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.

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 yurak-qon tomir kasalliklarining erkaklar va ayollar o‘rtasida uchrash chastotasi, klinik ko‘rinishlari, tashxis va davolashga bo‘lgan yondashuvlardagi farqlar tahlil qilinadi. Jinsiy farqlarning yurak kasalliklari patogenezi, simptomatika va natijaviy prognozga qanday ta’sir ko‘rsatishi tibbiy-amaliy nuqtai nazardan o‘rganilgan. Tadqiqotlar ayollarda yurak kasalliklarining kechish xususiyatlari ko‘pincha kech tashxislanishiga olib kelishini ko‘rsatmoqda. Shuningdek, maqolada klinik amaliyotda jinsga asoslangan individual yondashuv zarurati asoslab berilgan.

Markaziy Osiyoda suv xavfsizligi tobora dolzarb masalaga aylanib bormoqda. Bunga iqlim o‘zgaruvchanligining kuchayishi, suvga bo‘lgan talabning ortishi hamda transchegaraviy daryolarni boshqarish bilan bog‘liq muammolar sabab bo‘lmoqda. Ushbu maqolada mintaqadagi transchegaraviy suv resurslarini boshqarish murakkabligi, milliy manfaatlar bilan mintaqaviy hamkorlik o‘rtasidagi o‘zaro bog‘liqlik asosida o‘rganiladi.

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.