Arailym-tleubayeva/sist-english-corpus huggingface dataset:
Title: Study of Cardiovascular Diseases in the Retina, Obtained by Optical Coherence Tomography
Abstract: With the rapid development of artificial intelligence technology, the degree of integration of medicine and artificial intelligence is increasingly strengthened, and in the medical field, due to the aggravated aging of population in China, the impact of cardiovascular risk factors on the residents' health has become more and more significant. In our country, diseases of the cardiovascular system are the main cause of death every year, almost on a par with the consequences of COVID-19, cardiovascular diseases annually claim the lives of more than 2.5 million people a year. This number is steadily growing every year. The negative upward trend in the incidence of the cardiovascular system increases the relevance of the proposed work. For this reason, the object of study of the proposed article was the study of pathologies of the cardiovascular system.The main object of the research is an automated artificial intelligence system for the study of three types of cardiovascular diseases (CVD) in the retina (hypertensive retinopathy, retinal artery occlusion, ischemic neuropathy), obtained by photographing the fundus using modern artificial intelligence algorithms (Deep Neural Networks (DNN).This paper aimed to develop an intelligent system for the study of cardiovascular pathologies (hypertensive retinopathy, retinal artery occlusion, ischemic neuropathy) based on images of the retina of the fundus with the possibility of diagnosing some complications.As a result, the study of three types of cardiovascular diseases based on images of optical coherence tomography, implemented with a machine learning module for predicting the risk of developing the disease with diagnostic and consulting functionality. The model showed an accuracy of 92% which obtained results are good performance indicators of the system.
Keywords: optical coherence tomography;artificial intelligence;cardiovascular diseases;retina;neural networks;pattern recognition
Review score: Moderate
Review comment: 1. The characteristics of the dataset on which the study was conducted need to be sufficiently reflected in the research. In particular, the ratio of patients without CVD could be more precise.
2. The results of training accuracy presented in the conclusions are outside the article's main text and require detailed disclosure.
3. The advantages of the proposed technology over competitors should be highlighted more clearly
Title: Study of Cardiovascular Diseases in the Retina, Obtained by Optical Coherence Tomography
Abstract: With the rapid development of artificial intelligence technology, the degree of integration of medicine and artificial intelligence is increasingly strengthened, and in the medical field, due to the aggravated aging of population in China, the impact of cardiovascular risk factors on the residents' health has become more and more significant. In our country, diseases of the cardiovascular system are the main cause of death every year, almost on a par with the consequences of COVID-19, cardiovascular diseases annually claim the lives of more than 2.5 million people a year. This number is steadily growing every year. The negative upward trend in the incidence of the cardiovascular system increases the relevance of the proposed work. For this reason, the object of study of the proposed article was the study of pathologies of the cardiovascular system.The main object of the research is an automated artificial intelligence system for the study of three types of cardiovascular diseases (CVD) in the retina (hypertensive retinopathy, retinal artery occlusion, ischemic neuropathy), obtained by photographing the fundus using modern artificial intelligence algorithms (Deep Neural Networks (DNN).This paper aimed to develop an intelligent system for the study of cardiovascular pathologies (hypertensive retinopathy, retinal artery occlusion, ischemic neuropathy) based on images of the retina of the fundus with the possibility of diagnosing some complications.As a result, the study of three types of cardiovascular diseases based on images of optical coherence tomography, implemented with a machine learning module for predicting the risk of developing the disease with diagnostic and consulting functionality. The model showed an accuracy of 92% which obtained results are good performance indicators of the system.
Keywords: optical coherence tomography;artificial intelligence;cardiovascular diseases;retina;neural networks;pattern recognition
Review score: Moderate
Review comment: The article is interesting and relevant. But there are remarks:
- the annotation needs to be reworked.
(The summary should be built according to the following scheme: the object of the study - the problem that was being solved - the essence of the results obtained - thanks to which features and characteristic differences these results allowed to solve the specified problem - how these results are explained - under what conditions they can be used in practice. )
- to expand information about data collection, their preliminary processing;
- there is no justification for choosing a neural network.
- revise the introduction. Reduce information from the medical field, and add from IT.
- the article needs to be mathematically formalized.
- to present the purpose and tasks of the research, as well as scientific novelty.
