Ushbu maqolada raqamli texnologiyalar yordamida talabalarning kreativ tafakkurini rivojlantirish masalasi yoritilgan. Bugungi kunda taʼlim jarayoniga raqamli vositalarning keng joriy etilishi talabalarda mustaqil fikrlash, muammoni tahlil qilish, yangi gʻoyalarni ilgari surish va ijodiy yondashuv kabi ko‘nikmalarni shakllantirishda muhim omil hisoblanadi. Maqolada raqamli taʼlim platformalari, sunʼiy intellekt asosidagi dasturlar, virtual haqiqat va boshqa interaktiv texnologiyalarning kreativ tafakkurga ta’siri tahlil qilinadi. Shuningdek, raqamli texnologiyalardan samarali foydalanish orqali talabalarning innovatsion salohiyatini oshirish imkoniyatlari ko‘rib chiqiladi.

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.

Ushbu maqolada raqamli texnologiyalarning alohida ta’limga ehtiyoji bor bolalar ta’limida tutgan o‘rni yoritilgan. Maxsus ehtiyojli bolalarning ta’lim olish imkoniyatlarini kengaytirish, ularning individuallashtirilgan o‘quv ehtiyojlarini qondirishda raqamli vositalarning imkoniyatlari tahlil qilingan. Shuningdek, inkluziv ta’limni qo‘llab-quvvatlovchi interaktiv platformalar, mobil ilovalar va sun’iy intellekt asosidagi yondashuvlar haqida fikr yuritilgan.

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.

This scientific work explores the clinical features, causes, and contemporary treatment strategies for tension-type headache in children, one of the most prevalent and often underdiagnosed neurological conditions in the pediatric population. The study highlights the multifactorial origin of tension-type headache, emphasizing psychological stress, musculoskeletal strain, and lifestyle imbalances as central contributing factors. Special attention is given to the importance of early diagnosis based on clinical evaluation, patient history, and the use of structured assessment tools designed for children. The research reviews both pharmacological and non-pharmacological treatment approaches, with a focus on behavioral therapy, cognitive-behavioral interventions, physical therapy, and biofeedback techniques. Preventive strategies such as stress management, sleep hygiene, physical activity, and nutritional regulation are also discussed as key elements in reducing the frequency and severity of headache episodes. Furthermore, the work highlights the psychosocial impact of chronic headache on children’s academic performance, emotional health, and social development.