Arailym-tleubayeva/sist-english-corpus huggingface dataset:
Title: Ontological Analysis of Cognitive Information Technologies Subject Area
Abstract: The most important problem of automated ontology building is intellectualisation, and the related data integration and qualitative information retrieval. In the light of the issues of data science and advanced analytics, the task of automated ontology formation is quite relevant. A common criterion for the quality of an ontology is based on an assessment of the convenience and efficiency of working with it and the connection of cognitive processes with semantic ones for its construction and updating. The main difference of the analysis, the results of which are presented in this paper, is the cognitive information technologies of the subject area, cognitive and semantic analysis based on the theory of categories, mathematical logic and universal algebra, construction of an ontological dictionary, ontological constructions, which was carried out for the first time. The information interaction of the intellectual environment of the object with the subject is determined. For the formation of the concept in the intellectual environment due to the connected information space, the possibility and justification of its use for normalising the concept and its features within the framework of the problematic is determined.
Keywords: cognitive;technology;ontology;concept;thesaurus;information object;semantics;intellectual environment;definition;formalisation
Title: Deep Transformer Network and CNN Model with About 200k Parameters to Classify P300 EEG Signal
Abstract: This research gathers participants“ electroencephalographic (EEG) data to build classifiers that can decode users” mental states. Although deep learning models can incorporate domain-dependent feature extraction into the classifier design, the architecture selection process for BCIs is often based on domain expertise. This paper examines whether it can build reliable classifiers for interpreting P300 event-related potentials using a systematic model selection mixed with common deep learning architectures. We report the findings of a CNNTransformer network model with 50k and 200k parameters in particular. We systematically investigate if a hybrid architecture which is Transformer and CNN, can improve the classification performance of P300 datasets. Because we would like to know how to improve the model selection process for P300 signals data analysis. To help the readers understand that the best model selection strategy with more muscular models than the existing ones may make the lives of stroke patients more convenient. If our readers are targeting to know the modern muscular deep learning architectures to analyze their recorded P300 dataset, then we recommend reading this paper.
Keywords: P300;Brain-computer interface (BCI);Deep Neural Network (DNN);Transformer Network;CNN
Review score: High
Review comment: This study collects electroencephalographic (EEG) data from participants to create classifiers that can interpret users' emotional states. The authors used a hybrid CNN transformer with 50k parameters and a hybrid CNN transformer with 200k parameters to create classifiers for the ERP P300. The authors used three well-known deep learning architectures—conventional layer CNNs, LSTMs, and hybrid CNN-LSTMs, Transformers—in a methodical, two-step approach to model selection to create classifiers for the ERP P300. 
The authors showed that hybrid architectures with transformers can improve classification efficiency. The authors propose a strategy for a two-stage systematic choice of a model, which allows to reduce the influence of knowledge of the subject area on the choice of architecture. The authors demonstrated the promise of using transformers in combination with deep learning models for signal classification.
The article is well structured and contains all the necessary sections for a scientific article. The section concerning datasets from open sources, preprocessing of experimental data is described in detail. A review of works on this topic is given. The authors described in detail the proposed architecture of the hybrid neural model with the rationale for applying methods such as Dropout on certain layers of the model. A large amount of experiments have been carried out, the results of which demonstrate the scientific value of the presented work.
Recommendations: 
1.	On the graph in fig. 2 add labels to the axes and units of measure.
2.	Table II with the results of the experiments is cumbersome. It should be divided for a more compact and easy-to-read look.
Title: Deep Transformer Network and CNN Model with About 200k Parameters to Classify P300 EEG Signal
Abstract: This research gathers participants“ electroencephalographic (EEG) data to build classifiers that can decode users” mental states. Although deep learning models can incorporate domain-dependent feature extraction into the classifier design, the architecture selection process for BCIs is often based on domain expertise. This paper examines whether it can build reliable classifiers for interpreting P300 event-related potentials using a systematic model selection mixed with common deep learning architectures. We report the findings of a CNNTransformer network model with 50k and 200k parameters in particular. We systematically investigate if a hybrid architecture which is Transformer and CNN, can improve the classification performance of P300 datasets. Because we would like to know how to improve the model selection process for P300 signals data analysis. To help the readers understand that the best model selection strategy with more muscular models than the existing ones may make the lives of stroke patients more convenient. If our readers are targeting to know the modern muscular deep learning architectures to analyze their recorded P300 dataset, then we recommend reading this paper.
