Arailym-tleubayeva/sist-english-corpus huggingface dataset:
Title: Some Aspects of The Influence of Environmental Factors for the Development of Human Capital
Abstract: The article explored the environmental factor in the development of human capital on the example of the Kyrgyz Republic. The negative impact of the environment on the development of demographic processes in the Kyrgyz Republic was established. Statistical analysis showed that for 20202022 in the Kyrgyz Republic, the death rate increased significantly, while the birth rate decreased significantly. Mortality and morbidity in recent years has been growing for various reasons, including not only socio-economic factors, but also environmental ones.
Keywords: environment;ecology;population;birth rate;mortality;natural population growth;emissions of harmful substances into the atmosphere;air quality;pollution city ranking
Review score: Low
Review comment: The article does not correspond to the direction of the conference, since it presents only a statistical analysis of mortality and fertility in the Kyrgyz Republic in recent years and does not use information technology tools. It is recommended that the authors expand the research materials by adding mortality and fertility forecasting using statistical methods or artificial intelligence methods. After this, the article will meet the requirements of the conference.
Title: An investigation of sensing and technologies for supporting the intelligent transport management system in urban area
Abstract: The process of urbanization has significantly contributed to economic growth, improved human capabilities, and enhanced living standards. However, it has also introduced challenges in managing transportation systems, including issues such as traffic congestion, safety concerns, and pollution. To address these challenges, there is a growing adoption of intelligent technologies across various transportation applications, leading to the emergence of innovative transportation methods. This paper aims to provide the following key contributions: i) Overview of the urban transport system: The paper presents a concise explanation of the urban transport system, highlighting its importance and the need for effective management; ii) Introduction of an intelligent total transport managing system: The paper proposes the implementation of an intelligent total transport managing system that utilizes a hierarchical concept to classify different segments of transportation; iii) Integration of sensor technologies: The paper explores the integration of sensor technologies into vehicles and infrastructure to enable durable and intelligent total transport management; iv) Applications in safety, traffic management, and control: The paper discusses the potential applications of numerous sensors deployed within an intelligent transport management system, including areas such as safety, traffic management, and control. By addressing these research aspects, the paper aims to contribute to the understanding of intelligent transport management systems in urban areas. It emphasizes the significance of integrating sensor technologies and highlights their potential applications in enhancing safety, traffic management, and control. Ultimately, the findings of this research can inform the development of smarter and more efficient transportation systems in urban environments.
Keywords: Sensor;Intelligent Transport System;IoT;Smart City;Transportation Management System
Title: A Comparative Study of Supervised Machine Learning and Deep Learning Techniques with Feature Selection Methods for Classifying Parkinson’s Disease Based on Speech Impairments
Abstract: This paper compares and analyzes machine learning (ML) and deep learning (DL) techniques with different feature selection methods for classifying Parkinson’s disease based on a speech impairments dataset. The dataset was explored by various methods to obtain vocal features, including Mel Frequency Cepstral Coefficients (MFCCs), Wavelet Transform Features, Vocal Fold Features, and Tunable Q-factor wavelet transform (TQWT). It consists of 754 features and 756 instances. In addition, the study evaluates various classification techniques, including Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbor (KNN), Naive Bayes (NB), Deep Neural Network (DNN), 1D Convolution Neural Network (1D CNN). Additionally, we demonstrated the effectiveness of feature selection techniques, namely Principal Component Analysis (PCA), Minimum Redundancy Maximum Relevance (mRMR), and SelectKBest. Among these, the most notable accuracy and precision were achieved by the KNN algorithm combined with PCA, recording values of 93.43% and 93.45%, respectively. Moreover, the Random Forest (RF) algorithm achieved an outstanding recall rate of 100%
Keywords: Parkinson’s disease;speech impairment;machine learning;deep learning;feature selection;dysphonia;detection disease
Review score: Moderate
Review comment: The abstract briefly mentions the dataset used in the study, but it could benefit from providing more specific details about the dataset's size, source, and composition to give readers a better understanding of the experimental setup. While the abstract mentions the use of feature selection methods like PCA, mRMR, and SelectKBest, it could briefly explain how these methods work and their significance in the context of the study. The abstract could provide a glimpse of the key findings or results obtained from the comparative study, such as which machine learning algorithms performed best and their corresponding performance metrics.Some sentences could be rephrased for better clarity and coherence. For example, "The different classification techniques involve..." could be revised to "The study evaluates various classification techniques, including..."
