OJS Tashkent State University of Economics
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554 research outputs found
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GRAFEMA-FONEMA TRANSFORMATSIYASINI KOMPYUTERLI MODELLASHTIRISH
No full textGrafema-fonema o‘rtasidagi bog‘liqlik tilshunoslikning muhim sohalaridan biri hisoblanadi va ayniqsa tilni raqamli qayta ishlash uchun muhimdir. O‘zbek tilida murakkab tovush tizimi mavjud bo‘lib, uning grafema-fonema ifodasini kompyuter lingvistikasi orqali modellashtirish talab etadi. Ushbu tadqiqot o‘zbek tilida grafema-fonema bog‘liqligini, uning tarixiy rivojlanishi va zamonaviy muammolarini o‘rganadi hamda bu bog‘liqlikni transformatsiya qilish uchun qo‘llaniladigan algoritmlar va dasturiy vositalarni ko‘rib chiqadi
SHAHAR INFRATUZILMASIDA TIRBANDLIK MUAMMOSINI MA’LUMOTLAR BAZASI ASOSIDA FRAKTAL MODELLASHTIRISH
No full textUshbu maqolada shahar infratuzilmasida tirbandlik muammolarini hal qilish uchun fraktal modellashtirishning katta ma’lumotlar va ma’lumotlar bazasi texnologiyalari bilan integratsiyasi yoritiladi. Tirbandlik transport tizimlarining murakkabligi va shahar infratuzilmasining noaniq dinamikasi tufayli global muammoga aylangan. Fraktal modellar shahar transport tarmoqlarining murakkab tuzilmalari va ulardagi o‘z-o‘zini takrorlash xususiyatlarini aniqlash imkonini beradi. Maqolada katta ma’lumotlar texnologiyalari yordamida transport oqimlari va yo‘l harakati haqidagi real vaqtli ma’lumotlarni yig‘ish, tahlil qilish va bashorat qilish usullari ko‘rib chiqiladi. Ma’lumotlar bazalari, xususan, NoSQL va SQL tizimlari, fraktal modellarni qo‘llash uchun zarur bo‘lgan katta hajmdagi ma’lumotlarni boshqarish vositasi sifatida tavsiya etiladi. Shuningdek, ma’lumotlarni saqlash, qayta ishlash va transport tizimlarini avtomatlashtirishda ushbu texnologiyalarning ahamiyati yoritilgan. Natijada maqolada shahar transport tizimini optimallashtirish, tirbandlikni kamaytirish va resurslardan samarali foydalanish bo‘yicha innovatsion yechimlar taklif etiladi. Ushbu yondashuv shaharsozlik sohasidagi muammolarni texnologik va ilmiy nuqtai nazardan hal qilish uchun katta salohiyatga ega
ҲОМИЛАНИНГ ПРЕНАТАЛ РИВОЖЛАНИШ ДАВРИДА ОЗИҚЛАНИШ ЖАРАЁНИ ТАҲЛИЛИ
No full textУшбу маколади кўп босқичли ҳомиланинг пренатал ривожланиш даврида ҳар бир триместрга оид мавсумий диетологик озиқланиш жараёнлари таҳлил қилинди. Ҳомиладорлик даврида аёл истеъмол қилаётган оқсил, ёғ, углевод, витамин ва минераллар миқдорлари ҳисоблаб чиқилди. Статистик маълумотларга таянган ҳолда математик моделлари шакллантирилди. Дифференциаллашган-диетологик озиқланиш жараёнини оптималлаштиришга асосланган қарорлар дарахти алгоритми ишлаб чиқилди
QASHQADARYO VILOYATIDA SAFARI TURIZMNI RIVOJLANTIRISH MASALALARI
No full textUshbu maqola Qashqadaryo viloyatida safari turizmini rivojlantirishning tashkiliy iqtisodiy mexanizimlarini tashkil etish maqsadida, yuqori iqtisodiy, ijtimoiy va ekologik naflilik berish imkoniyatini yarata oladigan Safari turizmini shakillantirish modelini ishlab chiqishga qaratilgan
GLOBAL RAQAMLI TRANSFORMATSIYA DAVRIDA SIYOSATCHILAR UCHUN SUN’IY INTELLEKTNING ZARURIY JIHATLARI
No full textUshbu maqola raqamli transformatsiya jarayonida sun’iy intellekt (SI)ning siyosatchilar uchun qanday ahamiyatga ega ekanligini tahlil qiladi. Raqamli texnologiyalarning tez rivojlanishi siyosiy qarorlar qabul qilishda yangi imkoniyatlar va muammolarni keltirib chiqarmoqda. Maqola, SI yordamida ma’lumotlarni tahlil qilish, jamiyat ehtiyojlarini yaxshiroq anglash va strategik rejalashtirish jarayonlarini qanday takomillashtirish mumkinligini ko‘rsatadi. Maqolaning maqsadi, siyosatchilarni sun’iy intellektni samarali va mas’uliyatli ravishda qo‘llashga undash va ularning raqamli transformatsiya jarayonida qanday yangi strategiyalar ishlab chiqishi kerakligini ko‘rsatishdir. Bu, o‘z navbatida, jamiyatning kelajagi va raqamli iqtisodiyotning barqarorligini ta’minlashga xizmat qiladi
THE ROLE OF HUMAN JOURNALISTS IN AN AI-DRIVEN MEDIA LANDSCAPE
