DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE
type: channel
description: The Journal is a publication specializing in the field of digital economy and information technologies. Raqamli transformatsiya va sun’iy intellekt ilmiy jurnali
publisher: Tashkent State University of Economics
language: en
publication name: DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE
issn: 3030-3346
items: AXBOROT TEXNOLOGIYALARI ASOSIDA DAVLAT XARIDLARIDA SHAFFOFLIK VA SAMARADORLIKNI TA’MINLASH
items: GASTROENTEROLOGIK KASALLIKLARNI KOʻP MEZONLI TASHXISLASH JARAYONLARI UCHUN AXBOROT MODELI
items: KASALLIKLARNI TASHXISLASHDA ZARRACHALAR TO‘DASI VA INTELLEKTUAL SUV TOMCHISI ALGORITMLARIGA ASOSLANGAN GIBRID YONDASHUVDAN FOYDALANISH
items: SO‘ZLOVCHILARNI AJRATISHDA ECAPA-TDNN ASOSIDAGI XUSUSIYATLAR VEKTORLARIDAN FOYDALANISH
items: TURIZMNING BARQAROR RIVOJLANISHIDA KREATIV INDUSTRIYALARNING ROLI
items: IOT TIZIMLARIDA XESH FUNKSIYALARIDAN FOYDALANISHNING XAVFSIZLIK VA SAMARADORLIK JIHATLARI
items: FORECASTING PERFORMANCE INDICATORS WITH THE HELP OF ARTIFICIAL INTELLIGENCE: TSUE PRACTICE
items: AXBOROT XAVFSIZLIGIDA KO‘P AGENTLI TIZIMLARDAN FOYDALANISH AFZALLIKLARI
items: SUN’IY INTELLEKT VA RAQAMLI BOSHQARUVNING TURIZM SOHASIDAGI AHAMIYATI
items: KUTUBXONA TIZIMLARIDA FOYDALANUVCHILARGA AXBOROT EHTIYOJLARIGA KO‘RA RESURSLARNI TAVSIYA ETISH
items: THEORETICAL FOUNDATIONS AND EFFICIENT ALGORITHMS FOR FEATURE DETECTION AND EXTRACTION
items: R-FUNKTSIYALAR VA ITERATSION FUNKSIYALAR TIZIMI ASOSIDA KUB-TSILINDR KOMPOZITSIYASIDAN HOSIL BOʻLGAN 3D FRAKTAL STRUKTURALARNI GEOMETRIK MODELLASHTIRISH
items: COMPACT DIFFERENCE SCHEMES FOR THE ALLER-LYKOV MOISTURE TRANSFER EQUATION
items: TASVIR SIFATINI BAHOLASH KO‘RSATKICHLARI
items: TO‘LIQ BO‘LMAGAN MA’LUMOTLARGA ASOSLANGAN MURAKKAB TEXNIK TIZIMLARNING INTELLEKTUAL BOSHQARUV MODELLARINI ISHLAB CHIQISH
items: OʻZBEK TILIDAGI MATNLARNI TAHLIL QILISHDA NOMLI OBYEKTNI TANIB OLISH (NER) YONDASHUVI
items: SELF-ADAPTING HYBRID EVOLUTIONARY ALGORITHM FOR TRANSPORT LOGISTICS OPTIMIZATION: DEVELOPMENT, STABILITY ANALYSIS AND PRACTICAL APPLICATION
items: SELECTING THE OPTIMAL COMBINATION OF MEMBERSHIP FUNCTIONS FOR QUERIES BASED ON FUZZY LOGIC BY EVALUATING THE SENSITIVITY
items: MUHIM XUSUSIYATLARNI ANIQLASH MASALASIDA TAKOMILLASHTIRILGAN GROVER ALGORITMI
items: TIBBIY MA’LUMOTLARNI TAHLIL QILISHNING INNOVATSION ALGORITMLARI ORQALI INSULTNI ERTA ANIQLASH
items: INTEGRATIVE MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING FRAMEWORK FOR THE DETECTION AND CLASSIFICATION OF AI-GENERATED TEXTS IN ACADEMIC RESEARCH PUBLICATIONS
items: QISHLOQ XO‘JALIGI MAHSULOTLARINI SAQLASHDA KO‘P BOSQICHLI ADAPTIV BOSHQARUV TIZIMI MODELI VA ALGORITMI
items: YEYILISH DINAMIKASINI TADQIQ ETISHDA EMPERIK TENGLAMALARNI KELTIRIB CHIQARISHDA MAHSUS DASTURLARDAN FOYDALANISHNING ISTIQBOLLARI
items: TURKIY TILLAR GRAMMATIKASINING KOMPYUTERGA YO‘NALTIRILGAN FORMAL MODELLARI TAHLILI
items: 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
items: MODAL GRAPH TRANSFORMER FOR GROUP ENGAGEMENT IN ONLINE MULTIPARTY CONVERSATIONS
items: SSRE-ID: KO‘P OBYETLAR KUZATUVLARIDA TO‘LIQ O‘Z-O‘ZINI O‘QITISHGA ASOSLANGAN QAYTA IDENTIFIKATSIYALASH
items: COMPARATIVE ANALYSIS OF PHYSICAL DEVELOPMENT IN CHILDREN ENGAGED IN SPORTS AND PHYSICAL EDUCATION
items: TARMOQ MA’LUMOTLARIGA INTELLEKTUAL ISHLOV BERISH MODELLARI VA USULLARI
items: O‘ZBEK TILIDAGI GAPLARNI PERIFRAZ QILISH AXBOROT TIZIMINING FUNKSIONAL JARAYONLARINI LOYIHALASHTIRISH

AXBOROT TEXNOLOGIYALARI ASOSIDA DAVLAT XARIDLARIDA SHAFFOFLIK VA SAMARADORLIKNI TA’MINLASH
type: item
description: Mazkur maqolada budjet buyurtmachilari tomonidan tovar, ish, xizmatlar sotib olishda davlat xaridlarining zaruriyati ko‘rsatilgan. Davlat xaridlari ko‘lamining kengayishi mahalliy ishlab chiqaruvchilarni qo‘llab-quvvatlash, ish o‘rinlari yaratish, soliq tushumlarini oshirish bilan bog‘liqligi tahlil qilingan. Raqamli texnologiyalardan foydalanish asosida davlat xaridlarining ochiqligi va samaradorligini ta’minlash bo‘yicha amaliy taklif va tavsiyalar ishlab chiqilgan.
subject: Technical sciences
  topic: section
subject: Davlat budjeti
  topic: keywords
subject: ijtimoiy soha xarajatlari
  topic: keywords
subject: budjet tashkiloti
  topic: keywords
subject: davlat xaridlari
  topic: keywords
subject: shartnoma
  topic: keywords
subject: raqamli iqtisodiyot
  topic: keywords
subject: axborot texnologiyalari
  topic: keywords
subject: elektron hujjat
  topic: keywords
subject: elektron platformalar
  topic: keywords
subject: korrupsiya
  topic: keywords
creator: Kasimova Gulyar Axmatovna
creator: Abdushukurov Zafar Ismatovich
rights: Copyright (c) 2025 Kasimova Gulyar Axmatovna, Abdushukurov Zafar Ismatovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-28
publication date: 2025-12-28
starting page: 181
ending page: 188