Title: Attack Detection in IoT using RF and ANN
Abstract: Internet of Things (IoT) devices are the weak link in organizing a Wireless Sensor Network. Various Attacks on IoT devices can lead to different complex consequences. Real applications of the IoT generate a large amount of data every second, the confidentiality of which is of very high value. Therefore, detecting attacks in IoT interactions is of paramount interest from both science and industry. Among various attack detection approaches, machine learning methods show great potential due to their early detection ability. The paper presents a methodology for detecting attacks based on two machine learning methods: Random Forest (RF) and Artificial Neural Network (ANN). To conduct the experiment, various data sets were considered, the descriptions of which are given in the work. The experiment was carried out using open data sets obtained from real IoT devices. As a result, RF demonstrated a high accuracy of 98.6%.
Keywords: Internet of Things;cybersecurity;attack detection;machine learning
Review score: Moderate
Review comment: Citation in Introduction part should be improved especially with statistics. Formula 1, 3 are not complete. Equations part is not formatted with IEEE standards. he methodology is robust, and the findings are both original and impactful. Overall, this paper makes a valuable contribution to the academic discourse.
Title: Attack Detection in IoT using RF and ANN
Abstract: Internet of Things (IoT) devices are the weak link in organizing a Wireless Sensor Network. Various Attacks on IoT devices can lead to different complex consequences. Real applications of the IoT generate a large amount of data every second, the confidentiality of which is of very high value. Therefore, detecting attacks in IoT interactions is of paramount interest from both science and industry. Among various attack detection approaches, machine learning methods show great potential due to their early detection ability. The paper presents a methodology for detecting attacks based on two machine learning methods: Random Forest (RF) and Artificial Neural Network (ANN). To conduct the experiment, various data sets were considered, the descriptions of which are given in the work. The experiment was carried out using open data sets obtained from real IoT devices. As a result, RF demonstrated a high accuracy of 98.6%.
Keywords: Internet of Things;cybersecurity;attack detection;machine learning
Review score: High
Review comment: The topic of this article is interesting. The paper well written and the objectives is presented very clearly. However, the authors may revise this article to enhence its quality by considering the following concerns:
1. Unfortunately, there is text in Russian on the second page of the article. Please ensure that all content is in English.
2. There are some errors in illustrating the formulas. Please review the article and proofread it.
Title: Developing Intelligent Supply Chain System Adopting Lean and Agile Attributes for Construction Projects in Malaysia
Abstract: The purpose of this paper is to examine the impact of lean and agile attributes towards triple constraints and develop intelligent supply chains for construction projects in Malaysia. The research model on the topic was constructed based on literature review and pilot study, wherein the most significant lean and agile attributes that impact time, cost and scope constraints towards project success were selected as the independent variables. In addition to exploring research opportunity to close existing research gap, the main outcome of the research revealed the critical factors that impact the respective triple constraints towards construction project success in Malaysia and they have been identified. Systematic evaluation of the research model based on four tested variables, which are supply chain networks, employee empowerment, quality control and supplier networking was conducted. The data collected was analyzed using SPSS and SmartPLS. The result suggested that the research model and hypotheses were statistically supported. Significant factors which impact supply chains in construction project success in Malaysia are identified from this study.
Keywords: Intelligent Supply Chains;Lean and Agile Attributes;Construction Projects
Review score: Moderate
Review comment: This paper investigated relevant agile and lean attributes dealing with triple constraints in order to ensure project success and develop intelligent supply chain in the construction industry. Authors are advised to showcase the contribution of the paper with  respect to previous published literature. Also, make Figure 1 and 2 more visible.
