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Journal articles on the topic 'Numeric traces and learning indicators'

Author: Grafiati

Published: 8 June 2024

Last updated: 31 July 2025

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1

Gregory, Peter, and Alan Lindsay. "Domain Model Acquisition in Domains with Action Costs." Proceedings of the International Conference on Automated Planning and Scheduling 26 (March 30, 2016): 149–57. http://dx.doi.org/10.1609/icaps.v26i1.13762.

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This paper addresses the challenge of automated numeric domain model acquisition from observations. Many industrial and commercial applications of planning technology rely on numeric planning models. For example, in the area of autonomous systems and robotics, an autonomous robot often has to reason about its position in space, power levels and storage capacities. It is essential for these models to be easy to construct. Ideally, they should be automatically constructed. Learning the structure of planning domains from observations of action traces has produced successful results in classical p

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Batchakui, Bernabé, Thomas Djotio, Ibrahim Moukouop, and Alex Ndouna. "Object-Based Trace Model for Automatic Indicator Computation in the Human Learning Environments." International Journal of Emerging Technologies in Learning (iJET) 16, no. 21 (2021): 26. http://dx.doi.org/10.3991/ijet.v16i21.25033.

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This paper proposes a traces model in the form of an object or class model (in the UML sense) which allows the automatic calculation of indicators of various kinds and independently of the computer environment for human learning (CEHL). The model is based on the establishment of a trace-based system that encompasses all the logic of traces collecting and indicators calculation. It is im-plemented in the form of a trace database. It is an important contribution in the field of the exploitation of the traces of apprenticeship in a CEHL because it pro-vides a general formalism for modeling the tr

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Jędrzejec, Bartosz, and Krzysztof Świder. "Automatically conducted learning from textually expressed vacationers’ opinions." ITM Web of Conferences 21 (2018): 00024. http://dx.doi.org/10.1051/itmconf/20182100024.

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The automatically conducted consumers’ opinions investigation is one of the most interesting potential applications of text analytics. In our study we perform a two steps procedure of learning from the textually expressed reviews concerning hotel services offered by a travel company. In the first stage we accomplish the necessary Extract-Transform-Load process utilizing one of the available web portals and required language resources. In the second stage each of the suitably pre-processed opinions is “linguistically evaluated”, which results in a vector of numeric indicators characterizing its

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Yang, Linyi, Jiazheng Li, Ruihai Dong, Yue Zhang, and Barry Smyth. "NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-Task Financial Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (2022): 11604–12. http://dx.doi.org/10.1609/aaai.v36i10.21414.

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Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvements in prediction accuracy or forecasting may entail. Traditionally, financial forecasting has heavily relied on quantitative indicators and metrics derived from structured financial statements. Earnings conference call data, including text and audio, is an important source of unstructured data that has been used for various prediction tasks using deep earning and related approaches. However, current deep learning-base

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Ozerova, G. P. "Usage of Learning Management System Web Analytics in Blended Learning Self-Study Evaluation." Vysshee Obrazovanie v Rossii = Higher Education in Russia 29, no. 8-9 (2020): 117–26. http://dx.doi.org/10.31992/0869-3617-2020-29-8-9-117-126.

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Learning Management System (LMS) analytics data is proposed to be used in developing algorithms for evaluating students’ self-studies. Development of such algorithms is relevant considering annual growth of disciplines that apply blended learning. In blended learning model selfstudy can be done online in LMS which makes it possible to analyze patterns how students interact with learning materials and perform exercises of various complexity. Different criteria and indicators are aggregated into numeric metrics that following designed methodology evaluates self-study performance of each student.

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Gunawan, G., Ahmad Harjono, Ni Made Yeni Suranti, Lovy Herayanti, and Nina Nisrina. "The impact of LMS-based mechanics course on the creativity of prospective physics teachers in the post-pandemic era: A quasi-experimental study." Journal of Infrastructure, Policy and Development 8, no. 11 (2024): 8644. http://dx.doi.org/10.24294/jipd.v8i11.8644.

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This quasi-experimental study examined the effect of a mechanics course delivered through a Learning Management System (LMS) on the creativity of prospective physics teachers at a teacher training college in Mataram, Indonesia. The study was conducted in the post-pandemic era. Using a pretest-posttest one-group design, the researchers evaluated changes in creativity across three domains: figural, numeric, and verbal. The results showed significant improvements in overall creativity, with the most critical gains observed in the figural domain. Further analysis revealed that fluency was the crea

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Mohssine, Bentaib, Aitdaoud Mohammed, Namir Abdelwahed, and Talbi Mohammed. "Adaptive Help System Based on Learners ‘Digital Traces’ and Learning Styles." International Journal of Emerging Technologies in Learning (iJET) 16, no. 10 (2021): 288. http://dx.doi.org/10.3991/ijet.v16i10.19839.