No full textAs artificial intelligence (AI) continues to advance, its impact on the journalism industry is becoming increasingly evident. AI-powered tools are being used to automate tasks such as content creation, fact-checking, and distribution. However, while AI can enhance efficiency and productivity, it cannot fully replace the unique contributions of human journalists. Human journalists bring a level of critical thinking, creativity, and empathy that AI cannot replicate. They are able to interpret complex information, identify biases, and provide context to news stories. Additionally, human journalists can develop relationships with sources and build trust with audiences, which is essential for credible and reliable journalism. However, the role of human journalists is evolving in an AI-driven media landscape. Journalists must adapt to new technologies and develop skills such as data analysis, digital storytelling, and social media engagement. They must also be mindful of the ethical implications of using AI and ensure that it is used responsibly and transparently. So, human journalists will continue to play a vital role in the media industry, even as AI becomes more sophisticated. By combining their unique skills with the capabilities of AI, journalists can produce more accurate, informative, and engaging content that serves the public interest
TRAFFIC SIGN RECOGNITION USING DEEP LEARNING ALGORITHMS
No full textThis paper explores the neural network architecture of traffic sign recognition. The YOLO model based on deep learning is used to recognize traffic signs in order to implement safety. In the study, processes such as pre-processing of images, object detection and classification are widely covered. According to the results of the study, the accuracy of traffic sign recognition was increased by 3.9% using the improved neural network model. This method is effective in different weather conditions and is important in preventing traffic accidents
INTEGRATING LARGE LANGUAGE MODELS WITH VISUAL DATA FOR ENHANCED HUMAN-OBJECT INTERACTION DETECTION
No full textIn recent years, the widespread use of visionbased intelligent systems has significantly advanced image and video analysis technologies. One key research area within this field is human activity recognition. Recent studies have primarily concentrated on specific tasks such as human action recognition and human-object interaction detection, employing depth data, 3D skeleton data, image data, and spatiotemporal interest point-based methods. Most of these approaches rely on bounding-box techniques to recognize human-object interactions. However, limited research has been conducted on using language models for this purpose. In this paper, we propose a model that combines language and image data to detect human-object interactions and discuss the challenges and future directions in this domain
A REVIEW FOR DIFFERENT APPROACHES OF TOMATO LEAF DISEASE DETECTION
No full textIn recent years, computer vision researchers are proposing different algorithms for agricultural domain. For example, they are using Machine learning and Deep learning for plant disease identification. This paper discussed some approaches for tomato leaf disease detection. And reviewed different researchers’ works by using different methods in tomato leaf disease identification. In the end of this paper, as a result, it is defined available methods such as strength and some limitations for different conditions
APPLICATION OF THE ALGORITHM FOR ENRICHMENT THE KNOWLEDGE GRAPH WITH NUMERICAL PREDICATES IN DECISION-MAKING SUPPORT SYSTEM
No full textIn this paper, the theoretical and practical principles of creating a knowledge graph by forming a set of rules for expert systems are studied. At the same time, the method of enriching the graph made from the predicates created according to First Order Logic by numerical predicates was studied. as the object of the research, the classification problem of selecting crops for repeated cropping was taken, among which, using the set of real data collected in agriculture, test-experimental work was carried out on the algorithm mentioned above and the results were obtained. All results were presented in table and graph form