Title: Developing Intelligent Supply Chain System Adopting Lean and Agile Attributes for Construction Projects in Malaysia
Abstract: The purpose of this paper is to examine the impact of lean and agile attributes towards triple constraints and develop intelligent supply chains for construction projects in Malaysia. The research model on the topic was constructed based on literature review and pilot study, wherein the most significant lean and agile attributes that impact time, cost and scope constraints towards project success were selected as the independent variables. In addition to exploring research opportunity to close existing research gap, the main outcome of the research revealed the critical factors that impact the respective triple constraints towards construction project success in Malaysia and they have been identified. Systematic evaluation of the research model based on four tested variables, which are supply chain networks, employee empowerment, quality control and supplier networking was conducted. The data collected was analyzed using SPSS and SmartPLS. The result suggested that the research model and hypotheses were statistically supported. Significant factors which impact supply chains in construction project success in Malaysia are identified from this study.
Keywords: Intelligent Supply Chains;Lean and Agile Attributes;Construction Projects
Review score: Moderate
Review comment: Figure 2 quality should be impoved. There must be no citation in conclusion part. "According to Fronell-Larcker criterion,
HTML and model fit results, it was concluded that
discriminant validity of relationship between independent
variables and dependent variables were supported' HTML is supposed to be HTMT.
Title: Game-Theory Model of a Two-Level Hierarchical Game with Distributed Control
Abstract: Synergic soundness of combining activities of competence points at managing a particular item being a player in a hierarchical game was confirmed as per the game and theoretical pattern. An arbitrary set comprising a couple of points of intelligence was studied as a bi-level hierarchical game. Authors have scrutinized all prerequisites for antagonism and game equilibrium, they have confirmed the efficiency of strategies of merger or cooperation of the player management centers in a system with distributed control. The thesis is exploring the elaborated methodology of investigating propositions raised by crew personnel towards precluding contradictory statuses within the phase of the crew foundation. The scrutinized procedure is built-up on fundamentals of the game and theory ideas. Controversies among multiple crew players basically emerge during the crew establishing period. For a program leader, the main assignment is to reveal a deviating status beforehand enough and to discover a path forward to solve the same for the benefit of every crew player and with no injury to the crew activities in the whole. A crew that was constituted towards fulfilment of a joint project frequently faces a position in which a couple of players involved in it form their deviating opinion about the concepts of the ultimate produce establishing. In that situation, either of the players possesses a vast knowledge in elaborating produces and activities of such kind in a series of crews belonging to their practical skills.
Keywords: Nash equilibrium;hierarchical game;point;Pareto efficiency;participant;objective functional;tactics;mitigation matrix
Title: Development of a Method for Finding Scientific Partners Based on Document Clustering in the Form of Key Phrase Vectors
Abstract: The article is dedicated to the development of a method for identifying key phrases in the works of subjects engaged in scientific activities with the aim of automating the process of searching for scientific partners. The method is capable of identifying key phrases from documents, taking into account the context and semantics of the subject area requested by the user in the form of a vector. This method represents an effective tool for the analysis and identification of potential scientific partners.The proposed method is implemented as a software module of the information system for evaluating the scientific activities of universities, research institutes, and their departments. The paper also presents the algorithm of this method, which includes extracting semantic structures, determining the similarity between the identified key words and the user's query, and searching for scientific partners. The results of this research are of interest to scientific fields oriented towards collaboration and partnership in scientific research.
Keywords: context-oriented search;scientific partners;semantic relations;text analysis;information systems;collaborations in science;information extraction
Review score: High
Review comment: 1. It is necessary to number the formulas in accordance with the requirements
2. Figures should be designed according to the specified requirements
3. There is no information available regarding the integration of the information system into the evaluation of scientific activities at universities and other organizations.
Title: Development of a Method for Finding Scientific Partners Based on Document Clustering in the Form of Key Phrase Vectors
Abstract: The article is dedicated to the development of a method for identifying key phrases in the works of subjects engaged in scientific activities with the aim of automating the process of searching for scientific partners. The method is capable of identifying key phrases from documents, taking into account the context and semantics of the subject area requested by the user in the form of a vector. This method represents an effective tool for the analysis and identification of potential scientific partners.The proposed method is implemented as a software module of the information system for evaluating the scientific activities of universities, research institutes, and their departments. The paper also presents the algorithm of this method, which includes extracting semantic structures, determining the similarity between the identified key words and the user's query, and searching for scientific partners. The results of this research are of interest to scientific fields oriented towards collaboration and partnership in scientific research.
