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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Kljajić, Ružica Kraus, Zorislav Fekete, Krešimir Marić, Predrag Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

Small industrial utilities, connected to the distribution grid, can cause various disturbances that need to be eliminated or mitigated. Due to the complexity of the system and the large number of motors, industrial consumers may have problems with the voltage deviations caused by the excessive amount of reactive energy which is a natural consequence of their operation and construction. Since industrial consumers have to pay for both active and reactive power delivered from the grid, the goal is to reduce those costs as well as to reduce feeder loadings. Delivered energy can be reduced by installing compensation devices or by connecting photovoltaic power plant, which would produce active and reactive energy at the point of consumption. This paper analyzes the power flows and voltage conditions of a small industrial facility in three scenarios: the basic scenario, the second scenario with built-in compensation devices and in the third scenario with integrated photovoltaic power plant. For all three scenarios, power flow analysis is performed and results are presented in the form of tables and graphically. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy efficiency

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An Advanced Tactile-Haptic Controller for Smart Home 32nd

An Advanced Tactile-Haptic Controller for Smart Home

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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Radić, Miloš Keser, Tomislav Blažević, Damir Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

A smart home philosophy strongly relies on a technical principle of automatization almost every aspect of today’s way of living. Sole automation of does not only manage system processes in household, or living environment in general, but all adjacent systems and corresponding subsystems which helps to maintain system-in-whole in operational state. From control of environmental temperature, air conditioning, lighting, utility control, etc., all existing "smart" systems predominantly control actuation part of smart home. Very miniscule "smart" systems do manage and serve human-machine interaction part of it and, if are made "smart", they rely on solutions that utilizes some sort of existing ICT technologies that are mainly optimized for communication and visual presentation, not for in-situ smart home interaction. This paper deals with the problem of development of a tactile-haptic solution for control of smart home specific subsystem and that utilize IoT platform, giving feel and user experience similar to traditional one in form of an advanced switch with regulation ability. Tactile commanding with haptic feedback is presented and applied in smart home temperature regulation. Finally, an IoT platform solution is developed, tactile-haptic relation investigated with optimal solution established, and its functionality is verified as well as is proven in real time environment. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Air conditioning

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Evaluating Optimization Approaches for Deep-Reinforcement-Learning-based Navigation Agents 10

Evaluating Optimization Approaches for Deep-Reinforcement-Le...

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10th IEEE International Conference on Cybernetics and Intelligent Systems and IEEE Conference on Robotics, Automation and Mechatronics, CIS-RAM 2023

作者： Kästner, Linh Roberts, Liam Bhuiyan, Teham Lambrecht, Jens Berlin Institute of Technology Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350303087

In recent years, Deep Reinforcement learning has made remarkable progress in various application areas such as control of robots and vehicles, simulation, and natural language processing. In recent years, various research works applied DRL to conduct different kinds of tasks for autonomous navigation of vehicles and robots such as lane changing, cruise control, or obstacle avoidance. However, DRL training is still a tedious and difficult process due to long training times, catastrophic forgetfulness and the myopic nature of DRL agents. In this paper, we integrate and explore the effect of a variety of state-of-the-art optimization approaches for DRL agents such as imitation learning, behavior cloning, frame stacking, and hindsight replay for autonomous obstacle avoidance. We evaluate the effect of each of these changes to the DRL agent in terms of training- as well as navigational performance. The resulting agents are compared against baseline approaches without those optimizations and we found an increase in navigational performance for some of these methods while other optimization approaches surprisingly resulted in decreased performing. The findings of this paper should aid in development of DRL approaches for autonomous navigation approaches. © 2023 IEEE.

关键词： Natural language processing systems

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Automated Titration of SO2 in the Winery Environment: Conceptual Design and Proof of Concept 1

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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Keser, Tomislav Miling, Robert Miličević, Davorin Blažević, Damir Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

The wine production industry competes every day for better product quality, same time lowering production costs. As product quality strongly relies on winemaker expertise and quality of raw materials, lower production costs are tightly related to the automation level of whole production process. One of parameter that significantly influences on the wine quality is sulphur-oxide based compound in its free form which is measurable using process so called titration of SO (sulphur oxide titration). Currently the state of titration measurement automation highly correlates to the scale of production and only the biggest winemakers have some sort of automated titration devices. Such devices are not suitable for small or medium winemakers due their high costs, either of purchase of measurement services. This paper proposes, make conceptual development and evaluate functionality for an automated titration device for SO compounds in winemaking industry which is suitable for small and medium winemakers and does not break their banks. The concept elaborates and deduce setup for distributed wine supplying, conditioning of the measurement device and metrology of the measurement. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Titration

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Photovoltaic Power Forecasting with an Ensemble Multi-Input Deep Learning Approach 8

Photovoltaic Power Forecasting with an Ensemble Multi-Input ...

