bluuebunny/crossref_metadata_2025 huggingface dataset:
Navigating the digital currency landscape: A comprehensive examination from blockchain foundations to website security
Authors: Wang Ziyue
Published: March 2024

This paper offers an exhaustive exploration of the burgeoning digital currency realm, spanning from the foundational tenets of blockchain technology to the evaluation of pivotal website security vulnerabilities. The rise of decentralized cryptocurrencies, anchored in pioneering cryptography and consensus protocols, has deeply transformed traditional financial interactions. However, this transformation brings to the forefront new cybersecurity risks, borne from the intricate nature of these systems. Addressing these imminent challenges, the study introduces a holistic security model, meticulously designed for the Ethereum blockchain environment. This model integrates methods such as smart contract rigorous validation, transaction irregularity spotting, and network assault emulation. Rigorous experiments and simulations vouch for the models efficiency in pinpointing security breaches, marking an impressive 85% detection precision and an 81% robustness against uncharted zero-day onslaughts not encountered during model preparation. When juxtaposed with individual security tactics, the model exhibits a dominant stance in terms of attack deterrence, threat spectrum, and system productivity. Yet, the relentless advent of innovative attack strategies in this field means vulnerabilities remain. To bolster applicability in real-world scenarios, delving deeper into forecasting methodologies and broader tests on active systems prove essential. In essence, this multifaceted research initiative illuminates both theoretical and practical pathways to refine the strategic outline for unyielding security measures, championing prudent innovation and oversight in the rapidly evolving cryptocurrency landscape.
Deep Neural Network-based lap time forecasting of Formula 1 Racing
Authors: Zhao Zhixuan
Published: March 2024

Making comparisons and analyzing players in the sporting world is extremely valuable. The media, coaching staff, and players all rely on this data to assess performance, develop strategies, and make critical decisions. Therefore, neural networks can be employed to create a practical system that uses previous years data to predict future performance. This paper uses a Deep Neural Network (DNN) to predict the fastest lap time in qualifying for Formula 1 (F1) races. The network categorizes data to learn each drivers performance at each circuit and provides separate predictions. By doing so, it considers the unique characteristics of each driver and track, enabling more accurate predictions. The paper demonstrates that neural networks tend to have better performance and adaptability in such complex environments compared to traditional mathematical methods like linear regression. Neural networks can learn from the data and detect patterns that are difficult to capture with traditional methods. As a result, they can achieve a relatively precise prediction, providing valuable insights and decision-making support for coaches, drivers, and fans.
Comparison of machine learning-based book comments sentiment analysis for constructing recommendation system
Authors: Weng Jiaqi
Published: March 2024

The exponential growth in the volume of books available, along with the proliferation of online platforms, has made it increasingly challenging for readers to find books tailored to their interests. This research paper aims to address this challenge by developing an effective book recommendation system based on user reviews and ratings, primarily drawn from Amazons dataset covering the period from May 1996 to July 2014. Using a K-Nearest Neighbors (KNN) algorithm and a Random Forest baseline model, the study focuses on comparative analyses in terms of Mean Squared Error (MSE) and computational costs. The KNN model outperformed the baseline model with a lower MSE of 0.15 compared to 0.38 and proved to be computationally less exacting. While the KNN model is currently the more tenable option for deployment, the paper posits that an ensemble approach may offer a more robust solution. Future work aims to include sentiment analysis, explore other recommendation algorithms, and make use of more advanced evaluation metrics. This study provides a foundation for the advancement of book recommendation systems, offering insights into their efficiency and effectiveness.
A comprehensive research of deep learning approaches for High Definition map construction in autonomous driving
Authors: Wang Zimo
Published: March 2024

In the realm of autonomous driving, High Definition Maps (HD maps) are indispensable for safe and precise navigation. Traditional HD map construction methods involving point cloud capture and SLAM have proven effective but labor-intensive. This paper addresses the growing interest in leveraging deep learning techniques to streamline HD map creation. This paper presents a systematic exploration of deep learning methodologies for HD map construction. It categorizes these approaches into two core components: Feature Extraction and Feature Decoding. Feature Extraction involves the transformation of input data, comprising images and LiDAR point clouds, into Bird's Eye View (BEV) representations. Feature Decoding is dissected into rasterized map objectives and vector map objectives. Detailed analysis is conducted on prominent methodologies. The paper provides a nuanced evaluation of these deep learning techniques, highlighting their respective strengths and limitations. Factors such as precision, computational efficiency, and the preservation of fine-grained details are considered when selecting the most suitable method. This comprehensive review summarizes and prospects the research in related fields.
Statistical and sentiment analysis based on comments of skin care products
Authors: Jiang Yunhan
Published: March 2024

With the continuous development of the Internet economy and the strong promotion in various aspects, the rise of new domestic brands has led to an increasing number of consumers paying attention to and purchasing cosmetics online. Grasping the pulse of the times in this context is a crucial key to understanding the Internet economy. This paper first crawled the product links of the JD.com skin care essence category, randomly selecting 100 products. Subsequently, a total of 49,560 comments were crawled for the selected products. Furthermore, employing text mining techniques, this paper conducts word frequency statistics, generates word clouds, performs cluster analysis, and analyzes the emotions expressed in the JD.com skin care essence product comments, aiming to achieve comprehensive mining and analysis of the comment content from multiple perspectives. Additionally, descriptive statistics and visual representations are utilized to enhance the accuracy and intuitiveness of the text processing. Finally, this paper summarizes the insights gained from the product comments on the internet e-commerce platform and provides some prospects for future development.
An open intent detection model optimized for datasets based on the Bert large model
Authors: Dong Yichen , Wang Zhen , Wu Tianjun
Published: March 2024

