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
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
SUN’IY YO‘LDOSH TASVIRLARI VA SUN’IY INTELLEKT YORDAMIDA OROL DENGIZI HUDUDLARINI TADQIQ ETISH: TAJRIBALAR VA ILMIY MUAMMOLAR
Orol dengizi ekologik inqirozining oqibatlarini o‘rganish, uning geografik va ekologik holatini monitoring qilish dolzarb bo‘lgan ilmiy-texnik muammolardan hisoblanadi. Ushbu maqolada Orol dengizi hududlarida hozirgi kunga qadar olib borilgan ilmiy izlanishlar, mavjud muammolar va sun’iy yo‘ldosh tasvirlari hamda sun’iy intellekt (SI) texnologiyalari yordamida tadqiq qilish tahlil qilingan. Xususan, mashinali o‘qitish (MO‘) va chuqur o‘qitish (ChO‘) algoritmlarining tuproq sho‘rlanishi, o‘simlik qoplamining o‘zgarishi hamda suv sathining pasayishini aniqlashdagi roli ko‘rib chiqilgan. Shuningdek, mavjud geoma’lumotlar bazalari, ulardan foydalanish, sun’iy intellekt modellari uchun zarur bo‘lgan ma’lumotlar to‘plamlariga dastkabki ishlov berish usullari tahlil etilgan. Maqola yakunida Orolbo‘yi mintaqasida SI asosida samarali monitoring tizimini yo‘lga qo‘yish uchun taklif va tavsiyalar berilgan.
Copyright (c) 2025 Rashid Nasimov, Nigoraxon Nasimova, Charos Xidirova, Akmalbek Abdusalomov, Zavqiddin Temirov https://creativecommons.org/licenses/by/4.0
SVM ALGORITMI ASOSIDA SUN’IY NUTQNI ANIQLASH VA IDENTIFIKATSIYA QILISHNING INTELLEKTUAL YONDASHUVI
Ushbu maqolada sun’iy nutqni aniqlash va uni identifikatsiya qilish uchun SVM (Support Vector Machine) algoritmiga asoslangan yondashuv taklif etiladi. Taklif etilgan pipeline 8 kHz chastotada yozilgan nutq yozuvlarini qayta ishlashga moslashtirilgan bo‘lib, akustik xususiyatlar sifatida quyidagi parametrlar tanlangan: MFCC₁–MFCC₁₃, F₀, H, Eₗₒg, ZCR, ΔMFCC, Jitter va HNR. Ushbu parametrlar nutq signalining kepstral, fonatsion va prosodik xususiyatlarini qamrab olib, model uchun informativ vakillikni ta’minlaydi. Xususiyatlar freym darajasida ajratilib, utterance (gap) darajasida statistik agregatsiyalar (o‘rtacha qiymat, dispersiya, percentillar, diapazon) yordamida fiks uzunlikdagi vektorlarga aylantiriladi. Olingan vektorlar z-score normalizatsiyasi orqali standartlashtiriladi. Klassifikatsiya bosqichida esa RBF yadrosiga ega SVM modeli qo‘llaniladi. Model gipermetrlari nested k-fold cross-validation yordamida optimallashtiriladi, sinflar o‘rtasidagi nomutanosiblik esa sinf og‘irliklari orqali balanslanadi. Baholash jarayonida Accuracy, Macro-F1, ROC-AUC hamda anti-spoofing vazifasiga xos EER/HTER mezonlari qo‘llanilgan. Shuningdek, ablyatsiya tahlili(modelning qaysi qismi yoki qaysi xususiyat(lar) haqiqatan foyda berayotganini aniqlash uchun u(lar)ni tizimli ravishda olib tashlab (yoki alohida qo‘shib) ko‘rsatkichlar qanday o‘zgarishini solishtirish usuli) orqali har bir parametrning model natijalariga qo‘shgan hissasi alohida o‘rganilgan. Eksperimental natijalar shuni ko‘rsatdiki, MFCC parametrlarini ΔMFCC, Jitter va HNR kabi qo‘shimcha xususiyatlar bilan boyitish modelning diskriminativ qobiliyatini sezilarli darajada oshiradi. Taklif etilgan yondashuv yengil, barqaror va real vaqtli tizimlarga integratsiyaga tayyor bo‘lib, sun’iy nutqni aniqlashda yuqori aniqlikni ta’minlaydi.
