DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE
The Journal is a publication specializing in the field of digital economy and information technologies. Raqamli transformatsiya va sun’iy intellekt ilmiy jurnali
TIBBIY MA’LUMOTLARNI TAHLIL QILISHNING INNOVATSION ALGORITMLARI ORQALI INSULTNI ERTA ANIQLASH
Ushbu maqolada ko‘p tipli ma’lumotlar — nominal va qiymatli belgilardan tashkil topgan o‘quv tanlanmalarni tahlil qilishda Fisher mezoniga asoslangan informativ belgilarning tanlanishi masalasi yoritiladi. Ma’lumotlarning turlicha tabiati tahlil jarayonini murakkablashtirishi sababli, sinflararo farqlanish va sinflar ichidagi o‘xshashlik darajasini aniqlash imkonini beruvchi funksional mezonlardan foydalanish muhim ahamiyatga ega. Shu nuqtai nazardan Fisher mezoni eng samarali yondashuvlardan biri sifatida ko‘rib chiqilib, optimal informativ belgilarning aniqlanishi bo‘yicha ikki bosqichli algoritm taklif etiladi. Birinchi bosqichda qiymatli va nominal belgilarga asoslangan optimizatsiya masalasi yordamida informativ vektorlar tanlanadi, ikkinchi bosqichda esa sinf obyektlarining o‘zaro o‘xshashlik darajasi hisoblanib, optimal kombinatsiya aniqlanadi. Taklif etilgan usul turli tipdagi ma’lumotlar fazosida samarali natijalar berishi va tahlil jarayonining aniqligini oshirishi bilan ahamiyatlidir.
Copyright (c) 2025 Aktamov Shohruhbek Ulug’bek o’g’li https://creativecommons.org/licenses/by/4.0
INTEGRATIVE MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING FRAMEWORK FOR THE DETECTION AND CLASSIFICATION OF AI-GENERATED TEXTS IN ACADEMIC RESEARCH PUBLICATIONS
The rapid proliferation of large language models (LLMs) has transformed the landscape of academic writing and scientific communication, yet it has also raised serious concerns about the authenticity and integrity of scholarly publications. This study proposes an integrative Machine Learning (ML) and Natural Language Processing (NLP) framework designed to detect and classify AI-generated texts within academic research articles. The framework combines linguistic, semantic, and stylometric features extracted from large, open-source datasets collected from Kaggle and other academic repositories. The analytical pipeline—implemented and validated using Google Colab—integrates both supervised and deep transformer-based models such as Support Vector Machines (SVM), Random Forest, and fine-tuned BERT-derived architectures. Experimental results demonstrate that the ensemble classifier achieves an overall F1-score of 0.94 and exhibits strong generalization when applied to unseen AI-generated texts. The proposed model not only outperforms existing AI-text detectors in cross-domain evaluations but also remains robust against paraphrased and hybrid human-AI compositions. The findings contribute to the development of transparent and reliable tools for preserving academic integrity in the era of generative artificial intelligence.
Copyright (c) 2025 Mukhriddin Mukhiddinov, Kungratov Ilmurod Kuzibay ugli, Mirzarahmatov Shahzodbek Ulugbekovich, Sanakulov Otaniyoz Erjigit ugli https://creativecommons.org/licenses/by/4.0
QISHLOQ XO‘JALIGI MAHSULOTLARINI SAQLASHDA KO‘P BOSQICHLI ADAPTIV BOSHQARUV TIZIMI MODELI VA ALGORITMI
Ushbu maqolada ko‘p bosqichli o‘zgaruvchan parametrli ob’yektlar (KBO‘PO) uchun adaptiv boshqaruv modeli va algoritmi ishlab chiqilgan. Texnologik jarayonlar dekompozitsiya qilinib, ularning modellashtirish va boshqarish imkoniyatlari o‘rganilgan. Har bir boshqaruv bosqichiga mos matematik modellar va optimizatsiya usullari tanlangan. Model parametrlarini real sharoitlarga moslashtirish adaptiv identifikatsiya algoritmlari orqali amalga oshirilgan. Tadqiqot davomida kartoshka, bodring va pomidor mahsulotlarini saqlash jarayonlari bo‘yicha tajribalar o‘tkazilib, ularning asosida moslashuvchan matematik model tuzilgan. Modelning adekvatligi Fisher mezoni bilan baholanib, tuzatishlar kiritilgan. Tadqiqot natijalariga ko‘ra tez buziluvchi qishloq xo‘jaligi mahsulotlari omborlarida mikroiqlimni samarali boshqarish bo‘yicha amaliy tavsiyalar ishlab chiqilgan.