Within current task-oriented dialogue systems, the focus of intent detection predominantly centers on closed domains. Nevertheless, in real-world usage scenarios, a substantial proportion of interactions fall into the open-domain category. User intentions frequently transcend predefined boundaries, giving rise to a multitude of out-of-domain intents, which pose a formidable challenge to existing models, ultimately leading to diminished recognition rates and accuracy. The demand for open intent detection models is increasing in today's society to address this issue effectively. This paper proposes a method to optimize datasets, thereby enhancing the training accuracy of open intent detection models. Specifically, this paper employs the Adaptive Decision Boundary Learning algorithm, which is currently popular in open intent detection. Leveraging this algorithm, this paper suggests using the K-means clustering algorithm to refine the intent labels within the dataset. This process helps identify and remove outliers in the dataset, making the distinction between known domain and open-domain intent labels more precise. Experimental results on two datasets, banking77 and stackoverflow, demonstrate the effectiveness of our approach in significantly improving model accuracy.
The investigation and development of chatbot related to NBA players
Authors: Zhang Hengrui
Published: March 2024

At present, the utilization and development of large language models have been relatively mature, but there are still some areas that have not yet been involved, nba player information retrieval is one of them, this paper will be on through the development and design of large language models, so that it becomes a chatbot to facilitate user retrieval. This project uses mata's llama2-13b model to act as a chatbot, the model can play a great performance in the case of minimizing the memory, and can well meet the user's needs, by imitating the database of the big language model to build a database on nba player information, so that the nba player information is filled into the model for the model to learn, and through the model itself to continuously learn and Through the model's own continuous learning and imitation of human language, the model can be made to output as concise a language as possible to describe the personal information of the nba players, and then meet the user's needs. In this project, the model successfully reads the database and outputs the information that the user wants to get in easy-to-understand language, so that the user can get the personal information of the NBA players more conveniently and intuitively, and the correctness rate reaches the expectation, which makes the study successful.
Application and challenges of artificial intelligence in cybersecurity
Authors: Li Fangshu
Published: March 2024

This paper delves into the multi-faceted role of Artificial Intelligence (AI) in the field of cybersecurity. It conducts an in-depth analysis of two common security problems, spam email and DDos/Dos attacks. It focuses on the application of AI in resolving these problems and further on Event Management (SIEM) and Intrusion Detection Systems (IDS). Furthermore, this article outlines and discusses five key challenges that AI may encounter throughout its development, including issues related to reliability, unidentified threats, data privacy, ethical considerations, and the importance of an explainable AI. The paper underscores the remarkable potential of AI to improve our defences against emerging cybersecurity threats. It highlights the growing importance of addressing ethical and legal issues in the evolving technological environment. Finally, the article offers a comprehensive summary and valuable insights into the future prospects of AI in the realm of cybersecurity, confirming its crucial role in shaping the security landscape in the digital era.
Predicting taxi unmet trip demand
Authors: Ahmed Anita , Kalinin Alexey , Famili Pooneh , Tang Xin , Zhou Ziman
Published: March 2024

The purpose of this project is to predict the number of taxi trip that goes unmet in NYC by using available trip data generated by Taxi Cabs. The expected outcome from this project is to identify the areas in NYC that experiences unmet demand and to identify socio-economic features that impact trip demand.
The project was broken down into 2 phases. To account for daily trip trends the study is broken down in 7 periods on Monday to Saturday and 4 periods on weekends. In the rst phase 3 approaches were developed to identify census tract where the demand of taxi is not met. The rst approach was to compare the monthly total pickup and drop-of counts. The second approach identied the underserved census tracts by nding those with the least number of vacant taxis within a given time duration. In the third approach, the rate of change Uber pickup was compared with the rate of change of combined pick up of all taxi services over a 6 months period. The nal output was: 358 unmet trip demand CT that had pick-ups to drop-offs ratio lower than 25%, Less than 2 vacant taxi a minute and a Uber growth rate more than 4%. These areas were in North-east Queens, South Brooklyn and North of the Bronx. In Phase II, the socio-economic features were ranked to understand their inuence on taxi demand. Out of the 11 selected features the top 5 features were neighborhoods with high number of offices and employees, residential areas, income and rent. Using the 11 features as predictors and pick-up from CT with satisfactory as target variable a model was developed to predict demand for underserved areas. The model predicted overall 92,000 trips per day goes unmet in NYC which is 4.2% of the total current daily trips.
Research on the electronic control system for multispectral infrared detectors
Authors: Yu Jing , Liu Nan , Ding Peng , Ru Zhanqiang , Cheng Suzhen , Wang Zhengguang , Gong Jingwu , Yin Zhizhen , Wu Fei , Song Helun
Published: March 2024

In order to acquire and fully exploit multispectral information of scenes, and to establish a foundation for the research of multispectral image algorithms, a laboratory has developed a multispectral infrared detector capable of detecting short-wave infrared, mid-wave infrared, and long-wave infrared in three bands. Additionally, a preliminary electronic control system has been designed. The system employs a field-programmable gate array (FPGA) to accomplish the timing control, data acquisition, preprocessing of individual channel images, and multispectral image fusion of the detector. The preprocessing involves black level correction, blind element correction, non-uniformity correction, and histogram equalization of the raw images. For trispectral fusion, color enhancement is applied to linearly combined images in the YUV color space using a color transfer method. The system utilizes a pipeline design to ensure algorithm efficiency. In simulation, the electronic control system for the multispectral infrared detector obtains trispectral information of the scenes, and through image preprocessing and fusion, enhances the understanding of scene information.
Temporal Rainfall Variations Induce Forecast Errors in Rainfed Agriculture in the Brazilian State of Ceará, Brazil
Authors: Lemos Jose de Jesus Sousa , Bezerra Filomena Nadia Rodrigues , Paiva Elizama Cavalcante , Ipolito Antonia Leudiane Mariano , Sousa Erika Costa , Filho Joao Da Costa
Published: March 2024

