The exponential growth in the use of network services through the design of various network infrastructures, has led to increased complexities and challenges in the network. A major problem in computer networks is privacy and security breach. Cyber attackers exploit loopholes to infiltrate and disrupt the operation of the network through various attacks. Anomaly-based intrusion detection often employs Artificial Neural Network techniques like Multi-layer Perceptron (MLP) to classify malicious and legitimate traffic. Nevertheless, these techniques are vulnerable to overfitting and require extensive labeled data and computational resources. Consequently, this reduces the accuracy of intrusion detection systems and increases the error detection rate. To minimize the error detection rate of the intrusion detection system, it is necessary to optimize the connection parameters of the MLP neural network such as weights and biases. To this end, we proposed an optimized MLP-based Intrusion Detection using Gray Wolf Optimization (GWOMLP-IDS) to optimize the learning process of the MLP neural network by optimizing weights and biases. GWO aims to select an optimal connection parameter during the learning process to minimize the error rate of intrusion detection. Extensive simulations in Python reveal the effectiveness of the proposed approach in terms of designated performance metrics.

The presented paper is devoted to the development of a method for identifying and correcting spelling errors in Kazakh texts. In this paper, the study object is methods for more accurate correction of spelling errors in Kazakh texts. The aim of the study is to develop an augmented version of the Damerau-Levenshtein method for correcting spelling errors in Kazakh language texts. Automatic detection and correction of spelling errors have become a default feature in modern text editors for working with text data, in text messaging applications such as chatbots, messengers, etc. However, although this task is well solved in geographically widespread languages, it has not been fully solved in languages with a small audience, such as the Kazakh language. The methods developed so far cannot correct all spelling errors found in Kazakh texts. Therefore, the development of a method with specific algorithms for spelling error correction in Kazakh texts is considered. As a result of the research work, algorithms for correcting errors found in Kazakh language texts were developed, and the developed algorithms were included in the Damerau-Levenshtein method. The experimental testing results of the augmented Damerau-Levenshtein method showed 97.2 % accuracy in correcting specific errors found only in Kazakh words and 92.8 % accuracy in correcting common errors from letter symbols. The standard Damerau-Levenshtein method testing results showed 76.4 % accuracy in correcting specific errors found only in Kazakh words. The results of the tests in correcting common errors from letter symbols with the standard Damerau-Levenshtein were approximately the same with the augmented Damerau-Levenshtein method, the accuracy is 92.2 %. The extent and conditions of practical application of the results are implemented by including them in text editors, messengers, e-mails and similar applications that work with text data.

A hardware-software system has been implemented to monitor the environmental state (EnvState) at the site of railway (RY) accidents and disasters. The proposed hardware-software system consists of several main components. The first software component, based on the queueing theory (QT), simulates the workload of emergency response units at the RY accident site. It also interacts with a central data processing server and information collection devices. A transmitter for these devices was built on the ATmega328 microcontroller. The hardware part of the environmental monitoring system at the RY accident site is also based on the ATmega328 microcontroller. In the hardware-software system for monitoring the EnvState at the RY accident site, the data processing server receives information via the MQTT protocol from all devices about the state of each sensor and the device's location at the RY accident or disaster site, accompanied by EnvState contamination. All data is periodically recorded in a database on the server in the appropriate format with timestamps. The obtained information can then be used by specialists from the emergency response headquarters. © 2023 Polish Academy of Sciences. All rights reserved.

This paper presents a certificateless group signature scheme designed specifically for Unmanned Aerial Vehicle (UAV) communications in resource-constrained environments. The scheme leverages Physical Unclonable Functions (PUFs) and elliptic curve cryptography (ECC) to provide a lightweight security solution while maintaining essential security properties including anonymity, unforgeability, traceability, and unlikability. We describe the cryptographic protocols for system setup, key generation, signing, verification, and revocation mechanisms. The implementation shows promising results for UAV applications where computational resources are limited, while still providing robust security guarantees for group communications. Our approach eliminates the need for computationally expensive certificate management while ensuring that only legitimate group members can create signatures that cannot be linked to their identities except by authorized group managers.

В статье рассматриваются современные методы адсорбционной очистки промышленных сточных вод металлургических предприятий от ионов тяжелых металлов, включая медь, никель и цинк. Исследуется применение модифицированных цеолитных сорбентов, содержащих наноструктурные соединения ванадия и титана, полученные методом золь-гель технологии. Представлены экспериментальные данные по сорбционной емкости адсорбентов, демонстрирующие значительное повышение эффективности очистки при использовании гибридных нанокомпозитов. Оптимизированы условия адсорбции, включая влияние рН, температуры и концентрации металлов в растворе. Разработанная технология направлена на повышение уровня очистки сточных вод металлургического производства, минимизацию негативного воздействия на окружающую среду и возможность вторичной переработки извлеченных металлов для их повторного использования в производственных процессах.

