Ilimiy maqalada social pedagogtıń atqaratın xizmetleri,tiykarǵı waziypaları,social pedagogtıń xizmetkerler menen birge islesiw shárt-sharayatları,xizmetkerlerdi tańlaw siyaqlı kásiplik iskerlikleri keń sóz etiledi.

Ilimiy maqalada mektep oqıwshılarınıń bilim,uqıplılıq hám kónlikpelerin tekseriw hám bahalawdıń pedagogikalıq áhmiyeti,bahalawdıń túrleri,bilimdi bahalawda qoyılatuǵın talaplar hár tárepleme keń sóz etilgen.

This study examines intercultural language development using Turkish and Uzbek as case studies. Both languages, belonging to the Turkic family, share significant lexical, grammatical, and phraseological similarities, which facilitate pedagogical processes. Additionally, culturally specific expressions and customs—such as “Kolay gelsin” and “Labbay”—enhance mutual understanding. This practice fosters intercultural competence, empathy, and inclusivity. A project-based teaching approach effectively integrates both language and culture. The annotation concludes that developing multilingual competencies is not only a matter of linguistic similarities but a holistic process that promotes cultural sensitivity, respect, and inclusive communication.

This article provides information on lexical-statistical methods of text analysis. The methods of psychological examination of the text are taught. This analysis provides valuable information about the content, tone, and meaning of the text, as well as the language and style of writing. Statistical analysis is a universal method, as it is used equally in all layers of the language. Lexical-statistical analysis helps to study the lexical and grammatical forms of the text. In this method, the appearance indicators of each word in the text, that is, the information, meanings, and concepts related to them, are analyzed.

Bugungi kunda sog‘liqni saqlash tizimi doimiy monitoring va aniq tashxisga muhtoj. Ayniqsa yurak urishi, nafas olish va qand miqdori kabi hayotiy ko‘rsatkichlarni real vaqtli tahlil qilish orqali kasalliklar erta bosqichda aniqlanishi mumkin. Ushbu maqola kognitiv texnologiyalar, sun’iy intellekt va real vaqtli monitoring usullarini birlashtirib, tibbiy ma’lumotlarga asoslangan ogohlantirish tizimini yaratishga bag‘ishlangan. Taklif etilayotgan model LSTM (Long Short-Term Memory) neyron tarmog‘i asosida yurak, nafas va glyukoza darajasini tahlil qiladi va anomaliyani avtomatik tarzda aniqlaydi. Bunda signal filtrlash, ketma-ketlikni bashorat qilish va individual sog‘liq profili orqali shaxsiy qaror qabul qiluvchi tizimlar ishlab chiqiladi. Tajribada real hayotga yaqinlashtirilgan sun’iy datasetlar asosida tahlillar o‘tkazilib, aniqlik, faollik va ogohlantirish tizimining ishonchliligi baholandi. Natijalar ushbu texnologiya yordamida sog‘liqni kuzatishda yuksak samaradorlikka erishish mumkinligini ko‘rsatdi. Modelga mobil ilova yoki web interfeys integratsiyasi orqali foydalanuvchi sog‘lig‘ini 24/7 nazorat ostida ushlab turish imkoniyati yaratish rejalashtirilgan. Maqolada kardiologik signallarga raqamli ishlov berishning kognitiv modeli va dasturiy majmuasini ishlab chiqish bo‘yicha kognitiv yondashuvlarni ishlab chiqish va u asosida model, algoritm, diagramma, dasturiy komponentlar va amaliy tahlillar taqdim etilgan. Yurakning EEG signallari asosida aritmiya kasalligini aniqlash uchun kognitiv parametrlar (yosh, jins, kasb, jismoniy faollik va anamnez) bilan birga yurakning muhim 8 ta xususiyati o‘rganildi. EKG signallarining asosiy intervallari (RR, PR, QRS, QT) va yurak ritmidagi o‘zgarishlar HRV, ST segment, T va P to‘lqinlar orqali o‘rganildi. Ma’lumotlar Random Forest klassifikatori yordamida tahlil qilindi.