Copyright (c) 2025 Pirova Rashida Qudratovna https://creativecommons.org/licenses/by/4.0
YEYILISH DINAMIKASINI TADQIQ ETISHDA EMPERIK TENGLAMALARNI KELTIRIB CHIQARISHDA MAHSUS DASTURLARDAN FOYDALANISHNING ISTIQBOLLARI
Maqolada dala tajriba sinovlaridan olingan ma‘lumotlar asosida o‘qyoysimon panjaning еyilishi uchun emperik tenglamalarni keltirib chiqarilish uchun mahsus dasturdan foydalanish va bu usul bilan tadqiqot ishlari uchun vaqtni tejab, katta hajmda еyilishini o‘rganish tadqiqotlarini olib borish hamda ishonchli natijalar olish mumkinligi kеltirilgan.
Copyright (c) 2025 Kuvandikov Yokub Tursunbayevich, Kabilov Begzod Uktam o‘g‘li https://creativecommons.org/licenses/by/4.0
TURKIY TILLAR GRAMMATIKASINING KOMPYUTERGA YO‘NALTIRILGAN FORMAL MODELLARI TAHLILI
Ushbu maqolada turkiy tillar grammatikasini kompyuterli qayta ishlash uchun formal modellashtirish tamoyillari yoritiladi. Morfologik agglyutinatsiya, erkin affiksatsiya kabi xususiyatlarga ega turkiy tillar uchun grammatik qoidalarni algoritmlashtirishda qo‘llaniladigan kompyuterli modellar: qoidalarga asoslangan grammatikalar (Rule Based Grammars), statistik modellar (Statistical Models), neyron tarmoqlar (Neural Network Models), gibrid NLP (Hybrid NLP) arxitekturalari tahlil qilinadi.
Copyright (c) 2025 Norov Abdisait Muradovich https://creativecommons.org/licenses/by/4.0
DEVELOPMENT OF THE DIGITAL ECONOMY OF UZBEKISTAN: IMPLEMENTATION OF PERSONALIZED MONETIZATION MODELS BASED ON ARTIFICIAL INTELLIGENCE AS A TOOL FOR INCREASING REVENUE FOR LOCAL VIDEO GAME STUDIOS
This article examines the implementation of a personalized AI-based monetization system in the Uzbek gaming industry. Particular attention is paid to recommendation systems as a tool for increasing revenue for local studios and developing the digital economy. A review of international practices and their potential for adaptation to the local context is provided, along with proposals for integrating AI technologies into game development processes. Using analytical and survey methods, this study serves as a foundation for subsequent applied research and practical recommendations.
Copyright (c) 2025 Shvets Stanislav Fedorovich https://creativecommons.org/licenses/by/4.0
MODAL GRAPH TRANSFORMER FOR GROUP ENGAGEMENT IN ONLINE MULTIPARTY CONVERSATIONS
Online multiparty conversations such as virtual classrooms, remote collaboration meetings, and live discussions pose unique challenges for understanding group engagement. Traditional models typically rely on isolated participant features or unimodal data, failing to capture the rich, relational dynamics across modalities. In this work, we propose a novel approach that models group engagement as a dynamic, multimodal graph learning problem. Our framework introduces a Multimodal Graph Transformer (MGT) that combines audio-visual fusion with structure-aware graph attention. Each participant is represented as a graph node enriched with fused video and speech embeddings, while edges capture interaction intensity through gaze, turn-taking, and vocal overlap. To preserve graph structure, we incorporate hop-level positional encodings and restrict attention to top-k neighbors for scalable relational modeling. The architecture is designed to capture both localized interaction cues and global group dynamics without requiring pre-defined templates or scripted behavior. By integrating techniques from graph representation learning, multimodal attention, and social signal processing, our method offers a generalizable and theoretically grounded framework for engagement estimation in complex multiparty scenarios.
