International Bulletin of Applied Science and Technology
type: channel
description: International Bulletin of Applied Sciences and Technology - (ISSN-2750-3402) is an open access international peer reviewed german journal. IBAST publishes research monthly frequency basis. we explore your research worldwide by international Database indexings. we provide all articles crossref metadata link, google scholar, microsoft academic, Metadata Indexing and much more worldwide international indexings.
publisher: Rseearch International Journals
language: en
publication name: International Bulletin of Applied Science and Technology
issn: 2750-3402
copyright: Articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). Under this license: Share: Copy and redistribute the material in any medium or format Adapt: Remix, transform, and build upon the material for any purpose, including commercially Attribution required: You must give appropriate credit, provide a link to the license, and indicate if changes were made. License URL: https://creativecommons.org/licenses/by/4.0/ Authors retain copyright of their work while granting the journal first publication rights.
items: UPCYCLING ASOSIDA ZAMONAVIY LIBOS KOLLEKSIYALARINI YARATISH
items: ЕNHАNCING ЕFFICIЕNCY, RЕLIАBILITY, АND SUSTАINАBILITY IN THЕ ЕNЕRGY SЕCTOR THROUGH THЕ АPPLICАTION OF DIGITАL TЕCHNOLOGIЕS
items: ALKALINE WATER ELECTROLYSIS FOR HYDROGEN PRODUCTION IN HIGH-IRRADIANCE REGIONS: STATE OF THE ART, EXPERIMENTAL EVIDENCE, AND PROSPECTS FOR UZBEKISTAN
items: PHOTOVOLTAIC-DRIVEN ALKALINE ELECTROLYSIS AS A PATHWAY TO DECENTRALISED GREEN HYDROGEN: A CRITICAL REVIEW
items: DISCHARGE PROCESS IN DIELECTRICS
items: STRUCTURAL COMPONENTS OF FAMILY DISCOURSE
items: THE SOCIO-PEDAGOGICAL NECESSITY OF FORMING SPIRITUAL IMMUNITY IN STUDENTS BASED ON THE TRANSFORMATION OF DOGMATIC TEACHING ELEMENTS
items: ZAMONAVIY TA’LIM STANDARTLARI VA KOMPETENSIYAVIY YONDASHUV
items: Integrated Reward-Guided Neural Intelligence Framework For Efficient Settlement Lag Management In Commercial Logistics Funding
items: Collaborative Machine Intelligence Approach For Streamlining Invoice Processing In Business Capital Management
items: Advanced Decision-Oriented Neural Framework for Improving Financial Settlement Performance Across Distribution Networks
items: THE ROLE AND IMPORTANCE OF ROBOTIZED TECHNICAL MEANS IN COMBAT ACTIONS
items: Smart Learning-Based Optimization Technique For Accurate Resource Planning Across Logistics Operations
items: СУБКУЛЬТИВИРОВАНИЕ РАСТЕНИЙ ЧУБУШНИКА (PHILADELPHUS L.) В КУЛЬТУРЕ IN VITRO И ИХ EX VITRO АККЛИМАТИЗАЦИЯ В УСЛОВИЯХ РЕСПУБЛИКИ КАРАКАЛПАКСТАН
items: Autonomous Decision Intelligence System Delivering Superior Predictive Performance Across Distribution Resource Planning
items: RAQOBATBARDOSH MARKETING STRATEGIYALARINI SHAKLLANTIRISH ORQALI KORXONA FAOLIYATI SAMARADORLIGINI OSHIRISH
items: SCIENTIFIC ANALYSIS AND FUTURE POSSIBILITIES OF SOLAR PANELS
items: SOLAR-DRIVEN ALKALINE WATER SPLITTING FOR GREEN HYDROGEN GENERATION: ROLE OF ELECTROLYTE COMPOSITION, ELECTRODE SELECTION, AND PHOTOVOLTAIC POWER MANAGEMENT
items: SOLAR-POWERED ALKALINE WATER ELECTROLYSIS FOR GREEN HYDROGEN GENERATION: A LITERATURE REVIEW
items: INVESTIGATION OF THE CHARACTERISTICS OF FRUIT PRESERVATION TECHNOLOGY IN AN IONIZED ENVIRONMENT
items: Identification Of Concealed User Profiles Via Modern Similarity-Based Classification Approaches
items: BADIIY ASARLARDA O’QITUVCHI OBRAZI
items: IMPROVING MECHANISMS FOR DEVELOPING 4C (4K) COMPETENCIES IN A DIGITAL EDUCATIONAL ENVIRONMENT
items: THE RELATIONSHIP BETWEEN INDIVIDUAL STYLE AND SOCIAL LANGUAGE UNITS IN LITERARY DISCOURSE
items: SOCIOLECTS THAT CREATE INDIVIDUAL SPEECH IN LITERARY DISCOURSE
items: ON THE HISTORY OF THE DEVELOPMENT OF MILITARY MODELING
items: IMPROVING SOCIAL ACTIVITY COMPETENCE OF PROSPECTIVE TEACHERS THROUGH PROJECT-BASED AND REFLECTIVE LEARNING
items: DEVELOPING STUDENTS’ INDEPENDENT THINKING THROUGH THE CASE-METHOD APPROACH
items: WAYS TO IMPROVE INVESTMENT EFFICIENCY IN THE TRANSITION TO A GREEN ECONOMY: INTERNATIONAL EXPERIENCE AND PROSPECTS FOR UZBEKISTAN
items: Assessing Digital Intelligence-Based Planning Architectures for Improved Operational Outcomes and Resource Utilization