The research aims to: a) assess the instabilities associated with rainfall and the variables that define the production of rice, beans, cassava and corn in the state of Ceará between 1945 and 2020; b) estimate models that can be used to make projections of harvested areas, yields and prices for these crops between 1945 and 2020; c) assess the impact of rainfall on the estimated forecasting models; d) assess how rainfall affects the likelihood of farmers making forecasts of the variables that define agricultural production. Rainfall data was obtained from the National Centers for Environmental Information (NOAA). Crop yield data came from the Brazilian Institute of Geography and Statistics (IBGE). Instabilities were measured by the coefficients of variation. ARIMA models (autoregressive, integrated and moving average model) were used to make the forecasts. The hypothesis that the residuals generated by the models are influenced by annual rainfall was tested. The results showed high instabilities in annual rainfall, which spread to the variables that define crop yields. Parsimonious and robust adjustments were obtained from a statistical point of view and it was shown that the errors generated, including their magnitudes, in the models used to forecast all the variables that define bean and corn yields, harvested areas and rice yields, as well as cassava yields, are influenced by annual rainfall in Ceará between 1945 and 2020.
Efektivitas Program Bantuan Sosial dalam Meningkatkan Kesejahteraan Fakir Miskin pada Dinas Sosial Kota Denpasar
Authors: Miracantika Anak Agung Putu Agung , Wirantari I Dewa Ayu Putri
Published: March 2024

Kota Denpasar, sebagai ibu kota Provinsi Bali, tidak terkecuali pada masalah ini, jumlah fakir miskin di Kota Denpasar teris mengalami peningkatan, memerlukan perhatian yang lebih serius dari pemerintahan daerah, khususnya Dinas Sosial. Isi dari jurnal ini memiliki tujuan untuk mengevaluasi efektivitas program bantuan sosial dalam meningkatkan kesejahteraan bagi fakir miskin pada Dinas Sosial Kota Denpasar. Metode yang digunakan adalah metode deskriptif kualitatif yaitu suatu prosedur penelitian yang menghasilkan data deskriptif berupa kata-kata, gambar, dan bukan angka-angka , dari orang-orang atau perilaku yang dapat diamati. Hasil penelitian menunjukkan bahwa program bantuan sosial telah memberikan dampak positif terhadap peningkatan kesejahteraan fakir miskin. Namun, masih ada beberapa tantangan yang perlu diatasi untuk meningkatkan efektivitas program ini kepada masyarakat. Kesimpulannya, program bantuan sosial ini efektif dalam meningkatkan kesejahteraan fakir miskin, namun perlu ada peningkatan dalam hal penyaluran dan sosialisasi program.
Strategy of Spreading Aswaja Understanding by Nurul Furqon Boarding School Tomia Wakatobi, Southeast Sulawesi
Authors: Irfan M. , Abdullah Abdullah
Published: March 2024

As a country rich in diversity, Indonesia has witnessed a red ink history of religion-related violence. In Southeast Sulawesi, the majority Muslim population lives a peaceful religious life. However, potential conflicts arise on the basis of ethnicity, not religion. Although violence in the name of religion has not yet occurred, radical and intolerant movements are growing, demanding in-depth understanding and effective preventive measures. this research aims to Know the strategy of Pondok pesantren nurul furqon in spreading aswaja understanding. The place of research conducted at the nurul furqon boarding school in Tomia Wakatobi, Southeast Sulawesi. Research conducted by researchers includes descriptive qualitative research with the type of case study. Data collection techniques include observation, interviews and documentation. The data analysis model includes data reduction, data presentation, and conclusion drawing. The results of this study show that Pondok Pesantren Nurul Furqon has successfully implemented a stunning strategy, involving elements such as Hadrah, majlis ta'lim, and the leadership role of the kiyai as key elements in the spread of Aswaja. More than just an educational institution, this study highlights the central role of pesantren in maintaining the sustainability of Aswaja values, while guarding against potential radicalism.
Perbandingan Pengembangan Kurikulum di PPM MBS Yogyakarta dan PPMI Assalaam Sukoharjo
Authors: Irfana Rahmi
Published: March 2024

Penelitian ini membahas tentang pondok pesantren Modern MBS Yogyakarta dan Pondok Pesantren Assalam Sukoharjo, kedua Pondok Pesantren ini memiliki keunggulan yang berbeda, baik dalam kurikulum Pondok dan Kurikulum Madrasahnya, ciri khas sebuah Pondok Pesantren adalah Pembelajaran Kitab Kuning, Pondok Pesantren Modern MBS Yogyakarta spesifikasi kajian kitab kuningnya adalah kitab Riyadus Shalihin sedangkan Spesifikan Kitab Kuning Pondok Pesantren Assalam Sukoharjo adalah kitab Arbain. Penelitian ini menggunakan pendekatan deskriptif kualitatif yang berusaha mengungkapkan suatu masalah atau peristiwa sebagaimana adanya. PPM MBS telah berinovasi dengan sistem boarding school. Pengembangan kurikulum PPM MBS Yogyakarta mengacu pada delapan (8) Standar Nasional Pendidikan [SNP] untuk menjamin pencapaian tujuan pendidikan nasional. Kurikulum PPM MBS Yogyakarta disusun untuk memberikan kesempatan kepada peserta didik gunanya untuk menganalisis pengembangan kurikulum di PPM MBS Yogyakarta, peneliti menggunakan teori pengembangan kurikulum Hilda Taba. Alasan peneliti menggunakan teori ini karena Hilda Taba lebih menekankan pada perhatian guru dalam proses pengembangan kurikulum. Teori ini sesuai dengan sistem KTSP yang lebih memberi ruang bagi sekolah atau guru untuk mengembangkan kurikulum sesuai dengan visi, misi, dan tujuan satuan pendidikan masing-masing.
Molecular detection of extended-spectrum β-lactamase-producing Escherichia coli from bat caves on Lombok Island
Authors: Mustika Yolla , Kinasih Kurnia , Effendi Mustofa , Puspitasari Yulianna , Kurniawan Shendy , Khairullah Aswin , Samodra Muhammad , Hasib Abdullah , Agustin Alfiana , Moses Ikechukwu , Silaen Otto
Published: March 2024

