bluuebunny/crossref_metadata_2025 huggingface dataset:
I NFLUENCE OF INTECTUAL CAPITAL ON THE FORMATION OF THE SCHOOL-INTENSIVE ECONOMY OF THE PSKOV REGION
Authors:   Pskov State University, Galdikas Larisa N. , Galdikas Vytautas A. ,   Pskov State University
Published: January 2024

This article discusses the response to the challenges facing the country. The country’s resilience is linked to the sustainable development of its regions. The results of a review of the concepts of intellectual capital of the region, knowledge-intensive economy and high-tech production are presented. A model was selected and an assessment of the intellectual capital of the Pskov region for the period 2018–2021 was carried out. The analysis showed that the integral value of intellectual capital over this period tended to decrease. An analysis of the elements of intellectual capital was carried out and critical indicators were identified: educational and scientific potential. To create new products, it has been proposed to create two regional scientific and educational clusters in the Pskov region with the participation of scientific and pedagogical personnel and students. A mechanism for organizational and economic management of the cluster has been developed, which will help create conditions for increasing regional human capital.
ANALYSIS OF THE STATE OF INNOVATION PROCESSES IN THE REGION: INDICATOR-GRAPHICAL APPROACH
Authors:   Vladimir State University named after Alexander Grigorievich and Nikolai Grigorievich Stoletov, Kudryakov Roman I.
Published: January 2024

This study is devoted to the analysis of the state of innovation processes in the region using the graph theory method. The paper discusses the theoretical and conceptual apparatus, carried out a statistical analysis of the dynamics of innovation processes in the region of Vladimir region from 2013–2022, based on statistical data developed mathematical tools to determine the indicators of innovation processes, identified problems, applied the graph theory method to identify the causes of problematic aspects in the region, the industrial sector was chosen as an example of the application of the method, and the author’s recommendations for minimizing the impact of problematic moments in the selected sector of the economy are presented.
CONTOURS OF INTENSIFICATION OF SOCIO-ECONOMIC DEVELOPMENT OF THE ARCTIC REGIONS IN THE CONTEXT OF THE IMPLEMENTATION OF OIL AND GAS PROJECTS
Authors:   Federal Research Center «Computer Science and Control» of the Russian Academy of Sciences, Voronina Elena P.
Published: January 2024

Oil and gas projects implemented in the Arctic zone of the Russian Federation are a strategic priority and their implementation should have important socio-economic significance in the development of regions. The article studies problems related to the impact of the implementation of oil and gas projects of the Arctic zone of the Russian Federation on the socio-economic development of regions, taking into account the transition to the domination of resource-innovative model of management, with priority given to social values. SWOT-analysis of implementation of arctic oil and gas projects is presented, strengths and weaknesses, opportunities and threats are identified and systematized, key criteria are analyzed, conditions of functioning and factors of influence on social and economic development of the arctic regions. Conclusions have been summarized and presented, measures have been proposed in the implementation of oil and gas projects in the interests of realization of priorities of socio-economic development. In order to solve these problems, the author substantiates the necessity of active state policy. The national interests of the Russian Federation in the arctic region require a systematic approach to the implementation of projects based on the principles: coherence of industrial and regional economy and environmental management, adaptive management, based on the integration of economic, innovative, social and environmental factors, taking into account well-defined and structured benchmarks.
THE IMPORTANCE OF INFORMATION SUPPORT IN PASSENGER AND TRANSPORT FLOW FORECASTING MODELS
Authors:   Institute for Regional Economic Studies Russian Academy of Sciences, Bulycheva Nelia V. , Losin Leonid A. ,   Institute for Regional Economic Studies Russian Academy of Sciences
Published: January 2024

The paper shows the influence of a number of parameters and restrictions used in mathematical models for predicting the intensity of passenger traffic in urban agglomerations. Such parameters can be the characteristics of the systems of settlement and distribution of service places, the speed characteristics of the transport network. The article describes the results of experimental calculations of flow distribution parameters on the example of the St. Petersburg agglomeration. The necessity of practical calculations in the development of design solutions in the documentation of strategic, territorial and transport planning is proved subject to the specific features of the functioning of all social and transport systems of the city.
Pemanfaatan Komik Digital sebagai Iklan Layanan Masyarakat Hari Bawa Bekal Nasional di Puskesmas Purwokerto Utara 2
Authors: Prita Suci Nurcandrani  , Ade Tuti Turistiati  , Antonius Ferdi Widiatmoko
Published: January 2024

Data of the Banyumas District Health Office for 2022 shows that in the 15-24 year age group, 3 to 4 out of 10 teenagers suffered from anemia. The 2013-2018 Riskesdas also noted that 32% of teenagers had anemia. Other findings were obesity, chronic energy deficiency, and eating disorders or unhealthy eating behaviors of teenagers’ lifestyles. Total of 1,150 students classified as teenagers is the responsibility of the Puskesmas Purwokerto Utara 2 to intervene more intensively. As a partner, Puskesmas needs promotional media applied to increase the nutritional status of teenagers. The method used is designing and socializing the use of digital comics. This comic is a form of public service advertisement used as one of the original National Bring Bekal Day social marketing strategies owned by partner. The results of this activity are in accordance with the planned stages by the team and the handover of comics with partner.
Program Pemetaan Potensi Daerah untuk Pemberdayaan Masyarakat Kabupaten Belitung Timur
Authors: Nurjanah Siti , Ari Wibowo  , Abi Nisaka  , Monica Sintawati
Published: January 2024