UPCYCLING ASOSIDA ZAMONAVIY LIBOS KOLLEKSIYALARINI YARATISH
type: item
description: Mazkur maqolada zamonaviy moda sanoatida keng qo‘llanilayotgan upcycling (qayta ishlash orqali qiymatni oshirish) tamoyillari, uning ekologik va iqtisodiy ahamiyati hamda ushbu yondashuv asosida zamonaviy libos kolleksiyalarini yaratish metodikasi tahlil qilinadi. Tadqiqotda eskirgan yoki foydalanilmay qolgan matolar, tayyor kiyimlar va tikuvchilik chiqindilaridan yangi, estetik va tijorat jihatdan raqobatbardosh liboslar yaratish bosqichlari, dizayn yechimlari hamda O‘zbekiston tikuvchilik-trikotaj sanoatida upcycling texnologiyasini joriy etish istiqbollari yoritiladi. Muallif tomonidan amaliy tavsiyalar va kolleksiya yaratish algoritmi taklif etiladi.
subject: Articles
  topic: section
subject: upcycling, ekomoda, qayta ishlangan matolar, barqaror dizayn, libos kolleksiyasi, tikuvchilik chiqindilari, zero waste, moda sanoati, ijodiy dizayn.
  topic: keywords
creator: Mahinbonu Akramova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 274
ending page: 277
doi: 10.37547/

ЕNHАNCING ЕFFICIЕNCY, RЕLIАBILITY, АND SUSTАINАBILITY IN THЕ ЕNЕRGY SЕCTOR THROUGH THЕ АPPLICАTION OF DIGITАL TЕCHNOLOGIЕS
type: item
description: Thе аrticlе ехаminеs thе implеmеntаtion аnd dеvеlopmеnt of digitаl tеchnologiеs in thе еnеrgy sеctor. It discussеs thе trаnsition from trаditionаl mаnаgеmеnt systеms to thе concеpt of digitаl еnеrgy, thе intеgrаtion of big dаtа, аutomаtеd control аlgorithms, аnd cloud аnd fog computing to еnhаncе thе еfficiеncy, rеliаbility, аnd sаfеty of еnеrgy infrаstructurе. Digitаl еnеrgy systеms еnаblе rеmotе monitoring аnd control, аdvаncеd diаgnostics аnd prognostics, аs wеll аs cybеrsеcurity, аllowing for rаpid dеtеction of еmеrgеnciеs аnd minimizаtion of humаn еrrors. Spеciаl аttеntion is givеn to thе importаncе of nаtionаl tеchnologiеs аnd locаlly dеvеlopеd softwаrе аnd hаrdwаrе solutions to еnsurе tеchnologicаl sovеrеignty аnd systеm rеsiliеncе. Thе аrticlе highlights thе rolе of digitаl solutions in improving thе еfficiеncy, sаfеty, аnd еnvironmеntаl sustаinаbility of еnеrgy systеm opеrаtions.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Digitаl еnеrgy, еnеrgy sеctor, smаrt grids, rеmotе monitoring, аdvаncеd diаgnostics, prеdictivе mаintеnаncе, cybеr-physicаl systеms, Intеrnеt of Things (IoT), fog computing, еnеrgy systеm еfficiеncy, cybеrsеcurity, intеgrаtion of rеnеwаblе еnеrgy sourcеs, tеchnologicаl sovеrеignty.
creator: Mukhаmmаd-Bobur Khodjimаtov
creator: Muslimbek Abdikhoshimov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 269
ending page: 273
doi: 10.37547/

ALKALINE WATER ELECTROLYSIS FOR HYDROGEN PRODUCTION IN HIGH-IRRADIANCE REGIONS: STATE OF THE ART, EXPERIMENTAL EVIDENCE, AND PROSPECTS FOR UZBEKISTAN
type: item
description: The combination of falling photovoltaic costs and rising policy pressure on carbon-intensive hydrogen production has created a compelling economic and environmental case for solar-powered alkaline water electrolysis (AEL). This review synthesises experimental data from four peer-reviewed publications produced at Andijan State Technical Institute (ASTI) [3–6] alongside seventeen international studies to examine the state of knowledge on electrolyte chemistry, electrode materials, and photovoltaic power integration. The ASTI dataset covers a 5-order-of-magnitude range of current density (3 mA cm⁻² to 500 mA cm⁻²), two electrode substrates (316L stainless steel and Ni-Mo alloy), and both direct and MPPT-mediated PV coupling. Across this parameter space, three design principles emerge as robust: (i) 30 wt% KOH at 60–80°C maximises ionic conductivity and electrode durability; (ii) the anode is the primary energy bottleneck on bare 316L, contributing 45% of total voltage loss and representing the highest-return upgrade target; and (iii) MPPT control captures 12–24% additional solar energy relative to direct coupling. Applying these principles to the Andijan solar resource, a 5 kW PV system can yield 160–180 kg of emission-free hydrogen per year at a levelised cost of $5–8 kg⁻¹, with a clear technical roadmap to below $5 kg⁻¹ through electrode coating and current density scaling.
subject: Articles
  topic: section
subject: alkaline water electrolysis, solar hydrogen, KOH electrolyte, SS316L electrode, NiFe-LDH, MPPT control, LCOH, Central Asia.
  topic: keywords
creator: Sh.K. Bakhramov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 262
ending page: 268
doi: 10.37547/

PHOTOVOLTAIC-DRIVEN ALKALINE ELECTROLYSIS AS A PATHWAY TO DECENTRALISED GREEN HYDROGEN: A CRITICAL REVIEW
type: item
description: Decentralised green hydrogen generation through photovoltaic-driven alkaline water electrolysis (AEL) is attracting growing research interest as the cost of solar electricity approaches parity with grid power across much of the developing world. This paper critically examines the published evidence on three pillars of system performance: the thermodynamic and kinetic roles of the electrolyte; the catalytic and durability properties of electrode materials available at low cost; and the power-conditioning strategies required to interface a variable photovoltaic source with the largely ohmic load of an AEL stack. Four experimental papers from Andijan State Technical Institute (ASTI) [3–6] are analysed within the context of seventeen international studies to identify design principles applicable to high-irradiance, resource-limited settings. The review concludes that 30 wt% KOH, 316L stainless steel electrodes operated below 10 mA cm⁻², and MPPT-equipped power converters together constitute a technically sound and economically accessible entry configuration, capable of yielding 160–180 kg H₂ yr⁻¹ from a 5 kW solar array under Uzbekistan conditions. Pathways to reduce the levelised hydrogen cost below $5 kg⁻¹ are discussed.
subject: Articles
  topic: section
subject: green hydrogen, alkaline electrolyzer, photovoltaic coupling, KOH electrolyte, 316L stainless steel, MPPT, levelised cost of hydrogen, Uzbekistan.
  topic: keywords
creator: Sh.K. Bakhramov
creator: M.U. Qosimov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 254
ending page: 261
doi: 10.37547/