Keywords: P300;Brain-computer interface (BCI);Deep Neural Network (DNN);Transformer Network;CNN
Review score: High
Review comment: As a result of reviewing the article I recommend the article for publication with minor (technical) corrections «Accepted with minor revision».
- it is necessary to issue an article according to a template:
•	paper title(In the paper title, capitalize the first letter of the first and last word and all the nouns, pronouns, adjectives, verbs, adverbs, and subordinating conjunctions);
•	figures(Figure Labels: Use 8 point Times New Roman for Figure labels. Place figures and tables after they are first cited in the text. Use the abbreviation “Fig. 1”, even at the beginning of a sentence, there should be a single indent before and after the figure);
•	-references(Capitalize only the first word in a paper title, except for proper nouns and element symbols).
- references should be no later than 5-7 years from the current year.
Check 1 paragrarhp of Methodology part, the numbering of the figure is replaced by signs ??
Title: The Future of Retail Investing: Goal-Oriented Asset Allocation Platforms
Abstract: This research paper examines the advantages of developing goal-oriented asset allocation platforms for retail investors who lack the time or expertise to allocate their assets. The study includes a survey of retail investors to identify their main concerns and preferences in asset allocation, as well as interviews with financial experts to gain insight into the current state of the industry. A case study of the largest asset allocation platforms is presented to demonstrate their effectiveness in meeting the needs of retail investors. The paper concludes by outlining the potential benefits of goal-oriented asset allocation platforms and their role in the future of retail investing. Overall, this paper provides valuable insights into how retail investors can achieve their investment goals with the help of automated asset allocation tools.
Keywords: asset allocation;risk tolerance;AI and machine learning;retail investing;robo-advisors
Review score: Low
Review comment: The publication is devoted to an interesting and relevant topic. However, the work has a practical nature and needs to be improved in terms of formulating the scientific significance of the proposed research.
Notes that must be taken into account in order for the article to be accepted for publication:
1. It is necessary to formulate the scientific novelty of the publication, both in the abstract and in the text of the article. Indicate the goals of the study and its objectives.
2. The use of the term "optimization" in the title implies the existence of an objective function, optimization criteria, etc. Optimization is an established technical term. The title of the article needs to be improved.
3. Section "Introduction" needs to be improved
4. How valid is a sample of 25-30 financial experts? Why was this number of experts chosen? Additional explanations are needed.
5. Conclusions need to be reworked. The conclusions should be fully correlated with the objectives of the study.
6. It is necessary to bring the structure of the publication in accordance with the requirements of the conference.

After correcting all the comments, the article can be accepted for participation in the conference.
Title: The Future of Retail Investing: Goal-Oriented Asset Allocation Platforms
Abstract: This research paper examines the advantages of developing goal-oriented asset allocation platforms for retail investors who lack the time or expertise to allocate their assets. The study includes a survey of retail investors to identify their main concerns and preferences in asset allocation, as well as interviews with financial experts to gain insight into the current state of the industry. A case study of the largest asset allocation platforms is presented to demonstrate their effectiveness in meeting the needs of retail investors. The paper concludes by outlining the potential benefits of goal-oriented asset allocation platforms and their role in the future of retail investing. Overall, this paper provides valuable insights into how retail investors can achieve their investment goals with the help of automated asset allocation tools.
Keywords: asset allocation;risk tolerance;AI and machine learning;retail investing;robo-advisors
Review score: Moderate
Review comment: You need to re-read the article carefully, there are a number of grammatical errors.
It is better to use the word "tool" rather than "instrument" in your context.
The title loudly states the development of the platform, but the article does a very basic market analysis for such a platform and outlines the technical requirements in general terms. It would still be good to describe at least something about the development of the platform as such.