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Learning management system (LMS) such as Claroline, Ganesha, Chamilo, Moodle ..., are commonly and well used in e-education (e-learning). Most of theTechnology Enhanced Learning (TEL) focus on supporting teachers in the creation and organization of online courses. However, in general, they do not consider individual differences of each learner. In addition, they do not provide enough indicators which will help to track the learners. In this paper, we investigate the benefits of integrating learning styles in the Web-based educational systems. Also we are interested in the use of interact

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Juhaňák, Libor, Karla Brücknerová, Barbora Nekardová, and Jiří Zounek. "Goal Setting and Goal Orientation as Predictors of Learning Satisfaction and Online Learning Behavior in Higher Education Blended Courses." Studia paedagogica 28, no. 3 (2024): 39–58. http://dx.doi.org/10.5817/sp2023-3-2.

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  This study investigated how goal setting and goal orientation are related to student learning behavior and engagement in an online learning environment, and how learning behavior, goal setting, and goal orientation are related to student satisfaction with the course they are studying. A total of 882 students from 76 different courses participated in this study, which used both self-reported data from a questionnaire and indicators based on digital traces in an online learning environment. The results of multilevel regression analyses showed that student ability to set learning go

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Salihoun, Mohammed, Fatima Guerouate, Naoual Berbiche, and Mohamed Sbihi. "How to Assist Tutors to Rebuild Groups Within an ITS by Exploiting Traces. Case of a Closed Forum." International Journal of Emerging Technologies in Learning (iJET) 12, no. 03 (2017): 169. http://dx.doi.org/10.3991/ijet.v12i03.6506.

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Computer Supported Collaborative Learning (CSCL) is a new mode of teaching and one of the popular approaches for learning process. It allows virtual interactions between groups by providing tools such as: chat, internal email and discussion forums. One of the major problems caused by this learning process is the neglect and isolation of learners in groups, and usually is the cause of a heterogeneous group through social, cognitive or emotional ways. The method used is based on the exploitation of traces left on the online learning platform by learners and groups. The data collected from the en

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Yudha, Firma, and Alex Haris Fauzi. "Efektivitas Penggunaan Media Kartu Numerik pada Siswa Jenjang Prasekolah." Indonesian Journal of Mathematics and Natural Science Education 2, no. 1 (2021): 28–33. http://dx.doi.org/10.35719/mass.v2i1.56.

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Abstrak Pembelajaran di jenjang prasekolah lebih banyak bermain sambil belajar. Pembelajaran matematika juga dapat diterima anak dalam dunia penddikan pra sekolah, yaitu dengan cara mengenal numerik 1-10. Hal demikian dilakukan dengan menggunakan media kartu numerik secara klasikal. Jenis penelitian ini adalah deskriptif kualitatif dengan subjek penelitian anak-anak pra sekolah dhiva school dengan jumlah 18 anak. Dalam penelitian ini diketahui bahwa siswa pra sekolah mampu mengenal numerik, mampu menulis dan mampu mengurutkan numerik 1-10. efektifitas media kartu numerik, dengan mengguna

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Martinez-Gil, Francisco, Miguel Lozano, Ignacio García-Fernández, Pau Romero, Dolors Serra, and Rafael Sebastián. "Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations." Mathematics 8, no. 9 (2020): 1479. http://dx.doi.org/10.3390/math8091479.

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Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in t

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Simorangkir, Frida Marta Argareta, and Dyan Wulan Sari HS. "LITERASI NUMERIK DI SD SWASTA PKMI EFESUS AEK BATU." JS (JURNAL SEKOLAH) 5, no. 4 (2021): 32. http://dx.doi.org/10.24114/js.v5i4.28198.

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Abstract: Numeric Literacy in Elementary School PKMI Efesus Aek Batu. The purpose of this study is to describe (1) the implementation of numerical literacy in learning, (2) efforts to overcome obstacles in numerical literacy, (3) supporting factors and (4) inhibiting factors of numerical literacy. This type of research is descriptive qualitative. The results of the research are (1) the implementation of numerical literacy in learning based on three stages, namely the stages of habituation, development, and learning and according to the five indicators of numerical literacy. (2) The efforts mad

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Zhang, Rener. "Machine learning application: A kind of prostate disease early warning model." Applied and Computational Engineering 74, no. 1 (2024): 40–52. http://dx.doi.org/10.54254/2755-2721/74/20240429.

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Prostate Diseases pose significant health risks, and the author has developed an integrated machine learning model using a medical indicator dataset of prostate patients. The article introduces seven different machine learning algorithms for classification tasks. The approach involved detailed exploratory data analysis, descriptive statistics, feature engineering, and data visualization. Additionally, data preprocessing was performed by addressing missing values and eliminating non-numeric characters. During the model training process, cross-validation techniques are employed to determine the

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Uvarov, A. Yu, and G. M. Vodopian. "About two indicators of the school digital renewal process." Informatics and education 38, no. 5 (2023): 5–15. http://dx.doi.org/10.32517/0234-0453-2023-38-5-5-15.