The activities of industrial enterprises in ferrous and non-ferrous metallurgy and other industries lead to environmental pollution with wastewater containing harmful substances that, even in small quantities, have a rather serious negative impact on human health and the state of the biosphere. There are a large number of natural sorbents used to solve water treatment problems. Among inorganic sorption materials, zeolites are widely used in practice. These natural materials have thermal and radiation stability and high selectivity. The purpose of this article is to study the sorption capacity of zeolites modified with nanostructured rare metals in several ways, with different options for activating the matrix to improve sorption properties with respect to ions of heavy and non-ferrous metals. Based on the experiments conducted, it was proven that zeolites modified with vanadium and titanium nanocompounds are highly effective in removing heavy metal ions from wastewater. The resulting composition on a zeolite matrix creates a highly dispersed solid phase of nanoparticles in the form of a sol-gel. Such systems have an excess of energy, which leads to increased reactivity and adsorbing properties. It is obvious that the activation of zeolites makes it possible to obtain a wider range of active centers of different nature. This determines the varied use of zeolites in the technological system for treating wastewater from heavy and non-ferrous metal ions, which will make it possible to achieve MPC standards. Key words: zeolite, sorption technologies, heavy metals, wastewater, adsorbent.

The research introduces a dual deep learning system which predicts salary ranges by processing job descriptions through BERT-based contextual embeddings and structured metadata integration. The proposed method utilizes more than 124,000 LinkedIn job postings to merge BERT-based contextual embeddings with structured information about location and industry and experience level and compensation type. The model uses multi-head attention to identify essential salary-related terms in job descriptions which results in better model interpretability and improved prediction accuracy. The model combines semantic embeddings with tabular data to create a multimodal representation which serves as input for supervised learning with an ordinal-aware loss function. The model achieves stable performance in salary classification across three categories through F1-scores between 0.82 and 0.84. The proposed model achieves excellent generalization capabilities for different sectors and job types while providing precise predictions and clear decision-making processes for salary benchmarking and recruitment analytics applications.

Основной целью настоящих исследований являлось изучение химико-минералогического состава руды месторождения Кеншокы-1 с последующим проведением поисковых опытов по извлечению меди из рудного материала методом сернокислотного выщелачивания. В ходе исследований установлено, что руда относится к типу окисленных медистых песчаников, и наряду с медью в ней содержится значительное количество свинца и небольшое количество цинка. Основными минералами меди и свинца в этой руде являются карбонатные – малахит и церуссит. Присутствует довольно значительное количество фосфатного минерала свинца – пироморфита. Основными минералами пустой породы являются кварц, ортоклаз и клинохлор. Железо по данным дифрактометрического анализа находится связанным в клинохлоре. Поисковые опыты по выщелачиванию меди из указанной руды растворами серной кислоты показали, что даже при комнатной температуре и концентрации серной кислоты в растворе 11,3 г/дм3 достигается извлечение меди в водный раствор более 60%, а основными технологическими факторами, влияющими на процесс выщелачивания меди, являются: продолжительность, концентрация серной кислоты в исходном растворе, интенсивность перемешивания и соотношение твердой и жидкой фаз. Концентрация меди в полученном продуктивном растворе составляла в зависимости от концентрации серной кислоты от 6,32 до 10,15 г/дм3, что является недостаточной для дальнейшей переработки раствора методом электролиза, поэтому следует донасыщать продуктивные растворы по меди путем возврата продуктивного раствора в голову процесса. Поведение свинца во время поисковых исследований не изучалось, но ввиду малой растворимости сульфата свинца в водных растворах основная часть свинца должна оставаться в кеке.

Modern air compressors used in the mining industry have a high margin of safety when operating in difficult conditions: This includes uneven terrain, high temperature differences and work underground. Scientific research, complex of theoretical and experimental studies, is carried out in order to obtain sound initial data, to find principles and ways to create a new generation of compressors for use in a mining field. Air compressors are used in deep mines, including supplying clean air, since there may not be enough air in the mine. The compressor can take in outside air, compress and filter it, then feed it into the tunnel. It is necessary to choose compressor equipment for use in mines very carefully; there are many potential risks and limitations. The basic problem, its relevance – in this paper, the issues related to the device, operation and the possibility of optimizing the design of a screw compressor, gas compressor station in the mining industry are considered. The modeling of processes and the construction of flowcharts were carried out using programs MathCad, Drawio, MS PP. A simplified mathematical model of a screw compressor is obtained. Of the work carried out, the optimal regulator capable of controlling the system with minimal energy consumption has been determined. The relevance of the topic is explained by the fact that in Kazakhstan and other developing countries special attention is paid to the issue of energy conservation. This requires an increase in the efficiency of gas compressor equipment in general and compressor stations in particular. The practical value is an optimal regulator capable of controlling the system with minimal energy consumption.

The fight against avalanches and the elimination of their consequences is urgent. The purpose of the article is to develop measures for preventing avalanches, especially sudden but not only planned ones. The subject of the study is snow avalanches, their volumes, and their causes. The result of the study is the development of standard technological flowcharts for snow removal work on the backbone network of the NC KTZh JSC. Freight trains travel 1000 km per day. It is necessary to increase this speed to 1200 km/day. The nominal FTI amounted to 75 trillion tenge in 2020; in 2024 it will be 106 trillion tenge. This will require transportation of construction materials and minerals, gasoline and diesel fuel, grain and flour, fertilizers, seeds, herbicides and pesticides, crop and livestock products.