Background:
The discovery of antibiotic-resistant Enterobacteriaceae bacteria in wild animals is an indication of their potential for wildlife as a reservoir. Bats are natural reservoir hosts and a source of infection for several microorganisms and have the potential to become vectors for the spread of zoonotic diseases.
Aim:
A study was conducted based on these characteristics to identify and detect the blaTEM gene in Eschericia coli isolated from bat excrements in Tanjung Ringgit Cave, East Lombok.
Methods:
Bat faecal samples were firstly inoculated onto EMB agar media. Recovered bacterial isolates were further characterized using standard microbiological techniques. Antimicrobial susceptibility testing was done using the Kirby-Bauer disc diffusion method. blaTEM gene detection was carried out using polymerase chain reaction (PCR).
Results:
Out of the 150 bat fecal samples obtained from Tanjung Ringgit cave, Lombok Island, Indonesia, 56 (37 %) were positive for E. coli. Eight (8) out of the 56 E. coli isolates that underwent antimicrobial susceptibility testing using the disc diffusion method were confirmed to be multidrug-resistant as they exhibited resistance to at least three different classes of antibiotics. Out of the eight (8) MDR E. coli isolates recovered from fecal samples of bats, 2 (two) harbored the blaTEM gene.
Conclusion:
The discovery of the blaTEM gene in bat fecal samples indicates the potential for wild animals, especially bats, to spread ESBL resistance genes to the environment and to humans.
МЕТОДЫ УПРАВЛЕНИЯ КРЕДИТНЫМ ПОРТФЕЛЕМ КОММЕРЧЕСКИХ БАНКОВ
Authors: Светлана Николаевна Кузьмина  , Арзикулов Отабек Али угли  , Атамуратова Гулрух Музафаровна
Published: March 2024

В данной статье рассматривается кредитный портфель банков и способы управления им, а также вопросы классификации качества активов и развития системы формирования резервов для покрытия возможных убытков коммерческих банков.
INFLUENCE OF THE VOLUME OF INDUSTRIAL PRODUCTION IN UZBEKISTAN ON THE IMPORT TREND
Authors: Sabirov Khasan Nusratovich  , Akbarova Asidaxon
Published: March 2024

The main goal of the scientific research is to study the interaction of industrial production in Uzbekistan with the volume of imports, and statistical data for the period of 2010-2021 were used in the research. First, a summary of the scientific articles on the topic was shown, and an econometric model was used to conduct the research. During the research, a multi-factor correlation-regression analysis was conducted and a model was created. Fisher test and Durbin-Watson test were used. In the results of scientific research, it was found that there is no connection between industrial production and import. At the end of the article, proposals and conclusions are given on the rapid development of industrial production and reduction of imports.
RAQAMLI IQTISODIYOT SHAROITIDA OZIQ-OVQAT SANOATI KORXONALARI FAOLIYATIDA ZAMONAVIY BOSHQARUV ISTIQBOLLARI
Authors: Turg‘unov Muxriddin Moʻydinjon oʻg‘li
Published: March 2024

Maqolada raqamli iqtisodiyot mamlakat iqtisodiy tarmoqlarini, xususan, oziq-ovqat sanoatini yanada rivojlantirishning asosiy omili sifatida qaralgan. Oziq-ovqat sanoati korxonalari faoliyatini tashkil etishda raqamli iqtisodiyotning unsurlaridan samarali foydalanish va yoʻlga qoʻyish usullari oʻrganilgan. Oziq-ovqat sanoati korxonalari faoliyatiga zamonaviy boshqaruv mexanizmini tatbiq etish hamda uni rivojlantirish, ushbu jarayonda boshqaruvga ta’sir etuvchi omillarni, xususan, raqamli iqtisodiyotni alohida oʻrganish, oziq-ovqat sanoat tarmoqlarini modernizatsiya qilish va oziq-ovqat ishlab chiqaruvchi korxonalarnini qoʻllab-quvvatlash muhim sanaladi. Oziq-ovqat sanoati korxonalari faoliyatini zamovaniy boshqaruv tizimlaridan foydalanish hamda uning dolzabrligi ochib berilgan.
MAMLAKAT YALPI ICHKI MAHSULOTINI RIVOJLANTIRISHDA KICHIK BIZNESNI O‘RNI VA DUCH KELISHI MUMKIN BO‘LGAN MUAMMOLAR TAHLILI
Authors: Gafurov Xurshid Maxsudovich  , Abdulhamidov Sarvarbek Akramjon o‘g‘li
Published: March 2024

