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2006 research outputs found
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Creation of effective chatbots based on neural networks
Get PDFThis paper presents a comprehensive exploration of the development process for a neural network-based chatbot. Given the increasing popularity of neural networks and chatbots in recent years, investigating the creation process of such a chatbot is both pertinent and valuable. The primary objective of this study is twofold: first, to construct an effective chatbot, and second, to identify the most precise model for text classification. Furthermore, the paper delves into the mathematical aspects of creating a chatbot and provides a detailed explanation of neural networks. The initial step in our project involved the creation of a database containing a sufficient number of student questions, which were then categorized into ten distinct categories. ‘To achieve this, we carefully selected the ten most commonly asked questions and generated multiple paraphrased versions of each question. These variations were employed for training and evaluating our models. During the course of our research, we identified three text classification models that proved to be the most suitable for our purposes: Multinomial Logistic Reeression, Naive Bayes, and Neural Network. We conducted extensive tests using these models and documented the results in a table, providing a comprehensive analysis of their performance. Following the successful completion of the database collection and the identification of the optimal text classification model, we proceeded to create the chatbot using DialogF low. Additionally, we integrated our chatbot into the Telegram messenger for wider accessibility and user convenience
Solving the exam scheduling problems with Genetic Algorithms
Get PDFThe exam scheduling problem is a complex task faced by educational institutions worldwide. Efficiently allocating exams within limited time slots while considering various constraints, such as student preferences, room capacities, and faculty availability, poses a significant challenge. This dissertation aims to address the exam scheduling problem by leveraging the power of Genetic Algorithms (GAs). Genetic Algorithms are robust search and optimization techniques inspired by the process of natural selection. By employing evolutionary principles, GAs have proven to be effective in finding optimal or near-optimal solutions for a wide range of combinatorial optimization problems. In this study, Ipresent a new application of genetic algorithms to solve the exam scheduling problem, to devise a solution that can be applied to Kazakhstan universities, and to evaluate the performance of GA compared to other existing algorithms commonly used in this field
The Effects of Trade Related Sanctions on Russia on Kazakhstan’s International Trade in Goods
Get PDFThe aim of this study is to explore the effects of sanctions on the international trade of Kazakhstan using data from TradeMap database. The Russia-Ukraine conflict has brought instability to the broader Eurasian continent and significantly affected neighboring states. Kazakhstan and Russia share the second-longest international land border and both participate in the Eurasian Economic Union with a high level of economic integration. Given Kazakhstan's landlocked status, the country relies on Russian territory for its main export routes. Despite expectations of potential issues with oil and gas transportation for Kazakhstan due to sanctions on Russia, there was an increase in mineral exports from Kazakhstan in 2022, resulting in a positive trade balance. High energy prices and inflation in the EU at the start of the invasion led to the delay of oil and gas import bans by the bloc until late 2022. There is also evidence of sanction evasion by Kazakhstani companies, reflected in changes in the structure of exports to Russia. This has prompted visits by officials from sanctioning countries and increased monitoring. Overall, the conflict and subsequent comprehensive sanctions have created uncertainty for investors and require scenario-based longterm planning and additional compliance costs. It is recommended to improve awareness of local companies about the possibility of violating sanctions through corporate training and cooperation with business associations. This will help local businesses to prevent the risk of being subjected to secondary sanctions
ЦИФPЛAНДЫPУ ЖAҒДAЙЫНДA БIЛIМ БEРУДIҢ 8-СЫНЫП ГЕОМЕТРИЯСЫН ОҚЫТУДА ҚОЛДАНУДЫҢ ӘДІСТЕМЕЛІК ЕРЕКШЕЛІКТЕРІ
No full textАңдатпа. Осы тақырыпта цифрландыру аясында ортанғы сыныптарда геометрия пәніне талдау жүргізіп, дайарлаудың керекті әдістерін пайдалану керектілігі теориялық тұрғыда көрсетілген. Цифрландырудың қиын тұстары білім беру саласында болуы мүмкін. Математика сабақтарында скаляр шамаларды тиімді шешу жолдары қарастырылған. Ақпараттық технологияларда геометриялық жүйенің тиімділігі көрсетілген. Қандайда бір есептерді түрлі формулалармен шешу жолдары нақтыланған. Ғылыми калькулятормен қалай дұрыс жұмыс жасау керек екендігі баяндалған. Кез келген тақырыпты оқытқанда басқа геометриялық фигураларды және оларға сәйкес скалярларды пайдаланып есептер құрастыруға және шешуге болады. Сонымен қатар, әртүрлі математикалық модельдерді қолдана отырып, мәселені әртүрлі тәсілдермен шешу мүмкіндігін атап, өту маңыздығын арттыру бағыты нақты баяндалған. Пайдаланылған әдебиеттер де дәлме дәл көрсетілген
KAZAKH LANGUAGE-BASED QUESTION ANSWERING SYSTEM USING DEEP LEARNING APPROACH
No full textAbstract. Deep learning advances have resulted in considerable gains in a variety of natural language processing applications, including questionanswering (QA) systems. QA systems are intended to retrieve data from big datasets and respond to user queries using natural language. Deep learning-based techniques have yielded encouraging results in the development of QA systems capable of providing consistent answers to a wide range of inquiries. This research presents a deep learning-based Kazakh language-based QA system. A pre-processing module is also included in the proposed system to improve the quality of the input text and the accuracy of the final output. The results reveal that the system has a high level of accuracy. This study promotes to the advancement of question-answering technology and contributes to the development of natural language processing tools in the Kazakh language
Understanding the effects of gender, age, and cultural orientation on users’ flow experience during the use of a gameful educational system
