Mazkur maqolada jamiyatda huquqiy ong va huquqiy madaniyatni shakllantirish va rivojlantirishning dolzarb masalalari yoritilgan. Huquqiy ong fuqarolarning qonunlarga bo’lgan munosabati, ularning huquq va majburiyatlari to‘g‘risidagi bilimlari va huquqiy xulq-atvorining shakllanishida asosiy o‘rin tutadi. Huquqiy madaniyat esa insonlarning huquqiy tushunchalari, qonunlarga hurmat ruhidagi tarbiyasi, davlat va jamiyat hayotidagi faol ishtirokini ifodalaydi. Maqolada jamiyatda huquqiy ong va madaniyatni oshirish vositalari, davlat siyosati, ta’lim tizimi, OAV va fuqarolik jamiyati institutlarining roli tahlil etilgan. Shuningdek, O‘zbekistonda olib borilayotgan islohotlar kontekstida mazkur jarayonning rivojlanish istiqbollari yoritiladi.

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.

The food industry is a branch of the national economy that produces food products. The industry includes enterprises of meat and dairy, oil and fat, fish, flour and cereals, pasta, fruit and vegetable canning, dairy and cream, sugar, tea, confectionery, bakery, grape and champagne wines, alcohol, vodka, tobacco, brewing, thirst-quenching, soap and other industries.

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.

Ushbu maqolada o‘smir yoshdagi og‘ir atletikachilar uchun ratsional ovqatlanishni samarali tashkil etish bo‘yicha tadqiqot natijalari yoritilgan. Eksperimental metod asosida ishlab chiqilgan ovqatlanish dasturi 12–16 yoshdagi sportchilarda kuch ko‘rsatkichlari, mushak massasi, tiklanish darajasi va biokimyoviy ko‘rsatkichlar o‘zgarishlariga sezilarli ta’sir ko‘rsatdi. Tadqiqot natijalari ovqatlanishning sport tayyorgarligidagi o‘rnini ilmiy asoslashga yordam berdi va amaliy tavsiyalar ishlab chiqildi.