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The indicators of the process of digital technologies introduction (school digital renewal indicators) widely used today successfully capture the innovative processes that occur at the initial stages (levels) of digital renewal. At the stages of mature informatization and digital transformation, the changes associated with the expansion of the traditional classroom system and the transition to personalized and competency-based learning organization come to the fore.The authors propose two indicators that capture changes in the chronotope of study work and the teaching individualization level.

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Aman Anand and Prof. Manish Kumar Singhal. "A Machine Learning Framework for Distributed Denial of Service Attack Detection." International Journal of Scientific Research in Science and Technology 12, no. 1 (2025): 37–45. https://doi.org/10.32628/ijsrst25121154.

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This paper explores the nature of threats posed by Distributed Denial of Service (DDoS) attacks on large networks, such as the Internet, emphasizing the need for effective detection and response mechanisms. These mechanisms must be implemented not only at the network edge but also within its core. The paper introduces methods to detect DDoS attacks by analyzing entropy and frequency-sorted distributions of specific packet attributes. Anomalies in these attributes' characteristics serve as indicators of potential DDoS attacks. The proposed methods are evaluated for detection accuracy and perfor

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Park, Hyunjae, and Young-June Choi. "Frequency-Based Representation of Massive Alerts and Combination of Indicators by Heterogeneous Intrusion Detection Systems for Anomaly Detection." Sensors 22, no. 12 (2022): 4417. http://dx.doi.org/10.3390/s22124417.

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Although the application of a wide range of sensors has been generalized through the development of technology, the processing of massive alerts generated through data analysis and monitoring remains a challenge. This problem is also found in cyber security because the intrusion detection system (IDS) produces a tremendous number of alerts. Massive alerts not only significantly increase resources for analysis, but also make it difficult to analyze the overall situation of the system. In order to handle massive alerts, we propose using an indicator as a frequency-based representation. The propo

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Chemsi, Ghizlane, Mounir Sadiq, Mohamed Radid, and Mohammed Talbi. "Formative E-Assessment and Behavioral Commitment of Students: Case of the Faculty of Science Ben M’sik." International Journal of Emerging Technologies in Learning (iJET) 14, no. 12 (2019): 4. http://dx.doi.org/10.3991/ijet.v14i12.10389.

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Digital technology contributes to the development of new teaching practices and a new assessment culture [1,2,3]. Various studies [4,5] show that digital technology facilitates the formative assessment process, an assessment mode that favors the learner’s commitment and encourages the learner to adopt an efficient learning method [6]. All the more, the media coverage of this type of assessment generates a large number of indicators enabling to analyze the behavioral commitment of students in their learning process. The objective of this study is to analyze the impact of formative E-asses

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Supriana, I. Wayan Supriana, Made Agung Raharja, and I. Made Satria Bimantara. "Pengembangan Sistem Prediksi Bantuan Program Keluarga Harapan (PKH) Berbasis Machine Learning." SINTECH (Science and Information Technology) Journal 6, no. 1 (2023): 26–36. http://dx.doi.org/10.31598/sintechjournal.v6i1.1297.

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The Family Hope Program (PKH) is a poverty alleviation program which is one of the government's strategies in reducing the poverty line. This program provides cash social assistance to poor families who are included in the list of beneficiary families with a focus on education and health. The purpose of implementing the PKH program is not only to reduce poverty and increase human resources but to break the poverty chain. The implementation of PKH in its realization experienced many obstacles that caused the program not to be on target, this was because the data verification process was not yet

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Islam, Farheen, Aprajita Krishna, Devanshu Kumar, and Sangeeta Kumari. "Factors Influencing Academic Performance: An Empirical Study Using Predictive Analytics." Multidisciplinar (Montevideo) 3 (January 1, 2025): 51. http://dx.doi.org/10.62486/agmu202551.

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Introduction: Student academic performance is commonly measured using indicators like credit scores, class rankings, or passing thresholds, each offering insight into a student’s comprehension and progress. These measures give a numeric evaluation of a student's understanding of the course content, enabling educators and institutions to monitor growth over time. Moreover, the capacity to forecast academic performance proves highly beneficial for both students and teachers, as it enables early interventions and course corrections. This predictive ability can lead to tailored learning strategies

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Begimbetova, Guldana, Ultusyn Zauirbek, and Akbota Seitova. "EVALUATION OF INDIVIDUAL WORK OF STUDENTS IN DISTANCE LEARNING BASED ON A DIGITAL EDUCATIONAL TRACK." Bulletin Series of Physics & Mathematical Sciences 75, no. 3 (2021): 173–81. http://dx.doi.org/10.51889/2021-3.1728-7901.21.