Let's consider the article as a prelude to quality application development, so I'm going to pass it over conditionally
Title: Using of Fuzzy Logic for Risk Assessment of Construction Enterprise Management System
Abstract: This study presents a fuzzy production model (FPM) for risk assessment of the construction enterprise management system. The task of the research is to explore the feasibility of risk analysis model based on fuzzy logic, which allows it to be adapted to existing risk management models and modified taking into account the real conditions for the implementation of an investment and construction project. The authors suggest FPM with a set of input parameters that characterize risk factors, a set of output parameters that characterize the risks indicators and base of fuzzy production rules. The result is presented by the process of implementing fuzzy modeling of the rule base using the developed ModelingFuzzyLogic system based on the Mamdani algorithm and allows getting a linguistic description of the degree of risk and its numerical value. The results of the study are recommended for use in the management system of a construction enterprise to identify potential risks in the implementation of an investment and construction project.
Keywords: fuzzy production model;risk assessment;management system;construction enterprise;fuzzy logic
Review score: Moderate
Review comment: The formulas' quality must be improved.
Title: Using of Fuzzy Logic for Risk Assessment of Construction Enterprise Management System
Abstract: This study presents a fuzzy production model (FPM) for risk assessment of the construction enterprise management system. The task of the research is to explore the feasibility of risk analysis model based on fuzzy logic, which allows it to be adapted to existing risk management models and modified taking into account the real conditions for the implementation of an investment and construction project. The authors suggest FPM with a set of input parameters that characterize risk factors, a set of output parameters that characterize the risks indicators and base of fuzzy production rules. The result is presented by the process of implementing fuzzy modeling of the rule base using the developed ModelingFuzzyLogic system based on the Mamdani algorithm and allows getting a linguistic description of the degree of risk and its numerical value. The results of the study are recommended for use in the management system of a construction enterprise to identify potential risks in the implementation of an investment and construction project.
Keywords: fuzzy production model;risk assessment;management system;construction enterprise;fuzzy logic
Review score: Moderate
Review comment: The presented study introduces a novel fuzzy production model that utilizes fuzzy logic to assess risks associated with construction enterprise management systems. The primary objective of this research is to assess the feasibility of a risk analysis model based on fuzzy logic, which can be adapted to existing risk management models and modified based on the actual conditions of implementing an investment and construction project. The model utilizes a set of input parameters that describe the risk factors and a set of output parameters that indicate risk indicators along with a base of fuzzy production rules.

The authors employed the Mamdani algorithm to implement fuzzy modeling of the rule base, which enabled the linguistic description of the degree of risk and its numerical value. The study recommends using the results of this FPM in the management system of a construction enterprise to identify potential risks during the implementation of an investment and construction project.

Overall, this study presents a valuable contribution to the field of construction enterprise risk assessment by introducing a new approach to modeling risks using fuzzy logic. The use of fuzzy logic allows for a more adaptable and flexible model that can be modified based on real-world conditions, enabling more accurate risk assessments. The application of the Mamdani algorithm to implement the fuzzy modeling of the rule base is also commendable, as it enables the linguistic description of the degree of risk and its numerical value. This study's findings are recommended for use in the management system of a construction enterprise to identify potential risks and enable informed decision-making during the implementation of investment and construction projects.
Title: Application of the Algorithm for Analyzing Stock Prices Based on Sentiment Analysis
Abstract: Making predictions about stock prices aloneis difficult and can lead to inaccurate results. Thus, the rise or fall in the price of a stock can also be influenced by psychological factors such as new investments, current events, new product launches, or even natural disasters. All of the above factors shape the mood of the market, which may be directly related to investors to a particular stock or financial market. This article will explain what stock sentiment analysis is, examples of sentiment indicators, and how this semantic kind of analysis can be applied to stock analysis.
Keywords: Cross market analysis;algorithms;sentiment analysis;financial instruments;investment decisions
Review score: Moderate
Review comment: The article is relevant and devoted to applying the algorithm for analyzing stock prices based on sentiment analysis. The paper has a high similarity index (> 30%). In general, the paper can be recommended for the conference, but you'll need to improve it.
Title: Application of the Algorithm for Analyzing Stock Prices Based on Sentiment Analysis
Abstract: Making predictions about stock prices aloneis difficult and can lead to inaccurate results. Thus, the rise or fall in the price of a stock can also be influenced by psychological factors such as new investments, current events, new product launches, or even natural disasters. All of the above factors shape the mood of the market, which may be directly related to investors to a particular stock or financial market. This article will explain what stock sentiment analysis is, examples of sentiment indicators, and how this semantic kind of analysis can be applied to stock analysis.