GASTROENTEROLOGIK KASALLIKLARNI KOʻP MEZONLI TASHXISLASH JARAYONLARI UCHUN AXBOROT MODELI
type: item
description: Mazkur tadqiqot ishida gastroenterologik kasalliklarni ko‘p mezonli tashxislash jarayonlarini avtomatlashtirishga mo‘ljallangan axborot modeli ishlab chiqilgan bo‘lib, taklif etilgan model bemordan olinadigan elektrogastrogramma signallari, klinik simptomlar, laborator va instrumental tekshiruv natijalarini kompleks tahlil qilishga asoslanadi. Axborot modeli signalni yig‘ish, filtrlash, tahlil qilish va qaror qabul qilish bosqichlarini o‘z ichiga olgan holda matematik va algoritmik yondashuvlar asosida shakllantirilgan. Bemorning biofizik signallarini qayta ishlash jarayonida Butterworth bandpass filtri qo‘llanilib, signalning foydali chastota diapazonlari ajratib olinadi. Filtrlangan signal ma’lumotlar bazasida saqlanayotgan diagnostik signallar bilan kosinus o‘xshashligi usuli yordamida solishtiriladi va kasalliklarga tegishlilik darajalari aniqlanadi. Qaror qabul qilish jarayonida avtomatlashtirilgan algoritmlar bilan bir qatorda ekspert shifokor ishtiroki ham ta’minlanadi, bu esa tashxisning aniqligi va ishonchliligini oshiradi. Tizimning funksional modeli IDEF0 diagrammalari asosida ishlab chiqilib, unda axborot oqimlari, kirish va chiqish ob’ektlari, boshqaruv va mexanizmlar aniq belgilangan. Tadqiqot natijalari gastroenterologik kasalliklarni tezkor, aniqligi yuqori va xolis tarzda tashxislash imkonini beruvchi axborot tizimini yaratishga xizmat qiladi hamda tibbiy qaror qabul qilish jarayonlarini qo‘llab-quvvatlashda muhim amaliy ahamiyatga ega.
subject: Technical sciences
  topic: section
subject: Gastroenterologik kasalliklar
  topic: keywords
subject: ko‘p mezonli tashxislash
  topic: keywords
subject: axborot modeli
  topic: keywords
subject: elektrogastrogramma signali
  topic: keywords
subject: raqamli signalni qayta ishlash
  topic: keywords
subject: Butterworth filtri
  topic: keywords
subject: kosinus o‘xshashligi
  topic: keywords
subject: biometrik signallar
  topic: keywords
subject: tibbiy axborot tizimi
  topic: keywords
subject: qaror qabul qilish modeli
  topic: keywords
subject: IDEF0 diagrammasi
  topic: keywords
subject: avtomatlashtirilgan tashxislash
  topic: keywords
creator: Aliqulov Akmal Xushmuratovich
rights: Copyright (c) 2025 Aliqulov Akmal Xushmuratovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-28
publication date: 2025-12-28
starting page: 164
ending page: 173

KASALLIKLARNI TASHXISLASHDA ZARRACHALAR TO‘DASI VA INTELLEKTUAL SUV TOMCHISI ALGORITMLARIGA ASOSLANGAN GIBRID YONDASHUVDAN FOYDALANISH
type: item
description: Ushbu maqolada ko‘p sinfli klassifikatsiya masalalarini samarali yechish uchun zarrachalar to‘dasi va intellektual suv tomchisi algoritmlarining afzalliklarini birlashtiruvchi PSO–IWD gibrid algoritmi taklif etilgan. Taklif etilgan yondashuvda PSO algoritmi global qidiruv mexanizmi sifatida yechimlar maydonini keng ko‘lamda o‘rganib, maqbul yechimlarni aniqlaydi. IWD algoritmi yordamida esa lokal qidiruv jarayonida suv tomchilarining harakati orqali eng qisqa va samarali yo‘llar aniqlanadi hamda global qidiruvda topilgan eng yaxshi yechimlar optimallashtiriladi. Taklif etilgan PSO–IWD algoritmi yurak-qon tomir kasalliklari tashxisida qo‘llaniladigan ikki xil tanlanmada sinovdan o‘tkazildi va mos ravishda 99 % hamda 98 % klassifikatsiya aniqligiga erishildi. Olingan natijalar gibrid yondashuvning murakkab tibbiy va ko‘p sinfli klassifikatsiya masalalarini yechishda yuqori samaradorlikka ega ekanini ko‘rsatadi.
subject: Technical sciences
  topic: section
subject: zarrachalar to‘dasi
  topic: keywords
subject: pozitsiya
  topic: keywords
subject: intellektual suv tomchisi
  topic: keywords
subject: tuproq
  topic: keywords
subject: global qidiruv
  topic: keywords
subject: gibrid yondashuv
  topic: keywords
creator: Klicheva Firuza Gulmuratovna
rights: Copyright (c) 2025 Klicheva Firuza Gulmuratovna https://creativecommons.org/licenses/by/4.0
date: 2025-12-25
publication date: 2025-12-25
starting page: 159
ending page: 163

SO‘ZLOVCHILARNI AJRATISHDA ECAPA-TDNN ASOSIDAGI XUSUSIYATLAR VEKTORLARIDAN FOYDALANISH
type: item
description: So‘zlovchilarni ajratishda xususiyatlar vektorlarini shakllantirish eng muhim bosqichlardan biri hisoblanadi. Zamonaviy chuqur neyron tarmoqlar so‘zlovchining individual xususiyatlarini aniqlash va ularni ifodalashda yuqori aniqlikni ta’minlay oladi. Xususan, x-vector kabi mashhur xususiyatlar vektorlari hozirgi tizimlarda asosiy komponent sifatida qo‘llanib kelmoqda. So‘nggi yillarda TDNN arxitekturasi ustida turli takomillashtirishlar ishlab chiqildi. ECAPA-TDNN modeli esa o‘ziga xos kanal e’tibor mexanizmi va ko‘p qatlamli agregatsiya orqali so‘zlovchini tekshirish vazifalarida yuqori samaradorlikni ko‘rsatdi. Tadqiqot mazkur modelni diarizatsiya sohasiga tatbiq etish imkoniyatlarini namoyish etadi.
subject: Technical sciences
  topic: section
subject: So‘zlovchilarni ajratish
  topic: keywords
subject: so‘zlovchilarni ifodalovchi xususiyatlar vektori
  topic: keywords
subject: ECAPA-TDNN
  topic: keywords
subject: X-vektor
  topic: keywords
subject: Spektral klasterlash
  topic: keywords
creator: Umidjon Xasanov Komiljon o‘g‘li
rights: Copyright (c) 2025 Umidjon Xasanov Komiljon o‘g‘li https://creativecommons.org/licenses/by/4.0
date: 2025-12-25
publication date: 2025-12-25
starting page: 152
ending page: 158