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The article considers the assessment of students' independent work in a distance learningon the basis of digital educational traces. Independent work in a mixed training can be performed on the online platform LMS, and the use of educational digital data allows you to study the specifics of student interaction with the course materials and the ability to solve the problem. For the assessment of time and the quality of independent work of students is determined by a set of criteria and indicators, selected quantitative metrics and offers a methodology that can be used to assess the progress of

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Cruz-Iglesias, Esther, Pilar Gil-Molina, and Itziar Rekalde-Rodríguez. "A Navigation Chart for Sustainability for the Ocean i3 Educational Project." Sustainability 14, no. 8 (2022): 4764. http://dx.doi.org/10.3390/su14084764.

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The complex nature of sustainability challenges implies the need to provide students with interdisciplinary learning experiences and environments based on active and reflective learning. To know whether these experiences result in real learning, there must be a way of capturing and measuring the competences required to promote sustainable development using suitable indicators. This paper presents the process of building a competence map that is used as a navigation chart to monitor the sustainable education competences in the Ocean i3 experience. An action-research methodological approach is u

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Fazira, Aumi, Syaiful, and Rohati. "The Role of Adversity Quotient in Enhancing Students’ Mathematical Problem-Solving Skills." Asian Journal of Education and Social Studies 51, no. 7 (2025): 1122–30. https://doi.org/10.9734/ajess/2025/v51i72197.

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This research is motivated by the low mathematical problem solving ability of students at State Junior High School 19 Kerinci. The purpose of this study is to determine and analyze students' mathematical problem solving abilities in terms of Adversity Quotient (AQ) on quadratic equation material. The problem solving indicators in this study use the problem solving ability indicators according to Polya. This research is a qualitative study. This research was conducted at State Junior High School 19 Kerinci with the subject selection technique used was purposive sampling. The selection of resear

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Kuntariati, Utik, Putu Dian Yuliani Paramita, and Gede Eka Wahyu. "IMPLEMENTATION OF HIGHER ORDER THINKING SKILLS (HOTS)-BASED EDUCATION TO ENHANCE THE QUALITY OF ENGLISH LANGUAGE FOR STUDENTS AT SDN 1 TIMPAG." JURNAL PAJAR (Pendidikan dan Pengajaran) 7, no. 3 (2023): 671. http://dx.doi.org/10.33578/pjr.v7i3.9441.

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Quality of education 4.0 is aimed at producing competent and quality human resources in carrying out activities in the industrial world later ( Pohan , 2019). In the current implementation of education in capturing information on the resulting human resources, it is required to obtain information on a very broad scale and human resources are also required to be able to understand various matters, one of which is understanding related to English. In this study, the researcher used a qualitative descriptive method to describe the HOTS concept which would be implemented in English learning activi

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COHEN, WILLIAM W., and PREMKUMAR T. DEVANBU. "AUTOMATICALLY EXPLORING HYPOTHESES ABOUT FAULT PREDICTION: A COMPARATIVE STUDY OF INDUCTIVE LOGIC PROGRAMMING METHODS." International Journal of Software Engineering and Knowledge Engineering 09, no. 05 (1999): 519–46. http://dx.doi.org/10.1142/s0218194099000292.

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We evaluate a class of learning algorithms known as inductive logic programming (ILP) methods on the task of predicting fault density in C++ classes. Using these methods, a large space of possible hypotheses is searched in an automated fashion; further, the hypotheses are based directly on an abstract logical representation of the software, eliminating the need to manually propose numerical metrics that predict fault density. We compare two ILP systems, FOIL and FLIPPER, and conclude that FLIPPER generally outperforms FOIL on this problem. We analyze the reasons for the differing performance o

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NEVREDINOV, Aleksandr R. "An approach to neural network analysis of text information in the economic assessment of companies." Economic Analysis: Theory and Practice 20, no. 8 (2021): 1574–94. http://dx.doi.org/10.24891/ea.20.8.1574.

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Subject. When evaluating enterprises, maximum accuracy and comprehensiveness of analysis are important, although the use of various indicators of organization’s financial condition and external factors provide a sufficiently high accuracy of forecasting. Many researchers are increasingly focusing on the natural language processing to analyze various text sources. This subject is extremely relevant against the needs of companies to quickly and extensively analyze their activities. Objectives. The study aims at exploring the natural language processing methods and sources of textual information

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Mohiddin Hasan, Umer Mukthar, and Dr Shreevamshi N. Dr. Shreevamshi N. "AI-Powered Predictive Analytics for Financial Forecasting and Strategic Insight." International Journal of Research and Innovation in Applied Science X, no. VI (2025): 532–55. https://doi.org/10.51584/ijrias.2025.10060039.

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The rapid evolution of artificial intelligence (AI) has significantly reshaped the financial services landscape, particularly in the domain of predictive analytics. The integration of machine learning (ML), deep learning (DL), and advanced statistical models has empowered financial institutions to forecast market trends, identify anomalies, and enhance investment strategies with improved precision and agility. This chapter explores the theoretical foundations, algorithmic techniques, and practical applications of AI-driven predictive analytics in financial trend forecasting. It traces the prog

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Legashev, L. V., I. P. Bolodurina, L. S. Grishina, I. A. Lashneva, and A. A. Sermyagin. "Prediction of milk quantitative traits based on infrared spectroscopy using machine-learning methods." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 22, no. 3 (2022): 47–56. http://dx.doi.org/10.14529/ctcr220305.