Copyright (c) 2025 Raxmatov Furqat Abdurazzoqovich, Abdirazakov Faxriddin Bekpulatovich, Nasirov Sulton Uali o‘g‘li, Javliyev Shahzod Alisher o‘g‘li, Sayfullaeva Nargiza Akromovna https://creativecommons.org/licenses/by/4.0
POST-QUANTUM CRYPTOGRAPHY AND ITS MATHEMATICAL FOUNDATIONS
The rapid advancement of quantum computing technologies has posed a significant challenge to the security and reliability of classical cryptographic systems, particularly those based on integer factorization, discrete logarithms, and elliptic curve cryptography. Post-quantum cryptography (PQC) has therefore emerged as one of the most crucial research directions in modern information security, focusing on the design and analysis of cryptographic algorithms that remain secure even in the presence of powerful quantum adversaries. This article provides a comprehensive overview of post-quantum cryptography and its mathematical foundations, highlighting the theoretical underpinnings, algorithmic approaches, and current trends in this evolving field. The discussion begins with an examination of the fundamental mathematical problems upon which post-quantum cryptographic constructions are based, including lattice-based problems, error-correcting codes, multivariate polynomial equations, isogenies of elliptic curves, and hash-based cryptographic techniques. These problems are believed to be resistant to both classical and quantum attacks, making them suitable candidates for the next generation of secure communication protocols. The article also explores the complexity assumptions, reductions, and hardness proofs that establish the security of post-quantum schemes, thereby emphasizing the importance of rigorous mathematical reasoning in cryptographic design. Furthermore, the article analyzes the advantages and limitations of different PQC families, considering aspects such as key sizes, computational efficiency, implementation challenges, and resistance to side-channel attacks. Special attention is given to the ongoing standardization process led by the National Institute of Standards and Technology (NIST), which aims to select algorithms for widespread adoption across governmental and commercial applications. The paper also reflects on the future prospects of post-quantum cryptography in the context of global cybersecurity, digital infrastructure, and secure data transmission in the post-quantum era. The annotation highlights that the significance of post-quantum cryptography extends far beyond academic interest, as it directly addresses the urgent need for cryptographic resilience in finance, healthcare, defense, e-governance, and critical digital services. The mathematical foundations outlined in this article provide a bridge between abstract theory and practical cryptographic systems, ensuring that security in the digital age can withstand the transformative impact of quantum technologies.
mathematical foundations of cryptography
Copyright (c) 2025 Mustafoyev Azamat Botir o‘g‘li, Mavlonov Alisher Bagbekovich https://creativecommons.org/licenses/by/4.0
IJTIMOIY TARMOQLARDA KONTENT ASOSIDAGI MEDIA TA’SIRINI O‘RGANISH: RAQAMLI IZ MA’LUMOTLARINI YIG‘ISHNING API, MA’LUMOT HADYA QILISH VA KUZATISH USULLARI
Ijtimoiy tarmoqlar ta’sirini o‘rganish sohasida aniq kontentning roli yetarlicha tadqiq etilmagan. Bunga qisman ilgari kommunikatsiya fanida ijtimoiy tarmoq kontentiga bevosita kirish imkonini beradigan usullar mavjud emas edi. Raqamli iz ma’lumotlari (Digital Trace Data, DTD) ijtimoiy tarmoqlardan foydalanish jarayonida yaratilgan matnli va audiovizual kontentni yoritib berib, avval imkoni bo‘lmagan darajada alohida foydalanuvchi darajasida kontentdan foydalanishni tahlil qilish imkonini yaratadi. Biroq, raqamli iz ma’lumotlari maxsus ilmiy tadqiqot uchun ishlab chiqilmagani sababli, ularni yig‘ish va tahlil qilishda bir qator noaniqliklar mavjud. Ushbu maqola, raqamli iz ma’lumotlarini yig‘ishning uchta usuli – API lar, foydalanuvchi ma’lumotlarini topshirish (data donation) va kuzatish (tracking) – kommunikatsiya tadqiqotining uchta muhim yo‘nalishida (soxta axborot, algoritmik usullar) qanday qo‘llanishi mumkinligi haqida umumiy ma’lumot beradi. Biz ijtimoiy tarmoqlardagi mukammal bo‘lmagan kontent ma’lumotlarini qanday yig‘ish va ularni mazmunli ko‘rsatkichlarga aylantirish mumkinligi masalasini ko‘rib chiqamiz. Maqola yakunida har bir usulni amalga oshirish bo‘yicha yechimlar muhokama qilinadi hamda ularning afzalliklari va kamchiliklari taqqoslanadi.
