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2021 International Symposium of Asian control Association on Intelligent Robotics and Industrial Automation, IRIA 2021

作者： Bhat, Manohar Mahto, Gopikishan Kesaria, Smit Femandes, Vikrant Arya, Kavi BMS College of Engineering Dept. of Electrical and Electronics Bangalore560019 India UPU Government Polytechnic Dept. of Computer Science and Engg. Durg491001 India Indian Institute of Technology Dept. of Systems and Control Mumbai400076 India Indian Institute of Technology Dept. of Computer Science and Engg. Mumbai400076 India

ISBN: (纸本)9781665433235

This study showcases a low-resource framework that enables people with no technical know-how to interact with drones, it also explores the capabilities of 2D- computer vision and deep learning techniques for gesture based interface systems on a low-cost micro drone with an onboard RGB camera. This Human-Robot Interaction system processes the real-time human pose to allow a user to command the drone, i.e., by providing direction to move and execute actions. A linear PD controller and image processing techniques are implemented to track humans whilst maintaining a safe distance from the user by perceiving dept. information through pose estimation. We incorporated the gesture recognition results into a drone using the Robot Operating System (ROS) and evaluated system performance indoor and outdoor. This low computation framework can be applied further to control robotic arms or mobile robots. © 2021 IEEE.

关键词： Drones

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Addressing Weight Competition in Long Short-Term Memory (LSTM) Networks for Improving Temperature Prediction

Addressing Weight Competition in Long Short-Term Memory (LST...

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International Conference on Awareness Science and Technology (iCAST)

作者： Kun-Wei Lin Yu-Fan Li Che-Yu Lin Zheng-Han Jiang Wei-Jian Chen Dept. Computer Science and Information Engineering Chaoyang University of Technology Taichung Taiwan R.O.C Dept. Information Management Chaoyang University of Technology Taichung Taiwan R.O.C

This conference paper presents a study on the application of Long Short-Term Memory (LSTM) networks to predict temperature changes in the upcoming week. During our research, we encountered the issue of weight competition within the LSTM architecture, which can lead to suboptimal predictions. To overcome this challenge, three novel methods including Independent Time Series (ITS) Model, Arithmetic Segmented Time Series (ASTS) Model and Arithmetic Segmented Rolling Time Series (ASRTS) Model, respectively, were used to address weight competition and enhance the accuracy of temperature change forecasts. The effectiveness of these methods were evaluated through extensive experiments and compared against standard LSTM models. The results demonstrate the significance of mitigating weight competition to achieve more reliable and accurate temperature predictions.

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A Deep Learning for Predicting Possibility of Bluetooth Low Energy Tag Signals

A Deep Learning for Predicting Possibility of Bluetooth Low ...

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International computer Symposium (ICS)

作者： Hao-Pei Teng Vincent S. Tseng Josh Jia-Ching Ying Dept. Management Information Systems National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering National Yang Ming Chiao Tung University Hsinchu City Taiwan

ISBN: (数字)9798331509071

ISBN: (纸本)9798331509088

With the rapid growth of IoT technology, using Bluetooth Low Energy (BLE) gateways to track the trajectory of elderly individuals can help prevent them from getting lost. However, BLE tag signals do not persist, and BLE gateways often enter standby mode for extended periods, resulting in unnecessary energy waste and reducing the lifespan of the devices. To address this issue, predicting the likelihood of BLE tag signals is essential to conserve energy. This paper presents a deep learning approach to enhance the operational efficiency and lifespan of BLE gateways deployed in an IoT system. The system consists of two major modules: the Number of BLE Tags Estimation Module and the Next Accessed BLE Gateway Prediction Module. The Number of BLE Tags Estimation Module leverages a CNN-GRU (Convolutional Neural Network - Gated Recurrent Unit) architecture to predict the time lapse between the sensing of signals from BLE tags. The Next Accessed BLE Gateway Prediction Module employs a self-attention mechanism to predict which specific BLE gateway will receive the BLE tag signal, further optimizing system performance. Experimental results show that the proposed prediction model effectively reduces unnecessary energy consumption, thereby improving the efficiency and service life of the entire IoT system.

关键词： Deep learning Urban areas Estimation Logic gates Transformers Sensors Convolutional neural networks Older adults Bluetooth Low Energy Protection

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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine

Process-Model-Free Design of MPC via a Reference-Model-Based...

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Electrical engineering, control and Robotics (EECR), International Conference on

作者： Gengjin Shi Chengbo Dai Miaomiao Ma Donghai Li Yanjun Ding Dept. of Energy & Power Engineering State Key Lab of Power Systems Tsinghua University Beijing China School of Control & Computer Engineering North China Electric Power University Beijing China

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller – desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine.

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Parameter fault diagnosis in heat exchange networks with distributed time delay

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IFAC-PapersOnLine 2022年第18期55卷 39-44页

作者： Wijaya Kurniawan Katalin M. Hangos Lőrinc Márton Dept. of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary Systems and Control Laboratory Institute for Computer Science and Control P.O. Box 63 H-1518 Budapest Hungary Dept. of Electrical Engineering Sapientia Hungarian University of Transylvania Tirgu Mures Romania

This paper deals with parameter fault diagnosis in heat exchange networks (HENs) with joining and splitting connections where the change in the heat transfer coefficient is considered as fault. The fault diagnosis oriented model of the HEN elements was developed based on the equivalent LTI realization of distributed delay models. The Signed Directed Graph (SDG) method is used to derive the fault observability conditions. The presence of faults induces bilinear fault-input terms into the system model. Thus, a nonlinear adaptive observer was proposed for fault diagnosis. To verify and validate the proposed method, a case study is presented. The simulation results show that the observers are successfully detecting and estimating the faults and unknown system states.