Mazkur maqolada kichik biznes faoliyatini mamlakat yalpi iсhki mahsulotini oshirishdagi o‘rni va bu faoliyat turini yuritish hamda rivojlantirish jararayonida duch kelishi mumkin bo‘lgan muammolar bo‘yicha tadqiqotlar o‘tkazilgan va olingan natijalar bayon qilingan. O‘zbekiston Respublikasi hududi miqyosida o‘tkazilgan so‘rovnomada jami 320 nafar kichik biznes bilan shug‘ullanuvchilar ishtirok etdi. So‘rovnoma natijasida eng ko‘p uchraydigon muammolar resurslarni notekis taqsimlanishi, adolatsiz raqobat, iste’molchilarni o‘zgaruvchan xohish-istaklari kabilar ekanligi aniqlandi. Resurslarning notekis taqsimlanishi muammosini hal qilishda kichik biznes uchun soliq bo‘yicha imtiyozlar berish zarur. Yirik kompaniyalarning adolatsiz raqobat amaliyotiga kirishish imkoniyatlarini cheklash uchun har bir davlat o‘zining monopoliyaga qarshi qonunlarni kuchaytirishi lozim. Iste’molchilarning o‘zgaruvchan xohish-istaklar muammosini bartaraf etishda ularni ehtiyojlari va umidlarini tushunish uchun mijozlar bilan muntazam ravishda muloqot qilish zarur.  Maqolaning oxirida mazkur muammolarning yechimlari haqida umumiy xulosa va takliflar berib o‘tilgan.
ERTA BOLALIK TA’LIMINI QOʻLLAB-QUVVATLASHDA OILALARNING ROLI
Authors: Sanginova Gulnoza Baxodirovna
Published: March 2024

Ushbu maqolada bola tug‘ilgan kundan boshlab, uni maktabga borgunigacha boʻlgan davrda har tomonlama yetuk barkamol qilib tarbiyalash qonuniyatlarini oʻrganish va soha olimlarining fikrlari keltirib oʻtilgan. Bolaning bilim olishiga boʻlgan qiziqish, havasini oshirishda u tarbiyalanayotgan muhit, ya’ni oila muhim oʻrinni egallashi haqida soʻz yuritilgan. Erta bolalik davridagi ta’lim – bu bolaning oʻrganishga boʻlgan mehrini oshirishga yordam beradigan tajriba va turli xil vositalarni oʻrganishdir. Ota-onalar erta bolalik davridagi ta’lim nima uchun muhimligini tushunishlari kerak.
ALISHER NAVOIY IJODIDA SAKKOKIY AN’ANALARI
Authors: Xoldorova Gulnoza Husniddinovna
Published: March 2024

Maqolada Alisher Navoiy ijodining turkiy zaminlari haqida soʻz yuritilgan. Xususan, adibning “Farhod va Shirin” dostoni va Sakkokiy ijodi orasidagi umumiy jihatlar yoritilgan. Fikrlar har ikki ijodkor asarlaridagi baytlar bilan izohlab berilgan. Maqolada gʻarbda haligacha hukm surayotgan “turkiy adabiyot toʻla qimmatga ega emas”, Alisher Navoiy fors adabiyotining tarjimoni edi” qabilidagi qarashlarga javob tarzida Navoiy ijodining turkiy ildizlari mavjudligini asoslash maqsad qilib olingan va buning uchun turkiy adabiyotdagi Navoiygacha mavjud tasvirlar baytlar asosida dalillab  berilgan. Ayniqsa, Alisher Navoiy ijodi turkiy xalqlar adabiyotining ma’naviy sarchashmalari bilan uzviy aloqadorligi va ayni damda uning mahsuli ekanligi qayta-qayta ta’kidlangan.
АКТУАЛЬНЫЕ ВОПРОСЫ ИЗУЧЕНИЯ РУССКОГО ЯЗЫКА
Authors: М.M.Парпиева
Published: March 2024

в данной статье рассматриваются вопросы изучения русского языка в высших учебных заведениях. Целью исследования является раскрытие сущности актуальных вопросов изучения русского языка. В исследовании использована описательная методология. В ходе исследования изучены работы специалистов в области языкознания. В рамках исследования изучены прогрессивные методики изучения русского языка, а так же вопросы профессиональной и педагогической компетентности преподавателей. В ходе исследования автор приводит выводы в рамках темы, согласно которым при изучении русского языка необходимо обращать внимание на методические, социальные, межличностные, профессиональные, педагогические составляющие. В заключении автор приводит выводы по исследуемой теме опираясь на результаты проведённого анализа.
ПРИМЕНЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ОБРАЗОВАНИИ
Authors: Гулямов С.С  , Шермухамедов А.Т  , Шермухамедов  Б.А.
Published: March 2024

В статье рассматриваются вопросы использования искусственного интеллекта в образовании.
AMBIENTES DIGITAIS E PROMOÇÃO DE COMPETÊNCIAS METACOGNITIVAS
Authors: Goulão Maria de Fátima
Published: March 2024

Os contextos digitais de aprendizagem promovem a autonomia dos estudantes.  Para isso é pertinente que estes consigam refletir e planear as suas ações. Os Exames Wrappers são uma ferramenta metacognitiva que incentiva a reflexão estruturada e o planeamento para a aprendizagem futura. Foi nosso objetivo conhecer as estratégias utilizadas por um grupo de estudantes para a preparação de uma prova de avaliação. Também, a perceção dos mesmos relativamente à avaliação que irão ter, bem como, pretendem orientar o seu estudo. Fizeram parte da amostra 67 estudantes, sendo 76,1% do sexo feminino e 23,9% do sexo masculino. A sua média de idade é de 37,66. Em conclusão, pelas respostas obtidas verificou-se que os estudantes compreenderam o objetivo desta reflexão e, que a partir desta conseguiram perceber alguns aspetos que deveriam ser tidos em conta num outro momento de avaliação. Isto leva-nos a crer que esta autorreflexão induzida produziu os resultados esperados.
Development and Application of Bioorthogonal Reactions for Drug Imaging and Activation
Authors: Vrábel Milan , Šlachtová Veronika
Published: March 2024