TURIZMNING BARQAROR RIVOJLANISHIDA KREATIV INDUSTRIYALARNING ROLI
type: item
description: Mazkur ilmiy maqolada kreativ sanoatlarning turizmning barqaror rivojlanishidagi o‘rni va ahamiyati tahlil qilinadi. Tadqiqotning asosiy maqsadi kreativ iqtisodiyot elementlari – hunarmandchilik, gastronomiya, san’at, dizayn, madaniy meros va raqamli kreativ faoliyatning turizmning iqtisodiy, ijtimoiy hamda ekologik barqarorligiga ta’sirini aniqlashdan iborat. Tadqiqot sifatli analitik va qiyosiy metodologiyaga asoslanib, BMTning Jahon Turizm Tashkiloti (UNWTO), UNESCO, UNCTAD va OECD ma’lumotlari, shuningdek, O‘zbekiston, Indoneziya va Ispaniya tajribalarini qamrab oladi. Tadqiqot natijalari shuni ko‘rsatadiki, kreativ sanoatlar turizm mahsulotlarini diversifikatsiya qilish, mahalliy jamoalarni iqtisodiy jihatdan qo‘llab-quvvatlash, madaniy merosni asrash va ekologik mas’uliyatni kuchaytirish orqali barqaror turizmni rivojlantirishda strategik omil hisoblanadi. O‘zbekiston misolida Xiva, Buxoro va Samarqand shaharlari tajribasi ushbu yondashuvning yuqori samaradorligini tasdiqlaydi.
subject: Technical sciences
  topic: section
subject: kreativ sanoatlar
  topic: keywords
subject: barqaror turizm
  topic: keywords
subject: madaniy turizm
  topic: keywords
subject: kreativ iqtisodiyot
  topic: keywords
creator: Qurbonova Zebiniso Azimovna
rights: Copyright (c) 2025 Qurbonova Zebiniso Azimovna https://creativecommons.org/licenses/by/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 146
ending page: 151

IOT TIZIMLARIDA XESH FUNKSIYALARIDAN FOYDALANISHNING XAVFSIZLIK VA SAMARADORLIK JIHATLARI
type: item
description: Internet of Things (IoT) texnologiyasining jadal rivojlanishi butun dunyo bo‘ylab ulangan qurilmalar sonini keskin oshirmoqda. So‘nggi statistik ma’lumotlarga ko‘ra, 2024 yilga kelib dunyoda 15 milliarddan ortiq IoT qurilmalari faoliyat ko‘rsatmoqda, bu raqam 2025 yilga borib 25 milliardga yetishi kutilmoqda. Bu o‘sish nafaqat texnologik taraqqiyotni, balki kiberxavfsizlik sohasida yangi muammolarni ham keltirib chiqarmoqda. IoT tizimlarining o‘ziga xos xususiyatlari – cheklangan protsessor quvvati, kam xotira, past energiya sarfi – an’anaviy kriptografik usullarni qo‘llashni qiyinlashtiradi. Ayniqsa, sog‘liqni saqlash, moliya, transport va energetika kabi muhim sohalarda IoT qurilmalarining ishonchliligi va xavfsizligi inson hayoti bilan bevosita bog‘liq bo‘lishi mumkin. Shu sababli, resurslar chegaralangan muhitda samarali ishlay oladigan kriptografik yechimlarni ishlab chiqish dolzarblik kasb etmoqda. Xesh funksiyalari IoT tizimlarida ma’lumotlar butunligini tekshirish, parollarni xavfsiz saqlash va raqamli imzolarni yaratishda asosiy vositadir. Biroq, turli xesh algoritmlarining xavfsizlik darajasi va samaradorligi turlicha bo‘lib, ularni maqsadli tanlash va qo‘llash talab etiladi. Ushbu maqolaning asosiy maqsadi IoT muhitida eng ko‘p qo‘llaniladigan xesh algoritmlarining tezlik, energiya sarfi va xavfsizlik ko‘rsatkichlarini qiyosiy tahlil qilish, shu asosida turli soha va talablar uchun optimal algoritmlarni tavsiya etishdan iborat.
subject: Technical sciences
  topic: section
subject: IoT
  topic: keywords
subject: xesh funksiyalari
  topic: keywords
subject: kriptografiya
  topic: keywords
subject: maʼlumotlar butunligi
  topic: keywords
subject: autentifikatsiya
  topic: keywords
subject: xavfsizlik
  topic: keywords
subject: SHA-256
  topic: keywords
subject: resurs cheklovlari
  topic: keywords
creator: Allanov Orif Menglimuratovich
creator: Saidahmedov Eldor Islomovich
rights: Copyright (c) 2025 Allanov Orif Menglimuratovich, Saidahmedov Eldor Islomovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 141
ending page: 145

FORECASTING PERFORMANCE INDICATORS WITH THE HELP OF ARTIFICIAL INTELLIGENCE: TSUE PRACTICE
type: item
description: This article presents an AI-driven approach for predicting employee performance within the KPIup digital platform, designed to enhance staff evaluation processes in higher education institutions. Multidimensional HR data were analyzed and predictive models were developed using Gradient Boosting, Random Forest, and regression algorithms to forecast future employee productivity. Data preprocessing, normalization, and feature engineering significantly improved prediction accuracy. The results demonstrate that integrating AI analytics into the KPIup platform increases the speed and reliability of managerial decision-making, reduces subjectivity in performance evaluation, and enables full automation of HR processes.
subject: Technical sciences
  topic: section
subject: KPI
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: employee performance
  topic: keywords
subject: prediction model
  topic: keywords
subject: KPIup platform
  topic: keywords
subject: business analytics
  topic: keywords
subject: Gradient Boosting
  topic: keywords
subject: HR technologies
  topic: keywords
creator: Shuhratov Mamurjon Shuhrat o‘g‘li
rights: Copyright (c) 2025 Shuhratov Mamurjon Shuhrat o‘g‘li https://creativecommons.org/licenses/by/4.0
date: 2025-10-28
publication date: 2025-10-28
starting page: 19
ending page: 24