DISCHARGE PROCESS IN DIELECTRICS
type: item
description: In the process of ionization, positive ions appear between the electrodes and move towards the cathode. Due to the difference in mobility of electrons and ions, during the movement of the electron beam to the anode, the positive ions remain in the place where they appeared. It is known that due to many ionizers in nature (space particles, radioactive radiation, ultraviolet radiation of the sun), free electrons continuously appear between the electrodes. A continuous avalanche of electrons occurs under the influence of the voltage placed between the electrodes
subject: Articles
  topic: section
subject: electrodes, discharge, ionization, charge, voltage, dielektr, gas, amper, transformation, energy
  topic: keywords
creator: Muslimbek Abdixoshimov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 248
ending page: 253
doi: 10.37547/

STRUCTURAL COMPONENTS OF FAMILY DISCOURSE
type: item
description: This article examines the concept of family discourse, its structural components, and its sociolinguistic features within the Uzbek family. It analyzes the role of social positions, hierarchical statuses, and norms of verbal behavior in family communication. The study highlights the relationships of dominance and subordination in the speech of roles such as father, mother, child, and mother-in-law/daughter-in-law, as expressed through forms of address and emotive-pragmatic tools.
subject: Articles
  topic: section
subject: family discourse, social status, speech behavior, linguistic communication, hierarchy, dominance, forms of address, pragmatics, Uzbek family, social role.
  topic: keywords
creator: Saidaxon Numonova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 240
ending page: 247
doi: 10.37547/

THE SOCIO-PEDAGOGICAL NECESSITY OF FORMING SPIRITUAL IMMUNITY IN STUDENTS BASED ON THE TRANSFORMATION OF DOGMATIC TEACHING ELEMENTS
type: item
description: This article provides a scientific and theoretical justification for the socio-pedagogical necessity of fostering spiritual immunity among students amidst globalization, the information age, and digital transformation. The study analyzes opportunities to develop students' independent thinking, critical reasoning, conscious attitude toward values, and spiritual stability by transforming elements of traditional dogmatic education through modern pedagogical approaches. Furthermore, the restructuring of dogmatic educational elements in alignment with the requirements of the modern educational paradigm is substantiated as a crucial pedagogical factor in building spiritual immunity. The author elucidates the socio-pedagogical essence of this process and highlights its practical significance.
subject: Articles
  topic: section
subject: spiritual immunity, dogmatic education, transformation, student, pedagogical transformation, value, critical thinking, spiritual security, higher education.
  topic: keywords
creator: Gulxayo Omonova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 234
ending page: 239
doi: 10.37547/

ZAMONAVIY TA’LIM STANDARTLARI VA KOMPETENSIYAVIY YONDASHUV
type: item
description: Ushbu maqolada professional ta’lim jarayonida zamonaviy ta’lim vositalari imkoniyatlaridan foydalanishning pedagogik jihatlari bayon etilgan. Shuningdek, zamonaviy ta’lim vositalarining professional ta’lim jarayonidagi o‘rni va ahamiyati yoritib berilgan. Zamonaviy ta’lim vositalari samaradorligini ta’minlaydigan didaktik tamoyillar tahlil qilingan. Jumladan, mavjudlik, ilmiylik, tasviriylik, onglilik va ijodiy faollik, tizimlilik, ta’limni hayot va amaliyot bilan bog‘lash, bilimlarni o‘zlashtirishning mustahkamligi va o‘quvchilarning kognitiv kuchlarini rivojlantirish kabi tamoyillar keltirib o‘tilgan.Bundan tashqari maqolada kompetensiyaviy yondashuvlarga asoslangan ta’limning bir qator jihatlari ko’rib o’tilgan. Xususan kasbiy, amaliy kompetentlik turlari va ularning rivojlanish bosqichlari haqida fikr yuritilgan.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: kompetentlik, baholash, ma’lumot, o’qituvchi, o’quvchilar, munosabat, shaxsiy, amaliy, ijtimoiy, tashabbuskor, professional ta’lim, kasbiy tayyorlash, ta’lim vositalari, innovatsion ta’lim vositalari, an’anaviy o‘qitish vositalari, o‘quv-uslubiy ta’minot.
creator: Azizabonu Ochilova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-31
publication date: 2026-07-31
starting page: 228
ending page: 233
doi: 10.37547/