Chemical transformations compatible with biological systems serve as invaluable tools for probing biomolecules, drug compounds, and biological processes in their native environments. The complex environment of living organisms requires these reactions to be highly selective and efficient, posing a formidable challenge to the field of organic chemistry. A number of chemical reactions have recently emerged to meet this challenge, providing a diverse toolkit for researchers. This manuscript presents a comprehensive survey of current bioorthogonal reactions, emphasizing their applications in bioimaging, diagnostics, and medicine.
Medis-Alarm Significant Database of Hazardous Substances in Czech Republic
Authors: Mika Otakar Jiří , Polívka Lubomír , Malinovský Karel , Matýs Tomáš
Published: March 2024

This article deals with the security of the population and the fire brigade, which uses the Czech database of hazardous substances, Medis-Alarm. This database is connected with the long-term operation of the proven safety transport system TRINS (transport, information and accident system) in the Czech Republic. The Medis-Alarm database is the most widespread one used in the Czech Republic. In this paper, this database is therefore characterized and described in detail, and various possibilities of its use at universities are indicated. The article also aims to provoke a public professional discussion on the necessary increase of the safety of both the population and rescuers and the improvement of environmental protection in the Czech Republic.
TAXATION AND TAXES OF PRIVATE HOUSEHOLDS: REPORTING, REPORTING PROCEDURE
Authors: Лайпанова З.М. , Халкечев Р.Г.
Published: March 2024

Целью данной статьи является определение правового статуса личных подсобных хозяйств и предложение рекомендаций по повышению роли личных подсобных хозяйств в контексте развития сельскохозяйственных территорий. Авторами рассмотрены особенности правового регулирования деятельности личных подсобных хозяйств, рассмотрены законодательные аспекты предоставления земель личным подсобным хозяйствам, их правовой статус, а также определены проблемы системы налогообложения. Авторами сделаны выводы о тенденциях развития личных подсобных хозяйств в настоящее время. Показано, что основная цель ведения личного подсобного хозяйства заключается в удовлетворении собственных потребностей и потребностей семьи в сельскохозяйственной продукции. На современном этапе социально-экономического развития, личные подсобные хозяйства являются важным элементом сельскохозяйственной отрасли, поскольку производят все виды сельскохозяйственных культур, а также продукцию животноводства. Сделан вывод, что одним из ключевых элементов системы господдержки должны стать налоговые механизмы, стимулирующие ведение деятельности личным подсобным хозяйством и снижающие риски налоговых нарушений. Поддержка личных подсобных хозяйств является необходимым условием обеспечения устойчивого развития сельских территорий Российской Федерации и достижения продовольственной безопасности.
Трансформація соціально-економічного ландшафту України під впливом війни: аналіз основних макроекономічних показників
Authors: Голота М. М.
Published: March 2024

За останні роки інтенсивність військових конфліктів стрімко зростає, при цьому російсько-українська війна стала однією з найбільш значущих подій в сучасній історії. Стаття присвячена вивченню впливу цього конфлікту на соціально-економічний розвиток України, що є актуальною та важливою проблемою національного та міжнародного рівнів. Мета дослідження полягає у виявленні та аналізі економічних наслідків війни на різних етапах конфлікту та в різних сегментах економіки, що вимагає комплексного підходу та використання різних методологічних інструментів. Методологія дослідження базується на аналізі широкого спектру статистичних даних, а також на порівняльному аналізі. Особлива увага приділяється динаміці основних макроекономічних показників, таких як обсяг реального валового внутрішнього продукту (ВВП), рівень інфляції та безробіття, що дозволяє зробити висновки щодо змін в економіці країни внаслідок війни. Розглядаються як прямі, так і непрямі наслідки бойових дій на економіку, включаючи масштаби руйнувань, завданих промисловості та інфраструктурі. Окрему увагу приділено екологічним та економічним наслідкам підриву Каховської гідроелектростанції, який мав серйозний вплив на екологічну та економічну ситуацію в регіоні. Досліджено стан основних галузей економіки, зокрема сільського господарства, торгівлі та енергетики, в умовах війни, що дає можливість зрозуміти їхню реакцію на конфлікт та визначити стратегії розвитку в умовах нестабільності. Дослідження наслідків війни на економіку має велике значення для розробки ефективної політики, визначення пріоритетів для відновлення, моніторингу прогресу, прогнозування майбутніх ризиків, підвищення обізнаності, сприяння миру, забезпечення справедливості, збереження історичної пам'яті та розвитку науки. Практична цінність даного дослідження полягає в покращенні стратегій управління економікою в умовах конфлікту, розробці політики відновлення після війни та прогнозуванні можливих економічних наслідків для розвитку країни. За типом дослідження стаття є оглядовою.
Developing Capabilities for Machine Operators: A Path Towards Industry 5.0
Authors:   Dr. A. P. J. Abdul Kalam University, Indore, Sulakhe Mr. Prakash , Samuel Dr Rajeev ,   Dr. A. P. J. Abdul Kalam University, Indore
Published: March 2024

The dawn of Industry 5.0 promises a paradigm shift in human-machine collaboration, rewriting the role of the machine operator. This abstract delves into the transformative potential of Industry 5.0 technologies in empowering machine operators and reshaping their contributions to industrial processes. The conclusion emphasizes the potential of Industry 5.0 to create a more equitable, engaging, and empowering work environment for machine operators, while urging further research and policy discussions to ensure a smooth and responsible transition towards this transformative future. Keywords: Industry 5.0, machine operators, empowerment, AI, data, upskilling, reskilling, collaborative work, ethical considerations, social impact.
Enhancing Trust and Security in IoT Architecture for Low-Cost Microcontroller Devices using Elliptic Curve Cryptography
Authors:   Presidency University, Bangalore, India - 560064, D H R Dr. Murthy
Published: March 2024