AXBOROT XAVFSIZLIGIDA KO‘P AGENTLI TIZIMLARDAN FOYDALANISH AFZALLIKLARI
type: item
description: Maqolada raqamli texnologiyalar tez sur’atlar bilan rivojlanayotgan bugungi kunda axborot xavfsizligini ta’minlashda ko‘p agentli axborot xavfsizligi tizimlaridan foydalanishning nazariy asoslari, tarkibiy tuzilmasi va amaliy qo‘llanilish sohalari tahlil qilingan. Intellektual agentlar va ularning "zaif" hamda "kuchli" shakllari, xususiyatlar orqali axborot tizimlarida tahdidlarni aniqlash, monitoring qilish yoritilgan. Agentlar asosidagi yondashuvning IDPS, DDoS himoyasi, bulutli hisoblash va IoT tizimlaridagi rollari ko‘rsatilgan.
subject: Technical sciences
  topic: section
subject: Ko‘p agentli tizim
  topic: keywords
subject: axborot xavfsizligi
  topic: keywords
subject: intellektual agent
  topic: keywords
subject: anomaliya
  topic: keywords
subject: kiberxavfsizlik
  topic: keywords
subject: IDPS
  topic: keywords
subject: DDoS
  topic: keywords
subject: bulutli hisoblash
  topic: keywords
subject: IoT
  topic: keywords
subject: sun’iy intellekt
  topic: keywords
creator: Umarov Shuxratjon Azizjonovich
rights: Copyright (c) 2025 Umarov Shuxratjon Azizjonovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-23
publication date: 2025-12-23
starting page: 136
ending page: 140

SUN’IY INTELLEKT VA RAQAMLI BOSHQARUVNING TURIZM SOHASIDAGI AHAMIYATI
type: item
description: Bugungi kunda turizm sanoati sun’iy intellekt (AI) va raqamli texnologiyalar yordamida tubdan o‘zgarib bormoqda. Ushbu texnologiyalar sayohat tajribasini shaxsiylashtirish, xizmat ko‘rsatish sifatini oshirish va operatsion jarayonlarni optimallashtirish imkonini beradi. Raqamli turizm va AI qo‘llanilishi orqali bronlash, yo‘nalish tavsiyalari, narxni optimallashtirish va xavfsizlik monitoringi kabi jarayonlar avtomatlashtiriladi, natijada sayyohlar va korxonalarga qulayliklar yaratiladi. Shu bilan birga, AI va raqamli boshqaruv innovatsiyalarni rag‘batlantiradi va turizm sanoatining raqobatbardoshligini oshiradi.
subject: Technical sciences
  topic: section
subject: raqamli turizm
  topic: keywords
subject: sun’iy intellekt
  topic: keywords
subject: AI
  topic: keywords
subject: raqamli boshqaruv
  topic: keywords
subject: turizm sanoati
  topic: keywords
subject: innovatsiyalar
  topic: keywords
subject: avtomatlashtirish
  topic: keywords
subject: bronlash tizimi
  topic: keywords
creator: Husenova Madina Farxodovna
rights: Copyright (c) 2025 Husenova Madina Farxodovna https://creativecommons.org/licenses/by/4.0
date: 2025-12-23
publication date: 2025-12-23
starting page: 132
ending page: 135

KUTUBXONA TIZIMLARIDA FOYDALANUVCHILARGA AXBOROT EHTIYOJLARIGA KO‘RA RESURSLARNI TAVSIYA ETISH
type: item
description: Hozirda kutubxona tizimlari jamiyatning axborotga bo‘lgan ehtiyojlarini qondirishda muhim o‘rin tutadi hamda ular katta foydalanuvchilar auditoriyasiga ega. Ushbu tizimlar katta hajmdagi qimmatli axborot resurslarini o‘z ichiga olgan bo‘lib, foydalanuvchilarga zarur adabiyotlarni topishda yordam beruvchi qidiruv xizmatlarini ham taklif etadi. Qidiruv tizimlari foydalanuvchi so‘rovlarini qayta ishlaydi va mos deb topilgan natijalarni taqdim etadi. Biroq, bu jarayon natijasida foydalanuvchilar ko‘plab ma’lumotlar orasidan o‘zlariga eng mosini tanlashda qiyinchiliklarga duch kelishadi. Shu bois, zamonaviy axborot tizimlarida sun’iy intellektga asoslangan tavsiya etish tizimlari keng qo‘llanilib, foydalanuvchiga mos obyektlarni samarali tarzda taklif etish imkonini bermoqda. Kutubxona tizimlariga bunday tavsiya etish tizimi vositalarini joriy etish orqali foydalanuvchilarning axborot ehtiyojlarini aniqlash va ularga axborot ehtiyojiga ko‘ra resurslarni taqdim etish mumkin. Ushbu maqolada tavsiya etish tizimlari asosida foydalanuvchilarning axborot ehtiyojlarini aniqlash va resurslarni taqdim etishning nazariy asoslari hamda amaliy yondashuvlari tahlil qilinadi.
subject: Technical sciences
  topic: section
subject: kutubxona tizimi
  topic: keywords
subject: tavsiya etish
  topic: keywords
subject: axborot resurslari
  topic: keywords
subject: foydalanuvchilar
  topic: keywords
subject: axborot ehtiyojlari
  topic: keywords
subject: kontentga asoslangan tavsiya etish
  topic: keywords
subject: hamkorlikka asoslangan tavsiya etish
  topic: keywords
creator: Fayzi Bekkamov
rights: Copyright (c) 2025 Fayzi Bekkamov https://creativecommons.org/licenses/by/4.0
date: 2025-12-23
publication date: 2025-12-23
starting page: 127
ending page: 131