Integrated Reward-Guided Neural Intelligence Framework For Efficient Settlement Lag Management In Commercial Logistics Funding
type: item
description: The rapid expansion of commercial logistics networks has increased the complexity of financial settlement processes, where delayed payments, inventory uncertainty, transportation dependencies, and capital flow interruptions create significant operational inefficiencies. Traditional logistics financing systems generally rely on predefined rules and static optimization methods that struggle to adapt to dynamic market conditions, changing transaction patterns, and heterogeneous supply chain structures. This research proposes an Integrated Reward-Guided Neural Intelligence Framework (IRGNIF) designed to improve settlement lag management by combining adaptive decision intelligence, reinforcement-based optimization, and neural learning mechanisms. The proposed framework integrates transaction monitoring, logistics state analysis, reward-driven decision adjustment, and predictive financial optimization to reduce settlement delays and enhance capital circulation efficiency. The conceptual foundation of the framework is derived from decision optimization approaches in logistics, inventory management, and intelligent financial systems. Previous research has demonstrated that integrated transportation and inventory decision models can improve operational coordination by balancing resource allocation and timing constraints (CAO Xue ming et al., 2006). Similarly, inventory-oriented optimization studies emphasize the importance of adaptive strategies for managing uncertainty and improving supply chain responsiveness (Fleischmann et al., 2002). Building upon these principles, this study introduces a neural intelligence architecture where financial settlement decisions are continuously refined through feedback-based learning. The proposed methodology consists of four major components: logistics-financial data acquisition, neural state representation, reward-guided settlement optimization, and adaptive decision execution. The framework evaluates transaction conditions, payment risks…
subject: Articles
  topic: section
subject: Neural Intelligence
  topic: keywords
subject: Reinforcement Learning
  topic: keywords
subject: Logistics Finance
  topic: keywords
subject: Settlement Optimization
  topic: keywords
creator: Dr. Vikram Singh
rights: Copyright (c) 2026 Dr. Vikram Singh https://creativecommons.org/licenses/by/4.0
date: 2026-08-01
publication date: 2026-08-01
starting page: 01
ending page: 09

Collaborative Machine Intelligence Approach For Streamlining Invoice Processing In Business Capital Management
type: item
description: The increasing adoption of artificial intelligence (AI) has transformed business capital management by enabling intelligent systems for improving financial efficiency and decision-making. Invoice processing remains a critical operational activity but faces challenges such as manual verification, delayed approvals, inconsistent data processing, and limited integration between automation and human expertise. This research proposes a Collaborative Machine Intelligence (CMI) approach that combines AI-driven automation with human financial judgment to improve invoice management. The study uses a conceptual research methodology based on existing literature related to human-machine collaboration, generative artificial intelligence, intelligent systems, and financial optimization. The proposed framework integrates intelligent invoice acquisition, AI-based document analysis, collaborative validation, predictive capital management, and continuous learning mechanisms. Unlike traditional automation approaches focused on replacing human activities, CMI emphasizes cooperation where machines handle data-intensive tasks while humans provide contextual interpretation and strategic decisions. The findings suggest that CMI can improve invoice processing speed, payment accuracy, cash-flow visibility, and capital allocation efficiency. However, successful implementation requires addressing challenges related to data quality, transparency, organizational readiness, and human-machine interaction. This research contributes to intelligent financial management by presenting a collaborative framework that extends beyond conventional automation toward sustainable AI-enabled business transformation.
subject: Articles
  topic: section
subject: Collaborative Machine Intelligence
  topic: keywords
subject: Invoice Processing
  topic: keywords
subject: Business Capital Management
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
creator: Dr. Aino Virtanen Korhonen
rights: Copyright (c) 2026 Dr. Aino Virtanen Korhonen https://creativecommons.org/licenses/by/4.0
date: 2026-06-30
publication date: 2026-06-30
starting page: 790
ending page: 794

Advanced Decision-Oriented Neural Framework for Improving Financial Settlement Performance Across Distribution Networks
type: item
description: Financial settlement efficiency has become a critical factor in modern distribution networks due to increasing transaction complexity, interconnected supply chains, and the need for faster capital circulation. Traditional settlement mechanisms often depend on rule-based systems and delayed decision processes, which can create inefficiencies in payment coordination, liquidity management, and financial risk control. This research proposes an Advanced Decision-Oriented Neural Framework (ADNF) designed to improve financial settlement performance across distribution networks through intelligent decision-making, predictive analysis, and adaptive learning capabilities. The study adopts a conceptual research methodology based on the integration of neural intelligence, financial decision optimization, and digital financial management principles. The proposed framework combines transaction data processing, predictive settlement analysis, intelligent risk evaluation, and adaptive decision optimization to support efficient financial operations. Unlike conventional automation approaches that focus primarily on transaction execution, the proposed framework emphasizes decision-oriented intelligence, enabling systems to recommend optimal settlement strategies according to dynamic financial conditions. The theoretical foundation of this research is supported by studies examining financial development, digital financial services, banking efficiency, and intelligent payment optimization. Financial systems play an important role in economic efficiency by improving capital allocation and transaction effectiveness (Levine, 1999). Similarly, advanced learning-based approaches have demonstrated potential for optimizing payment-related decisions in supply chain finance (SinghJatav et al., 2025). The proposed framework identifies four major capabilities: intelligent transaction monitoring, neural-based settlement prediction, adaptive financial decision support, and continuous optimization. T…
subject: Articles
  topic: section
subject: Decision-Oriented Neural Framework
  topic: keywords
subject: Financial Settlement
  topic: keywords
subject: Distribution Networks
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
creator: Dr. Claire Martin Dubois
rights: Copyright (c) 2026 Dr. Claire Martin Dubois https://creativecommons.org/licenses/by/4.0
date: 2026-05-30
publication date: 2026-05-30
starting page: 676
ending page: 682

THE ROLE AND IMPORTANCE OF ROBOTIZED TECHNICAL MEANS IN COMBAT ACTIONS
type: item
description: This article analyzes the importance and widespread use of robotic equipment (RTV) in the context of the ongoing military conflict between Ukraine and Russia and their impact on combat operations. In this regard, the strategies, tactical tasks, and directions for implementing robotic platforms of the NATO, Ukrainian, and Russian armies will be considered.
subject: Articles
  topic: section
subject: robotics, platform, robotics.
  topic: keywords
creator: B.В. Chorshanbiyev
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-30
publication date: 2026-07-30
starting page: 224
ending page: 227
doi: 10.37547/