Menggali potensi daerah serta melihat permasalahan masyarakat Kabupaten Belitung Timur merupakan tujuan dari penelitian ini. Dari hasil potensi ini akan dibuat kajian maupunrekomendasi dari potensi daerah diantaranya, Pengentasan Kemiskinan, Pengelolaan Lingkungan dan Kawasan, Pengembangan. Pemetaan program dilakukan dengan metode pemetaan partisipatif dengan pendekatan pemantuan cepat (Rapid Appraisal Methods). Metode pengumpulan data dilakukan melalui wawancara terstruktur dengan kuesioner, wawancara mendalam dengan panduan pertanyaan, pengamatan, dan Focus Group Discussion (FGD). Hasil dari pemetaan program ada beberapa potensi yang bisa dijadikan sebagai program unggulan diantaranya adalah Program Sekolah Perempuan, Program Budidaya Madu serta Program pengembangan desa wisata Eks Jepang.
Perancangan Sistem Informasi Penjualan & Persediaan Menggunakan Odoo Ver 15 Pada Toko New Palapa Elektronik
Authors: Fernando Erick , Sellyvia Meida
Published: January 2024

The New Palapa Elektronik store is a shop engaged in the marketing of electronic goods whose main activity is selling various kinds of electronic devices for household needs. Currently at the New Palapa Elektronik Store the process that runs on the sales and inventory process is still manual, namely in the process of making sales invoices, adding up the profits from selling goods in making sales reports, in checking inventory inventory it is necessary to check one by one the items available in the warehouse and it takes a lot of time. For this reason, this research is to design the sales module and inventory module using the Odoo application version 15.0 and system design using the ASAP method. The results of research on sales and inventory system design, can be used to display stored information, automate and provide information on the amount of profits from the sales report process and stock inventory reports.
Pengaruh Berita Penanganan Kasus oleh Kepolisian Terhadap Citra POLRI di Kalangan Remaja
Authors: Haloho Heppy , Kalila Azkya
Published: January 2024

Bagi sebuah institusi, citra memiliki peranan penting untuk menunjukkan baik buruknya suatu organisasi di mata publik. Oleh sebab itu, institusi atau perusahaan terus berusaha mengupayakan agar terciptanya citra yang baik. Tujuan penelitian adalah mengetahui adanya pengaruh berita penanganan kasus oleh kepolisian terhadap citra POLRI di kalangan remaja akhir dan mengukur besar dari berita penanganan kasus oleh kepolisian terhadap citra POLRI di kalangan remaja akhir. Teori yang digunakan dalam penelitian ini adalah teori stimulus-respons (S-R). Sedangkan pendekatan yang digunakan adalah pendekatan kuantitatif dengan metode survei eksplanatif. Data dianalisis menggunakan koefisien korelasi pearson’s product moment dan regresi linear sederhana dengan SPSS versi 27. Berdasarkan hasil analisis ditemukan bahwa terdapat pengaruh variabel berita yang menunjukkan pengaruh terhadap citra dengan nilai t hitung lebih besar dari t tabel (18,447 > 1,966), yang berarti Ha diterima serta menunjukkan ada pengaruh dari berita penanganan kasus oleh kepolisian terhadap citra Polri di kalangan remaja.
Pengaruh Kualitas Layanan Aplikasi Zalora Indonesia terhadap Loyalitas Pelanggan
Authors: Komaro Regita Mahardika , Siregar Irwan
Published: January 2024

Penelitian ini bertujuan mengukur sejauhmana pengaruh kualitas layanan aplikasi zalora indonesia terhadap loyalitas pelanggan. Metode  digunakan ialah validitas konstruk, Cronbach’s Alpha, Regresi Linier Sederhana, Uji F/ANOVA, dan Uji T (Coefficient Corelation). Hasil Penelitian menunjukkan regresi linier sederhana pengaruh kualitas layanan terhadap loyalitas memiliki R1 sebesar 0,885 artinya layanan berpengaruh positif terhadap loyalitas pelanggan sebesar 88,5%, R square sebesar 0,783 dan sig 0,000 yang artinya 79,3% variasi terjadi terhadap tinggi rendahnya loyalitas pelanggan disebabkan oleh variasi kualitas layanan sedangkan sisanya 21,7% dijelaskan oleh faktor lain di luar penelitian. Hasil uji F atau ANOVA pengaruh kualitas layanan terhadap loyalitas menghasilkan angka Fhitung sebesar 173.354 dengan tingkat signifikan 0,000 dan Ftabel 4,04. Artinya Fhitung lebih besar dari Ftabel, maka dapat dikatakan ada pengaruh kualitas layanan Aplikasi Zalora Indonesia terhadap loyalitas pelanggan. Hasil uji T (coefficient) pengaruh kualitas layanan terhadap loyalitas memiliki sig 0,000 dengan B sebesar 0,885, Thitung 13,166, dan Ttabel 1.677.
La sindrome di Poland
Authors: Abramo Michele , Selicorni Angelo
Published: January 2024

Con quella faccia un po' così, quella statura un po' così, che abbiamo noi con una cardiopatia...
Quando pensare alla splenectomia in presenza di Beta-talassemia con depranocitosi?
Authors: Stera Giacomo , Legnani Elena , Grasso Antonio
Published: January 2024