THEORETICAL FOUNDATIONS AND EFFICIENT ALGORITHMS FOR FEATURE DETECTION AND EXTRACTION
type: item
description: Feature detection and extraction play a critical role in numerous applications within artificial intelligence, computer vision, and data science. As datasets grow in complexity and volume, traditional feature extraction techniques often struggle to maintain efficiency and accuracy. This paper explores the theoretical foundations and efficient algorithms for feature detection and extraction, emphasizing the intersection of classical statistical methods and modern machine learning-based approaches. The study provides an in-depth analysis of key methodologies, including edge detection algorithms, deep learning-based feature extraction, and dimensionality reduction techniques such as Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). Furthermore, the research highlights the challenges associated with computational efficiency, accuracy trade-offs, and real-time processing constraints. A critical gap in existing literature is identified—the disconnect between theoretical models and their practical implementations—which often hinders the optimization of feature extraction processes. By synthesizing current advancements and addressing these challenges, this paper aims to provide a comprehensive framework for improving feature detection and extraction methodologies, ultimately contributing to the development of more efficient and adaptable systems across various domains.
subject: Technical sciences
  topic: section
subject: Feature detection
  topic: keywords
subject: feature extraction
  topic: keywords
subject: machine learning
  topic: keywords
subject: deep learning
  topic: keywords
subject: dimensionality reduction
  topic: keywords
subject: computer vision
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: edge detection
  topic: keywords
subject: real-time processing
  topic: keywords
subject: Principal Component Analysis (PCA)
  topic: keywords
subject: t-Distributed Stochastic Neighbor Embedding (t-SNE)
  topic: keywords
creator: Iskandarov Sanjar
creator: Rakhmonova Ma’rifat
rights: Copyright (c) 2025 Iskandarov Sanjar, Rakhmonova Ma’rifat https://creativecommons.org/licenses/by/4.0
date: 2025-12-22
publication date: 2025-12-22
starting page: 122
ending page: 126

R-FUNKTSIYALAR VA ITERATSION FUNKSIYALAR TIZIMI ASOSIDA KUB-TSILINDR KOMPOZITSIYASIDAN HOSIL BOʻLGAN 3D FRAKTAL STRUKTURALARNI GEOMETRIK MODELLASHTIRISH
type: item
description: Mazkur maqolada R-funktsiyalar va iteratsion funksiyalar tizimi (IFS) integratsiyasi asosida kub va tsilindr shakllarining analitik kombinatsiyasidan hosil bo‘lgan uch o‘lchovli fraktal struktura modellashtirilgan. Tadqiqotda kubning chegaralari va uchta o‘zaro perpendikulyar tsilindr tenglamalari R-funktsiyalar yordamida differensial tarzda birlashtirilib, natijada silliq sirtli va markaziy simmetriyaga ega fraktaldan avvalgi shakl (pred-fraktal) modeli hosil qilindi. So‘ngra ushbu shakl IFS yondashuvi orqali rekursiv takrorlanib, Menger tipidagi 3D fraktal strukturalar ketma-ket iteratsiyalar asosida yaratildi. Natijalar fraktal antennalar dizayni, 3D bosma texnologiyalar, grafik dizayn va matematik vizualizatsiya sohalarida amaliy qo‘llanish imkoniyatiga ega.
subject: Technical sciences
  topic: section
subject: R-funktsiyalar
  topic: keywords
subject: iteratsion funksiyalar tizimi (IFS)
  topic: keywords
subject: 3D fraktal modellashtirish
  topic: keywords
subject: kub
  topic: keywords
subject: tsilindr
  topic: keywords
subject: fraktal antennalar
  topic: keywords
subject: geometrik modellashtirish
  topic: keywords
subject: Menger gubkasi
  topic: keywords
subject: kompyuter grafika
  topic: keywords
creator: Nuraliyev Faxriddin Murodillayevich
creator: Narzulloyev Oybek Mirzayevich
creator: Nurimbetov Baxbergen Tolibayevich
rights: Copyright (c) 2025 Nuraliyev Faxriddin Murodillayevich, Narzulloyev Oybek Mirzayevich, Nurimbetov Baxbergen Tolibayevich https://creativecommons.org/licenses/by/4.0
date: 2025-12-22
publication date: 2025-12-22
starting page: 117
ending page: 121

COMPACT DIFFERENCE SCHEMES FOR THE ALLER-LYKOV MOISTURE TRANSFER EQUATION
type: item
description: The generalized Aller-Lykov equation is a mathematical model for many applied heat and moisture transfer problems. This includes nonstationary problems in hydrogeology, agrophysics, biology, ecology, and other fields, which are primarily solved using numerical methods. In this paper, high-precision difference schemes (compact schemes) are constructed and analyzed for the nonstationary generalized Aller-Lykov equation. The scheme is constructed in space and time using the finite difference method. The stability and convergence of the resulting difference scheme are proven, and accuracy estimates are obtained for a sufficiently smooth solution to the original differential problem. An implementation algorithm for the constructed scheme is proposed.
subject: Technical sciences
  topic: section
creator: Tleuov Kuatbay Orazbayevich
rights: Copyright (c) 2025 Tleuov Kuatbay Orazbayevich https://creativecommons.org/licenses/by/4.0
date: 2025-12-22
publication date: 2025-12-22
starting page: 112
ending page: 116

TASVIR SIFATINI BAHOLASH KO‘RSATKICHLARI
type: item
description: Tasvirlash sohasidagi yutuqlar tez sur’atlar bilan davom etmoqda va bozorga yangi hamda ilg‘or mahsulotlar doimiy ravishda kirib kelmoqda. Yangi texnologiyalar joriy texnologiyaga nisbatan yuqori sifatli tasvirlarni ishlab chiqarishini tekshirish uchun sifatni baholashning samarali bir turi talab etiladi. Bu o‘z navbatida, tasvir sifatini baholash ko‘rsatkichlarini keng qamrovli tahlil qilish hamda ularni har biri bo‘yicha ma’lumotlarni bitta joyga yig‘ishni dolzarb masalaga aylantiradi. Shuning uchun, mazkur ishda tasvir sifatini baholash ko‘rsatkichlarini tarixi va tavsifi, ularni tasniflanishi haqida ma’lumotlar keltirilgan. Shuningdek, soha bo‘yicha mavjud adabiyotlar tahlili, tasvir sifatini baholash ko‘rsatkichlarini yutuq hamda kamchiliklari keltirilgan. Mazkur tadqiqot ishini maqsadi sifatni baholash ko‘rsatkichlarini alohida guruhlarga ajratish hamda ularni subyektiv idrok bilan mos kelishini baholashdan iborat. Bunday tasniflash ma’lum bir muammo yoki buzilish uchun eng mos keladigan sifatni baholash ko‘rsatkichini tanlashda foydali bo‘lishi mumkin.
subject: Technical sciences
  topic: section
subject: tasvir sifati
  topic: keywords
subject: piksel
  topic: keywords
subject: etalon
  topic: keywords
subject: shovqin
  topic: keywords
subject: ko‘rsatkich
  topic: keywords
subject: qayta ishlash
  topic: keywords
subject: xalaqit
  topic: keywords
subject: neyron tarmoq
  topic: keywords
subject: fazoviy va chastotali soha
  topic: keywords
subject: algoritm
  topic: keywords
creator: Mamatov Narzullo Solidjonovich
creator: Jalelova Malika Moyatdin qizi
creator: Jumayev Bobur Juma o‘g‘li
rights: Copyright (c) 2025 Mamatov Narzullo Solidjonovich, Jalelova Malika Moyatdin qizi, Jumayev Bobur Juma o‘g‘li https://creativecommons.org/licenses/by/4.0
date: 2025-12-20
publication date: 2025-12-20
starting page: 102
ending page: 111