Copyright (c) 2025 Pirimqulova Zilola Avaz qizi, Hojiyev Sunatullo Nasridin o‘g‘li, Xo‘jamqulov Abdulaziz Xazrat o‘g‘li https://creativecommons.org/licenses/by/4.0
SSRE-ID: KO‘P OBYETLAR KUZATUVLARIDA TO‘LIQ O‘Z-O‘ZINI O‘QITISHGA ASOSLANGAN QAYTA IDENTIFIKATSIYALASH
Ko‘p obyektli kuzatish (Multi-object Tracking, MOT) kompyuter ko‘rishida eng murakkab masalalardan biri bo‘lib qolmoqda. Buning asosiy sabablari — obyektlarning bir-birini to‘sib qo‘yishi, keskin harakat trayektoriyalari, detektorlar keltirib chiqaradigan shovqinlar va vizual muhitning keskin farqlanishidir. So‘nggi yillarda Tracking-by-detection paradigmalarida yangi yutuqlar kuzatildi, ammo ular hanuzgacha, ayniqsa murakkab sahnalarda, obyektlarning identifikatsiya barqarorligini saqlashda muammolarga uchraydi.Ushbu tadqiqotda biz OCSORT algoritmi asosidagi assotsiatsiya mexanizmi bilan integratsiyalangan to‘liq o’z-o’zini o’qitishga asoslangan re-ID modelini taklif qilamiz. Avvalgi yondashuvlardan farqli ravishda, bizning tizim katta hajmdagi belgilangan ReID ma’lumotlar bazasiga tayanmaydi. Taklif etilgan metod MOT17 dagi belgilanmagan o‘quv ketma-ketliklaridan bevosita kuchli identifikatsiya embeddinglarini o‘rganadi. Bu jarayon videoketma-ketlik darajasidagi self-supervised kontrastiv o‘qitish orqali amalga oshirilib, vizual belgilar to‘silish, yoritilishning o‘zgarishi va pozalardagi farqlar mavjud bo‘lgan holatlarda ham barqaror bo‘lib qoladi.Bundan tashqari, biz geometrik IoU ko‘rsatkichlari va ko‘rinish o‘xshashligini birlashtiruvchi gibrid assotsiatsiya strategiyasini ishlab chiqdik. Bu yondashuv faqat harakat signallariga tayanuvchi kuzatuv tizimi(tracker)larning cheklovlarini bartaraf etishga imkon beradi. MOT17 ning barcha 21 ta ketma-ketligida o‘tkazilgan keng qamrovli tajribalar shuni ko‘rsatadiki, bizning tizim identifikatsiya izchilligida sezilarli yaxshilanishga erishadi. Bu ko‘rsatkichlar bir nechta mavjud supervised bazaviy modellardan yuqori natija beradi. Kod:https://github.com/zilolapirimqulova/SSL_MOT
COMPARATIVE ANALYSIS OF PHYSICAL DEVELOPMENT IN CHILDREN ENGAGED IN SPORTS AND PHYSICAL EDUCATION
This study explores the functional characteristics of the cardiovascular and pulmonary systems in children engaged in physical education and sports. It examines how different types of physical training influence heart rate, blood pressure, oxygen uptake, lung capacity, and ECG indicators. The research highlights physiological adaptations resulting from endurance, strength, and control group, providing insights into optimizing training programs and early diagnosis of potential cardiovascular and pulmonary conditions. Recommendations include regular ECG and spirometry screenings. The findings suggest that early engagement in structured physical activity significantly improves cardiovascular efficiency, pulmonary function and overall health
Copyright (c) 2025 Usmankhodjaeva Adibakhon Amirsaidovna, Rakhmatova Fotima Utkirovna https://creativecommons.org/licenses/by/4.0
TARMOQ MA’LUMOTLARIGA INTELLEKTUAL ISHLOV BERISH MODELLARI VA USULLARI
Ushbu ishda tarmoq ma’lumotlariga intellektual ishlov berishning zamonaviy modellari va usullari tahlil qilingan. Tarmoq ma’lumotlarining hajmi va murakkabligi ortib borayotgani sababli, ularni samarali tahlil qilish va qayta ishlash uchun sun’iy intellekt, mashinali o‘qitish hamda ma’lumotlar mayning (data mining) texnologiyalaridan foydalanish zarurligi asoslab berilgan. Tadqiqotda tarmoq ma’lumotlarining tuzilishi, ularning turlari (ijtimoiy tarmoqlar, kompyuter tarmoqlari, sensor tarmoqlari va boshqalar) hamda ma’lumot oqimlari bilan bog‘liq muammolar yoritilgan. Shuningdek, intellektual ishlov berishda qo‘llaniladigan asosiy usullar — klassifikatsiya, klasterlash, prognozlash, anomaliyalarni aniqlash va graf analizi usullarining afzalliklari va qo‘llanilish sohalari keltirilgan. Ishda shuningdek, neyron tarmoqlar, graf neyron tarmoqlari (GNN), konvolyutsion va rekurrent modellardan foydalanish imkoniyatlari hamda ularning tarmoq ma’lumotlari tahlilidagi samaradorligi tahlil qilingan. Natijada, intellektual ishlov berish usullari orqali tarmoq ma’lumotlaridan qimmatli ma’lumotlarni avtomatik tarzda ajratib olish, xavfsizlikni ta’minlash va boshqaruv qarorlarini qabul qilishni takomillashtirish mumkinligi ko‘rsatilgan.