- to build conclusions according to the research objectives
Title: Spatial Analysis of Turkey 2023 Seismic Activity: Geographical Distribution Research
Abstract: Pre-crisis management involves selecting the most suitable sites for construction and emergency response centers to minimize risk and vulnerability. The southeastern part of Turkey sits at the intersection of the Anatolian and Arabian lithospheric plates. Prolonged, consistent pressure has led to a devastating earthquake. To optimally locate future buildings and aid centers, as well as reduce risks to affected populations, the underlying ground for construction should be thoroughly investigated. To address this, the study utilized geographic information systems (GIS). ArcGIS was employed to overlay layers and epicenters of seismic activity in Turkey, illustrating the methods and tools used for earthquake data analysis and visualization on a map. The article covers key data processing steps, including data collection and preprocessing, selection of pertinent geographic data, and creation of geospatial visualizations based on data analysis. The outcomes of this analysis offer valuable insights for geologists, seismologists, and urban planners, aiding in a better understanding of regional seismic activity and informing measures to reduce risks, enhance safety, and guide future development.
Keywords: seismic activity;Turkey;visualization;ArcGIS Spatial Analysis;interpolation
Review score: Low
Review comment: 1. It is recommended to improve English in the paper
2. Abstract is too small. It must be appx 200-250 words
3. Inlcude Literature review either inside of introduction or as a separate section
4. There is no clear problem statement/hypothesis/research question, include indication of research contribution in the introduction.
5. Include limitations or constraints of the research in the conclusion
6. Inadequate organization and structure: A research paper should have an IMRAD structure, clear introduction, methods, results and conclusion or/and discussion.  Ensure that each paragraph has a clear topic sentence, and the overall paper  structure follows a logical progression
7.The references need to be expanded to include more recent sources (last 3-5 years, indexed in Scopus)
8. It is recommended to include a methodology figure that explains the approach taken in this research paper
Title: Spatial Analysis of Turkey 2023 Seismic Activity: Geographical Distribution Research
Abstract: Pre-crisis management involves selecting the most suitable sites for construction and emergency response centers to minimize risk and vulnerability. The southeastern part of Turkey sits at the intersection of the Anatolian and Arabian lithospheric plates. Prolonged, consistent pressure has led to a devastating earthquake. To optimally locate future buildings and aid centers, as well as reduce risks to affected populations, the underlying ground for construction should be thoroughly investigated. To address this, the study utilized geographic information systems (GIS). ArcGIS was employed to overlay layers and epicenters of seismic activity in Turkey, illustrating the methods and tools used for earthquake data analysis and visualization on a map. The article covers key data processing steps, including data collection and preprocessing, selection of pertinent geographic data, and creation of geospatial visualizations based on data analysis. The outcomes of this analysis offer valuable insights for geologists, seismologists, and urban planners, aiding in a better understanding of regional seismic activity and informing measures to reduce risks, enhance safety, and guide future development.
Keywords: seismic activity;Turkey;visualization;ArcGIS Spatial Analysis;interpolation
Review score: Low
Review comment: The material presented in the article is more methodological than scientific in nature. It is well-suited for teaching ArcGIS and it lacks scientific novelty, focusing on the study of tools. To strengthen the scientific component, it is necessary to expand the literature review and more clearly demonstrate the novelty of the approach.
Title: A hybrid approach for a movie recommender system using Content-Based, Collaborative and Knowledge-Based Filtering methods
Abstract: Rapid evolution of information technology has rapidly increased the significance of Internet-generated data. As a result, finding specific information within this vast data landscape has become increasingly challenging for individuals. Recommender systems have emerged as precious tools in response to this challenge, offering assistance in navigating and extracting relevant information from the abundance of available data. As user engagement increases in importance, recommender systems will be considered an integral part of personalized marketing. The most common methods leverage product features (Content-Based), user similarity (Collaborative Filtering), and personal information (Knowledge-based). However, with the increasing popularity of Neural Networks, companies have started experimenting with new Hybrid Recommendation Systems that combine them all. This study thoroughly assesses the strengths and limitations of prevalent filtering methods, aiming to introduce an advanced hybrid recommender system. By integrating content-based, collaborative, and knowledge-based techniques, the hybrid model notably enhances recommendation accuracy, effectively addressing challenges like the "cold start" problem and data sparsity issues.
Keywords: Machine Learning;Neural Networks;Collaborative filtering;Content-Based filtering;Knowledge-based filtering;Hybrid Recommendation System
Review score: High
Review comment: Dear authors, the proposed approach is very interesting and relevant but you should to add some experiments comparing your new method with baselines. So you need some real data and should get reliable values of scores to assess your  method.