TO‘LIQ BO‘LMAGAN MA’LUMOTLARGA ASOSLANGAN MURAKKAB TEXNIK TIZIMLARNING INTELLEKTUAL BOSHQARUV MODELLARINI ISHLAB CHIQISH
type: item
description: Ushbu maqolada to‘liq bo‘lmagan va noaniq ma’lumotlar sharoitida murakkab texnik tizimlarni samarali boshqarish masalalari ko‘rib chiqiladi. Tadqiqotning maqsadi – axborot yetishmovchiligi, o‘lchov xatoliklari va tashqi omillar ta’siri ostida ishlaydigan tizimlar uchun intellektual boshqaruv modellarini ishlab chiqish va ularning barqarorligini ta’minlashdir. Taklif etilgan yondashuv sun’iy intellekt, noaniqlik nazariyasi, hamda moslashuvchan boshqaruv usullariga asoslanadi. Maqolada ma’lumotlarni qayta ishlashning ehtimollik va neyron tarmoqlar asosidagi metodlari, shuningdek, qaror qabul qilishning gibrid algoritmlari tahlil qilinadi. Natijada, to‘liq bo‘lmagan ma’lumotlar sharoitida tizim holatini aniqlash, prognozlash va optimal boshqaruv signalini shakllantirish imkonini beruvchi model taklif etiladi. Tadqiqot natijalari avtomatlashtirilgan ishlab chiqarish, robototexnika, energetika va transport tizimlarida qo‘llash uchun amaliy ahamiyatga ega.
subject: Technical sciences
  topic: section
subject: Intellektual boshqaruv
  topic: keywords
subject: modellashtirish
  topic: keywords
subject: noravshan mantiq
  topic: keywords
subject: tegishlilik funksiyasi
  topic: keywords
subject: algoritm
  topic: keywords
creator: Zayniddinov Bobirjon G‘ofirovich
rights: Copyright (c) 2025 Zayniddinov Bobirjon G‘ofirovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-20
publication date: 2025-12-20
starting page: 94
ending page: 101

OʻZBEK TILIDAGI MATNLARNI TAHLIL QILISHDA NOMLI OBYEKTNI TANIB OLISH (NER) YONDASHUVI
type: item
description: Ushbu maqolada o‘zbek tilidagi matnlarni tahlil qilish jarayonida nomlangan obyektlarni tanib olish (Named Entity Recognition-NER) yondashuvlari har tomonlama tahlil qilingan. Tadqiqot doirasida NER tizimlarining nazariy asoslari, qoida asoslangan, mashinali o‘qitishga asoslangan hamda gibrid yondashuvlar batafsil ko‘rib chiqilgan va ularning afzalliklari hamda cheklovlari solishtirma tahlil asosida yoritilgan. Shuningdek, turli tillar va sohalarda, jumladan tibbiyot, oziq-ovqat va axborot tizimlarida qo‘llanilgan zamonaviy NER modellarining ishlash samaradorligi tahlil qilingan. Tadqiqot natijalari NER tizimlarining katta hajmdagi matnli ma’lumotlardan semantik axborotni avtomatik ajratib olishdagi ahamiyatini ko‘rsatadi hamda kam resursli tillar, xususan o‘zbek tili uchun moslashuvchan va samarali NER modellarini ishlab chiqish istiqbollarini belgilab beradi.
subject: Technical sciences
  topic: section
subject: tabiiy tilni qayta ishlash
  topic: keywords
subject: nomlangan obyektlarni tanib olish
  topic: keywords
subject: NER
  topic: keywords
subject: mashinali o‘qitish
  topic: keywords
subject: chuqur o‘rganish
  topic: keywords
subject: gibrid yondashuv
  topic: keywords
subject: matn tahlili
  topic: keywords
subject: semantik axborot
  topic: keywords
creator: Kenjayev Xamdam Bazarbayevich
rights: Copyright (c) 2025 Kenjayev Xamdam Bazarbayevich https://creativecommons.org/licenses/by/4.0
date: 2025-12-18
publication date: 2025-12-18
starting page: 87
ending page: 93

SELF-ADAPTING HYBRID EVOLUTIONARY ALGORITHM FOR TRANSPORT LOGISTICS OPTIMIZATION: DEVELOPMENT, STABILITY ANALYSIS AND PRACTICAL APPLICATION
type: item
description: This paper presents a self-adaptive hybrid evolutionary algorithm for solving transport route optimization problems in agricultural logistics. The developed algorithm combines differential evolution (DE), a genetic algorithm (GA), and variable-environment local search (VNS) with a self-adaptive parameter optimization (SaDE) mechanism. SaDE automatically adjusts key algorithm parameters based on their success in previous generations, ensuring an adaptive balance between global search and local exploitation. A comprehensive analysis of the algorithm's stability was conducted on problems of varying dimensions (from 50 to 200 orders). Experimental results demonstrate a 15-18% reduction in transportation costs compared to baseline heuristics with a variation coefficient of only 1.40%, which is 3.5 times better than a classical genetic algorithm. The high stability and reproducibility of the results confirm the algorithm's readiness for integration into real-world transport logistics management systems.
subject: Technical sciences
  topic: section
subject: Self-adaptation
  topic: keywords
subject: algorithm stability
  topic: keywords
subject: hybrid evolutionary algorithm
  topic: keywords
subject: differential evolution
  topic: keywords
subject: genetic algorithm
  topic: keywords
subject: local search
  topic: keywords
subject: route optimization
  topic: keywords
subject: transport logistics
  topic: keywords
subject: agricultural products
  topic: keywords
creator: Sulyukova Larisa Faritovna
creator: Akhmedzhanova Zarrina Iskandarovna
creator: Shamsiev Rasul Zairovich
rights: Copyright (c) 2025 Sulyukova Larisa Faritovna, Akhmedzhanova Zarrina Iskandarovna, Shamsiev Rasul Zairovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-18
publication date: 2025-12-18
starting page: 77
ending page: 86