Copyright (c) 2025 Ochilov Bekzod Baxadirovich https://creativecommons.org/licenses/by/4.0
ANSAMBL USULLARIDAN FOYDALANIB KO‘KRAK BEZI SARATONINI TASHXISLASHNING SAMARADORLIGINI BAHOLASH
Mazkur maqolada ko‘krak bezi saratonini tashxislashda qo‘llaniladigan ansambl mashinaviy o‘qitish usullarining samaradorligi ilmiy jihatdan tahlil qilinadi. Tadqiqot doirasida Random Forest, Gradient Boosting, Bagging, AdaBoost va Model Stacking algoritmlaridan foydalanildi hamda ularning aniqlik, aniqlik darajasi, eslab qolish, F1-mezon va AUC-ROC kabi ko‘rsatkichlari taqqoslab o‘rganildi. Tahlil natijalari Model Stacking yondashuvi umumiy aniqlik va muvozanatli ko‘rsatkichlar bo‘yicha yuqori samaradorlik namoyon etganini ko‘rsatadi. Shu bilan birga, Random Forest algoritmi sinflarni ajratish qobiliyati jihatidan afzalliklarga ega ekani aniqlandi. Ushbu izlanishlar ansambl usullarining tibbiy tashxislashda qo‘llanish imkoniyatlarini kengaytirishini hamda klinik qarorlarni qo‘llab-quvvatlash tizimlarida samarali integratsiya qilinishi mumkinligini asoslab beradi.
Copyright (c) 2025 Dildora Muhamediyeva, Madina Shoazizova, Zilola Saidova https://creativecommons.org/licenses/by/4.0
AUTOMATIC SEGMENTATION OF MALIGNANT SKIN TUMORS IN DERMOSCOPIC IMAGES USING U-NET ARCHITECTURE
Oncological diseases remain one of the most pressing health problems on a global scale. According to data for the last 10 years, the prevalence of cancer has increased by almost 26%, and according to the age-specific standardized morbidity rate (ASIR), by 15%. As overall morbidity rates increase globally, the mortality rate is gradually decreasing. The decrease in cancer-related mortality by 2% is explained by the effectiveness of the use of automated diagnostic processes in early detection and treatment strategies. However, these indicators are very low compared to cases of infection. This indicates the need for the deep application of information technologies in the field of medicine. In particular, it plays an important role in analyzing medical images and optimizing early diagnostic processes using artificial intelligence. In this study, one of the tasks that serves as the basis for the accuracy of automated diagnostics using medical images - the problem of segmentation of medical images - was considered. In this case, the U-Net model based on deep learning was used as an object for the purpose of automatic detection of malignant skin tumors, in particular melanoma, based on dermoscopic images and segmentation of their boundaries, and an accuracy of 92% was achieved.
Copyright (c) 2025 Gulmirzayeva Go‘zal Alisher qizi https://creativecommons.org/licenses/by/4.0
Maqolada raqamli iqtisodiyotning asosiy jihatlari va raqamli bandlikni shakllantirish jarayonlari ko‘rib chiqiladi. Raqamli texnologiyalarning tarqalishi natijasida yuzaga kelgan mehnat faoliyatining yangi shakllarining paydo bo‘lishi uchun shart-sharoitlar va zarur shart-sharoitlar tahlil qilinadi. U mehnat bozori tarkibidagi o‘zgarishlarni, raqamli muhitni rivojlantirish bilan bog‘liq kasb va mutaxassisliklarning paydo bo‘lishini, shuningdek, iqtisodiy jarayonlarni avtomatlashtirish va raqamlashtirish ta’sirida bandlikning an’anaviy shakllarini o‘zgartirishni batafsil o‘rganadi.
Copyright (c) 2025 Sattorov Sanjar Abdumurodovich https://creativecommons.org/licenses/by/4.0
POS TEGLARNI BELGILASH UCHUN MAKSIMAL ENTROPIYA ASOSIDAGI BILSTM-CRF MODELINI QO‘LLASH
Ushbu maqolada imlo xatolarni tuzatish va o‘zbek tili matnlari uchun so‘z turkumni aniqlash vazifasi uchun turli xil Long Short-Term Memory (LSTM) tarmoqlariga asoslangan modellarni taklif qilinadi. Ushbu modellar quyidagilarni o‘z ichiga oladi: oddiy LSTM tarmoqlari, BiLSTM tarmoqlari, Shartli Tasodifiy Maydon (Conditional Random Field - CRF) qatlami bilan birgalikdagi LSTM (LSTM-CRF) modeli va CRF qatlami bilan birgalikdagi BiLSTM (BiLSTM-CRF) modeli. Ushbu tadqiqot o‘zbek tili uchun birinchi bo‘lib BiLSTM-CRF modelini tabiiy tilni qayta ishlash (NLP) bo‘yicha standart imlo tuzatish va POS teglarni belgilashni ma’lumot to‘plamlariga tatbiq etadi. BiLSTM-CRF modelining afzalligi shundaki, u BiLSTM orqali oldingi va keyingi xususiyatlarni samarali o‘rganishi mumkin. Bundan tashqari, CRF qatlami yordamida butun gap darajasidagi teg ma’lumotlarini ham hisobga oladi. Ushbu model so‘z turkumini aniqlash (POS – Part of speech), segmentatsiya (chunking) va yangi so‘zlar (NER - Named Entity Recognition) bo‘yicha eng ilg‘or yoki unga yaqin aniqlikka erisha oladi. Shuningdek, u mustahkam ishlaydi va so‘z ifodalariga nisbatan kamroq bog‘liq bo‘ladi. Shuningdek testlash natijalari eng yaxshi ko‘rsatgichi 93,6 % ni tashkil etadi.