No full textGameful approaches (e.g., gamification, games, and alternate reality games) have been widely used in education in recent years. However, the results are still contradictory and generated different challenges. One of the main challenges is to understand how different individual aspects affect the users’ experience in gameful educational systems. To face this challenge, in this paper, we present a study (N = 205) analyzing the effects of demographic aspects (i.e., age, gender, and cultural orientation) on users’ flow experience (i.e., challenge-skill balance, action awareness merging, clear goals, unambiguous feedback, concen tration, sense of control, loss of self-consciousness, transformation of time, and autotelic experience) during the use of a gamified educational system. The main results indicated that age positively affected the overall flow experience while individualism negatively affected the overall flow experience. Our results contribute to the fields of educational technologies and gamification, providing insights into how different demographic aspects can affect the user flow experience in gamified educational systems
Development of a strategy for the implementation of technologies and innovations in commercial banks of Kazakhstan
No full textThe purpose of this to explore the current state of technology adoption and innovation in commercial banks in Kazakhstan and identify the challenges they face in implementing these technologies. The research paper aim to understand and recognize the relationship between innovation and financial performance of commercial banks in Kazakhstan. The research considered the theory of Disruptive innovations. Audited Financial reports of twenty-one commercial banks were used in Data analysis. The Dynamic Panel model was used to understand the impact of financial technology innovations to financial performance. Additionally, the research paper could also contribute to the existing literature on technology adoption and innovation in the banking sector in emerging economies
INVESTIGATION OF THE MODERN EXPORT POTENTIAL OF SME IN THE REPUBLIC OF KAZAKHSTAN
Get PDFThis study, titled "Investigation of the Modern Export Potential of SMEs in the Republic of Kazakhstan," embarks on an empirical examination of the factors influencing the export potential of Small and Medium-sized Enterprises (SMEs) in Kazakhstan. SMEs are recognized globally for their pivotal role in economic development, innovation, and employment creation. Their involvement in international trade, particularly exports, is increasingly acknowledged as significant for economic growth and diversification. This study, drawing upon Internationalization theory and Entrepreneurship theory, aims to elucidate the current status, challenges, and opportunities pertaining to SMEs' export potential in Kazakhstan. The research utilized a quantitative approach, employing a survey questionnaire disseminated to 400 SME owners and managers in Kazakhstan. The final analysis was based on 372 valid responses. Data were analyzed using descriptive statistics, correlation analysis, and multiple regression analysis. The findings from the study indicate that firm size, industry, and government support are key determinants of the export potential of SMEs in Kazakhstan. Challenges, such as access to finance and market information, were also identified. This research contributes to the existing literature on SMEs' export potential in emerging economies, providing valuable insights for policymakers and business practitioners. The findings can inform the formulation of strategies and policies that bolster SMEs' capacity for internationalization. Despite its contributions, the study acknowledges limitations, such as its cross-sectional design and reliance on selfreported data, suggesting avenues for future research
SIR DERYA BÖLGESİ´NİN ETNİK OLUŞUMUNUN TARİHİ SÜRECİ (VI-XIII YY.).
Get PDFÖzet. Orta Asya Türki cumhuriyetlerinin orta çağ tarihi genel Türk tarihi açısından bir bütün olarak incelenmesi önem arz etmektedir. Orta Asya bölgesinde kendi coğrafi özelliği, etnik yapısı, iktisadi üretim biçimleri ve kültürel hayatı bakımından önem arz eden ehemiyetli birkaç yöre bulunmaktadır. Bunlardan birisi de Sır Derya veya Sır yöresidir. Sır Derya Havzası, eski çağlardan beri insanoğlunun yaşadığı bir bölgedir. Türklerin ata yurdu olan Orta Asya’nın can damarı mahiyetindeki Seyhun ile Ceyhun vadilerinin eski bir medeniyet merkezi olduğu kaynaklarca da ifade edilmektedir. Burası Z. V. Toğan’ın tabiriyle sadece “Kent Türkleri”nin yerleşik hayat yaşadığı bölge değil aynı zamanda, çeşitli etnik unsurlapın, kültürlerin buluştuğu ve harmanlaştığı bölgedir. Orta Asya Türk halklarının etnik yapısı incelenirken, bu meselede kendine özgü yeri ve katkısı olduğunu düşündüğümüz Sır Derya bölgesi´nin ayrıca üzerinde durulması gerektiğine inanıyoruz.
Development of Recommendation System for Online Library
No full textThis dissertation is devoted to the development of a recommendation system for an online library. The aim of the research is to create an efficient and personalized recommendation system that takes into account user preferences, comments in Kazakh language and likes to provide up-to-date book recommendations. The paper considers various methods of data collection, including the use of a telegram bot to generate comments in the Kazakh language and the collection of information from familiar users. Created a dataset containing 330 comments in Kazakh for model training and was divided into positive and negative comments using sentiment analysis methods. Various classification models were used for sentiment analysis, including Logistic Regression, Random Forest, Naive Bayes, and Support vector machine. The Support vector machine model achieved the highest accuracy of 95%, outperforming other models. In addition, the analysis of comments using histogram showed that positive comments usually contain more words than negative comments, which indicates more detailed and informative reviews. The identification of influential words and phrases provided insight into what aspects of books are valued by users. The developed recommendation system was integrated into the website of the online library. Two new users were created, who were given the opportunity to choose their preferred genres and languages. The system used the positive comments and likes associated with each book to generate personalized recommendations. This approach allows users to quickly find books they are interested in, which have already been popular and received positive feedback from other readers. arch has practical implications for developers of online libraries and other This rese platforms where personalized recommendations are required. The results and conclusions of this work can be used in the further development and improvement of recommendation systems, which will lead to an improvement in the quality of user service and an increase in their satisfaction