The authors describe the positive effect of splenectomy in two brothers affected by micro-drepanocytosis.
EFFECT OF THIDIAZURON AND 2,4-DICHLORO PHENOXY ACETIC ACID ON CALLUS DEVELOPMENT IN TEA CLONE UPASI 9 TDZ AND 2,4-D ON TEA CALLUS INITIATION
Authors: RISHIKESH M  , BOOPATHI N. MANIKANDA , P. MEENAKSHISUNDARAM  , LOURDUSAMY D. KEISAR , M. KANNAN
Published: January 2024

A commonly cultivated tea clone, UPASI 9, is currently propagated through cuttings, an endeavor that has been proved to be environmentally hazardous (due to the use of large quantities of excavated soil) and unprofitable. As an alternative, this study highlights tissue culture as a viable option for the robust and easy regeneration strategy for the tea clone UPASI 9. A study was initiated to establish an in vitro culture protocol for Nilgiris tea (Camellia sinensis) by standardizing explant sources, disinfestation methods, and the constitution of culture media. Segments were dissected from greenwood stem (current year growth) internodes of field-growntea plants. Disinfestation was achieved by successive treatments of fungicide (bavistin), 0.1% mercuric chloride, and 7.5% CaCl2 . MS medium supplemented with sucrose (30 g/l), citric acid (100 mg/l), and ascorbic acid (100 mg/l) was used with combinations of the auxins (2,4- dichlorophenoxyacetic acid; 2,4-D) and cytokinin (Thidiazuron; TDZ). It was found that 1.1 mg of 2,4-D and 1.1 mg of TDZ induced the most callus proliferation. Though equal proportions of TDZ (1.1, 2.2, 3.3 mg) and 2,4-D (1.1, 2.2, 3.3 mg) were effective in inducing callus formation, it was noticed that 1.1 mg each of TDZ and 2,4-D made a major impact by reducing the time required for the callus initiation and proliferation
DEVELOPMENT OF ACTIVE PACKAGING SHEET BY CHITOSAN WITH INCORPORATION OF ASCORBIC ACID
Authors: BABAR ABDUL , SINGH VISHAL , MITRA ABHIRUP
Published: January 2024

Active packaging Sheets have gained significant attention in recent years due to their ability to maintain the quality and extend the shelf life of food products. In this study, we aimed to develop an active packaging Sheet by incorporating chitosan with ascorbic acid. The Sheet was prepared using a solvent casting method, and its biodegradability, thickness, tensile profile, and antioxidant properties were evaluated. The Sheet showed good biodegradability, with a degradation rate of 73% after 60 days of soil burial. The addition of ascorbic acid resulted in improved antioxidant properties, and the Sheet showed a tensile strength of 15.02kgf/cm2 and a thickness of 250 microns. The developed active packaging Sheet has the potential to extend the shelf life of food products and contribute to the reduction of plastic waste in the environment. The study aimed to develop a chitosan-based active packaging Sheet with the incorporation of ascorbic acid to enhance the shelf-life of food products. The Sheet’s physicochemical and mechanical properties, as well as its antioxidant and antimicrobial activities, were evaluated. Results showed that the addition of ascorbic acid improved the Sheet’s tensile strength, elongation at break, and water vapor permeability. The Sheet also exhibited significant antioxidant and antimicrobial properties, indicating its potential use in food packaging applications. The study suggests that the development of active packaging Sheets using chitosan and ascorbic acid can help extend the shelf-life of food products while maintaining their quality and safety.
Desenvolvimento pessoal e profissional com ênfase em Soft Skills
Authors: Lima Elizabeth Karine Freire de , Machado Tannara Patrícia Costa , Nascimento Samara Naiane de Souza , Silva Dinara Rute Gomes , Cavalcante Aline Spíndola , Soares Stela Lopes , Ruiz Erasmo Miessa
Published: January 2024

O estudo se concentra na evolução constante do ser humano ressaltando a importância das habilidades interpessoais e comportamentais (Soft Skills) juntamente com as habilidades técnicas (Hard Skills) na formação dos profissionais de saúde. Destaca-se a relevância dessas competências no ambiente acadêmico e laboral, enfatizando que as Soft Skills desempenham um papel essencial na permanência e sucesso no emprego. A pesquisa relata a experiência de uma disciplina de Desenvolvimento Profissional e Pessoal ministrada em um curso de Mestrado Profissional em Ensino na Saúde em uma Instituição de Ensino Superior (IES). Foram realizadas atividades como rodas de conversa, discussões em grupo e apresentações individuais, visando explorar competências comportamentais e promover reflexões sobre o percurso pessoal e profissional dos alunos. Infere-se que embora as competências técnicas sejam essenciais, as competências socioemocionais desempenham um papel diferenciado no sucesso profissional. Destaca-se que a formação focada no desenvolvimento de Soft Skills não apenas capacita os profissionais para lidar com desafios complexos, mas também os prepara para uma prática mais humanizada e ética.
A Research on the Cashback of Positive Reviews
Authors: Liu Zhiyuan , Tang Longsheng
Published: January 2024

