Multimodal human–AI systems generally consider facial expressions and body motions as separate input streams, leading to disjointed interpretations and diminished emotional coherence. To overcome this issue, we offer the Engagement-Safe Expressive Alignment (ESEA) paradigm and the Unified Visual Synchrony (UVS) framework as its computational implementation. UVS models the coherence between facial expressions and gestures, offering an interpretable visual synchrony signal that can function as adaptive feedback in human–AI interactions. The framework’s key component is the Consistency Index for Affective Synchrony (𝐶𝐼𝐴𝑆 ), which correlates brief visual segments with scalar synchrony scores through a common latent representation. Facial and gestural signals are processed by modality-specific projection networks into a unified latent space, and 𝐶𝐼𝐴𝑆 is derived from the similarity and short-term temporal consistency of these latent trajectories. The synchrony index is regarded as an estimation of affective visual coherence within the ESEA paradigm. We formalize the UVS/𝐶𝐼𝐴𝑆 framework and conduct a comparative experimental evaluation utilizing matched and mismatched face–gesture segments derived from rendered dialog footage. Utilizing ROC analysis, score distribution comparisons, temporal visualizations, and negative control tests, we illustrate that 𝐶𝐼𝐴𝑆 effectively captures structured face–gesture alignment that surpasses similarity-based baselines, while also delivering a persistent, time-resolved synchronization signal. These findings establish 𝐶𝐼𝐴𝑆 as a principled and interpretable feedback signal for future affect-aware, engagement-focused multimodal agents.

This paper discusses an adaptive method of image steganography issues based on the application of a linear hash function over the GF (2) field to control the embedding process. The method uses staggered splitting of an image into 8 × 8-pixel blocks to provide blind steganography. Classification thresholds are defined as the percentiles of the distribution of gradients throughout the image, allowing for efficient load distribution between textured and smooth areas. Experiments on the BOSSBase, SIPI and Kaggle kits show that the method provides an actual capacity of up to 0.7 bpp at PSNR 47–50 dB and is resistant to statistical tests and RS analysis. At the same time, like other approaches based on modification of pixel differences, it remains vulnerable to modern stegoanalysis based on spatial rich models (SRMs). However, thanks to the modular structure of embedding control based on linear hash function, the proposed architecture allows direct integration with many modern adaptive strategies aimed at minimizing statistical anomalies.

This paper presents a comprehensive study aimed at systematically analyzing and evaluating natural language processing (NLP) techniques for military information operations, with a special focus on social media intelligence. Among an ever-growing complicated information environment, NLP methods like sentiment analysis, named entity recognition, and topic modeling have been essential in tracking online propaganda efforts, discovering emerging issues and threats globally with dialogues on military operations. These techniques make an impact on available decision making via situational awareness and getting the added extraction from volumes of unstructured data outputs thus increasing the overall strategic benefits to military organizations. There are technical and operational challenges concerning the use of NLP in a military context such as requirements for real-time data processing; language diversity; and maintaining data privacy while preserving ethical standards. To address these challenges, the study conducts an exhaustive survey of NLP methods, reviewing their range of applications, and highlights the relevance of several approaches for military information operations, with special emphasis on social media intelligence. The work further provides discussion on the comprehensive adoption of artificial intelligence (AI), edge computing, and multilingual NLP models for enhancing adaptability, efficiency, and transparency of the systems. It also extols the need for explainable AI (XAI) to improve accountability and trust by making term or even whole early warning systems derived from NLP analyses, transparent and interpretable for these military research applications with significant financial consequences. The paper also emphasizes the strategic importance of multilingual and multimodal analysis and the integration of specialized military lexicons to improve the contextual understanding of military discourse in social media environments. We also elucidate the important capabilities of NLP in enabling military operations to be responsive, rapid and data-driven while also adapting to the evolving nature of warfare. Key conclusions suggest that applying advanced NLP tools enhances situational awareness, enables timely threat detection, and supports more agile, data-informed decision-making within modern military operations. The paper shows a perspective to optimize NLP and AI technologies, leveraging various perspectives to benefit the operational needs of military and defense sectors in more data-rich environments.