Smart Learning-Based Optimization Technique For Accurate Resource Planning Across Logistics Operations
type: item
description: The rapid evolution of logistics networks, driven by increasing market volatility, globalization, and the complexity of supply chain ecosystems, has created a significant demand for intelligent resource planning approaches capable of improving operational accuracy and adaptability. Traditional resource allocation methods in logistics often rely on historical trends, manual decision-making, and static optimization models, which are insufficient for handling dynamic transportation conditions, fluctuating demand patterns, and multi-dimensional operational constraints. This research presents a smart learning-based optimization technique for accurate resource planning across logistics operations by integrating data-driven intelligence, machine learning principles, predictive analytics, and adaptive optimization mechanisms. The proposed conceptual framework focuses on utilizing heterogeneous operational data, intelligent forecasting models, and continuous learning approaches to enhance resource utilization, reduce inefficiencies, and improve decision accuracy. The study develops a research-oriented optimization framework that combines multi-source data integration, intelligent prediction, and reinforcement-based decision mechanisms for logistics resource planning. The theoretical foundation of the framework is aligned with recent developments in intelligent construction management, spatial data fusion, deep learning applications, and supply chain optimization. Existing research demonstrates that information-based management systems and intelligent technologies significantly influence operational efficiency by improving data accessibility, automation capability, and decision support mechanisms (Liu, 2025; Xing, 2025). Furthermore, deep learning-based approaches for complex data environments provide opportunities for improved modeling accuracy and real-time operational analysis (Sun et al., 2024; Yang et al., 2025).
subject: Articles
  topic: section
subject: Smart learning
  topic: keywords
subject: Logistics optimization
  topic: keywords
subject: Resource planning
  topic: keywords
subject: Machine learning
  topic: keywords
creator: Dr. Camila Martínez Herrera
rights: Copyright (c) 2026 Dr. Camila Martínez Herrera https://creativecommons.org/licenses/by/4.0
date: 2026-07-30
publication date: 2026-07-30
starting page: 189
ending page: 196

СУБКУЛЬТИВИРОВАНИЕ РАСТЕНИЙ ЧУБУШНИКА (PHILADELPHUS L.) В КУЛЬТУРЕ IN VITRO И ИХ EX VITRO АККЛИМАТИЗАЦИЯ В УСЛОВИЯХ РЕСПУБЛИКИ КАРАКАЛПАКСТАН
type: item
description: В статье рассматривается возможность размножения растений рода Чубушник способом микроклонирования, а так же оценка эффективности ex vitro акклиматизации растений чубушника (Philadelphus L.), выращенных в культуре in vitro, в условиях Республики Каракалпакстан.
subject: Articles
  topic: section
subject: чубушник, микроклональное размножение, in vitro, питательная среда WPM (Woody Plant Medium), ризонегез, акклиматизация ex vitro.
  topic: keywords
creator: Айгуль Ешмуратова
creator: Несибели Бердимуратова
creator: Бахтыгул Пирланова
creator: Абдирашит Мирзамбетов
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-30
publication date: 2026-07-30
starting page: 219
ending page: 223
doi: 10.37547/

Autonomous Decision Intelligence System Delivering Superior Predictive Performance Across Distribution Resource Planning
type: item
description: Distribution resource planning has evolved into a strategic function that requires intelligent decision-making capabilities capable of responding to dynamic market conditions, uncertain demand, and increasingly complex logistics networks. Conventional forecasting approaches often struggle to process large-scale operational data and adapt to rapidly changing supply chain environments, resulting in suboptimal inventory allocation, delayed deliveries, and increased operational costs. The emergence of autonomous decision intelligence integrates artificial intelligence, predictive analytics, and adaptive learning mechanisms to support real-time planning decisions with minimal human intervention. This study investigates the design and application of an Autonomous Decision Intelligence System (ADIS) for improving predictive performance in distribution resource planning. The proposed framework combines data acquisition, feature engineering, predictive modeling, autonomous decision optimization, and continuous feedback mechanisms to enhance planning efficiency across interconnected distribution networks. The research adopts a conceptual methodology supported by an analytical review of existing literature and theoretical foundations associated with intelligent forecasting and autonomous decision-making systems. Special emphasis is placed on predictive intelligence, adaptive optimization, and continuous learning capabilities that enable organizations to improve forecasting precision under uncertain operational conditions. The proposed architecture illustrates how integrated decision intelligence can synchronize inventory management, warehouse operations, transportation scheduling, and demand planning while minimizing forecasting errors and improving resource utilization. Recent developments in deep reinforcement learning further demonstrate that adaptive decision models significantly improve forecasting accuracy in supply chain optimization by continuously learning from operat…
subject: Articles
  topic: section
subject: Autonomous Decision Intelligence
  topic: keywords
subject: Distribution Resource Planning
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
creator: Dr. Priyanshi Dev
rights: Copyright (c) 2026 Dr. Priyanshi Dev https://creativecommons.org/licenses/by/4.0
date: 2026-06-30
publication date: 2026-06-30
starting page: 779
ending page: 788

RAQOBATBARDOSH MARKETING STRATEGIYALARINI SHAKLLANTIRISH ORQALI KORXONA FAOLIYATI SAMARADORLIGINI OSHIRISH
type: item
description: Ushbu maqolada raqobatbardosh marketing strategiyalarini shakllantirishning nazariy-metodologik asoslari yoritilgan. Korxonaning bozordagi raqobat mavqeini mustahkamlashda SWOT-tahlil, farqlanish (differensiatsiya) va pozitsionerlash usullarining ahamiyati ko'rsatib berilgan. Raqobatbardosh strategiyalarni tanlash mezonlari, ularni amalga oshirishda uchraydigan muammolar tahlil qilingan hamda korxona faoliyati samaradorligini oshirish bo'yicha ilmiy-amaliy tavsiyalar ishlab chiqilgan.
subject: Articles
  topic: section
subject: raqobatbardoshlik, marketing strategiyasi, SWOT-tahlil, differensiatsiya, pozitsionerlash, bozor ulushi, korxona samaradorligi.
  topic: keywords
creator: Maxsuma Sayfullayeva
creator: Sherali Mamatqobilov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-28
publication date: 2026-07-28
starting page: 212
ending page: 218
doi: 10.37547/