In recent years, China's e-commerce market has developed rapidly, but some businesses have engaged in unfair competition by using the method of cashing back positive reviews. This competitive approach not only seriously infringes on the legitimate rights and interests of other operators and consumer groups, but also hinders the healthy development of China's e-commerce market economy. The article outlines the reasons for the repeated prohibition of "positive feedback cashback", including weak legal regulations, inadequate supervision of merchant platforms, and increased concealment of "positive feedback cashback". At the same time, it proposes to improve and expand existing laws, establish a "cooling off period for evaluations", and use big data to strengthen platform supervision to crack down on "positive feedback cashback" behavior.
Research on Air Filter Monitoring System of Oxygen Generator
Authors: Yao Xin , Liao Jinghen , Sun Jing , Lin Shaoyin , Zhang Lu
Published: January 2024

Zeolite is an expensive consumable material in oxygen generator which needs to be replaced regularly. The life of zeolite is mainly determined by dust, humidity and temperature. Among which, dust has a great influence on the life span of zeolite. In the process of oxygen production, the dust in the air will be adhered to the molecular sieve, and shorten the life of zeolite. PSA (Pressure Swing Adsorption) oxygen generator has a filter at the air inlet end, which is used to filter out the dust particles in the air. The filters of PSA oxygen generator are disposable regularly. The replacement cycle depends on the air environment, and the cycle is short if under much dust particles.This thesis investigates the architecture of the filter failure detection. The architecture can detect the air environment dust condition, detect the filter failure, prolong the life of the filter.
Simulation Analysis of Ti6Al4V Cutting Under Liquid Nitrogen Cryogenic Cooling
Authors: Xia Yongjie , Zhang Qi
Published: January 2024

Liquid nitrogen cryogenic cooling technology has great advantages in cutting machining. A thermodynamic finite element model of liquid nitrogen cryogenic cooling based on the plane strain assumption is established to observe the changes in cutting force and tool temperature corresponding to different cutting parameters (feed rate and cutting speed) under liquid nitrogen cryogenic cooling conditions. Existing tests verified the accuracy of the simulation model, and the prediction error of the simulation model was controlled within 10%. Analyzing the data obtained from the simulation model, it is found that a lower tool temperature is obtained when the cutting parameters are selected to be lower values; under the conditions of liquid nitrogen cryogenic cooling and dry cutting machining, the effect of the cutting speed on the cutting force is not obvious, while the effect of the feed volume on the cutting force is more significant; under the conditions of different cutting parameters, the tool temperature as well as the cutting force are lower under the conditions of liquid nitrogen cryogenic cooling compared to the dry cutting machining method.
Research and Application Progress of Insulation Materials in Cold Chain Logistics
Authors: Dong Yuexia , Li Xiaofeng , Liu Di , Zhu Lihua , Zhang Peisi
Published: January 2024

In cold chain logistics equipment, the role of insulation materials is very important. With the continuous development of cold chain logistics, the requirements for insulation materials are getting higher and higher, and future insulation materials need to be more energy-saving and environmentally friendly. This paper introduces the development of cold chain logistics and the insulation materials commonly used in cold chain logistics, which include extruded polystyrene foam (XPS), polyurethane foam (PU), vacuum insulation panels (VIP), and aerogel materials. The performance of these insulation materials and their applications in cold chain logistics are also summarized. In addition, the future development direction of thermal insulation materials is envisioned to promote the sustainable development of the cold chain logistics industry.
Development of Coal Slime Drying System with the Low Concentration Coal Bed Methane Regenerative Oxidation
Authors: Chen Yutao
Published: January 2024

The pollutants exceeding the standard exists in the coal furnace in the current coal slime drying system. In order to solve the industrial application difficulty of coal slime in coal mine, by using low concentration coal bed methane regenerative oxidation reactor instead of coal furnace to produce the high temperature flue gas and combining with slime drying system, a low concentration coal bed methane regenerative oxidation slime drying system which is applied to coal slime drying is formed. Taking the scale of a single regenerative oxidation reactor which processing capacity is 100,000m3/h as an example, the thermal calculation of the whole coal slime drying system is carried out. The results show that the system can dry coal slime 39t/h and has a large-scale effect.
Mechanical Performance Forecast for BP Neural Network Materials Optimized by Genetic Algorithm
Authors: Wu Xiangxiang , Wang Shihao
Published: January 2024

The mechanical properties of steel materials play a crucial role in their design, selection, and application. In order to better predict the mechanical properties through chemical composition and process parameters, this paper uses genetic algorithm to optimize the BP neural network to establish a mechanical property prediction model for steel materials. The model can predict three mechanical properties, including yield strength, tensile strength, and elongation, through chemical composition and process parameters. After optimization by genetic algorithm, the problems of insufficient convergence effect, random initialization of weights and thresholds in the BP neural network model are improved, and the prediction error is significantly reduced. The experimental results show that the GA-BP algorithm model has excellent performance in predicting the mechanical properties of steel materials.
Research on Continuous Pipeline Life Prediction Method Based on Fully Connected Neural Network
Authors: Zhang Zhikui , Wu Lina
Published: January 2024

Aiming at the low accuracy of traditional empirical formulas in predicting the fatigue life of continuous oil pipelines, a fully connected neural network is utilized to predict the low-week fatigue life of continuous oil pipelines. Considering the influence of internal pressure on the fatigue life of continuous oil pipeline during operation, a prediction method combining the fully connected neural network and gated recirculation unit is proposed, and the experiment proves that the FCNN-GRU neural network performs better in terms of prediction accuracy and stability compared with the BP neural network.
InkFusion3D: 3D Printing Flexible Sensors with Silicone Rubber and Conductive Ink Materials
Authors: Xu Jiahao
Published: January 2024