The rapid digitalisation of the medical field has heightened concerns over protecting patients’ personal information during the transmission of medical images. This study introduces a method for securely transmitting X-ray images that contain embedded patient data. The proposed steganographic approach ensures that the original image remains intact while the embedded data is securely hidden, a critical requirement in medical contexts. To guarantee reversibility, the Interpolation Near Pixels method was utilised, recognised as one of the most effective techniques within reversible data hiding (RDH) frameworks. Additionally, the method integrates a statistical property preservation technique, enhancing the scheme’s alignment with ideal steganographic characteristics. Specifically, the “forest fire” algorithm partitions the image into interconnected regions, where statistical analyses of low-order bits are performed, followed by arithmetic decoding to achieve a desired distribution. This process successfully maintains the original statistical features of the image. The effectiveness of the proposed method was validated through stegoanalysis on real-world medical images from previous studies. The results revealed high robustness, with minimal distortion of stegocontainers, as evidenced by high PSNR values ranging between 52 and 81 dB.

Kazakh Sign Language (KSL) is a crucial communication tool for individuals with hearing and speech impairments. Deep learning, particularly Transformer models, offers a promising approach to improving accessibility in education and communication. This study analyzes the syntactic structure of KSL, identifying its unique grammatical features and deviations from spoken Kazakh. A custom parser was developed to convert Kazakh text into KSL glosses, enabling the creation of a large-scale parallel corpus. Using this resource, a Transformer-based machine translation model was trained, achieving high translation accuracy and demonstrating the feasibility of this approach for enhancing communication accessibility. The research highlights key challenges in sign language processing, such as the limited availability of annotated data. Future work directions include the integration of video data and the adoption of more comprehensive evaluation metrics. This paper presents a methodology for constructing a parallel corpus through gloss annotations, contributing to advancements in sign language translation technology.

Kazakh Sign Language (KSL) is a crucial communication tool for individuals with hearing and speech impairments. Deep learning, particularly Transformer models, offers a promising approach to improving accessibility in education and communication. This study analyzes the syntactic structure of KSL, identifying its unique grammatical features and deviations from spoken Kazakh. A custom parser was developed to convert Kazakh text into KSL glosses, enabling the creation of a large-scale parallel corpus. Using this resource, a Transformer-based machine translation model was trained, achieving high translation accuracy and demonstrating the feasibility of this approach for enhancing communication accessibility. The research highlights key challenges in sign language processing, such as the limited availability of annotated data. Future work directions include the integration of video data and the adoption of more comprehensive evaluation metrics. This paper presents a methodology for constructing a parallel corpus through gloss annotations, contributing to advancements in sign language translation technology.

The article is devoted to the introduction of digital watermarks, which formthe basis for copyright protection systems. Methods in this area are aimed at embedding hidden markers that are resistant to various container transformations. This paper proposes a method for embedding a digital watermark into bitmap images using Lagrange interpolation and the Bezier curve formula for five points, called Lagrange interpolation along the Bezier curve 5 (LIBC5). As a means of steganalysis, the RS method was used, which uses a sensitive method of double statistics obtained on the basis of spatial correlations in images. The output value of the RS analysis is the estimated length of the message in the image under study. The stability of the developed LIBC5 method to the detection of message transmission by the RS method has been experimentally determined. The developed method proved to be resistant to RS analysis. A study of the LIBC5 method showed an improvement in quilting resistance compared to that of the INMI image embedding method, which also uses Lagrange interpolation. Thus, the LIBC5 stegosystem can be successfully used to protect confidential data and copyrights.

t. This paper is dedicated to the study of the importance and efficiency of developing and implementing ozone purification systems for disinfecting drinking water sources, water pipes, and wells. Ozone is a powerful oxidizer capable of effectively eliminating microorganisms, including bacteria, viruses, and protozoa in water pipes and wells. Such systems serve as alternatives to traditional chlorination methods and leave no polluting purification by-products in the environment. The research explores the technical parameters of applying ozone to various water sources and purification systems, as well as operational parameters like ozone concentration, treatment time, and water flow regime. It also covers issues related to the design, installation, and operation of ozone purification systems. The topic contributes to the development and improvement of efficient and ecologically sustainable water disinfection solutions by providing an overview of the working principles, technical specifications, and mobility capabilities of ozone purification systems. The introduction of ozone purification systems extends the possibilities for improving water quality and adhering to safety standards. This study also identifies key factors such as ozone solubility, reaction time, and its efficiency in dispersing through water, which can enhance the effectiveness of this method.

