Ushbu maqola O‘zbekiston Respublikasi Oliy Majlisi Senatining ijro hokimiyati faoliyati ustidan parlament nazorati bo‘yicha vazifa va funksiyalarini yangi tahrirdagi Konstitutsiya (2023-yil) asosida tahlil qilgan. Tadqiqotda Senatning qonun ijrosini monitoring qilish, parlament so‘rovlari, tinglovlar va maxsus komissiyalar orqali nazorat mexanizmlari o‘rganilgan. Yangi Konstitutsiya doirasida Senat vakolatlarining kengayishi, xususan, parlament tekshiruvi institutining joriy etilishi tahlil qilingan. Maqola nazorat jarayonidagi muammolarni aniqlab, samaradorlikni oshirish bo‘yicha takliflar bergan.

Ushbu maqolada O‘zbekiston transport tarmoqlari bilan bog‘liq holda motel va kichik mehmonxonalarning yangi dizayn tendensiyalari tahlil qilinadi. Tadqiqot davomida transport infratuzilmasi, ekologik innovatsiyalar va milliy arxitektura elementlari asosida yangi loyihalarning istiqbollari o‘rganildi.

This article focuses on enhancing mathematics education in academic lyceums through the application of interactive methods. It discusses the role of modern educational technologies, active learning strategies, and project-based learning in mathematics education. Additionally, the effectiveness of interactive methods in increasing student engagement, fostering critical thinking, and developing problem-solving skills is analyzed. The article serves as a valuable resource for teachers, education specialists, and academic lyceum administrators.

Ushbu maqolada fizika yo‘nalishidagi universitet talabalari uchun yarimo‘tkazgichli lazerlarni o‘qitishda axborot texnologiyalari va virtual laboratoriyalardan foydalanish masalasi nazariy jihatdan tahlil qilingan. Amaldagi ta’lim jarayonida mazkur texnologiyalarning yetarli darajada qo‘llanilmayotgani muammo sifatida ko‘rsatib o‘tilgan. Lazer hodisasining murakkab fizik tabiati va uni an’anaviy metodlar bilan tushuntirishdagi qiyinchiliklar yoritilgan. Shuningdek, zamonaviy axborot-kommunikatsiya texnologiyalari, xususan interaktiv dasturlar, 3D modellashtirish, virtual laboratoriyalar va multimedia vositalarining talabalarda mavzuni tushunishga bo’lgan ta’siri o’rganilgan.

This paper focuses on the selection and justification of deep learning models for emotion classification tasks. It provides a comprehensive analysis of various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, Long Short-Term Memory networks, and Transformer models, assessing their performance in recognizing and classifying human emotions from multimodal data sources. The study examines the strengths and limitations of each model with respect to data type, training efficiency, computational complexity, and generalization capabilities. Furthermore, criteria for optimal model selection tailored to real-world emotion recognition applications are discussed. The findings contribute to enhancing the accuracy and robustness of emotion classification systems and offer valuable guidelines for researchers and practitioners developing advanced affective computing solutions.