Copyright (c) 2025 Mo‘minov Bahodir Boltayevich, Husanov Sherzod Abdimonnonovich https://creativecommons.org/licenses/by/4.0
O‘ZBEK TILIDAGI GAPLARNI PERIFRAZ QILISH AXBOROT TIZIMINING FUNKSIONAL JARAYONLARINI LOYIHALASHTIRISH
Hozirgi kunda biznes-jarayonlarni modellashtirish metodologiyalari va vositalari bir vaqtning o‘zida ilmiy tadqiqot yo‘nalishi va dasturiy ta’minot (DT) bozorining rivojlanayotgan sektoriga aylangan. Ushbu usullar axborot tizimlarining zaif tomonlarini aniqlash va ularni bartaraf etish uchun zarur choralarni taklif qilish uchun ishlatilishi mumkin. Ushbu maqolada o‘zbek tilida gaplarni perefraz qiluvchi axborot tizimining biznes-jarayonlari BPMN metadologiyasi yordamida shakllantirildi. Semantik analizator axborot tizimining umumiy biznes-jarayonidagi har bir jarayonda alohida to‘xtalib o‘tilgan. Tabiiy tildagi matnlarni perefraz qilishda foydalaniladigan yondashuvlar ko‘rib chiqilgan.
Copyright (c) 2025 Axmedova Xusniya Xusanovna https://creativecommons.org/licenses/by/4.0
KO‘P FAZALI SUYUQLIKLARNI GIDRAVLIK TRANSPORTI UCHUN OQUVCHANLIKNI BAHOLASHNING YANGI USULI
Sanoat ishlab chiqarish jarayonida hosil bo‘ladigan chiqindilarni qayta ishlash, tashish va utilizatsiya qilish masalasi bugungi kunda eng dolzarb muammolardan biri hisoblanadi. Ko’pgina yirik korxonalarda hosil bo‘ladigan chiqindilarni samarali boshqarish ishlab chiqarishning barqarorligi, atrof-muhitni muhofaza qilish hamda iqtisodiy samaradorlik bilan bevosita bog‘liqdir. Ushbu chiqindilar ko‘pincha yuqori konsentratsiyali pulpa shaklida bo‘lib, ularning oquvchanlik xossalari tashish jarayonining samaradorligiga va energiya sarfiga katta ta’sir ko‘rsatadi.Ushbu maqolada suv miqdori kamaytirilganda sanoat chiqindisini tashish masalasi va yaroqlilik muddatiga qanday tasir ko’rsatishi o’rganilgan.
sanoat chiqindilarini utilizatsiya qilish
Copyright (c) 2025 Mirzoyev Akmal Ahadovich, Ahmadov Ilhom Aktam o’g’li, Ahmadova E’zoza Fazliddin qizi, Axmedova Dilnoza Aktam qizi https://creativecommons.org/licenses/by/4.0
COMPARISON OF THE EXACT AND ASYMPTOTIC SOLUTIONS TO THE PROBLEM OF OSCILLATORY FLOW OF A VISCOUS FLUID IN A CYLINDRICAL PIPE
This article explores the problems of oscillatory flow of a viscous incompressible fluid in a cylindrical pipe with a given harmonic oscillation are solvedaverage velocity across the pipe cross-sectionThe transfer function and amplitude-phase frequency characteristics were determined. Using these functions, the influence of oscillation frequency on the ratio of shear stress to the cross-sectional average velocity was determined. By comparing the exact solution of the problem with the asymptotic solution, new asymptotic formulas are proposed that are of great importance in the study of the oscillatory flow of a viscoelastic fluid in a cylindrical pipe.
Copyright (c) 2025 Kuralbay Navruzov, Akmal Mirzoev, Ilhom Ahmadov https://creativecommons.org/licenses/by/4.0
USING ARTIFICIAL INTELLIGENCE TO CALCULATE SOLAR COLLECTOR PARAMETERS
This study explores the use of Artificial Intelligence to predict and optimize key parameters of solar collectors, such as thermal efficiency and heat transfer rate. Traditional analytical methods are often limited by nonlinear environmental factors, while AI techniques like Artificial Neural Networks and Genetic Algorithms offer more accurate and adaptive modeling. Results show that AI-based models provide high prediction accuracy and can effectively optimize collector performance under varying conditions, improving the overall efficiency of solar energy systems.