Title: A hybrid approach for a movie recommender system using Content-Based, Collaborative and Knowledge-Based Filtering methods
Abstract: Rapid evolution of information technology has rapidly increased the significance of Internet-generated data. As a result, finding specific information within this vast data landscape has become increasingly challenging for individuals. Recommender systems have emerged as precious tools in response to this challenge, offering assistance in navigating and extracting relevant information from the abundance of available data. As user engagement increases in importance, recommender systems will be considered an integral part of personalized marketing. The most common methods leverage product features (Content-Based), user similarity (Collaborative Filtering), and personal information (Knowledge-based). However, with the increasing popularity of Neural Networks, companies have started experimenting with new Hybrid Recommendation Systems that combine them all. This study thoroughly assesses the strengths and limitations of prevalent filtering methods, aiming to introduce an advanced hybrid recommender system. By integrating content-based, collaborative, and knowledge-based techniques, the hybrid model notably enhances recommendation accuracy, effectively addressing challenges like the "cold start" problem and data sparsity issues.
Keywords: Machine Learning;Neural Networks;Collaborative filtering;Content-Based filtering;Knowledge-based filtering;Hybrid Recommendation System
Review score: Moderate
Review comment: 1.	The critical analysis of the subject area is not of sufficient quality. Only 5 sources were considered, which is an insufficient number. About 20 is recommended.
2.	The algorithm is not a scientific result. Authors have to present a research model or method.
3.	In conclusion, the authors write that « The results indicate that using a hybrid approach can enhance the quality of recommendations compared to using only one method separately». But this has not been confirmed by anything. It is recommended to create a table of metrics to compare the numerical values of these approaches.
4.	 There is no formula (1), but there are two formulas (2).
Title: Development of Clustering Methods Based on Interval Fuzzy Sets of the Second Type and Genetic Algorithms
Abstract: Cluster analysis is often used to solve the problems of assessing the technical condition of construction objects. Among clustering methods, the cmeans method is the most popular. The application of the apparatus of the theory of fuzzy sets together with the method of c-means, namely, the algorithm of fuzzy cmeans, gives good results. The article considers the problem of solving the problem of object clustering using the algorithm of possible c-means together with interval fuzzy sets of the second type and the genetic algorithm. The results presented in the article demonstrate stable good results, which confirms the expediency of its application in solving clustering problems.
Keywords: clustering methods;fuzzy sets;fuzzy c-means;possibilistic c-means;typicality functions;membership functions;fuzzifier;"zone width"
Review score: Moderate
Review comment: 1) The author are advised to follow the prescribed format.
2) Reference are not cited well and authors are advised to increse the number of refrences . The Auhors presented only 04 reference .
3) The equation required to rewite in proper format with proper numbersing .
4) Technially paper is good .
Title: Development of Clustering Methods Based on Interval Fuzzy Sets of the Second Type and Genetic Algorithms
Abstract: Cluster analysis is often used to solve the problems of assessing the technical condition of construction objects. Among clustering methods, the cmeans method is the most popular. The application of the apparatus of the theory of fuzzy sets together with the method of c-means, namely, the algorithm of fuzzy cmeans, gives good results. The article considers the problem of solving the problem of object clustering using the algorithm of possible c-means together with interval fuzzy sets of the second type and the genetic algorithm. The results presented in the article demonstrate stable good results, which confirms the expediency of its application in solving clustering problems.
Keywords: clustering methods;fuzzy sets;fuzzy c-means;possibilistic c-means;typicality functions;membership functions;fuzzifier;"zone width"
Review score: Moderate
Review comment: It is strongly recommended that the authors increase the reference list as only 4 sources were used. Also recommended to include links to articles starting in 2020, which will allow for a more detailed review of the literature.
Title: Development of Clustering Methods Based on Interval Fuzzy Sets of the Second Type and Genetic Algorithms
Abstract: Cluster analysis is often used to solve the problems of assessing the technical condition of construction objects. Among clustering methods, the cmeans method is the most popular. The application of the apparatus of the theory of fuzzy sets together with the method of c-means, namely, the algorithm of fuzzy cmeans, gives good results. The article considers the problem of solving the problem of object clustering using the algorithm of possible c-means together with interval fuzzy sets of the second type and the genetic algorithm. The results presented in the article demonstrate stable good results, which confirms the expediency of its application in solving clustering problems.
Keywords: clustering methods;fuzzy sets;fuzzy c-means;possibilistic c-means;typicality functions;membership functions;fuzzifier;"zone width"
Review score: Low
Review comment: I propose to change the following in the article:
1) Wherever there are formulas or expression, use the same font types (use "Symbols"->"Equation"), especially within the text and in the figure title (specially for m, t, j and exc.) and in Eqn (12). Do not use italics to indicate "if","and" within equations.
2) Before mentioning the short name of methods and algorithms, expand on their full names, e.g. for FSM, IIMT1, IFST2 and exc. For GA, expand full name in first mention.