SCIENTIFIC ANALYSIS AND FUTURE POSSIBILITIES OF SOLAR PANELS
type: item
description: This article presents a scientific analysis of the working principles, energy efficiency, and future development prospects of solar panels. The physical foundations of the photovoltaic phenomenon, different types of solar panels, and their environmental and economic advantages are discussed. In addition, the efficiency of solar panels under the climatic conditions of Uzbekistan was studied using the examples of Tashkent, Samarkand, and Navoi regions, while the effects of temperature and solar radiation were analyzed. The article also examines the prospects of perovskite and tandem technologies, energy storage systems, and intelligent monitoring systems based on artificial intelligence.
subject: Articles
  topic: section
subject: solar panels, solar energy, efficiency, renewable energy, photovoltaic phenomenon, lithium-ion and sodium-ion batteries, silicon panels, solar radiation, artificial intelligence, carbon dioxide.
  topic: keywords
creator: Mukhammad-Bobur Khodjimatov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-28
publication date: 2026-07-28
starting page: 207
ending page: 211
doi: 10.37547/

SOLAR-DRIVEN ALKALINE WATER SPLITTING FOR GREEN HYDROGEN GENERATION: ROLE OF ELECTROLYTE COMPOSITION, ELECTRODE SELECTION, AND PHOTOVOLTAIC POWER MANAGEMENT
type: item
description: Three student research projects conducted at Andijan State Technical Institute are unified in this paper to deliver a system-level perspective on solar-powered alkaline hydrogen generation. The first project (Ibrohimov O.B.) screened five alkaline solutions — KOH at two concentrations, NaOH at two concentrations, and K₂CO₃ — with respect to ionic conductivity and long-term electrochemical stability. The second project (Yunusov Kh.F.) characterised five electrode configurations, ranging from conventional 316L stainless steel to a bespoke Ni-Mo cathode / NiFe-oxide anode pairing. The third project (Keldiboyev I.I.) quantified how maximum-power-point-tracking (MPPT) control shapes the annual hydrogen output of a grid-independent photovoltaic (PV) electrolyzer. Taken together, the data establish that a 5 kW PV installation operating under Andijan irradiance conditions, filled with 30 wt% KOH, and fitted with Ni-Mo | NiFe composite electrodes plus MPPT control, can deliver 160–180 kg of emission-free hydrogen annually.
subject: Articles
  topic: section
subject: green hydrogen, alkaline electrolysis, potassium hydroxide, Ni-Mo electrode, NiFe oxide, overpotential, MPPT, photovoltaic integration, Uzbekistan.
  topic: keywords
creator: Sh.K. Bakhramov
creator: O.B. Ibrohimov
creator: I.I. Keldiboyev
creator: h.F. Yunusov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-28
publication date: 2026-07-28
starting page: 202
ending page: 206
doi: 10.37547/

SOLAR-POWERED ALKALINE WATER ELECTROLYSIS FOR GREEN HYDROGEN GENERATION: A LITERATURE REVIEW
type: item
description: This paper presents a focused review of recent advances in solar-photovoltaic-coupled alkaline water electrolysis (AEL) for green hydrogen production, with particular attention to experimental findings from the authors' own research group at Andijan State Technical Institute (ASTI). Four publications from ASTI are synthesised alongside the broader international literature to map the current state of knowledge across three interrelated sub-topics: electrolyte selection and operating parameter optimisation, electrode material performance and durability, and photovoltaic-electrolyzer power integration. Key findings are that 30 wt% KOH at 60–80°C is the near-universal optimum electrolyte condition; that 316L stainless steel provides commercially adequate durability (corrosion rate < 0.01 mm yr⁻¹) but leaves substantial headroom for efficiency improvement through advanced electrode coatings; and that maximum-power-point-tracking (MPPT) converters raise system efficiency by 12–24% relative to direct photovoltaic coupling. Gaps in knowledge, particularly regarding long-term outdoor durability in continental climates and techno-economic scaling, are identified and directions for future work are proposed.
subject: Articles
  topic: section
subject: alkaline electrolysis, green hydrogen, potassium hydroxide, 316L stainless steel, MPPT, photovoltaic integration, Uzbekistan, literature review.
  topic: keywords
creator: Sh.K. Bakhramov
creator: M.U. Qosimov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-28
publication date: 2026-07-28
starting page: 195
ending page: 201
doi: 10.37547/

INVESTIGATION OF THE CHARACTERISTICS OF FRUIT PRESERVATION TECHNOLOGY IN AN IONIZED ENVIRONMENT
type: item
description: This article investigates the fundamental principles and technological processes of fruit preservation in an ionized environment and their effects on fruit quality and shelf life. Research shows that ionizing radiation significantly reduces microbial contamination, slows down the rotting process, and preserves the external appearance and beneficial properties of fruits. The article also analyzes the efficiency, energy-saving aspects, and environmental safety of storage in ionized conditions. The results obtained are of great importance for improving long-term fruit preservation technologies.
subject: Articles
  topic: section
subject: Ionization, fruit preservation, food safety, microflora, radiation technology, shelf life, environmental safety.
  topic: keywords
creator: Muslimbek Abdikhoshimov
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-28
publication date: 2026-07-28
starting page: 189
ending page: 194
doi: 10.37547/