Copyright (c) 2025 Turayev Boburxon Shuhrat o‘g‘li https://creativecommons.org/licenses/by/4.0
UZBEKISTAN’S TOURISM REGIONS’ POTENTIAL FOR INTEGRATION INTO SUSTAINABLE TOURISM PRACTICES
Uzbekistan is rapidly establishing itself as a key cultural and historical tourism hub in Central Asia. With five UNESCO World Heritage sites, over 7,000 historical monuments, and a growing tourism sector that contributes 4.5% to national GDP, the country has significant potential to integrate sustainable tourism practices. However, inequalities in regional tourism development, weak governance structures, and limited implementation of ESG principles remain significant challenges. This article assesses Uzbekistan's regional tourism potential for sustainable integration, analyzing statistical indicators, regional case studies (Samarkand, Bukhara, Khiva, Tashkent) and international best practices. Recommendations are provided for policymakers, local authorities and the private sector.
Copyright (c) 2025 Maxmudova Nodira Uktamovna https://creativecommons.org/licenses/by/4.0
ABOUT ONE METHOD OF FORMING CADASTRAL INFORMATION OF TELECOMMUNICATION FACILITIES
This article presents a method for creating a digital cadastre of telecommunications facilities based on the principles of single data entry, continuous event-driven updating, spatiotemporal modeling, and integration with departmental information systems. The proposed architecture improves the reliability and manageability of cadastral data, as well as regulatory compatibility with national and international standards. The article discusses the stages of method implementation, including data collection, standardization, database formation, quality control, and monitoring. It is shown that the application of the developed approach improves the integral quality of data, reduces updating time, reduces the number of duplicate records, and increases infrastructure coverage. The practical significance lies in the formation of a reliable information foundation for planning and regulating the development of telecommunications networks within the digital economy.
Copyright (c) 2025 Makhsum Makhmudov https://creativecommons.org/licenses/by/4.0
TADBIR TURIZMI ORQALI MAVSUMIY TURIZM OQIMLARINI MUVOZANATLASHTIRISH VA IJTIMOIY FAROVONLIKNI OSHIRISH IMKONIYATLARI
Tadbir turizmi turli yo‘nalishlarda turli xil samaradorlikka ega bo‘lsa-da, turizm mavsumiyligini yumshatish uchun strategik yondashuv sifatida paydo bo‘ladi. Tadqiqotlar shuni ko‘rsatadiki, tadbirlar yil davomida turizmga bo‘lgan talab taqsimotini muvozanatlashda yordam berishi mumkin, buni Makedoniyaning Sharqiy mintaqasida ko‘rish mumkin, bu yerda tadbir turizmi mavsumiylikning past darajasi va muvozanatli tashrif buyuruvchilar oqimiga hissa qo‘shgan [1]. Biroq, tadbirlar va mavsumiylikni boshqarish o‘rtasidagi bog‘liqlik murakkab bo‘lib, yil bo‘yi attraksionlarning atigi 39 foizi maxsus tadbirlarga mezbonlik qiladi, ayniqsa mahalliy hamjamiyatlarga mo‘ljallanmagan davrlarda [2]. Mavsumga qarshi turizm strategiyalari, shu jumladan madaniy, diniy va konferensiya turizmi bilan bir qatorda tadbirlar turizmi sayyohlarning kelishi va xarajatlaridagi vaqtinchalik nomutanosibliklarni bartaraf etish uchun tizimli yondashuvlarni ifodalaydi [3]. Shunga qaramay, kuchliroq mavsumiylik namunalari ishonchsiz turizm talabi prognozlari bilan bog‘liq bo‘lib, qo‘llaniladigan yumshatish strategiyalaridan qat’i nazar, rejalashtirish harakatlarini murakkablashtiradi [4]. Ushbu topilmalar shuni ko‘rsatadiki, tadbir turizmi mavsumiylikni kamaytirishga hissa qo‘shishi mumkin, ammo uning samaradorligi strategik harakatlar va mahalliy bozor sharoitlariga bog‘liq.
Copyright (c) 2025 Omonova Nilufar Rahmon qizi https://creativecommons.org/licenses/by/4.0