3) Сhange Ukrainian words in figures into English words, see Figure 2 and 3.
4) The following sentences are repeated twice in the Introduction section: "If a set of objects consists of compact and well-separated clusters, then the desired clustering result can be obtained using the c-means algorithm. But in practical problems, sets of objects are rarely like this.". You have to keep one of the variants.
5) There are very few reviews of existing works, and those mentioned in the reference list are old and new ones need to be included
6) Correct the spelling of some words, e.g. ALGORITHMN, SEOND, CLSTERING, FOT, INTEVAL and exc.
7) Correct the following points: x_i (1,n) --> x_i (i=1,n), X_i-->x_i, N_c/-->N_c. and exc.
8) replace "i" with "and" or delete it, e.g. η_j1 і η_j2, η_j1=0,25 і η_j2=0,75, : m_1 і m_2  and exc.
9) Instead of repeating the "zone width" η_j (j=(1,c)), use its notation η_j after the first mention of it.
10) Use the same form of sums in Eqn.(5) or generalize the two equations into one, using  the index for m_1 and m_2 and the same for Eqn.(6). Explain the parameters V and W in Eqns.(5)-(6)
11) in Eqn. (11) remove the bold font from the scalar parameters
Title: Methodology for Developing an Information System for Internal Audit Support
Abstract: This paper provides outlines after conducting a study of internal audit information systems that exist and are still used in Ukraine, we can conclude that to solve the problem in the dissertation research - the development of an intelligent system for supporting the internal audit of an entity (ISISA SG), it is necessary to use the latest (digital) technologies of version 4.0.Digital technologies (according to analytical reports of the Davos Economic Forum): Internet of Things, robotisation and cyber systems, artificial intelligence, big data, paperless technologies, additive technologies (3D printing), cloud and fog computing, unmanned and mobile technologies, biometric technologies, quantum technologies, identification technologies, blockchain (the list is not exhaustive and is being supplemented) [1].Digital transformation means the integration of digital technologies into all areas of business. This integration leads to fundamental changes in the way citizens and business entities operate, how they provide value for themselves, their employees, customers, and partners, achieving their own and common, economic and social goals faster, cheaper, and with new quality [1].An intelligent system for solving tasks to support the internal audit of a business entity contains subsystems that provide audit and the main functionalities of the built-in subsystems for supporting and ensuring audit.
Keywords: IASIS;software system;digital transformation;Big Data
Review score: Moderate
Review comment: The topic of the article is relevant, but it is possible to make adjustments in the Introduction section.
The section is mainly presented by a description of well-known terms. This section needs improvement.
Title: Methodology for Developing an Information System for Internal Audit Support
Abstract: This paper provides outlines after conducting a study of internal audit information systems that exist and are still used in Ukraine, we can conclude that to solve the problem in the dissertation research - the development of an intelligent system for supporting the internal audit of an entity (ISISA SG), it is necessary to use the latest (digital) technologies of version 4.0.Digital technologies (according to analytical reports of the Davos Economic Forum): Internet of Things, robotisation and cyber systems, artificial intelligence, big data, paperless technologies, additive technologies (3D printing), cloud and fog computing, unmanned and mobile technologies, biometric technologies, quantum technologies, identification technologies, blockchain (the list is not exhaustive and is being supplemented) [1].Digital transformation means the integration of digital technologies into all areas of business. This integration leads to fundamental changes in the way citizens and business entities operate, how they provide value for themselves, their employees, customers, and partners, achieving their own and common, economic and social goals faster, cheaper, and with new quality [1].An intelligent system for solving tasks to support the internal audit of a business entity contains subsystems that provide audit and the main functionalities of the built-in subsystems for supporting and ensuring audit.
Keywords: IASIS;software system;digital transformation;Big Data
Review score: High
Review comment: 1. The conclusions should be supplemented by an assessment of the simulation results of the proposed models and directions for future research
2. The list of references should be expanded.
3. Add the text to the full 4 pages.
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: Moderate
Review comment: Dear authors, we appreciate the effort you put into submitting your article to the SIST 2024. We carefully reviewed the submissions, and unfortunately, we regret to inform you that your article has not been accepted for presentation at the conference.

Our selection process was highly competitive, and we received numerous submissions covering a wide range of topics. While your work is undoubtedly valuable, we had to make difficult decisions to ensure that the selected presentations align closely with the conference theme and objectives.

We appreciate your understanding and encourage you to consider submitting your future work to SIST or other events that may be a better fit for your research.

Thank you for your interest in our conference, and we wish you continued success in your research endeavours.