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8th International Conference on Technology and Energy Management, ICTEM 2023

作者： Dehghan, Fariba Moghaddam, Mohsen Parsa Imani, Maryam Tarbiat Modares University Faculty of Interdisciplinary Science and Technology Tehran Iran Tarbiat Modares University Faculty of Interdisciplinary Science and Technology Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665452854

The inherent intermittency of solar power due to meteorological factors presents a significant challenge in integrating them into grids on large scales. An accurate Photovoltaic (PV) power generation forecasting effectively supports achieving optimal planning and operational stability of power systems. Motivated by satisfactory performance of deep learning methods in the energy sector, an ensemble multi-input deep learning method combining three-dimensional convolution (Conv3D) networks and bidirectional long short-term memory (BiLSTM) networks is proposed in this study. First, one-dimensional (vector) PV power production and atmosphere parameters series are rearranged into a bi-dimensional matrix (2D image) and stacked in the third dimension (3D image) to preserve dependency between the input data. Then, the Conv3D network is utilized to extract non-linear spatial features of the 3D image. Finally, the BiLSTM network is implemented to learn the long-term dependencies of the extracted spatial features. The proposed method is utilized for one-day, three-day, five-day, and seven-day ahead PV power forecasting with one-hour intervals for Tennent operators, Germany dataset. Experimental results show reduced prediction error compared to two-dimensional Convolution (Conv2D), Conv3D, long short-term memory (LSTM), BiLSTM, Conv-LSTM, and ConvLSTM networks. © 2023 IEEE.

关键词： Long short-term memory

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RS485 Network Design and Maintenance in Food Processing Industry: A Winery Application 1

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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Kovačević, Ivana Matić, Tomislav Keser, Tomislav Miling, Robert Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

The communication networks are widely in use in every aspect of our life, making our environment compliable to the ever-present IoT oriented technocratic society. Good and quality communication enables reliable and representative data transportation service which provides interoperability of various data-processing systems. Majority of industrial processes have some sort of communication topologies used for interconnection of various subsystems, required by their specific operation principles, and often works in harsh and electrically and mechanically unpleasant environment. Presence of electromagnetic noises, electric discharges, strong and high alternating magnetic fields, mechanical and chemical stresses, also environmentally caused impacts on data transportation scheme, cause data corruption and lowers availability and reliability of such network. This paper deals with the problem of design, implementation and verification of RS485 based communication network for multi-nodal data exchange in winery cellars. The wine cellar represents exceptionally harsh environment in aspects of environmental chemical and electrical related conditions. The paper proposes optimal topology among multi-nodal communication devices for an experimental cellar setup, and develop communication protocol for efficient data exchange. Furthermore, a strategy for successful maintenance is also presented through in-protocol and nodal-oriented topology integration. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Wine

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Optihybrid: a modified firebug swarm optimization algorithm for optimal sizing of hybrid renewable power system

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Neural Computing and Applications 2024年第34期36卷 21517-21543页

作者： Abd El-Sattar, Hoda Kamel, Salah Hashim, Fatma A. Sabbeh, Sahar F. Luxor Higher Institute of Engineering and Technology Luxor85834 Egypt Department of Electrical Engineering Faculty of Engineering Aswan University Aswan81542 Egypt Faculty of Engineering Helwan University Cairo Egypt MEU Research Unit Middle East University Amman1183 Jordan College of Computer Science and Engineering University of Jeddah Jeddah21493 Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha13518 Egypt