Copyright (c) 2025 Ibrokhimov Abdulfatto Raximjon ugli, Isakov Botirjon Umarovich, Muminov Bahodir Boltayevich https://creativecommons.org/licenses/by/4.0
KORXONA SAVDO MA’LUMOTLARINI INTELLEKTUAL TAHLIL QILISH UCHUN MA’LUMOTLARNI TO‘PLASH, QAYTA ISHLASH VA DASTLABKI ISHLOV BERISH
Ushbu maqolada korxonalar faoliyatida savdo ma’lumotlarini intellektual tahlil qilishning nazariy va amaliy jihatlari yoritilgan. Tadqiqotda ma’lumotlar bazasini tashkil etish va modellashtirishning zamonaviy yondashuvlari, shu jumladan ETL (Extract, Transform, Load) jarayonlari, ma’lumotlar ombori (Data Warehouse) arxitekturasi hamda OLAP texnologiyalarining qo‘llanilishi tahlil qilingan. Shuningdek, maqolada Mean usuli asosida savdo ma’lumotlarini statistik qayta ishlash va Z-Score normallashtirish natijalari keltirilgan. Ma’lumotlar tahlili korxona savdo samaradorligini oshirish, resurslardan oqilona foydalanish va boshqaruv qarorlarini ilmiy asosda qabul qilish imkonini beruvchi muhim bosqich sifatida baholangan. Tadqiqot natijalari shuni ko‘rsatadiki, ma’lumotlar omborini to‘g‘ri modellashtirish va intellektual tahlil metodlarini qo‘llash orqali korxonalarda Business Intelligence (BI) tizimlarini samarali yo‘lga qo‘yish mumkin.
Copyright (c) 2025 Raximov Nodir Odilovich, Baydullayev Ruslan Tuylibayevich, Baydullayeva Dildora Tuylibayevna https://creativecommons.org/licenses/by/4.0
GLOBALASHUV JARAYONIDA IQTISODIY STATISTIK TAHLILLASHDA SUN'IY INTELLEKTNING TUTGAN O’RNI VA AHAMIYATI
Ushbu maqola sun'iy intellektning iqtisodiy statistika sohasidagi transformatsiya jarayonini o'rganadi, mashinani o'rganish (machine learning), katta ma'lumotlar tahlili, ma'lumotlarni to'plash, qayta ishlash, tahlil qilish va prognozlashning an'anaviy yondashuvlarini qanday qayta shakllantirayotganini yoritilgan. Tadqiqot su’niy intelektning keng va xilma-xil ma'lumotlar to'plamini boshqarish, iqtisodiy bashoratlarning aniqligini oshirish , siyosatchilar va biznes egalari uchun dalillarga asoslangan qarorlar qabul qilishga yordam beradi. Bundan tashqari, sun'iy intellekt statistik natijalarning vizualizatsiyasi va aloqasini kuchaytiradi, bu esa o’z navbatida murakkab iqtisodiy tushunchalarni kengroq auditoriya uchun qulayroq qiladi. Maqolada, shuningdek, ma'lumotlarning maxfiyligi bilan bog'liq muammolar, algoritmik bog’liqlik, shaffof va izohlanadigan modellarga bo'lgan ehtiyoj kabi muhim muammolar ko'rib chiqiladi. Ushbu to’siqlarga qaramay, maqoladasu’niy intellekt iqtisodiy statistikani rivojlantirish uchun ulkan salohiyatni taqdim etadi, degan xulosaga keladi, bu raqamli iqtisodiyot davrida o'z vaqtida, ishonchli va dinamik iqtisodiy monitoringga yo'l ochib beradi.
Copyright (c) 2025 Hayitbayev Husniddin Farhodovich https://creativecommons.org/licenses/by/4.0
NARXLARNI MONOPOLIYAGA QARSHI TARTIBGA SOLISHNING BOZOR INSTITUTSIONALIZATSIYASINING MAKROIQTISODIY USTUVORLIKLARI
Maqolada monopoliyaga qarshi davlat tomonidan narxlarni tartibga solishning bozor institutsionalizatsiyasining makroiqtisodiy ustuvorliklari o‘rganilgan. Monopoliyaga qarshi tartibga solishning makroiqtisodiy ustunvorliklarining tahlili amalga oshirilgan. Narxlarni monopoliyaga qarshi tartibga solish mexanizmini takomillashtirish yo‘llari bo‘yicha xulosa va takliflar ishlab chiqilgan.
Copyright (c) 2025 Mingboyev Asqar Qandaharovich https://creativecommons.org/licenses/by/4.0
JAHON VALYUTA BOZORINI SUN’IY INTELLEKT VOSITALARI BILAN BOSHQARISH VA TAHLIL QILISH
Jahon valyuta bozori – bu global iqtisodiyotning yuragi hisoblanadi. Bu bozorda kunu tun faoliyat yuritib, har kuni trillionlab dollar qiymatdagi valyutalar almashinuvi amalga oshiriladi. Bozorning murakkabligi va o‘zgaruvchanligini tahlil qilish va boshqarish juda murakkab. Shu sababli, so‘nggi yillarda sun’iy intellekt (SI) vositalari va ularning algoritmik tahlil imkoniyatlari valyuta bozorini boshqarishda yangi davrni boshlab berdi. Ushbu maqolada jahondagi valyuta bozorini SI yordamida boshqarish va tahlil qilish imkoniyatlari, afzalliklari, amaliy qo‘llanilishi hamda uni qo’llash jarayonidagi yuzaga keladigan qiyinchiliklar haqida bayon etilgan.