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Fourier transform mid-infrared spectroscopy is a fast and cheap way to analyze cow's milk samples to determine fat, protein, lactose and other quantitative and qualitative indicators of milk quality. Modern tools for data analysis will reveal the relationship between different pairs of quantitative and qualitative characteristics of milk. Purpose of the study. Perform predictions on some key milk quality traits based on infrared spectroscopy data to study the accuracy of the developed mathematical model. Methods. The work was carried out in the winter period of 2022 on the basis of an experime

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Balanev, Dmitry Yu, and Viktor A. Shamakov. "Diagnostic markers of human motor activity in a digital learning environment." Vestnik Tomskogo gosudarstvennogo universiteta, no. 485 (2022): 138–44. http://dx.doi.org/10.17223/15617793/485/15.

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The article aims to study the dynamics of psychological and psychophysiological indicators of students’ cognitive activity in a digital learning environment. As a research platform, we used the well-known task of speed–accuracy tradeoff, adapted for work in the LMS Moodle using a set of plug-ins that implement both the stimulus situation itself and the ability to monitor the characteristics of the user’s motor activity displayed in the track of the cursor control device (mouse tracking). As part of the study, LMS users performed a cognitive test, included in the digital learning environment an

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Chang, Lipeng, Yuechuan Wei, Shuiyu He, and Xiaozhong Pan. "Research on Side-Channel Analysis Based on Deep Learning with Different Sample Data." Applied Sciences 12, no. 16 (2022): 8246. http://dx.doi.org/10.3390/app12168246.

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With the in-depth integration of deep learning and side-channel analysis (SCA) technology, the security threats faced by embedded devices based on the Internet of Things (IoT) have become increasingly prominent. By building a neural network model as a discriminator, the correlation between the side information leaked by the cryptographic device, the key of the cryptographic algorithm, and other sensitive data can be explored. Then, the security of cryptographic products can be evaluated and analyzed. For the AES-128 cryptographic algorithm, combined with the CW308T-STM32F3 demo board on the Ch

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Oh, Jiwon, Heesu Hwang, Yoonmi Nam, et al. "Machine Learning-Assisted Gas-Specific Fingerprint Detection/Classification Strategy Based on Mutually Interactive Features of Semiconductor Gas Sensor Arrays." Electronics 11, no. 23 (2022): 3884. http://dx.doi.org/10.3390/electronics11233884.

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A high-performance machine learning-assisted gas sensor strategy based on the integration of supervised and unsupervised learning with a gas-sensitive semiconductor metal oxide (SMO) gas sensor array is introduced. A 4-SMO sensor array was chosen as a test sensor system for detecting carbon monoxide (CO) and ethyl alcohol (C2H5OH) mixtures using 15 different combinations. Gas sensing detection/classification was performed with different numbers of gas sensor and machine learning algorithms. K-Means clustering was successfully employed to rationally identify the similarity features of targeted

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Ulumudin, Ikhya, Asma Aisha, and Ferdi Widiputera. "The Implementation of Knowledge Assessment In Curriculum 2013 in Elementary Schools." Technium Social Sciences Journal 7 (May 5, 2020): 86–97. http://dx.doi.org/10.47577/tssj.v7i1.442.

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The purpose of this study was to determine the understanding and implementation of the knowledge assessment carried out by teachers at the elementary school level starting from planning, implementing, processing results, utilizing results and identifying problems in implementing knowledge assessment. This study used a qualitative approach. Research took place in Sleman Regency, Yogyakarta Province. The research subjects were public and private elementary school teachers who had taught in classes applying Curriculum 2013. The research instruments consisted of questionnaires and FGD (focus group

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Muhtadi, Muhtadi, Sutama Sutama, Sofyan Anif, and Harun Joko Prayitno. "PENGEMBANGAN KEMITRAAN KA WASAN MATEMATIKA(MATH MASTER ZONE) DI KECAMATAN SA WAHAN KABUP ATEN NGANJUK." Warta LPM 18, no. 1 (2015): 20–28. http://dx.doi.org/10.23917/warta.v18i1.1163.

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PEMITRA service activities in the kecamatan Sawahan kabupaten Nganjuk, had conducted educational activities, training, and mentoring for elementary school teachers, principals, supervisors and the person in charge of Math Masters Zone program to improve the basic concepts of mathematics and its teaching method. In this Pemitra conducted training activities learning methods of Math Masters, so that teachers had an understanding and basic mathematical concepts were true, and instructed it so easy and fun to their students. In the implementation of this Pemitra service activities, had given resul

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Silva-Filho, José Humberto, Sonia Regina Pasian, and Francisco de Assis Carvalho do Vale. "Typical performance of elderly patients with Alzheimer disease on the Wisconsin Card Sorting Test (WCST)." Dementia & Neuropsychologia 1, no. 2 (2007): 181–89. http://dx.doi.org/10.1590/s1980-57642008dn10200011.