In areas where conventional energy sources are unavailable, alternative energy technologies play a crucial role in generating electricity. These technologies offer various benefits, such as reliable energy supply, environmental sustainability, and employment opportunities in rural regions. This study focuses on the development of a novel optimization algorithm called the modified firebug swarm algorithm (mFSO). Its objective is to determine the optimal size of an integrated renewable power system for supplying electricity to a specific remote site in Dehiba town, located in the eastern province of Tataouine, Tunisia. The proposed configuration for the standalone hybrid system involves PV/biomass/battery, and three objective functions are considered: minimizing the total energy cost (COE), reducing the loss of power supply probability (LPSP), and managing excess energy (EXC). The effectiveness of the modified algorithm is evaluated using various tests, including the Wilcoxon test, boxplot analysis, and the ten benchmark functions of the CEC2020 benchmark. Comparative analysis between the mFSO and widely used algorithms like the original Firebug Swarm Optimization (FSO), Slime Mold Algorithm (SMA), and Seagull Optimization Algorithm (SOA) demonstrates that the proposed mFSO technique is efficient and effective in solving the design problem, surpassing other optimization algorithms. © The Author(s) 2024.

关键词： Hybrid power

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REES AAEE special issue on engineering education research capability development: introduction by guest editors

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Australasian Journal of engineering Education 2023年第1期28卷 2-7页

作者： Dart, Sarah Seniuk Cicek, Jillian Sohoni, Sohum Learning and Teaching Unit & Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Centre for Engineering Professional Practice and Engineering Education University of Manitoba Winnipeg Canada Department of Electrical Engineering and Computer Science Milwaukee School of Engineering Milwaukee United States

Since the late 20th century, engineering Education Research (EER) has been expanding globally as a field, although its identity varies across institutions and countries around the world. This diversity in how EER is experienced across contexts impacts how capability is developed, including identities, knowledge, practices, agendas, funding, and pathways. The theme of ‘engineering Education Research Capability Development’ was explored in papers, presentations, and workshops throughout the jointly held 2021 Research in engineering Education Symposium and Australasian Association for engineering Education conference. This special issue presents a continuation of that theme. The papers collectively contribute to expanding global understanding of the field, with implications for future capacity building efforts in engineering education practice and research. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： engineering education

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The Use of Smartphones and Tablets for Teaching Biology at a Distance: A Comparison between Rural and Urban Schools 46

The Use of Smartphones and Tablets for Teaching Biology at a...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Lang, V. Sorgo, A. University of Maribor Faculty of Natural Sciences and Mathematics Maribor Slovenia University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9789532331042

Smartphones and tablets (SPT) have become an integral part of daily life, and their added value for biology education was seriously tested during the COVID -19 pandemic in distance education. We collected data from 355 elementary-aged children attending 6th to 9th grade;30% of the participants were from rural schools and 70% from urban schools. Results show that most children, 75.7%, used SPT very frequently to search for information on the World Wide Web and 65.9% used SPT frequently to participate in distance learning (videoconferencing). Very rarely, if ever, was SPT used to conduct experiments, virtual field trips, or hands-on work in virtual laboratories. PCA analysis revealed 2 components. The first component explained the non-use of SPT for hands-on work (33.6%, Cronbach's alpha =0.85) and the second component explained the use of SPT for communication and collaboration (28.8%, Cronbach's alpha =0.77). We were also interested in whether the environment of the school (rural or urban) influenced the use of SPT. There is no statistically significant difference in access to wearable smart technology between urban and rural students. © 2023 MIPRO Croatian Society.

关键词： Smartphones

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Classification of Network Traffic and Anomaly Detection Using Entropy in NetFlow Records 66

Classification of Network Traffic and Anomaly Detection Usin...

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66th International Symposium ELMAR, ELMAR 2024

作者： Fosic, Igor Zagar, Drago HEP-Telekomunikacije Osijek Croatia Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9798350375411

Within the field of machine learning and classification techniques, entropy represents a concept with great potential, especially within algorithms like Random Forest. The paper proposes a method for calculating the Shannon entropy of all features within individual NetFlow records in the dataset. By comparing four variations of the LUFlow dataset with and without the entropy feature, the obtained results of the AUC metric and confusion matrix showed improved classification performance using the proposed method for calculating the entropy of NetFlow record features. The suggested approach for calculating the entropy feature demonstrates a greater impact than the entropy feature included in the original LUFlow dataset. © 2024 IEEE.

关键词： classification entropy NetFlow supervised machine learning

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