Keywords: Cross market analysis;algorithms;sentiment analysis;financial instruments;investment decisions
Review score: High
Review comment: Nowadays it is hard to imagine how the financial market will go and what can be expected tomorrow. This article discusses an algorithm for analyzing stock prices based on sentiment analysis,

This method selects keywords, which are then assigned different degrees of positivity or negativity, and calculates the total value of the polarity of the news. The article presents visual panels on which you can get acquainted with the results of the analysis, on the second panel - changes in stock prices after a while.
Title: Modification of the SLAM Algorithm Based on Comparative Analysis of the Algorithm for Extracting Features From Images
Abstract: The SLAM algorithms used on inexpensive compact boards in many standalone mobile devices are not fast enough. To solve this problem, we modified the RTAB-Map method in order to increase its speed without losing the quality of the algorithm itself. One way to improve the speed of the algorithm is to replace the SIFT keypoint extraction algorithm. In this article, we made a comparative analysis of methods for identifying local features from images.
Keywords: SLAM;RTAB-Map;ORB;robotics
Review score: Moderate
Review comment: Article on a current topic. The author paid insufficient attention to the review of publications on this topic. The author did not make a comparative analysis with similar scientific results. In what exactly is its scientific result better than its analogues. The author analyzed only a few sources that are indexed in the Scopus or Web of Science databases. It is necessary to analyze more publications in top-ranked journals or in IEEE conference proceedings (Q1-Q4) that are indexed in Scopus or Web of Science.
After correction, this article can be accepted for publication.
Title: Modification of the SLAM Algorithm Based on Comparative Analysis of the Algorithm for Extracting Features From Images
Abstract: The SLAM algorithms used on inexpensive compact boards in many standalone mobile devices are not fast enough. To solve this problem, we modified the RTAB-Map method in order to increase its speed without losing the quality of the algorithm itself. One way to improve the speed of the algorithm is to replace the SIFT keypoint extraction algorithm. In this article, we made a comparative analysis of methods for identifying local features from images.
Keywords: SLAM;RTAB-Map;ORB;robotics
Review score: Moderate
Review comment:  It is necessary to clearly formulate the problem, show what the relevance of the study is, briefly reflect the content of the article and present the results of the study in the abstract. The goal should reflect the title of the article. The introduction and conclusion should correspond to the disclosure of the problem, its solution, the achievement of the research goal and the methods used. Rename the last part. It is recommended to rename the article as “Modification of the SLAM algorithm based on a comparative analysis of the algorithms for extracting features from images”, since comparative analysis is a tool for solving an existing problem. The authors in the article propose, based on studying the extraction of key points of objects and their corresponding algorithms using comparative analysis, to determine the optimality of several algorithms for use in a robotic system along with computer vision.
Title: Ethnocultural, Educational and Scientific Potential of the Interactive Dialects Map
Abstract: The article analyzes the features of an interactive map of dialects developed by Ukrainian scientists and available on the Internet at dialectmap.org. The client part of the interactive map was created using the React.js library of the JavaScript programming language, and the MOBX state management library was also used. The server side of the information system was written in Ruby programming language using the Ruby on Rails framework. The relational database management system Postgresql was used, and Redis cache was used for caching some frequently used data. Ukrainian universities successfully use the interactive map of dialects to conduct dialectological and ethnolinguistic practices, teach linguistic disciplines, and organize students' research work within linguistic clubs. The information system is a hub that more widely reflects local language features; the map contains materials from various studies created in different periods. The interactive map of dialects has more features than traditional (paper) dialectological atlases, makes the results of dialectological surveys accessible to many people, can hold a large amount of dialect data, and thus contributes to the preservation of linguistic diversity. The interactive map of dialects is developed to represent data from different languages and territories; thus, the project can be expanded to other countries in Europe, Asia, and other continents.
Keywords: interactive map of dialects;dialectological research;language preservation;React.js;MOBX;Postgresql;Redis cache;Jest;Enzyme;RSpec
Review score: Moderate
Review comment: It is possible to indicate as the advantages of the work wide application in various fields, not only in education, but for example in tourism. The literature review is very detailed. The authors have demonstrated examples of using the interactive map. There are two versions of the product and it is interesting. Interactive Dialect Map can be used by different people not only in Ukraine. Authors will be able to demostrate it during reporting.