With the continuous advancement in current sensor design research, most design schemes still rely on rigid or semi-flexible materials for sensor usage. These interactive devices are increasingly unable to meet the demands of users for adaptability, durability, and biocompatibility, limiting their use in dynamic environments. This paper introduces a novel flexible sensor, InkFusion3D, which is fabricated using a combination of low-cost conductive ink and silicone rubber through 3D printing technology. Due to the significant advantages of InkFusion3D material, such as low cost, durability, good biocompatibility, and wide applicability, it can be customized for various applications to address challenges. The paper elaborates on the manufacturing method of InkFusion3D and its sensing principle upon force application. It also proposes applications in medical and gaming scenarios, such as joysticks, buttons, tangible interaction models, and smart filler materials.
Biomechanical Analysis and Mobility Improvement of Auxiliary Mobile Equipment
Authors: Jiang Yufan
Published: January 2024

As an advanced auxiliary mobile device, exoskeleton booster has attracted wide attention in the field of rehabilitation and life assistance. Through biomechanical analysis, this paper discusses the effect of exoskeleton booster on user mobility. Using biomechanical tools such as kinematics, dynamics and muscle mechanics, this paper deeply studies the influence of exoskeleton booster in different motion States, and verifies its biomechanical effect through simulation and experiment. Firstly, this paper analyzes the influence of exoskeleton booster on gait from the perspective of kinematics. The research shows that the exoskeleton booster can improve the walking efficiency of users by optimizing the step size and step frequency. The precise adjustment of joint motion by intelligent control system enables exoskeleton to better adapt to the gait characteristics of different users. Secondly, through dynamic analysis, this paper deeply studies the influence of exoskeleton on joint torque. The exoskeleton is designed to apply appropriate torque at key joints to help users complete the movement. The synergistic effect of this moment not only reduces the muscle burden of users, but also improves the stability of joints and reduces the risks in sports. In terms of improving mobility, exoskeleton technology can significantly improve the gait of patients in rehabilitation training, which is helpful to improve the balance ability of patients. The improvement effect of exoskeleton technology directly affects the quality of daily life of patients. This biomechanical effect provides strong support for the extensive application of exoskeleton technology in rehabilitation, sports assistance and daily life.
Experimental Study on Wind Speed Distribution in Semi-circular Arch Tunnels Based on Mirror Stepped Grid Method
Authors: Luo Guang
Published: January 2024

Ventilation is the cornerstone of coal mine safety production. Accurate monitoring of ventilation parameters is the basic guarantee for ventilation technology decision. For the problem that the accuracy of wind speed monitoring in coal mine tunnels is difficult to meet decision-making needs, a combination of theoretical calculation and experimental research was used to study the relationship between the average wind speed line and the position of the tunnel wall. The theoretical calculation obtained the expression of the relationship between the average wind speed line of the semi-circular arch tunnel section and the position of the tunnel wall. The proposed multi section mirror stepped grid format was used to investigate the airflow field in a semi-circular arch roadway under different conditions in the laboratory. The contour map of wind speed distribution was drawn, and the position of the measured average wind speed line was obtained. The absolute error between the measured average wind speed line and the theoretical model calculation results was within 5%, which verified the reliability of the theoretical calculation results.
Intelligent Analysis Model for Civil Aviation Employees Safety Supervision Based on Knowledge Graph
Authors: Tu Hao , Zhang Ping , Cao Tie , Wei Jinhong
Published: January 2024

Ensuring the safety of civil aviation employees is crucial for the overall safety and quality of the aviation industry. However, traditional methods of safety supervision are inefficient. This research proposes a regulatory approach based on knowledge graph technology, aiming to extract relationships from safety incidents involving civil aviation employees, establish a framework for safety risk analysis, and utilize the Neo4j graph database to provide comprehensive visualized data support for the safety supervision of civil aviation employees. This approach has the potential to enhance the safety supervision of civil aviation employees and contribute to overall aviation safety.
The Application of Artificial Intelligence to The Bayesian Model Algorithm for Combining Genome Data
Authors: Shen Zepeng , Wei Kuo , Zang Hengyi , Li Linxiao , Wang Guanghui
Published: January 2024

The combination of bioinformatics and artificial intelligence (AI) has made significant progress in the current phase. AI technology, especially deep learning, has been widely used in biology, resulting in many innovations. Currently, AI plays a key role in genomics, proteomics, and drug discovery. Deep learning models are used to predict protein structures, discover potential drug compounds, interpret genomic sequences, analyze medical images, and make personalized medical recommendations. In addition, AI can also help accelerate the processing and interpretation of biological big data, helping biologists to understand complex problems in the life sciences more deeply. Compared to traditional genetic data analysis methods, AI combined with bioinformatics methods are often faster and more accurate, and are capable of processing large-scale, high-dimensional biological data, opening up unprecedented opportunities for life science research. In this paper, the whole genome data and biomedical imaging data are used from the perspective of Bayesian hypothesis testing. Genome-wide association analysis, led by large-scale multiple tests, is a very popular tool for identifying genetic variation points in new complex diseases. In genome-wide association analysis, tens of thousands of SNPS need to be tested simultaneously to find out some SNPS related to traits. These tests are related due to factors such as linkage imbalances in the genetic process, and the test questions are set against the background of high-dimensional data (p >=n).
Enhanced Recognition of Handwritten Marathi Compound Characters using CNN-SVM Hybrid Approach
Authors:   Department of Computer Science  Engineering, RKDF University, Bhopal (MP), India, Patil Ashwini ,   Department of Computer Science and Engineering, RKDF University, Bhopal (MP), India, Dwivedi Puneet
Published: January 2024