Abstract—In the rapidly expanding universe of the Internet of Things (IoT), low-cost microcontroller devices, such as the NodeMCU, have become ubiquitous. While these devices have transformed how we interact with the physical world, they also introduce significant security vulnerabilities. Chief among these is susceptibility to man-in-the-middle (MITM) attacks, which pose a serious risk to the confidentiality and integrity of data transmitted across these networks. This study addresses this critical issue by proposing the adoption of Elliptic Curve Cryptography (ECC), a cryptographic method known for its efficiency and strong security, despite the computational limitations of low-cost IoT devices. We conducted an experiment demonstrating the ease with which an MITM attack can intercept data from a NodeMCU device. Following this, we implemented ECC to secure data transmission, showcasing its viability as a lightweight yet robust security solution. Our research not only highlights the pressing need for enhanced security measures in the IoT ecosystem but also provides a practical framework for securing low-cost microcontroller devices against sophisticated cyber threats. Through our findings, we contribute to the development of more secure, trustworthy IoT architectures, ensuring that these devices can continue to safely serve as integral components of our digital lives. Keywords—NodeMCU, ESP8266, Data theft, Elliptic Curve Cryptography, Man-in-the-middle attack
Unraveling the Future: Emerging Trends of Financial Literacy in the Digital Age
Authors:   Associate Professor, Department of Commerce  Central University of Haryana, Meena Dr. Rajendra Prasad
Published: March 2024

Financial literacy plays a pivotal role in navigating the intricacies of contemporary finance, and as the financial landscape undergoes transformation, so do the trends in financial literacy. This theoretical paper delves into the emerging trends in financial literacy, focusing on their potential implications for both individuals and economies. The dynamic definition of financial literacy now encompasses a range of essential components, including digital literacy, sustainable investments, and comprehension of intricate financial instruments. Personalization and technology are facilitating tailored financial education, while the application of behavioural economics principles and nudging techniques is molding positive financial behaviours. Additionally, gamification and edutainment strategies are proving effective in engaging and motivating learners, thereby enhancing knowledge retention. Inclusive financial literacy initiatives are being developed to address the needs of underserved populations, contributing to the promotion of economic growth. Moreover, the relevance of education on digital currencies and blockchain is escalating as these innovations gain prominence, and investor education is gaining significance in response to the surge in retail investing. Concurrently, integrating financial literacy into educational institutions is equipping students early in life with essential financial skills. By comprehending these emerging trends, societies can design more efficacious financial education initiatives, empowering individuals to make well-informed financial decisions and bolstering economic resilience.
Farmer Friendly Solar Based Electric Fence for Rural Agriculture
Authors: Journal IJSREM
Published: March 2024

Agriculture provides all the people’s food needsas well as a variety of raw materials for industry. However, there is a significant loss of crops due to animal intrusion in agricultural lands. Wild animals will wreak havoc on crops. As a result, it’s critical to keep an eye out for animals in the region. Then various devices should be activated to repel the dangerous animals. Operational amplifier circuits are put in place primarily for the purpose of detecting animal intrusion into the farm. The completed protection system is responsible for providing early warning of potential wild animal intrusion and harm. Key Words: agriculture operational amplifier circuits farm
IoT Based Smart Irrigation System
Authors:   Head of the department Dept. of Electronics and Communication Engineering,  DRR government polytechnic, Davangere, Karnataka., T JYOTHISHREE
Published: March 2024

Smart irrigation refers to an advanced agricultural and landscaping technique that leverages technology, data, and automation to optimize water usage for irrigation. It encompasses the use of sensors, weather forecasts, and automation systems to monitor soil moisture levels, weather conditions, and plant requirements. By employing real-time data and intelligent algorithms, smart irrigation systems aim to deliver precise amounts of water to plants, reducing water wastage, conserving resources, and improving crop yields or landscape health. This approach holds the promise of addressing water scarcity issues and enhancing sustainable agriculture and landscaping practices. Keywords: 1.Arduino IDE program software. 2.Development board ESP8266. 3.Communication devices. 4.Sensors. 5.Watering devices. 6.Drip irrigation.
Smart Temperature Dependent Cooling of Solar panel Using Arduino
Authors: Journal IJSREM
Published: March 2024

This project involves the integration of various hardware components, including an Arduino board, a temperature sensor, an LCD display, a relay module, a CPU fan, and an ESP8266NodeMCU. The goal is to create a system that can monitor temperature, display information on an LCD screen, a relay to control fan, a CPU fan, and upload collected data to a web server for remote access and analysis. The temperature sensor is connected to the Arduino board to measure the ambient temperature. The LCD display provides real-time temperature readings and system status information. The relay module enables the Arduino to control an external device based on predefined temperature thresholds. Additionally, a CPU fan is integrated to manage the temperature of a system component. This enhances the overall system stability and efficiency. The ESP8266 Node MCU, acting as a Wi-Fi Module, connects the system to the internet. It gathers temperature data from the Arduino and periodically uploads it to a designated web server via HTTP or other suitable protocols. This enables users to monitor temperature trends and system performance remotely, providing insights into environmental conditions and operational effectiveness. The integration of these components involves programming the Arduino and Node MCU using relevant libraries and languages such as c / c++ and Arduino IDE. The Arduino code manages data collection, LCD display, relay control, and fan speed regulation, ensuring seamless coordination between the components. The Node MCU code establishes a connection to the Wi-Fi network, formats and transmits data to the web server, and handles any necessary security considerations. Keywords: CPU Fan, Arduino, solar panels, Templates, Journals.
Trening funkcjonalny jako forma terapii w przewlekłych dolegliwościach bólowych odcinka lędźwiowego kręgosłupa
Authors: Adamik Aleksandra , Mikołajczyk Edyta
Published: March 2024