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Abstract The Wisconsin Card Sorting Test (WCST) is a neuropsychological assessment tool designed to assess executive functions, frequently used in cases of cognitive disorders. However, Brazilian neuroscientific settings lack standardization studies of psychological assessment instruments, especially in the neuropsychological area. Thus, the assessment of clinical groups including dementias and particularly Alzheimer´s disease (AD) patients, may be compromised by the lack of analytical references. Objective: To characterize the performance of elderly patients with Alzheimer´s disease on the WC

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Gonzalez Romero, Alicia. "Un Hypertexto para la enseñanza de la Estadística No Paramétrica: Propuesta didáctica para el proceso de enseñanza-aprendizaje de las Ciencias Sociales / A Hypertext for the Teaching of Nonparametric Statistics: Didactic Proffer for the Teaching-Learning Process of the Social Sciences." Revista Internacional de Aprendizaje en Ciencia, Matemáticas y Tecnología 3, no. 2 (2016): 121–30. http://dx.doi.org/10.37467/gka-revedumat.v3.249.

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ABSTRACTA hypertext was realized as a didactic guide to construct and explain the different hypothesis tests related with nonparametric statistics by using the Raimon Duvals semiotic theoretical base, the learning based on Donald Shon´s problems, and exercises of social kind. Microsoft Excel was used as didactic software , the tests were developed according to the constructivism. There was an explanation consistent in an hypothesis test beginning with thw the binomial development and it was continued with exercises analysis and development of the hypothesis tests exercises included in the nonp

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Гурниковский, А. И., Р. Ю. Гурниковская, Т. В. Луговой, И. М. Тарарин та З. В. Шилова. "Влияние цифровизации на качество образования и развитие навыков самоорганизации и самостоятельного обучения у студентов, обучающихся в рамках многосеместровых дисциплин «Линейная алгебра» и «Математический анализ»". Management of Education 14, № 11-1 (2024): 51–61. https://doi.org/10.25726/k4465-4099-9898-j.

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Цифровизация образования трансформирует дидактический процесс, существенно влияя на качество подготовки специалистов. В частности, в рамках многосеместровых дисциплин, таких как «Линейная алгебра» и «Математический анализ», применение цифровых технологий может способствовать развитию у студентов навыков самоорганизации и самостоятельного обучения. В статье проанализированы результаты эмпирического исследования, в ходе которого были изучены особенности цифровизации образовательного процесса по указанным дисциплинам в ряде российских вузов в 2019-2023 гг. Выборка составила 587 студентов бакалавр

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Hashtarkhani, Soheil, Rezaur Rashid, Parnian K. Rahimabad, et al. "Abstract A062: Uncovering Social and Clinical Determinants of Baseline Distress Prior to Radiation Therapy: An Explainable Machine Learning Approach." Clinical Cancer Research 31, no. 13_Supplement (2025): A062. https://doi.org/10.1158/1557-3265.aimachine-a062.

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Abstract Background: Psychological distress impacts cancer treatment adherence, outcomes, and quality of life. While predictive models can identify patients at elevated risk, understanding the mechanistic drivers of distress will be essential to design personalized psychosocial interventions. In this study, we applied explainable machine learning to predict and interpret baseline distress levels in cancer patients preparing to undergo radiation therapy. Methods: We retrospectively analyzed data from 2,103 patients treated at the University of Tennessee Medical Center (UTMC) in Knoxville. 1,953

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Zhang, Huan, Yibin Yao, Chaoqian Xu, Wei Xu, and Junbo Shi. "Transformer-Based Global Zenith Tropospheric Delay Forecasting Model." Remote Sensing 14, no. 14 (2022): 3335. http://dx.doi.org/10.3390/rs14143335.

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Zenith tropospheric delay (ZTD) plays an important role in high-precision global navigation satellite system (GNSS) positioning and meteorology. At present, commonly used ZTD forecasting models comprise empirical, meteorological parameter, and neural network models. The empirical model can only fit approximate periodic variations, and its accuracy is relatively low. The accuracy of the meteorological parameter model depends heavily on the accuracy of the meteorological parameters. The recurrent neural network (RNN) is suitable for short-term series data prediction, but for long-term series, th

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Sota, Jani. "Contribution to the General History of School Health Service in Albania (From Origins to Nowadays)." Interdisciplinary Journal of Research and Development 9, no. 1 (2022): 13. http://dx.doi.org/10.56345/ijrdv9n103.