Identification Of Concealed User Profiles Via Modern Similarity-Based Classification Approaches
type: item
description: The increasing complexity of digital ecosystems has resulted in the generation of massive volumes of heterogeneous user data, making traditional profile identification approaches insufficient for discovering hidden behavioral structures. Modern applications require intelligent analytical mechanisms capable of identifying concealed user profiles that are not explicitly represented through conventional attributes. This research explores similarity-based classification approaches as a framework for discovering latent user characteristics through advanced data representation, pattern recognition, and classification strategies. The study examines how computational similarity measures, machine learning-based classification, and behavioral pattern analysis can contribute to identifying hidden relationships among users. The research develops a conceptual framework for concealed user profile identification by integrating principles of similarity analysis, clustering-based discovery, and intelligent classification. Existing studies related to customer segmentation, vulnerability detection, deep learning, and graph-based representation learning are critically analyzed to understand how hidden patterns can be extracted from complex datasets. Jatav et al. (2025) demonstrated that advanced clustering techniques can uncover latent behavioral patterns by identifying meaningful similarities among customer groups, providing a foundation for understanding concealed profile discovery through data-driven methods. The proposed analytical perspective considers user profile identification as a multi-stage process involving feature extraction, similarity measurement, classification modeling, and continuous refinement. Similarity-based approaches enable systems to compare complex behavioral and structural characteristics rather than relying only on predefined categories. Research in automated vulnerability detection further illustrates how machine learning and deep representation methods can…
subject: Articles
  topic: section
subject: Concealed user profiles
  topic: keywords
subject: similarity-based classification
  topic: keywords
subject: behavioral analytics
  topic: keywords
subject: machine learning
  topic: keywords
creator: Emily Carter
rights: Copyright (c) 2026 Emily Carter https://creativecommons.org/licenses/by/4.0
date: 2026-06-30
publication date: 2026-06-30
starting page: 326
ending page: 336

BADIIY ASARLARDA O’QITUVCHI OBRAZI
type: item
description: Ustoz-kamolot ko’zgusi. Bu shaxs biz uchun ham ta’lim, ham tarbiya beruvchidir. Ana shunday zahmatkash insonlar tasviri badiiy asarlarda ham keng yoritilgan. Ushbu maqolada pedagog yoki ustoz xatti-harakati, xarakter xususiyatlari haqida so‘z boradi.
subject: Articles
  topic: section
subject: pedagog, ta’lim, tarbiya usullari, axloq, kamolot, dars, tarbiyasi og‘ir o‘quvchilar, kompozitsiya.
  topic: keywords
creator: Dilnura Egamberdiyeva
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-27
publication date: 2026-07-27
starting page: 186
ending page: 188
doi: 10.37547/

IMPROVING MECHANISMS FOR DEVELOPING 4C (4K) COMPETENCIES IN A DIGITAL EDUCATIONAL ENVIRONMENT
type: item
description: This article provides a scientific and pedagogical analysis of improving the systemic and organizational mechanisms for developing 4C (4K) competencies — critical thinking, creativity, communication, and collaboration — among learners within a digital educational environment. Unlike individual digital tools and methods, the current state of systemic mechanisms that ensure sustainable and large-scale development of these competencies — curriculum integration mechanisms, assessment and monitoring mechanisms, teacher preparation mechanisms, and infrastructure provision mechanisms — is examined, and their limitations and directions for improvement are substantiated from a scientific and practical perspective.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: 4C competencies, digital educational environment, systemic mechanism, curriculum integration, assessment mechanism, teacher preparation, monitoring, 21st-century skills, digital infrastructure, education management.
creator: Gulnoza Ismoilova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-27
publication date: 2026-07-27
starting page: 181
ending page: 185
doi: 10.37547/

THE RELATIONSHIP BETWEEN INDIVIDUAL STYLE AND SOCIAL LANGUAGE UNITS IN LITERARY DISCOURSE
type: item
description: This article examines the relationship between individual style and social language units in literary discourse, arguing that literary meaning is co-constructed at the intersection of idiolectal choices and socially shared linguistic configurations. The study synthesizes insights from stylistics, sociolinguistics, discourse analysis, and systemic-functional linguistics to frame “individual style” as a pattern of motivated selections and “social language units” as repertoires including register, sociolect, and genre-linked norms. Methodologically, it combines qualitative discourse analysis with corpus-informed profiling of narratorial and character speech, triangulating collocational tendencies, appraisal resources, transitivity patterns, and indexical cues across a purposive sample of contemporary Anglophone fiction. Results indicate that authors’ stylistic signatures are legible not apart from but through social language units they orchestrate: narrative voice calibrates registers for stance management; character idiolects weave sociolectal markers to perform identity; and style-shifting across scenes functions as a discourse-level resource for heteroglossia and plot dynamics. The discussion articulates implications for theory (style as social action), method (mixed-methods stylistics), and pedagogy (teaching style via register awareness), while acknowledging limits of genre scope and language coverage. The article contributes a model in which “individual style” is best understood as a selective reconfiguration of social language units, yielding an integrated account of variation, meaning, and effect in literary discourse.
subject: Articles
  topic: section
subject: style; idiolect; sociolect; register; heteroglossia; dialogism; indexicality; stylistics; discourse; corpus
  topic: keywords
creator: Shoxista Nuraliyeva
creator: Mubina Nurmatova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-25
publication date: 2026-07-25
starting page: 175
ending page: 180
doi: 10.37547/

SOCIOLECTS THAT CREATE INDIVIDUAL SPEECH IN LITERARY DISCOURSE
type: item
description: This article explores how sociolects function as resources for crafting individual speech in literary discourse, focusing on the ways writers stylize social voices to build character identity, world-building, and narrative realism. Drawing on sociolinguistics and discourse analysis, the study conceptualizes sociolects as indexical repertoires that invoke social personae, positions, and communities of practice within fictional worlds. We integrate corpus-assisted stylistics with qualitative micro-analysis to examine markers such as lexicon, morphosyntax, represented phonology, code-switching, and jargon. Results show that authors strategically orchestrate sociolectal cues to differentiate idiolects, manage stance, and produce heteroglossic textures that guide reader inference. The discussion situates these findings within current debates on stylization, indexicality, and critical discourse analysis, arguing that sociolectal representation both reflects and reshapes social stratification, authenticity norms, and language ideologies. The article concludes with implications for literary linguistics, translation, and pedagogy, advocating transparent, reflexive approaches to sociolectal portrayal that balance aesthetic aims with ethical responsibility.
subject: Articles
  topic: section
subject: sociolect, idiolect, literary discourse, stylization, indexicality, heteroglossia, character voice, stance, register, code-switching
  topic: keywords
creator: Dilafruz Madazizova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-25
publication date: 2026-07-25
starting page: 169
ending page: 174
doi: 10.37547/