Cel: Celem pracy była ocena skuteczności zastosowanego treningu funkcjonalnego na poziom bólu, zakresy ruchomości odcinka lędźwiowego kręgosłupa, wielkość przodopochylenia miednicy i ograniczenia w codziennym funkcjonowaniu spowodowane występowaniem przewlekłych dolegliwości bólowych.
Materiał i metody: W badaniach brało udział 20 kobiet w wieku 20–24 lat z przewlekłymi dolegliwościami bólowymi odcinka lędźwiowego. Uczestniczyły w 12-tygodniowej terapii w formie treningu funkcjonalnego. U wszystkich kobiet, przed i po 12-tygodniach, przeprowadzono pomiary zakresów ruchomości odcinka lędźwiowego oraz stopnia przodopochylenia miednicy. Poziom bólu określono z wykorzystaniem skali VAS, stopień niepełnosprawności Kwestionariusza Oswestry Disability Index. Analizę statystyczną przeprowadzono w programie Statistica 13.3 (test t-Studenta, Wilcoxona, korelacja liniowa Pearsona).
Wyniki: Zaproponowany program treningu znacząco zmniejszył poziom bólu (p < 0,05) z 4,80 na 1,35. Ogólna ocena stopnia niepełnosprawności spowodowanej dolegliwościami bólowymi kręgosłupa w kwestionariuszu ODI uległa znaczącej poprawie. Ruchomość kręgosłupa lędźwiowego zmieniła się istotnie (p < 0,05) w każdej z badanych płaszczyzn. Stwierdzono istotne zmniejszenie wartości kąta przodopochylenia miednicy w pozycji neutralnej u badanych.
Wnioski: Zaproponowany trening funkcjonalny przyczynił się do zmniejszenia poziomu odczuwanego bólu, poprawy zakresów ruchomości kręgosłupa i zmniejszenia stopnia przodopochylenia miednicy. Otrzymane rezultaty dowodzą o skuteczności wykorzystania treningu funkcjonalnego jako formy terapii w leczeniu i prewencji dolegliwości bólowych odcinka lędźwiowego kręgosłupa oraz poprawy jakości życia badanych.
Penerapan Formulasi Strategi Daycare Islami: Studi Kasus Daycare “X” Surabaya 2023
Authors: Sumardianto Erdin
Published: March 2024

Artikel ini membahas tentang penerapan formulasi strategi pada lembaga daycare Islami sebagai organisasi dakwah. Studi ini dilatarbelakangi minimnya kajian formulasi strategi pada organisasi dakwah, sehingga penting untuk mengembangkan gagasan penerapan formulasi strategi pada organisasi dakwah untuk menghasilkan konsep yang genuine dan kompatibel. Daycare “X” Surabaya adalah daycare Islami yang sedang merumuskan strategi untuk mencapai target di tahun 2023. Hal tersebut mendorong studi ini untuk melakukan eksperimentasi penerapan formulasi strategi berbasis disiplin ilmu manajemen strategis pada sebuah lembaga penitipan anak (daycare) berbasis nilai-nilai Islam. Studi ini bertujuan untuk menerapkan framework formulasi strategi sebagai alat untuk merumuskan strategi di Daycare “X” Surabaya. Menggunakan pendekatan studi lapangan (field research) dengan metode kualitatif rasionalistik. Analisis yang diterapkan melibatkan penggabungan secara induktif dari faktor-faktor yang terungkap dalam data deskriptif lingkungan, dengan penekanan pada hubungan logis di antaranya, dengan tujuan mengembangkan solusi strategis. Strategi yang dihasilkan adalah optimalisasi produk pengasuhan dan pendidikan daycare, peningkatan kualitas SDM pengasuh dan delegasi kepemimpinan yang efektif, penegakan SOP pengasuhan, dan peningkatan kompensasi SDM.
Implementasi Case Based Reasoning untuk Mendiagnosa Penyakit Ibu Hamil
Authors: Yanto Robi , Mawartika Yayang Eluis Bali , Amalia Veradilla
Published: March 2024

Kehamilan merupakan masa yang rentan terhadap berbagai macam jenis penyakit. Mulai dari penyakit yang memiliki gejala yang ringan sampai dengan mematikan. Angka Kematian Ibu (AKI) di Kota Lubuklinggau masih jauh dibawah target nasional yaitu sebesar 226 per 100.000. Angka Kematian Ibu (AKI) ini akan terus bertambah jika kurangnya informasi pengetahuan atau rasa aware ibu hamil terhadap gejala-gejala penyakit selama kehamilan. Salah satu alasan utama kurangnya pengetahuan mengenai kehamilan adalah terkait biaya konsultasi yang mahal. Sehingga tidak jarang ibu hamil enggan untuk berkonsultasi dengan tenaga kesehatan seperti dokter atau bidan. Maka dari itu dengan memanfaatkan teknologi sistem pakar diharapkan mampu membantu ibu hamil untuk memperoleh informasi dan pengetahuan mengenai gejala-gejala penyakit ibu hamil sehingga dapat dilakukan upaya pencegahan sejak dini. Sistem pakar diterapkan dengan mengimplementasikan metode Case Based Reasoning (CBR). Metode Case Based Reasoning (CBR) ini melakukan pendekatan antara kasus baru dengan kasus lama. Berdasarkan pengetahuan dari kasus lama jenis penyakit ibu hamil ada 7 yaitu Hyperemesis Gravidarium TK I, Hyperemesis Gravidarium TK II, Hyperemesis TK III, Ptyalismus, Pre Eklampsia Ringan, Pre Eklampsia Berat, dan Eklampsia. Berdasarkan perhitungan kedekatan antara kasus baru dengan kasus lama diperoleh nilai kedekatan sebesar 70%, hal ini membuktikan bahwa metode Case Based Reasoning (CBR) mampu mendiagnosa penyakit ibu hamil dengan baik.