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We are all witnesses of the great traces left by the school health service in Albania, especially after the Second World War, in the protection of the health of preschool and school age, we are witnesses, when the bodies and personalities of health and education defined the role of health care in kindergartens and schools. The purpose of this study is to highlight the common features and characteristics of the health service in preschool and school institutions with a special identity, in order to care for the physical and mental health of children and students, hygienic care and disease preve

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Kryukov, V. V., I. A. Ryzhova, and I. N. Emelianova. "Dynamics of Psychosocial, Psychopathological and Neuropsychological Characteristics in Clean-up Workers of the Consequences of Chernobyl Disaster: Results of 30-years Study." Doctor.Ru 21, no. 8 (2022): 52–59. http://dx.doi.org/10.31550/1727-2378-2022-21-8-52-59.

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Study Objective: To assess the possibilities of social adaptation in persistent psychopathological, including cognitive impairments. Study Design: Longitudinal study. Materials and Methods. A 30-year observation, treatment and rehabilitation of clean-up workers of accident at the Chernobyl nuclear power plant, who underwent an in-wide clinical, psychopathological and neuropsychological examination at the Moscow Research Institute of Psychiatry, was carried out. 373 people were selected for the study. A dynamic psychopathological and neuropsychological assessment of their condition is given, as

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Olsen, A. L., L. H. Magnussen, L. H. Skjaerven, et al. "FRI0644-HPR PATIENT EDUCATION AND BASIC BODY AWARENESS THERAPY VERSUS PATIENT EDUCATION ONLY IN PATIENTS WITH HIP OSTEOARTHRITIS: A RANDOMIZED CONTROLLED TRIAL." Annals of the Rheumatic Diseases 79, Suppl 1 (2020): 926.1–926. http://dx.doi.org/10.1136/annrheumdis-2020-eular.2540.

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Background:Patients with hip osteoarthritis tend to develop stereotype and energy demanding movement strategies with potential negative effects on disease progression and daily life functioning. A multi-perspective view on movement quality is applied in the physiotherapy modality Basic Body Awareness Therapy (BBAT), with its movement awareness learning pedagogy. BBAT has been found beneficial for functional movement quality, symptoms, and psychological aspects of health in patients with various long-lasting conditions.Objectives:To investigate the short-term (6 months) effects of BBAT, added t

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Tomczyk, Łukasz, Darwin Muñoz, Julio Perier, et al. "ICT AND PRESERVICE TEACHERS. SHORT CASE STUDY ABOUT CONDITIONS OF TEACHER PREPARATION IN: DOMINICAN REPUBLIC, ECUADOR, URUGUAY AND POLAND." Knowledge International Journal 32, no. 1 (2019): 15–24. http://dx.doi.org/10.35120/kij320115t.

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The paper aims at presenting the most important indicators teacher preparation in the context of the developing information society. The text was written as part of the SELI project. It is the international study which seeks to answer the question about the factors determining the efficient use of ICT among the pedagogy students. This theoretical study joins the debate on the curricula and local, national and global conditions related to the education of teachers of the future. The text presents data from three countries from Latin America and the Caribbean region and one from Europe.The devel

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Siembieda, William. "Toward an Enhanced Concept of Disaster Resilience: A Commentary on Behalf of the Editorial Committee." Journal of Disaster Research 5, no. 5 (2010): 487–93. http://dx.doi.org/10.20965/jdr.2010.p0487.

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1. Introduction This Special Issue (Part 2) expands upon the theme “Building Local Capacity for Long-term Disaster Resilience” presented in Special Issue Part 1 (JDR Volume 5, Number 2, April 2010) by examining the evolving concept of disaster resilience and providing additional reflections upon various aspects of its meaning. Part 1 provided a mixed set of examples of resiliency efforts, ranging from administrative challenges of integrating resilience into recovery to the analysis of hazard mitigation plans directed toward guiding local capability for developing resiliency. Resilience was bro

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Li, Zhou. "Consumer behavior analysis model based on machine learning." Journal of Intelligent & Fuzzy Systems, December 7, 2020, 1–11. http://dx.doi.org/10.3233/jifs-189483.

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The accurate mastery of demand information enables retailers to better respond to consumers and effectively manage inventory. However, the precise connection and interaction between this information collection and inventory management is more difficult to measure. In view of this, this paper proposes a research on inventory model based on consumer web search. Moreover, centering on the two main actors in the online search environment, consumers and retailers, this paper fully considers their characteristics and situations to construct an inventory model in the online search environment, and an

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TOPALI, Paraskevi, Alejandro ORTEGA-ARRANZ, Alejandra MARTÍNEZ-MONÉS, Sara VILLAGRA-SOBRINO, Juan I. ASENSIO-PÉREZ, and Yannis DIMITRIADIS. "Identifying Learner Problems Framed within MOOC Learning Designs." International Conference on Computers in Education, November 22, 2021. https://doi.org/10.58459/icce.2021.4159.