This study presents a hybrid recognition system for multi-class compound Marathi characters, which addresses the problem of handwritten Marathi character recognition. The methodology efficiently bridges the gap between feature extraction and classification by integrating a Convolutional Neural Network (CNN) and Support Vector Machine (SVM). The first step is gathering and preprocessing a wide range of handwritten Marathi compound characters that are written in different styles. Using conventional supervised learning methods, the CNN is trained on this dataset, paying special attention to data augmentation and validation in order to reduce overfitting. High-level features taken from the final fully connected layer of the CNN are fed into an SVM classifier in the next step. By using these features in its training, the SVM improves prediction accuracy. For multi-class classification, the one-vs-all method is used. The hybrid CNN-SVM algorithm demonstrates its effectiveness in the crucial phases of feature extraction and classification by identifying handwritten compound Marathi characters with remarkable accuracy. Evaluation metrics, such as accuracy, precision, recall, F1-score, and confusion matrix analysis, are employed in the process of evaluating the effectiveness of the model. This assessment is carried out on a different testing dataset, offering a thorough examination of the model's functionality. The proposed algorithm demonstrates its superior performance and potential for improved character recognition by achieving training accuracy of 98.60% and validation accuracy of 97.69%. The development of handwriting recognition systems has benefited greatly from this research, especially when it comes to intricate scripts like Marathi. The suggested hybrid algorithm shows encouraging outcomes and has a great deal of potential for use in document processing, natural language comprehension, and character recognition in languages that use the Marathi script. Subsequent efforts will centre on refining the model and investigating ensemble methods to increase the robustness and accuracy of recognition.
Analysis of EEG signals with the use of wavelet transform for accurate classification of Alzheimer Disease, Frontotemporal Dementia and healthy subjects using Machine Learning Models
Authors:   Department of Electronics and Communication, UIT-RGPV, Bhopal, India, Parihar Akanksha ,   Department of Electronics and Communication, UIT-RGPV, Bhopal, India, Swami Preety D
Published: January 2024

Dementia is a brain disorder, if not prevented; takes the form of various types of diseases that have no cure yet. Accurate classification of multiple types of dementia diseases is required to provide proper medication to the patient so that growth of that disease can be delayed. This study analyzes EEG signal for the classification of multiple dementia diseases such as Alzheimer’s disease (AD), Fronto-temporal dementia (FTD) and control normal (CN) subjects using machine learning (ML) algorithms. Each of the 19 channels of EEG dataset is analyzed separately in this work to perform the classification. Combination of parameters like Hjorth Activity, Mobility and Complexity along with kurtosis value of the data has been extracted in time-frequency domain for each EEG frequency band (Delta, Theta, Alpha, Beta and Gamma) is applied to the machine learning algorithms. This research is focused on classification of multiple dementia classes (ADvsFTD) as well as three-way (ADvsFTDvsCN) classification. This research is validated using public EEG dataset with 23 participants of each category. Best classification result is achieved using random forest classifier and leave-one-subject-out (LOSO) cross validation method. The three-way classification i.e., ADvsCNvsFTD achieved best accuracy of 75.29%, whereas binary classifications i.e. ADvsCN, ADvsFTD and CNvsFTD achieved best accuracy of 88.90%, 88.44% and 84.10% respectively. The proposed framework shows better results than existing work on dementia classification using machine learning. The results obtained from proposed framework showed that combination of EEG frequency band features can be utilized for the classification of multiple dementia diseases with greater accuracy.
Leveraging Advanced Machine Learning Methods to Enhance Multilevel Fusion Score Level Computations
Authors:   Department of CSE(AIML), CMR Engineering College, Hyderabad, Telangana, India, Tiwari Rajesh ,   School of Electrical  Electronics Engineering, Fiji National University, Fiji,   Department of ECE, Velammal Institute of Technology, Chennai, TN, India,   Department of Computer Science and Artificial Intelligence, SR University, Warangal, Telangana, India,   Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India,   School of Electrical  Electronics Engineering, College of Engineering,  Science  Technology, Fiji National University, Fiji,   Senior instructor program coordinator, SEEE, CEST, Derrick Campus, Samabula, Fiji National University, Fiji, Singh Satyanand , Shanmugaraj G. , Mandala Suresh Kumar , Deepika Ch. L. N. , Soni Bhanu Pratap , Uluiburotu Jiuliasi V.
Published: January 2024

This research introduces a novel technique for determining numerous fusion score levels that works with many datasets and purposes. Each of the four system pieces works together. These are Feature Engineering, Ensemble Learning, deep neural networks (DNNs), and Transfer Learning. In feature engineering, raw data is totally transformed. This stage stresses the importance of PCA and MI for predictive power. AdaBoost is added during ensemble learning. It repeatedly teaches weak learners and adjusts weights depending on errors to create a strong ensemble model. Weighted input processing, ReLU activation, and dropout layers smoothly integrate DNNs. These reveal minor data patterns and correlations. In transfer learning (fine-tuning), a trained model is modified for the feature-engineered dataset. In comparative testing, the recommended technique had greater accuracy, precision, recall, F1 score, AUC-ROC, and training duration. Efficiency measures reduce reasoning time, memory, parameter count, model size, and energy utilization. Visualizations demonstrate resource consumption, method scores, and reasoning time distribution in research. This mathematical framework improves multilayer fusion score level computations, performs well, and is versatile in many scenarios, making it a good choice for large and diverse datasets.
REVIEW OF EMOTION CLASSIFICATION METHODS BASED ON AUDIO DATA ANALYSIS USING DEEP LEARNING
Authors: Сапакова Б.С. , Сарсембаев А.А.
Published: January 2024

