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Проектирование IoT-платформы для управления энергоресурсами интеллектуальных зданий
Прикладная информатика. 2018. Т. 13. № 4. С. 29–41.
The problem of designing a cyberphysical system used as a service for Smart buildings control using Internet technologies — Internet of Things (IoT) is considered. Such software platforms are part of the complex systems of the BEMS — Building Energy Management Systems and are an instrument for implementing energy savings in buildings. IoT servers and controllers form a management infrastructure in which the mechanisms of adaptation and data mining, which are continuously received from a large number of nodes, play a special role. In the absence of standards for the implementation of BEMS based on IoT, as well as increasing requirements for the composition and functions of analytical support, there is a need to unify software architectures and ensure their effective implementation in solving practical problems. Software component unification, including the scenario manager, provides operational software implementation using various information technologies, including cloud or foggy computing. The presented architectural templates clearly illustrate the possibilities of scaling and developing services for managing intelligent buildings using IoT. The projected open SaaS architecture software platform is an effective means for buildings energy managing with a contour of Data Mining. It can be used for replication of knowledge about the energy efficiency in buildings, including the use of renewable energy sources.
Language:
Russian
Keywords: data miningинтернет вещейинтеллектуальный анализ данныхоблачные технологиитуманные вычисления cloud computingfog computingcyberphysical systemsкиберфизические системыбеспроводная передача данныхSmart Buildingинтеллектуальное здание Internet of Thingswireless data transmissionproactive controlпроактивное управление
[б.и.], 2026.
While Large Language Models (LLMs) have revolutionized NLP, they remain prone to hallucinations, reasoning “mode-collapse” in open-ended generation, and a lack of factual provenance. The Automated Knowledge Base Construction (AKBC) workshop addresses a key missing piece of the generative era: structured knowledge. Knowledge Bases (KBs) serve as ground truth for fact verification, the semantic backbone ...
Added: October 28, 2026
Nikitiuk B., Lenev D., Pisarev V. et al., Journal of Colloid and Interface Science 2026 Vol. 718 Article 140444
Hypothesis:Accurate determination of interfacial tension values is crucial for many modeling applications in the oil and gas industry. However, many of the presently used empirical and theoretical models show poor prediction accuracy and do not allow for direct consideration of the concentrations of gases and salts dissolved in the system as well as the specific ...
Added: October 28, 2026
Deshchenya V., Nikolay D. Kondratyuk, Sivakova A. et al., Chemical Engineering Sciences 2027 Vol. 337 Article 124616
Accurate prediction of complex formulation viscosity is crucial for the lubricant industry and engineering processes. However, developing generalizable models remains challenging due to the complexity of industrial mixtures and the scarcity of public experimental data, often resulting from corporate proprietary restrictions. This study presents a machine-learning workflow for viscosity estimation from a proprietary pseudonymized dataset, ...
Added: October 28, 2026
Zubov A., Zubov A., Малявко, Я. et al., Computer Physics Communications 2025 Vol. 317 Article 109860
The concept of representative volume (REV, or RVE in material sciences) is the cornerstone of continuum scale models – one needs to get the volume big enough so that it could be represented with an averaged value (scalar, vector or tensorial, etc.). While REV should be established in all larger scale simulations, this is rarely ...
Added: October 28, 2026
Roman Prosvirnin, Suslov A., Aleksei Soldatov et al., Computation 2026 Vol. 14 No. 10 Article 261
Abstract
Safety-aligned language models often encode that a request is harmful yet still comply with it. We turn this gap between internal recognition and observable behavior into an inference-time defense. The proposed activation-steering method uses a multiplicative operator that amplifies the residual-stream component along a harm-recognition direction. Intervention strength scales with the model’s own assessment of ...
Added: October 27, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Big Data and Cognitive Computing 2026 Vol. 10 No. 11 P. 1–52
Camera traps are a key tool for non-invasive wildlife monitoring, yet models trained on existing benchmarks often generalize poorly to new regions due to domain shift, class imbalance, and natural variability in illumination, season, and background. We introduce PACTraD, a benchmark of 116,973 annotated camera trap images collected in a protected area of the Baikal ...
Added: October 27, 2026
IEEE, 2026.
Proceedings of the X Scientific School "Dynamics of Complex Networks and their Applications"
(DCNA'2026) contain papers of reports of scientists and specialists in the field of intelligent technologies,
engineering education, research and design of complex networks.
DCNA'2026 was held from 10 to 12 September 2026 in Moscow, Russia, as a part of the International
Forum on Artificial Intelligence and ...
Added: October 26, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Scientific data 2026 P. 1–20
We addressed the task of chemical characterization of the aerosol emitted by heated tobacco products (HTPs) and of the smoke emitted by conventional/commercial cigarettes, usually adopted as a reference. Emphasis was placed on quantifying constituents for enabling the identification of novel compounds through targeted and untargeted analyses, and the evaluation of reductions in toxicant exposure under ...
Added: October 26, 2026
Obsie E. Y., Zhan Y., Liu Y., Engineering Research Express 2026 Article 7
Maintaining plant health is crucial for crop quality, food security, and agricultural productivity. Although deep learning methods have shown strong potential for species, disease, and severity classification, most existing approaches tackle these tasks separately, failing to exploit shared representations and interdependencies among them. Furthermore, the variability of disease symptoms, such as subtle differences in size, ...