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Detecting learners who face problems in MOOCs usually poses difficulties due to the high instructor-learners ratio, the diversity of the population, and the asynchronous participation mode. Existing solutions mainly draw on self-reported problems in discussion forums and on dashboards displaying learners’ activity traces. However, these approaches cannot scale up easily or do not consider the course learning design. This paper presents a conceptual framework aimed at guiding MOOC instructors in the identification of potential learners' problems and indicators of such problems, considering the

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Gassais, Robin, Naser Ezzati-Jivan, Jose M. Fernandez, Daniel Aloise, and Michel R. Dagenais. "Multi-level host-based intrusion detection system for Internet of things." Journal of Cloud Computing 9, no. 1 (2020). http://dx.doi.org/10.1186/s13677-020-00206-6.

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AbstractThe growth of the Internet of things (IoT) has ushered in a new area of inter-connectivity and innovation in the home. Many devices, once separate, can now be interacted with remotely, improving efficiency and organization. This, however, comes at the cost of rising security vulnerabilities. Vendors are competing to create and release quickly innovative connected objects, without focusing on the security issues. As a consequence, attacks involving smart devices, or targeting them, are proliferating, creating threats to user’s privacy and even their physical security. Additionally, the

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Jeppu, Vineeth, Ayan A. Singh, and Alex Gonzalez. "Improvement of Key Financial Performance Indicators in the Insurance Industry Using Machine Learning – A Quantitative Analysis." International Journal of Smart Sensor and Adhoc Network., January 2023, 1–6. http://dx.doi.org/10.47893/ijssan.2023.1225.

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AI and Machine learning are playing a vital role in the financial domain in predicting future growth and risk and identifying key performance areas. We look at how machine learning and artificial intelligence (AI) directly or indirectly alter financial management in the banking and insurance industries. First, a non-technical review of the prior machine learning and AI methodologies beneficial to KPI management is provided. This paper will analyze and improve key financial performance indicators in insurance using machine learning (ML) algorithms. Before applying an ML algorithm, we must deter

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Caspari-Sadeghi, Sima. "Applying Learning Analytics in Online Environments: Measuring Learners’ Engagement Unobtrusively." Frontiers in Education 7 (January 25, 2022). http://dx.doi.org/10.3389/feduc.2022.840947.

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Prior to the emergence of Big Data and technologies such as Learning Analytics (LA), classroom research focused mainly on measuring learning outcomes of a small sample through tests. Research on online environments shows that learners’ engagement is a critical precondition for successful learning and lack of engagement is associated with failure and dropout. LA helps instructors to track, measure and visualize students’ online behavior and use such digital traces to improve instruction and provide individualized support, i.e., feedback. This paper examines 1) metrics or indicators of learners’

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Fazekas, Mihály, Salvatore Sberna, and Alberto Vannucci. "The extra‐legal governance of corruption: Tracing the organization of corruption in public procurement." November 15, 2021. https://doi.org/10.1111/gove.12648.

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AbstractThis article traces the organization of corruption in public procurement, by theoretically and empirically assessing the contribution of extra‐legal governance organizations (EGO) to supporting it. Theoretically, we explore the governance role played by organized criminal groups in corruption networks, facilitating corrupt transactions by lowering search costs, bargaining costs, and enforcement cots. Empirically, the analysis exploits a rare empirical setup of proven cases of both EGO presence and absence in contract awards by Italian municipalities. We use traditional regression and s

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Salah, Zaher, Elsoud Esraa Abu, Waleed Al-Sit, Esraa Alhenawi, Fuad Alshraiedeh, and Nawaf Alshdaifat. "Optimizing intrusion detection in 5G networks using dimensionality reduction techniques." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 5 (2024). https://doi.org/10.11591/ijece.v14i5.pp5652-5671.

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The proliferation of internet of things (IoT) technologies has expanded the user base of the internet, but it has also exposed users to increased cyber threats. Intrusion detection systems (IDSs) play a vital role in safeguarding against cybercrimes by enabling early threat response. This research uniquely centers on the critical dimensionality aspects of wireless datasets. This study focuses on the intricate interplay between feature dimensionality and intrusion detection systems. We rely on the renowned IEEE 802.11 security-oriented AWID3 dataset to implement our experiments since AWID was t

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Boekaerts, Monique, Mariel F. Musso, and Eduardo C. Cascallar. "Predicting attribution of letter writing performance in secondary school: A machine learning approach." Frontiers in Education 7 (November 23, 2022). http://dx.doi.org/10.3389/feduc.2022.1007803.

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The learning research literature has identified the complex and multidimensional nature of learning tasks, involving not only (meta) cognitive processes but also affective, linguistic, and behavioral contextualized aspects. The present study aims to analyze the interactions among activated domain-specific information, context-sensitive appraisals, and emotions, and their impact on task engagement as well as task satisfaction and attribution of the perceived learning outcome, using a machine learning approach. Data was collected from 1130 vocational high-school students of both genders, between

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