SELECTING THE OPTIMAL COMBINATION OF MEMBERSHIP FUNCTIONS FOR QUERIES BASED ON FUZZY LOGIC BY EVALUATING THE SENSITIVITY
type: item
description: Efficient request distribution is one of the important factors for the stable and uninterrupted operation of modern information systems. In the context of increasing cloud computing, real-time services and multi-user environments, traditional distribution algorithms (e.g. Round Robin, Least Connection, Weighted Response Time) are losing their effectiveness due to insufficient consideration of uncertainty and dynamic changes in server state. In this context, there is a growing need for decision-making systems based on adaptive and state-sensitive approaches. Fuzzy logic-based models have a significant advantage in representing uncertainties in real-world environments, especially due to the ability to estimate system parameters through linguistic variables. However, the effectiveness of these systems directly depends on the shape and parameters of the membership functions, i.e. their semantic relevance and sensitivity. Using membership functions of the same shape for each linguistic value (for example, only a triangle) can reduce the accuracy of the system's decision-making.
subject: Technical sciences
  topic: section
subject: linguistic variable
  topic: keywords
subject: membership function
  topic: keywords
subject: fuzzy logic
  topic: keywords
creator: Sanjar Sobirovich Kenjaev
creator: Akmal Rustamovich Akhatov
creator: Ma’ruf Ruziqulovich Tojiev
rights: Copyright (c) 2025 Sanjar Sobirovich Kenjaev, Akmal Rustamovich Akhatov, Ma’ruf Ruziqulovich Tojiev https://creativecommons.org/licenses/by/4.0
date: 2025-12-18
publication date: 2025-12-18
starting page: 70
ending page: 76

MUHIM XUSUSIYATLARNI ANIQLASH MASALASIDA TAKOMILLASHTIRILGAN GROVER ALGORITMI
type: item
description: Ushbu maqolada katta oʻlchamli ma’lumotlar toʻplamlarida muhim xususiyatlarni aniqlash masalasini hal etish uchun kvant Grover algoritmiga asoslangan takomillashtirilgan yondashuv taklif etiladi. Klassik statistik va mashinali oʻqitish usullari koʻp sonli xususiyatlar bilan ishlashda yuqori hisoblash murakkabligiga duch kelishi sababli, kvant hisoblash imkoniyatlaridan foydalanish dolzarb hisoblanadi. Tadqiqotda xususiyatlar kombinatsiyalarini baholash uchun Pearson korrelyatsiyasiga asoslangan maqsad funksiyasi ishlab chiqilib, Monte Karlo usuli yordamida qidiruv fazosi qisqartiriladi. Grover algoritmi doirasida Oracle operatori shakllantirilib, optimal xususiyatlar toʻplamining amplitudalarini kuchaytirish mexanizmi amalga oshiriladi. Shuningdek, xususiyatlar oʻrtasidagi statistik bogʻliqliklar kvant chalkashlik operatorlari orqali modellashtiriladi. Taklif etilgan yondashuv hisoblash samaradorligini oshirish, ortiqcha xususiyatlarni kamaytirish hamda yashirin korrelyatsion munosabatlarni aniqlash imkonini beradi. Natijada, model uchun eng informatsion xususiyatlar ajratib olinib, keyingi bashoratlash bosqichlarining aniqligi va barqarorligi oshiriladi.
subject: Technical sciences
  topic: section
subject: Kvant hisoblash
  topic: keywords
subject: Grover algoritmi
  topic: keywords
subject: Pearson korrelyatsiyasi
  topic: keywords
subject: xususiyatlarni tanlash
  topic: keywords
subject: kvant chalkashlik
  topic: keywords
subject: Oracle operatori
  topic: keywords
subject: kvant interferensiyasi
  topic: keywords
creator: Raximov Nodir Odilovich
creator: Primqulov Oybek Dilmurot oʻgʻli
rights: Copyright (c) 2025 Raximov Nodir Odilovich, Primqulov Oybek Dilmurot oʻgʻli https://creativecommons.org/licenses/by/4.0
date: 2025-08-28
publication date: 2025-08-28
starting page: 290
ending page: 295

TIBBIY MA’LUMOTLARNI TAHLIL QILISHNING INNOVATSION ALGORITMLARI ORQALI INSULTNI ERTA ANIQLASH
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: Fisher mezoni
  topic: keywords
subject: informativ belgi
  topic: keywords
subject: optimizatsiya
  topic: keywords
subject: nominal belgi
  topic: keywords
subject: qiymatli belgi
  topic: keywords
subject: sinflararo farqlanish
  topic: keywords
subject: o‘xshashlik ko‘rsatkichi
  topic: keywords
subject: funksional mezon
  topic: keywords
subject: informatsion vektor
  topic: keywords
subject: ma’lumotlar tahlili
  topic: keywords
subject: klassifikatsiya
  topic: keywords
subject: klasterlash
  topic: keywords
creator: Aktamov Shohruhbek Ulug’bek o’g’li
rights: Copyright (c) 2025 Aktamov Shohruhbek Ulug’bek o’g’li https://creativecommons.org/licenses/by/4.0
date: 2025-12-16
publication date: 2025-12-16
starting page: 62
ending page: 69

INTEGRATIVE MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING FRAMEWORK FOR THE DETECTION AND CLASSIFICATION OF AI-GENERATED TEXTS IN ACADEMIC RESEARCH PUBLICATIONS
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: AI-generated text detection
  topic: keywords
subject: academic integrity
  topic: keywords
subject: machine learning
  topic: keywords
subject: natural language processing
  topic: keywords
subject: BERT-based models
  topic: keywords
subject: Kaggle datasets
  topic: keywords
subject: ensemble classification
  topic: keywords
subject: Google Colab experiments
  topic: keywords
creator: Mukhriddin Mukhiddinov
creator: Kungratov Ilmurod Kuzibay ugli
creator: Mirzarahmatov Shahzodbek Ulugbekovich
creator: Sanakulov Otaniyoz Erjigit ugli
rights: Copyright (c) 2025 Mukhriddin Mukhiddinov, Kungratov Ilmurod Kuzibay ugli, Mirzarahmatov Shahzodbek Ulugbekovich, Sanakulov Otaniyoz Erjigit ugli https://creativecommons.org/licenses/by/4.0
date: 2025-12-15
publication date: 2025-12-15
starting page: 51
ending page: 61