Данная статья является первой публикацией в рамках реализации программы «Разработка прототипа модернизированной пограничной машины для повышения эффективности выполнения служебнобоевых задач по охране Государственной границы Республики Казахстан», финансируемой Комитетом науки Министерства науки и высшего образования Республики Казахстан (BR218010/0223). Актуальность. Учитывая военно-политическую обстановку в СНГ и протяженную сухопутную Государственную границу Казахстана, разработка прототипа модернизированной пограничной машины для повышения эффективности выполнения задач по охране Государственной границы на сегодняшний день для Казахстана является актуальной. Предмет. Исследования наиболее оптимальных технических параметров прототипа пограничной машины, используемой для решения задач охраны Государственных границы. Задачи. На основе исследования зарубежного и отечественного опыта эксплуатации обосновать наиболее оптимальные технические характеристики прототипа модернизированной пограничной машины для охраны Государственной границы. Цели. Предложить наиболее оптимальные технические характеристики прототипа модернизированной пограничной машины для охраны Государственной границы. Методы. Для раскрытия поставленной проблемы и получения результатов использовались следующие методы теоретического исследования: сравнительный и системный анализы, синтез, индукция, дедукция и обсуждение. Результаты. Одним из направлений по поиску решения проблем, обозначенных выше, является проведение исследования по разработке прототипа модернизированной пограничной машины, оборудованной всеми необходимыми техническими средствами, способными изменить качество несения службы пограничников по охране Государственной границы. Выводы и предложения. При создании прототипа модернизированной пограничной машины для охраны государственной границы целесообразно учитывать ряд необходимых критериев для выполнения служебного задания. Кузов автомобиля целесообразно использовать вместо грузовой платформы цельнометаллический кузов или кузов универсальный нулевого габарита с распашными задними дверями

Данная статья является первой публикацией в рамках реализации программы «Разработка прототипа модернизированной пограничной машины для повышения эффективности выполнения служебнобоевых задач по охране Государственной границы Республики Казахстан», финансируемой Комитетом науки Министерства науки и высшего образования Республики Казахстан (BR218010/0223). Актуальность. Учитывая военно-политическую обстановку в СНГ и протяженную сухопутную Государственную границу Казахстана, разработка прототипа модернизированной пограничной машины для повышения эффективности выполнения задач по охране Государственной границы на сегодняшний день для Казахстана является актуальной. Предмет. Исследования наиболее оптимальных технических параметров прототипа пограничной машины, используемой для решения задач охраны Государственных границы. Задачи. На основе исследования зарубежного и отечественного опыта эксплуатации обосновать наиболее оптимальные технические характеристики прототипа модернизированной пограничной машины для охраны Государственной границы. Цели. Предложить наиболее оптимальные технические характеристики прототипа модернизированной пограничной машины для охраны Государственной границы. Методы. Для раскрытия поставленной проблемы и получения результатов использовались следующие методы теоретического исследования: сравнительный и системный анализы, синтез, индукция, дедукция и обсуждение. Результаты. Одним из направлений по поиску решения проблем, обозначенных выше, является проведение исследования по разработке прототипа модернизированной пограничной машины, оборудованной всеми необходимыми техническими средствами, способными изменить качество несения службы пограничников по охране Государственной границы. Выводы и предложения. При создании прототипа модернизированной пограничной машины для охраны государственной границы целесообразно учитывать ряд необходимых критериев для выполнения служебного задания. Кузов автомобиля целесообразно использовать вместо грузовой платформы цельнометаллический кузов или кузов универсальный нулевого габарита с распашными задними дверями.