. Considering the temporal continuity and spatial diffusion of air pollutants, the prediction results of the two dimensions are dynamically combined. Comprehensive consideration of various factors to achieve better prediction results. In order to solve the problem that there are few air quality monitoring stations in cities an
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