Keywords: context-oriented search;scientific partners;semantic relations;text analysis;information systems;collaborations in science;information extraction
Review score: Moderate
Review comment: This article presents a method based on document clustering in the form of a vector of key phrases for extracting information from scientific works and searching for potential scientific partners.  The authors have successfully crafted the method that capable of identifying key phrases from documents, taking into account the context and semantics of the subject area requested by the user in the form of a vector. This method represents an effective tool for the analysis and identification of potential scientific partners.
Title: Structural analysis in the methodology of building an IT project model
Abstract: Dividing a project into hierarchical subsystems and components is a concept aimed at increasing the efficiency of project management and minimizing risks in achieving its objectives. Goals, works, performers, resources, and deadlines for completing the main stages of the project are subjects to be structured. The article examines how the construction of an IT project model interacts with its structure, the stages of project structuring were analyzed. Attention is focused on the use of hierarchical ordering methodology when planning a project, defining goals and constructing a matrix for the distribution of responsibilities and duties.
Keywords: structure;IT project models;structuring methods;project management
Review score: High
Review comment: It would be desirable to formulate a criterion for the effectiveness of the proposed approach
Title: Structural analysis in the methodology of building an IT project model
Abstract: Dividing a project into hierarchical subsystems and components is a concept aimed at increasing the efficiency of project management and minimizing risks in achieving its objectives. Goals, works, performers, resources, and deadlines for completing the main stages of the project are subjects to be structured. The article examines how the construction of an IT project model interacts with its structure, the stages of project structuring were analyzed. Attention is focused on the use of hierarchical ordering methodology when planning a project, defining goals and constructing a matrix for the distribution of responsibilities and duties.
Keywords: structure;IT project models;structuring methods;project management
Review score: High
Review comment: The article's discussion on the responsibility matrix and its role in linking work packages to project performers showcases a pragmatic approach to project management. This matrix is crucial for clear communication and the effective distribution of tasks among team members, ensuring that everyone understands their responsibilities and the expectations placed upon them. The emphasis on this aspect of project management is particularly relevant in today's team-oriented work environments, where collaboration and clear communication are key to achieving project goals.

While the article provides a robust framework for IT project management, it could further benefit from exploring the integration of modern project management tools and technologies. In the age of digital transformation, leveraging project management software, collaboration tools, and advanced analytics can enhance the efficiency and effectiveness of the methodologies discussed. Additionally, incorporating insights on agile project management methodologies could offer readers a more comprehensive view of the field, given the growing adoption of agile practices in IT projects.

Incorporating these elements into future discussions would not only enhance the article's comprehensiveness but also its applicability to current and future IT project management challenges. As IT projects continue to grow in complexity and scale, the methodologies outlined in the article provide a solid foundation for managing such projects effectively. However, integrating modern tools and methodologies could offer project managers additional strategies and techniques for navigating the dynamic and often unpredictable landscape of IT project management.
Title: Using Computer Modeling for Tracking high-order Nonlinear Systems with Time-Delay
Abstract: This paper investigates the challenge of globally practically tracking a class of high-order nonlinear systems with time delay via feedback. The object of study is a nonlinear system, the main goal is to develop a control function that allows you to regulate the output data of the specified nonlinear system using a reference signal. The article publication is distinguished by its scientific novelty due to the study of a system in which the degree of the upper limit of nonlinearity is determined within a continuous interval. The system under examination exhibits a distinctive characteristic, wherein the extent of the upper boundary limitation of nonlinearity is defined within a continuous interval. We propose a customizable and delay-independent tracking controller designed to mitigate the impact of delay time non-linearity. This is achieved by generating a Lyapunov function using a generalized approach that involves incorporating a signum function and a power integrator. The resulting controller ensures the global boundedness of all states within the closed system, along with a sufficiently small control error over a finite time. Additionally, this work places emphasis on computer simulations to validate previously obtained results.
Keywords: Nonlinear systems;tracking;signum function;time delay;computational modeling;Matlab graphical user interface (GUI)
Review score: Moderate
Review comment: The paper must be formatted according to the conference requirements.