В последние несколько лет наблюдается всё больший интерес к разработке технологий, направленных на определение эмоционального состояния человека. Наиболее затруднительным в решении этой проблемы является субъективность эмоций и сложность их отслеживания. Максимально эффективным инструментом для распознавания эмоций оказалось глубокое обучение, став по этой причине особенно привлекательной областью исследований. В этой статье мы рассматриваем недавние исследовательские работы по классификации эмоций, делая акцент на методах извлечения звуковых признаков и аугментации данных. Мы также сравниваем и анализируем существующие модели свёрточных нейронных сетей, с целью определения наиболее проверенных методов, позволяющих наилучшим образом классифицировать эмоции на основе анализа аудиоданных. Из множества публикаций, посвящённых исследованию распознавания эмоций и разработкам в этой области, мы отобрали только научные статьи, благодаря чему в нашей статье используются наиболее актуальные исследования. При этом мы рассматриваем только статьи хорошего качества, в которых предлагаются наилучшие решения рассматриваемых исследовательских вопросов.
ОБЗОР ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ МОНИТОРИНГА ЦЕЛОСТНОСТИ ПРОТЯЖЕННЫХ ОБЪЕКТОВ НА ОСНОВЕ РАСПРЕДЕЛЕННЫХ ВОЛОКОННО-ОПТИЧЕСКИХ ДАТЧИКОВ
Authors: Нефтисов А.В. , Саринова А.Ж. , Кириченко Л.Н. , Казамбаев И.М.
Published: January 2024

Бұл мақалада үлестірілген талшықты-оптикалық датчиктер негізінде кеңейтілген объектілердің тұтастығын бақылаудың қолданыстағы интеллектуалды жүйелеріне шолу жасалады.Үлестірілген талшықты-оптикалық датчиктерді қолдана отырып өлшеу жүйелерін әзірлеу бойынша нәтижелер ұсынылған. Өлшеу жүйелерін құру бойынша қолданыстағы шешімдерге талдау жасалды. Өлшеу схемаларының негізгі түрлері, Кеңейтілген объектілердің тұтастығын анықтау принциптері қарастырылады. Талшықты-оптикалық датчиктерді құрудың негізгі принциптері анықталды.Талдау әртүрлі оптикалық рефлектометрияны қолдану кезінде өлшеу дәлдігін арттыру бойынша жетістіктерді көрсетті. Өлшеу жүйелерінің кемшіліктері анықталып, оларды жою әдістері анықталды. Механикалық кернеулер мен температуралық әсерлерден туындаған қабаттасудан сүзу әдістері қарастырылады. Белгілі жұмыстарды қолданудың қиындықтары анықталды. Жасанды интеллект дамуының қазіргі жағдайына және оны өлшеу жүйелерінде қолдану саласына шолу жасалды. Уақыт аймағының оптикалық рефлектометріне(OTDR) негізделген жүйелер коагуляцияланған нейрондық желіні(CNN) қалай қолданатындығы дәлірек екендігі анықталды. Машиналық оқыту арқылы әртүрлі механикалық әсерлерді тану үшін нейрондық желілерді қолдану мүмкіндіктері қарастырылады. Таратылған талшықты- оптикалық датчиктердегі өлшеу жүйелерінде нейрондық желі жүйелерін қолданудың кемшіліктері мен артықшылықтары анықталды және ең оңтайлы түрі таңдалды. Бөлінген талшықты-оптикалық датчиктер негізінде техникалық жай-күйді мониторингілеу жүйесін одан әрі зерттеу және әзірлеу үшін бағыт айқындалды.
ORGANIZATION OF THE PROCESS OF TEACHING THE RUSSIAN (NON-NATIVE) LANGUAGE USING THE AKELIUS DIGITAL PLATFORM
Authors: Байтабенова А.С. , Ахметбекова К.Е.
Published: January 2024

Обучение русскому (неродному) языку с использованием цифровой платформы AKELIUS не просто открывает и обосновывает закономерности овладения русским языком, но и расширяет границы общеучебных навыков. По окончании курса обучающиеся должны владеть языком на элементарном уровне АО, А1, А1.1 (начальный уровень) согласно системе уровней Общеевропейской рамки владения языками (CEFR). Одна из главных целей уроков русского языка в рамках проекта – формирование коммуникативной речи, ориентированной на ситуацию общения. Смешанный формат обучения предполагает проведение занятий в очном режиме, когда ученик напрямую контактирует с учителем и использует гаджет со встроенной языковой программой (в нашем случае это цифровая платформа Akelius). Работа над пополнением словарного запаса обучающихся сопровождает весь процесс обучения. Из всех методов обучения русскому языку (неродному) наиболее оптимальным для детей-мигрантов на начальном этапе является коммуникативный. Необходимо систематически пробуждать интерес к тщательной работе над словом, к постоянному расширению тезауруса. Динамику прогресса можно отследить как в течение урока, наблюдая за действиями обучающихся, так и через квиз, размещенный на платформе Akelius в конце каждого занятия.
АНАЛИЗ УРОВНЯ ЦИФРОВОЙ ГРАМОТНОСТИ ИСПОЛЬЗОВАНИЕ МАШИННОГО ОБУЧЕНИЯ
Authors: Toygabyl S.A. , Sembina G.K.
Published: January 2024