ON THE HISTORY OF THE DEVELOPMENT OF MILITARY MODELING
type: item
description: This article examines the main stages in the emergence and development of military modeling from ancient times to the beginning of the twentieth century. It analyzes the approaches to military modeling employed by outstanding military commanders, investigates the features of the first professional military conflict simulation system, Kriegsspiel, and considers the contribution of twentieth-century military scholars to the development of the theory of military modeling.
subject: Articles
  topic: section
subject: military science, modeling, planning, simulation, force ratio, analysis, enemy disposition, scenario, commander training, terrain.
  topic: keywords
creator: Bauyrzhan Mekambayev
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-25
publication date: 2026-07-25
starting page: 161
ending page: 168
doi: 10.37547/

IMPROVING SOCIAL ACTIVITY COMPETENCE OF PROSPECTIVE TEACHERS THROUGH PROJECT-BASED AND REFLECTIVE LEARNING
type: item
description: This article provides a scientific and pedagogical analysis of developing the social activity competence of prospective teachers through project-based and reflective learning approaches. The concept of social activity competence and its structural components are examined. The practical potential of project-based learning oriented toward real social problems, along with the role of reflective learning in consciously drawing lessons from experience, are analyzed, and a step-by-step integrative model combining both approaches is substantiated from a scientific and practical perspective.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: social activity competence, project-based learning, reflective learning, prospective teacher, civic consciousness, social responsibility, collaboration, experiential learning, professional training, competence-based approach.
creator: Temur Salayev
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-23
publication date: 2026-07-23
starting page: 156
ending page: 160
doi: 10.37547/

DEVELOPING STUDENTS’ INDEPENDENT THINKING THROUGH THE CASE-METHOD APPROACH
type: item
description: This article examines the role of the case-method approach in developing students’ independent thinking skills. In modern education, fostering learners’ ability to analyze situations, make decisions, and think critically is considered a key objective. The case-method, as an interactive teaching strategy, provides real-life scenarios that encourage students to engage actively in problem-solving processes. The study highlights the effectiveness of this method in enhancing students’ intellectual abilities, creativity, and decision-making skills.
subject: Articles
  topic: section
subject: case-method, independent thinking, students, critical thinking, problem-solving, education, interactive learning
  topic: keywords
creator: Barno Yakubova
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-23
publication date: 2026-07-23
starting page: 153
ending page: 155
doi: 10.37547/

WAYS TO IMPROVE INVESTMENT EFFICIENCY IN THE TRANSITION TO A GREEN ECONOMY: INTERNATIONAL EXPERIENCE AND PROSPECTS FOR UZBEKISTAN
type: item
description: Ther article studies the theoretical and practical issues of increasing the efficiency of investment in the process of transition to a green economy. On the basis of experience of other countries, a comparative analysis of the methods applied by Germany, Japan, South Korea, China, Singapore, Finland, Australia, and Canada to attract and efficiently use green investments is carried out. The comparative method, statistical method, and system approach were used in the study of the effectiveness of green investment models. It was found that the development of green financial tools, the increase in investment in the renewable energy industry, the optimization of the PPP mechanism, and the application of the ESG principles in investment policy are the most important approaches to increase the efficiency of investments in Uzbekistan. On the basis of the international best practices, recommendations for the adaptation of successful green investment mechanisms in national economic conditions of Uzbekistan are given.
subject: Articles
  topic: section
subject: green economy, green investments, investment efficiency, Environmental, Social, and Governance (ESG), green finance, renewable energy, sustainable development, international experience.
  topic: keywords
creator: Guljahon Yangiyeva
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
date: 2026-07-22
publication date: 2026-07-22
starting page: 145
ending page: 152
doi: 10.37547/

Assessing Digital Intelligence-Based Planning Architectures for Improved Operational Outcomes and Resource Utilization
type: item
description: The increasing complexity of modern operational environments has created a demand for intelligent planning architectures capable of improving decision quality, resource utilization, and system-level performance. Traditional planning approaches based primarily on deterministic models and human expertise face limitations when managing highly dynamic, uncertain, and interconnected systems. This research paper examines digital intelligence-based planning architectures as an emerging paradigm for enhancing operational outcomes through artificial intelligence, automated decision support, reinforcement learning, distributed intelligence, and adaptive resource allocation mechanisms. The study analyzes how intelligent architectures integrate computational models, autonomous agents, and learning-based optimization methods to improve planning efficiency and operational resilience. The research adopts a conceptual analytical methodology based on synthesis of established studies related to automated air traffic management, intelligent control systems, reinforcement learning, and AI-driven resource optimization. Existing frameworks for automated arrival management, conflict resolution, distributed agent-based systems, and learning-based control are examined to identify their contribution toward intelligent planning architectures. The analysis demonstrates that digital intelligence enables improved prediction, real-time adaptation, and efficient allocation of constrained resources by transforming planning systems from static decision structures into dynamic learning environments. Findings indicate that intelligent planning architectures provide significant benefits in operational coordination, workload reduction, resource optimization, and decision accuracy. However, challenges remain regarding system integration, reliability, transparency, human-machine collaboration, and implementation barriers within complex socio-technical environments. The research highlights that successful …
subject: Articles
  topic: section
subject: Digital intelligence
  topic: keywords
subject: Intelligent planning architecture
  topic: keywords
subject: Artificial intelligence
  topic: keywords
subject: Resource utilization
  topic: keywords
creator: Dr. Jean Baptiste Ilunga
rights: Copyright (c) 2026 Dr. Jean Baptiste Ilunga https://creativecommons.org/licenses/by/4.0
date: 2026-03-31
publication date: 2026-03-31
starting page: 347
ending page: 359