OBJECT DETECTION SYSTEMS FOR DETERMINING CAR MODELS AND BODY COLOR: COMPREHENSIVE COMPARATIVE ANALYSIS AND PRACTICAL INTEGRATION BASED ON REAL IMAGES UNDER UZBEKISTAN CONDITIONS
This paper presents a practical solution for real-time recognition of vehicle model and body color on real-world CCTV streams in Uzbekistan. The dataset was annotated in CVAT and cleaned; to ensure fair evaluation, we applied a camera-wise train/val/test split (preventing cross-camera leakage). On the same dataset, we fine-tuned YOLOv8-l, DETR (ResNet-101), and CenterNet, and analyzed the quality–speed trade-off from a deployment perspective. Using detector-produced bounding boxes as ROIs, we integrated a fast color module into the pipeline based on a combined LAB+HSV approach. For inference threshold selection, we employed a practical method grounded in the F1–Confidence curve. The system operates robustly with multi-camera RTSP streams, supports auto-reconnect and resource monitoring (CPU/RAM/IO and, when available, GPU), and is ready for ONNX/TensorRT export. The results demonstrate practical applicability in traffic monitoring, security, and intelligent video surveillance systems.
Copyright (c) 2025 Davronov Rifkat Rakhimovich, Misirov Farhod Abdulla ugli https://creativecommons.org/licenses/by/4.0
OLORA+: A HYBRID APPROACH TO LOW-RANK ADAPTATION
This paper introduces and analyzes OLoRA+, a novel parameter-efficient fine-tuning method that enhances Low-Rank Adaptation (LoRA) by combining the orthonormal initialization of OLoRA with the differential learning rate optimization of LoRA+. The study compared the performance of OLoRA+ against the standard OLoRA baseline on the TinyLlama-1.1B-Chat-v1.0 model. Using a subset of the alpaca dataset, a collection of 52K instruction-following demonstrations, with 1000 samples for training and 500 for testing, model performance was assessed using evaluation loss, BLEU, and ROUGE metrics. The obtained results show that OLoRA+ consistently outperforms the OLoRA baseline across all considered metrics. Additionally, the study reveals that OLoRA+ is effective with learning rate ratios both greater and less than one, uncovering a novel trade-off between "Refinement" and "Exploration" learning strategies. This confirms OLoRA+'s potential as a more versatile and powerful approach for LLM adaptation under limited resource conditions.
Copyright (c) 2025 Davronov Rifkat Rakhimovich, Kushmuratov Samariddin Ibodulla ugli https://creativecommons.org/licenses/by/4.0
NUMERICAL MODELING OF THE PROCESS OF TRANSFER AND DIFFUSION OF AEROSOLIC PARTICLES IN THE ATMOSPHERE
The work developed a mathematical model and a numerical algorithm for monitoring and forecasting the process of the spread of harmful substances in the atmosphere, taking into account the change in the movement of particles in the atmosphere. A detailed analysis of the developed mathematical models and numerical algorithms related to the processes of transport and diffusion of harmful substances in the atmosphere was carried out.
Copyright (c) 2025 Shafiev Tursun Rustamovich, Nazarov Shakhzod Erkinovich, Bobozhonova Madina Abduakhat qizi https://creativecommons.org/licenses/by/4.0
O‘PKA KT (KOMPYUTER TOMOGRAFIYASI) TASVIRLARIDA SUN’IY INTELLEKT ASOSIDA SEGMENTATSIYA ALGORITMLARINI ISHLAB CHIQISH
Ushbu maqolada O‘pka kompyuter tomografiyasi (KT) tasvirlarida sun’iy intellekt texnologiyalari asosidagi segmentatsiya algoritmini ishlab chiqarishni ishlab chiqish masalasini ko'rib chiqamiz. O‘pka to‘g’irlash chegaralarini aniqlashtirish, Patologik o‘zgarishlarni erta bosqichda aniqlash va diagnostika jarayonini aniqligini oshirish. Maqolada chuqur o‘rganish (Deep Learning) usullaridan biri - U-Net konvolyutsion neyron manbasi asosida ishlab chiqarilgan va o'qitilgan. Maqolada LIDC-IDRI ochiq ma’lumotlar to‘plamiga KT tasvirlaridan foydalanildi. Modellashtirish IoU (Intersection over Union) va Dice koeffitsienti mezonlari yordamida baholandi. Natijalar ko‘rsatgichlari, taklif qilingan model O‘pka to‘qimasi segmentatsiyasini yuqori aniqlik bilan va kasallik o‘choqlarini avtomatik aniqlash jarayonini soddalashtirish va tibbiy tasvirlarni tahlil qilishda inson omillarini hamda klinik diagnostika tizimlarida amaliy qo‘llab-quvvatlash mumkin.