QISHLOQ XO‘JALIGI MAHSULOTLARINI SAQLASHDA KO‘P BOSQICHLI ADAPTIV BOSHQARUV TIZIMI MODELI VA ALGORITMI
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: adaptiv boshqaruv
  topic: keywords
subject: ko‘p bosqichli jarayon
  topic: keywords
subject: matematik model
  topic: keywords
subject: dekompozitsiya
  topic: keywords
subject: parametr identifikatsiyasi
  topic: keywords
subject: optimizatsiya
  topic: keywords
subject: qishloq xo‘jaligi mahsulotlari
  topic: keywords
subject: saqlash jarayoni
  topic: keywords
subject: mikroiqlim
  topic: keywords
subject: adekvatlik
  topic: keywords
creator: Pirova Rashida Qudratovna
rights: Copyright (c) 2025 Pirova Rashida Qudratovna https://creativecommons.org/licenses/by/4.0
date: 2025-12-15
publication date: 2025-12-15
starting page: 43
ending page: 50

YEYILISH DINAMIKASINI TADQIQ ETISHDA EMPERIK TENGLAMALARNI KELTIRIB CHIQARISHDA MAHSUS DASTURLARDAN FOYDALANISHNING ISTIQBOLLARI
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: Tuproq
  topic: keywords
subject: resurs
  topic: keywords
subject: o‘qyoysimon panja
  topic: keywords
subject: abraziv yeyilish
  topic: keywords
subject: ishchi organ
  topic: keywords
subject: tuproq zinchligi
  topic: keywords
subject: tuproq qattiqligi va tuproq namligi
  topic: keywords
creator: Kuvandikov Yokub Tursunbayevich
creator: Kabilov Begzod Uktam o‘g‘li
rights: Copyright (c) 2025 Kuvandikov Yokub Tursunbayevich, Kabilov Begzod Uktam o‘g‘li https://creativecommons.org/licenses/by/4.0
date: 2025-12-12
publication date: 2025-12-12
starting page: 39
ending page: 42

TURKIY TILLAR GRAMMATIKASINING KOMPYUTERGA YO‘NALTIRILGAN FORMAL MODELLARI TAHLILI
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: Statistical Models
  topic: keywords
subject: Neural Network Models
  topic: keywords
subject: Rule Based Grammars
  topic: keywords
subject: Hybrid NLP
  topic: keywords
creator: Norov Abdisait Muradovich
rights: Copyright (c) 2025 Norov Abdisait Muradovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-12
publication date: 2025-12-12
starting page: 27
ending page: 31

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
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: Game development
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: machine learning
  topic: keywords
subject: recommender systems
  topic: keywords
subject: monetization
  topic: keywords
subject: video games
  topic: keywords
subject: digital economy
  topic: keywords
subject: user experience
  topic: keywords
subject: data science
  topic: keywords
creator: Shvets Stanislav Fedorovich
rights: Copyright (c) 2025 Shvets Stanislav Fedorovich https://creativecommons.org/licenses/by/4.0
date: 2025-12-12
publication date: 2025-12-12
starting page: 19
ending page: 26

MODAL GRAPH TRANSFORMER FOR GROUP ENGAGEMENT IN ONLINE MULTIPARTY CONVERSATIONS
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: hop-level positional encoding
  topic: keywords
subject: Graph Transformer
  topic: keywords
subject: group engagement
  topic: keywords
subject: multimodal learning
  topic: keywords
subject: social signal processing
  topic: keywords
subject: collaborative learning
  topic: keywords
creator: Pirimqulova Zilola Avaz qizi
creator: Hojiyev Sunatullo Nasridin o‘g‘li
creator: Xo‘jamqulov Abdulaziz Xazrat o‘g‘li
rights: 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
date: 2025-12-12
publication date: 2025-12-12
starting page: 12
ending page: 18

SSRE-ID: KO‘P OBYETLAR KUZATUVLARIDA TO‘LIQ O‘Z-O‘ZINI O‘QITISHGA ASOSLANGAN QAYTA IDENTIFIKATSIYALASH
type: item
description: 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
subject: Technical sciences
  topic: section
subject: Ko‘p obyektli kuzatuv(MOT)
  topic: keywords
subject: Self-supervised learning
  topic: keywords
subject: reID
  topic: keywords
creator: Pirimqulova Zilola Avaz qizi
creator: Hojiyev Sunatullo Nasridin o‘g‘li
creator: Xo‘jamqulov Abdulaziz Xazrat o‘g‘li
rights: 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
date: 2025-12-09
publication date: 2025-12-09
starting page: 1
ending page: 11

COMPARATIVE ANALYSIS OF PHYSICAL DEVELOPMENT IN CHILDREN ENGAGED IN SPORTS AND PHYSICAL EDUCATION
type: item
description: 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
subject: Technical sciences
  topic: section
subject: physical development
  topic: keywords
subject: youth sports
  topic: keywords
subject: health
  topic: keywords
subject: education
  topic: keywords
subject: children
  topic: keywords
subject: rhythmic gymnastics
  topic: keywords
subject: swimming
  topic: keywords
creator: Usmankhodjaeva Adibakhon Amirsaidovna
creator: Rakhmatova Fotima Utkirovna
rights: Copyright (c) 2025 Usmankhodjaeva Adibakhon Amirsaidovna, Rakhmatova Fotima Utkirovna https://creativecommons.org/licenses/by/4.0
date: 2025-10-28
publication date: 2025-10-28
starting page: 290
ending page: 296

TARMOQ MA’LUMOTLARIGA INTELLEKTUAL ISHLOV BERISH MODELLARI VA USULLARI
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: tarmoq ma’lumotlari
  topic: keywords
subject: intellektual ishlov berish
  topic: keywords
subject: sun’iy intellekt
  topic: keywords
subject: mashinali o‘qitish
  topic: keywords
subject: ma’lumotlar mayningi
  topic: keywords
subject: graf neyron tarmoqlari
  topic: keywords
subject: anomaliya aniqlash
  topic: keywords
creator: Mo‘minov Bahodir Boltayevich
creator: Husanov Sherzod Abdimonnonovich
rights: Copyright (c) 2025 Mo‘minov Bahodir Boltayevich, Husanov Sherzod Abdimonnonovich https://creativecommons.org/licenses/by/4.0
date: 2025-06-28
publication date: 2025-06-28
starting page: 280
ending page: 288

O‘ZBEK TILIDAGI GAPLARNI PERIFRAZ QILISH AXBOROT TIZIMINING FUNKSIONAL JARAYONLARINI LOYIHALASHTIRISH
type: item
description: 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.
subject: Technical sciences
  topic: section
subject: biznes-jarayon
  topic: keywords
subject: modellashtirish
  topic: keywords
subject: perifraz
  topic: keywords
subject: axborot tizimi
  topic: keywords
subject: semantik analizator
  topic: keywords
creator: Axmedova Xusniya Xusanovna
rights: Copyright (c) 2025 Axmedova Xusniya Xusanovna https://creativecommons.org/licenses/by/4.0
date: 2025-10-28
publication date: 2025-10-28
starting page: 283
ending page: 289