Currently, digital technologies are penetrating deeper and deeper into all spheres of human activity. And it is difficult to imagine at least any area of human activity that is not affected by digital technologies. The transition to a digital way of transmitting information (digitalization) can be observed in all directions: in the development of interpersonal relationships, in professional activity, in receiving and providing services, recreation, and much more. Modern teenagers actively use laptops, gadgets are not only a means of communication and entertainment, but also as a tool for education. The following research paper examines the use of digital opportunities among the population. The input data were the results of the official website stat.gov and the questionnaire. The main purpose of this study is to evaluate and use several algorithms to determine the level of digital literacy of the population using raw data. Before extracting the data features, the sample was carefully processed. To improve the accuracy of the implemented model, hybrid methods were used to extract features. Six classifiers were used to classify the data. As a result, a detailed comparative evaluation was carried out for several trained models. All the results of the trained models are presented in the form of histograms and tables. The paper provides statistical data for 2020-2022. Based on the analysis of statistical data, the author of the article made conclusions that allow us to talk about the formation of new trends in the digital development of Kazakhstan.
УПРАВЛЕНИЕ КРЕДИТНЫМИ РИСКАМИ АО «НАРОДНЫЙ БАНК»: ПРОБЛЕМЫ И ПУТИ РЕШЕНИЯ
Authors: Azharbayeva A.Y. , Abdinova M.Kh.
Published: January 2024

The purpose of the research work is to reveal the essence of the credit risk system, study the causes of its occurrence, and conduct a detailed analysis of the loan portfolio and credit risk management methods on the example of the commercial bank "Halyk Bank of the Republic of Kazakhstan" JSC. The authors analyze the loan portfolio of the bank using CAMELS, Z - score methods and build a regression analysis using R-studio, identify the main problems in credit risk management in a commercial bank and propose some solutions. In this article such problems in credit risk management as incomplete credit risk assessment, weak credit risk monitoring, insufficient collateral assessment, improper risk diversification, insufficient credit risk management policy are identified, and several solutions and methods for their improvement are proposed. The informational approach to solving the set goals is formed based on existing scientific research, published periodicals, scientific articles and financial statements of the bank, and its statistical data is used as material for writing a research paper.
Nutritional epigenetics education improves diet and attitude of parents of children with autism or attention deficit/hyperactivity disorder
Authors: Dufault Renee J , Adler Katherine M , Carpenter David O , Gilbert Steven G , Crider Raquel A
Published: January 2024

BACKGROUND

Unhealthy maternal diet leads to heavy metal exposures from the consumption of ultra-processed foods that may impact gene behavior across generations, creating conditions for the neurodevelopmental disorders known as autism and attention deficit/hyperactivity disorder (ADHD). Children with these disorders have difficulty metabolizing and excreting heavy metals from their bloodstream, and the severity of their symptoms correlates with the heavy metal levels measured in their blood. Psychiatrists may play a key role in helping parents reduce their ultra-processed food and dietary heavy metal intake by providing access to effective nutritional epigenetics education.

AIM

To test the efficacy of nutritional epigenetics instruction in reducing parental ultra-processed food intake.

METHODS

The study utilized a semi-randomized test and control group pretest-posttest pilot study design with participants recruited from parents having a learning-disabled child with autism or ADHD. Twenty-two parents who met the inclusion criteria were randomly selected to serve in the test (n = 11) or control (n = 11) group. The test group participated in the six-week online nutritional epigenetics tutorial, while the control group did not. The efficacy of the nutritional epigenetics instruction was determined by measuring changes in parent diet and attitude using data derived from an online diet survey administered to the participants during the pre and post intervention periods. Diet intake scores were derived for both ultra-processed and whole/organic foods. Paired sample t -tests were conducted to determine any differences in mean diet scores within each group.

RESULTS

There was a significant difference in the diet scores of the test group between the pre- and post-intervention periods. The parents in the test group significantly reduced their intake of ultra-processed foods with a pre-intervention diet score of 70 (mean = 5.385, SD = 2.534) and a post-intervention diet score of 113 (mean = 8.692, SD = 1.750) and the paired t -test analysis showing a significance of P < 0.001. The test group also significantly increased their consumption of whole and/or organic foods with a pre-intervention diet score of 100 (mean = 5.882, SD = 2.472) and post-intervention diet score of 121 (mean = 7.118, SD = 2.390) and the paired t -test analysis showing a significance of P < 0.05.

CONCLUSION

Here we show nutritional epigenetics education can be used to reduce ultra-processed food intake and improve attitude among parents having learning-disabled children with autism or ADHD.
Outreach Schools: An Educational Innovation
Authors: Housego Billie E. J.
Published: January 2024

To benefit those students who cannot or will not pursue their educations in traditional high schools, that is, to prevent their leaving before graduation or to facilitate their return if they do leave prematurely, educators continue to address the problem of providing alternate educational programs. This study of Outreach Schools, a current system of alternative education, was conducted through staff and student interviews, student questionnaires, school visits, and an exploration of related literature. The school philosophy is outlined, the teachers and students are described, the operation of the schools is explained, and a case is made for this type of educational alternative.