Copyright (c) 2025 Saparov Saidqul Xo‘jamurotovich, Adilova Dinora Ablaqul qizi https://creativecommons.org/licenses/by/4.0
DEEP LEARNING APPROACHES IN CLASSIFICATION OF ECG SIGNALS FOR CARDIOVASCULAR DISEASE DETECTION
Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, emphasizing the critical need for early detection and accurate diagnosis. Electrocardiography (ECG) provides a noninvasive and cost-effective means of assessing cardiac health; however, manual interpretation is time-consuming and prone to human error. Recent advances in deep learning have shown great promise in automating ECG signal analysis by leveraging powerful feature extraction and classification capabilities. This study investigates multiple deep learning architectures, including convolutional neural networks (CNNs), hybrid CNN–LSTM models, and Transformer-based approaches, applied to benchmark ECG datasets. A comprehensive workflow is developed, consisting of data acquisition, preprocessing, beat segmentation, deep learning-based feature extraction, classification, and performance evaluation. Comparative experiments demonstrate that while CNNs effectively capture morphological features, the CNN–LSTM hybrid yields enhanced performance by modeling temporal dependencies. The Transformer-based model achieves the highest accuracy, sensitivity, and specificity, highlighting its ability to capture long-range dependencies in ECG signals. The results confirm the potential of advanced deep learning frameworks in supporting reliable, automated CVD detection. Future directions include cross-dataset validation, multimodal integration, and optimization for deployment on wearable and embedded platforms.
Copyright (c) 2025 Dushanov Begmamat Berdimurodovich, Mamatov Narzillo Solidjonovich https://creativecommons.org/licenses/by/4.0
INNOVATSION RAQAMLI MUHITDA SAVDO KORXONALARINING AXBOROT TIZIMINI RIVOJLANTIRISH YO‘LLARI
Ushbu maqolada innovatsion raqamli muhitda savdo korxonalarining axborot tizimini rivojlantirish yo‘llari masalasi keng qamrovda o‘rganiladi. Tadqiqotda savdo korxonalarida raqamli texnologiyalarni joriy etish, ma’lumotlar bazasi va axborot oqimlarini samarali boshqarish, biznes jarayonlarni avtomatlashtirish hamda raqobatbardoshlikni oshirish imkoniyatlari tahlil qilinadi. Milliy va xorijiy tajribalar asosida savdo korxonalarida axborot tizimining iqtisodiy samaradorligi, uning boshqaruv qarorlarini qabul qilishdagi roli va innovatsion yechimlari ko‘rib chiqiladi. Natijalarga ko‘ra, kompleks model savdo korxonalarining faoliyatini raqamlashtirish, xarajatlarni kamaytirish va iste’molchilarga xizmat ko‘rsatish sifatini oshirishda muhim ahamiyat kasb etishi aniqlangan. Maqola yakunida O‘zbekistonda savdo korxonalari uchun axborot tizimini rivojlantirishning ustuvor yo‘nalishlari bo‘yicha takliflar ishlab chiqilgan.
Copyright (c) 2025 Boltayev Alisher Ataboy o‘g‘li https://creativecommons.org/licenses/by/4.0
G‘OVAK MUHITLARDA IKKI QATLAMLI GAZ FILTRATSIYA JARAYONIDA BIR O’LCHOVLI MASALANI SONLI MODELLASHTIRISH
Maqolada mahsuldor qatlamlarda gaz qazib olishni ko’paytirish maqsadida ikki qatlamli o‘zaro dinamik bog‘langan gaz filtratsiya jarayonini matematik modellashtirish va hisoblash algoritmi keltirilgan. Modellashtirish jarayonida qatlam bosimi hamda o‘tkazuvchanlik koeffitsientlarining fazoviy va vaqtga bog‘liq o‘zgaruvchanligi inobatga olingan. Chegaraviy masalani sonli modellashtirishda chekli-ayirmalar usuli, kvazichiziqli usul va Kramer usullaridan foydalanilgan. Shuningdek, samarali sonli usullar va algoritmlar asosida dasturiy ta’minot ishlab chiqilgan.
Copyright (c) 2025 Eshqarayeva Narxol G‘uzarovna, Xujamurotova Mashxura G‘ayrat qizi https://creativecommons.org/licenses/by/4.0
MODERN APPROACHES TO FORECASTING FOR BREAST CANCER DIAGNOSIS BASED ON DATA MINING
The article examines modern approaches to prediction and classification in breast cancer diagnosis based on data mining techniques. It describes the most commonly used datasets and modalities, stages of preprocessing and feature extraction, classical and deep learning models, validation and evaluation methods, issues of interpretability, clinical validation, regulatory considerations, and ethical aspects. Recommendations for practical implementation and directions for further research are provided.