Added: October 22, 2026
Lev Pyatko, Sergey Aksenov, Regular and Chaotic Dynamics 2026 Vol. 31 No. 5 P. 794–813
In the circular restricted three-body problem, families of periodic and quasi-periodic orbits exist in the vicinity of the libration points and are of significant interest for practical applications. This work presents a neural network-based algorithm for orbit construction and station-keeping, applicable to both periodic and quasi-periodic orbits near collinear libration points. The method employs a ...
Added: October 19, 2026
Vorontsova T., М.: Академия, 2025.
The textbook has been prepared in accordance with the requirements of the federal state educational standards for secondary vocational education and is intended for studying the professional modules “Information Security in Information and Telecommunication Systems and Networks Using Software and Hardware‑Software Tools, Including Cryptographic Protection Tools” and “Information Security in Automated Systems Using Software and ...
Added: October 19, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 10 Article 330
Automated microscopic image analysis is essential for quantitative microbiology, yet manual acquisition and generic recognition models struggle with morphological variability and scene artifacts. We address both ends of this pipeline. First, we present a low-cost, open-source acquisition system, based on an Arduino UNO R3 microcontroller and NEMA 17 stepper motors, that automates focusing, magnification, and ...
Added: October 14, 2026
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Zhang Z., Ilvovsky D., Information Processing and Management 2026 Vol. 63 No. 7
Transformer-based Large Language Models (LLMs) rely on Key-Value (KV) cache to accelerate autoregressive decoding, but memory and compute requirements still grow with context length, limiting deployment on resource-constrained devices. Existing training-free KV cache compression methods mainly rely on attention-driven retention heuristics, which may under preserve structurally informative tokens under tight cache budgets, especially when such ...
Added: October 13, 2026
No Species Is an Island, Entire of Itself: Genetic Speciation Algorithm with Interplay among Species
Gromov V., Sohrabi M., Fathollahi-Fard A., International Journal of Engineering, Transactions B: Applications 2027 Vol. 40 No. 5 P. 1437–1460
This paper, with a particular emphasis on Genetic Algorithm (GA), proposes a novel approach that integrates clustering mechanisms, predator-prey dynamics, and a distinctive selection strategy for generating subsequent populations. The proposed evolutionary algorithm, referred to as Genetic Speciation Algorithm with Interplay Among Species (GSAIS), is comprehensively evaluated against several variants of GAs as well as ...
Added: October 12, 2026
Gorbunov A. A., Исаев Е. А., Приборы и системы. Управление, контроль, диагностика 2026 № 1 С. 42–46
В статье рассматриваются современные тенденции в развитии дата-центров, специализирующихся на обработке биоинформатических и
биомедицинских данных. Особое внимание уделено применению искусственного интеллекта для оптимизации работы дата-центров и анализа больших объемов биологических данных. Представлен обзор современных технологий и архитектурных решений, позволяющих обрабатывать растущие объемы данных в области биоинформатики и биомедицины. Обсуждаются перспективы развития специализированных
дата-центров в контексте экспоненциального роста ...
Added: October 12, 2026
Gorbunov A. A., Григорьев А. А., Демидов Л. Н. et al., Приборы и системы. Управление, контроль, диагностика 2025 № 7 С. 20–24
Быстрое развитие технологии квантовых вычислений потенциально может произвести революцию в сложных вычислениях в
физических, химических и биологических областях за счет использования квантовой суперпозиции и запутанности. Квантовые компьютеры используют кубиты, способные существовать в нескольких состояниях одновременно, в отличие от классических битов.
Эта функция позволяет хранить и обрабатывать больше информации, что дает значительное преимущество при решении задач с
обширным пространством ...
Added: October 12, 2026
Timur Teregulov, Elena R. Loubenets, / Series Quantum Physics "arXiv". 2026. No. 2609.31472.
We develop a new three-party quantum secret-sharing (QSS) protocol based on a three-qubit W state. This protocol encodes the secret-sequence bits using X gates and employs randomly selected Hadamard operations and measurement bases to generate information and security-test rounds. We evaluate the efficiency of the proposed protocol and analyze its security against an internal adversary ...
Added: September 28, 2026
Утешева Г. Ш., Громов Ю. Ю., Starodubov K. et al., Научно-техническая информация. Серия 2: Информационные процессы и системы 2026 № 9 С. 33–41
Проблема извлечения знаний из больших массивов данных, характерных для медицины, финансов и промышленности, осложняется неполнотой значений атрибутов. Существующие методы удаления объектов или импутирования значений искажают истинные паттерны, что при обработке данных приводит к неверным выводам. Цель настоящей работы – разработка математически строгого подхода, позволяющего выявлять интерпретируемые нечеткие ассоциативные правила в условиях неопределенности и пропуска отдельных ...
Added: September 15, 2026
Максимова Е. А., Утешева Г. Ш., Громов Ю. Ю. et al., Научно-аналитический журнал "Вестник Санкт-Петербургского университета Государственной противопожарной службы МЧС России" 2026 № 2 С. 92–103
When data are incomplete, standard fuzzy data mining methods face an unacceptable trade-off: deleting objects with missing values loses up to a third of the sample and introduces systematic bias under the MAR mechanism, while mean imputation destroys the covariance structure and produces rules with artificially inflated support. This paper proposes a different solution - ...
Added: September 6, 2026