This article discusses folk oral culture and its specific features.

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.

Mazkur maqolada offshor kompaniyalarining xalqaro xususiy huquq doirasidagi huquqiy maqomi tahlil qilinadi. Asosiy e’tibor kompaniyaga nisbatan qo‘llaniladigan shaxsiy qonunni (lex societatis) aniqlovchi ikkita asosiy yondashuv — inkorporatsiya nazariyasi va asosiy faoliyat ko‘rsatiladigan joy nazariyasining (real seat theory) nazariy hamda amaliy tafovutlariga qaratiladi. Tadqiqotda qiyosiy-huquqiy, keys-tahlil va doktrinal yondashuvlar orqali offshor yurisdiktsiyalarning huquqiy xususiyatlari, xalqaro sud amaliyoti va O‘zbekiston qonunchiligidagi mavjud tartiblar tahlil qilinadi.

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.