Copyright (c) 2025 Mukhamedieva Dildora Kabilovna, Doshanova Malika Yuldashovna, Shaazizova Madina Eldarovna https://creativecommons.org/licenses/by/4.0
KVANT HISOBLASH ASOSIDA FAKTORIZATSIYA MASALASINI YECHISHDA SHOR ALGORITMIDAN FOYDALANISH
Mazkur maqolada kvant hisoblash nazariyasining Piter Shor tomonidan 1994-yilda ishlab chiqilgan Shor algoritmi tahlil qilinadi. Ushbu algoritm butun sonlarni faktorlash masalasini polinomial vaqt ichida yechimini topish imkonini beruvchi kvant yondashuvni taqdim etadi. Maqolada Shor algoritmining kvant va klassik qismlari batafsil yoritilgan, kvant Furye transformatsiyasi yordamida funksiyaning davrini topish jarayoni va undan foydalanib faktorizatsiyani amalga oshirish bosqichlari tushuntirilgan. Asosiy e’tibor algoritmning amaliy qo‘llanilishiga, xususan qishloq xo‘jaligi sohasidagi ma’lumotlarni shifrlash va identifikatsiya qilish jarayonlarida foydalanish imkoniyatlariga qaratilgan. Maqolada Shor algoritmi yordamida shifrlangan urug‘ turlarining kodlari faktorizatsiya qilinib, ularning asl identifikatorlari aniqlanadi. Shu orqali kvant algoritmlarni agroinformatika, raqamli urug‘ identifikatsiyasi, va ma’lumotlarni xavfsiz saqlash tizimlarida qo‘llash istiqbollari asoslab berilgan.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
PROCESSING ALGORITHM INCORPORATING COMPLEX DEPENDENCIES IN INPUT DATA
In this article, an algorithm (QKV) was developed that takes into account many factors in predicting the level of cardiovascular diseases, in particular, taking into account the relationships between factors. With the help of machine learning, the accuracy of the model has been increased, taking into account the complex interconnection of the data included in the MLP model. In addition, in the process of training the dataset processed through the QKV algorithm to the MLP model, it was possible to quickly achieve the minimum value of the Loss function and find the optimal weight coefficient.
Copyright (c) 2025 Saidov A.D. https://creativecommons.org/licenses/by/4.0
MODEL-BASED ASSESSMENT OF ENERGY AND RELIABILITY EFFICIENCY IN WIRELESS SENSOR NODES
Wireless sensor networks (WSN) are increasingly used in various control and management applications, where the efficiency of sensor nodes plays a decisive role in the overall operation of the network. This work presents a model-based assessment approach for assessing the energy efficiency and reliability of wireless sensor nodes. The proposed models analyze the relationship between transmission energy, node operation time, and network reliability under various operating conditions. Simulation-based estimates show how energy constraints and packet loss levels affect the stable operation of sensor nodes. The study compares the effectiveness of several existing energy models and provides recommendations for optimizing the behavior of nodes in energy-restricted environments.
Copyright (c) 2025 Khayrullaev Alisher Fayzulla ugli https://creativecommons.org/licenses/by/4.0
HYBRID AI FOR GASTRIC DIAGNOSTICS: MULTI-MODAL FUSION AND INTERPRETABILITY FOR EARLY ULCER AND CANCER DETECTION
This study investigates the development of hybrid Artificial Intelligence (AI) models for the early and accurate diagnosis of gastric ulcer and gastric cancer. Traditional diagnostic methods such as endoscopy and biopsy, though widely used, face limitations including inter-observer variability, sampling errors, and delays in diagnosis. To address these challenges, two novel hybrid AI architectures are proposed: the Deep Feature-Attention SVM (DFA-SVM) and the Multi-Modal Fuzzy-Fusion Network (M2F2-Net). These models integrate multi-modal data sources, including endoscopic images, histopathology slides, and structured clinical records, while employing attention mechanisms, fuzzy logic, and interpretable AI approaches to enhance diagnostic performance. Experimental evaluation using the conceptual GIMIC-12K dataset demonstrates that M2F2-Net achieves superior performance, particularly in early gastric cancer detection, by significantly reducing false negatives and improving sensitivity. The findings highlight the transformative potential of hybrid AI in improving patient outcomes, optimizing healthcare efficiency, and supporting explainable decision-making in clinical practice.
Copyright (c) 2025 Iskandarova Sayyora Nurmamatovna, Abdurashidova Kamola Turg’unbayevna, Omonov Sanjarbek G‘anisher o’g’li, Sabitova Nazokat Qobuljon qizi https://creativecommons.org/licenses/by/4.0