关键词： Fault diagnosis Heat Exchange Networks, Distributed delay, Process systems

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Improving the 8T SRAM Cell Design for Fault Tolerance and Power Efficiency

Improving the 8T SRAM Cell Design for Fault Tolerance and Po...

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Intelligent Technologies (ACOIT), Asian Conference on

作者： Ajay Sudhir Bale S. Saranya T S Arulananth Varun Yogi Shanthakumar T Y Satheesha Gururaj Murtugudde Dept. of ECE New Horizon College of Engineering Bengaluru India Dept. of Mathematics BMS Institute of Technology & Management Bengaluru India Department of Electronics and communication Engineering MLR Institute of Technology Hyderabad Telangana India Department of Electrical and Electronic Engineering California State University Sacramento California USA School of Computer Science and Engineering Reva University Bengaluru India

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

We have designed an 8T SRAM model in this work where we have worked on the issues of read/write efficiency, leakage current and also fault tolerance. The design used in this work consists of 8 transistors, 2 PMOS and 6 NMOS. Here the two transistors make a 2-NOT gate structure. The objective of this work is to design a SRAM which can work in challenging conditions very efficiently. This work has concentrated on lowering the value of leakage current, which is key in read/write operations. The design shows promising results for the above-mentioned issues. We have used Tanner EDA tool to simulate the model. As seen in the results section of this work, the model is resistant to faults. The leakage current is reduced and is very less compared to traditional SRAM cells. The leakage power obtained with this model is $0.599 \mu \mathrm{~W}$ which is very less compared to the traditional methods. This model which we have proposed in this work, seems to be very much apt to density packed operations and also when power efficient operativity is required. This work tackled the basic issues of the traditional SRAM design, where R/W efficiency, leakage current and fault tolerance were taken into consideration. We were successful in achieving a system which provided solution to the above problems along with the issues of elevated temperatures, radiation, or EMI.

关键词： Fault tolerance Torque Microprocessors Fault tolerant systems Resistive RAM Electromagnetic interference SRAM cells Leakage currents Transistors Aerospace industry

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A Tanner Based Approach to analyse the comparisons between 6T and 8T SRAM 10

A Tanner Based Approach to analyse the comparisons between 6...

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10th International Conference on Internet of Everything, Microwave engineering, Communication and Networks, IEMECON 2021

作者： Sen, Soumva Saha, Souvik Biswas, Alpana Dasgupta, Agnibha Seacom Engineering College Sankrail Dept. of Electronics Communication Engineering Howrah India University of Engineering Management Dept. of Electronics Communication Engineering Jaipur India Maulana Abul Kalam Azad University of Technology Dept.of Computer Scienece Engineering Haringhata India Maulana Abul Kalam Azad University of Technology Dept. of Microelectronics and VLSI Design Haringhata India

ISBN: (纸本)9781665426862

The WRITE phase for a Complementary Metal Oxide Semiconductor (CMOS) Static Random-Access Memory (SRAM) cell was investigated. We've focused in particular on a phenomenon known as dynamic power dissipation. This occurrence occurs in the CMOS SRAM cell during the WRITE operation. During the Write 0 and Write 1 operations, we discovered that the discharging and charging of bit lines consumes greater power while the CMOS SRAM call is active. In the pull-down route of an 8T SRAM cell, two additional trail transistors are required for correct discharging and charging of the bit lines. The results are mostly taken into account based on various frequencies that have been set. For the circuit analysis, we employed 130 nm technology and a supply voltage of 1.5 V. We were able to lower the dissipated power of the low-power 8T SRAM cell by comparing the results to previous work, which was done with a 6T SRAM cell. © 2021 IEEE.

关键词： Static random access storage

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Creating Disaggregated Network Services with eBPF: the Kubernetes Network Provider Use Case

Creating Disaggregated Network Services with eBPF: the Kuber...

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IEEE Conference on Network Softwarization (NetSoft)

作者： Federico Parola Leonardo Di Giovanna Giuseppe Ognibene Fulvio Risso Dept. of Control and Computer Engineering Politecnico di Torino 24 Corso Duca degli Abruzzi Torino Italy

ISBN: (数字)9781665406949

ISBN: (纸本)9781665406956

The eBPF technology enables the creation of custom and highly efficient network services, running in the Linux kernel, tailored to the precise use case under consideration. However, the most prominent examples of such network services in eBPF follow a monolithic approach, in which all required code is created within the same program block. This makes the code hard to maintain, to extend, and difficult to reuse in other use cases. This paper leverages the Polycube framework to demonstrate that a disaggregated approach is feasible also with eBPF, with minimal overhead, introducing a larger degree of code reusability. This paper considers a complex network scenario, such as a complete network provider for Kubernetes, presenting the resulting architecture and a preliminary performance evaluation.

关键词： Performance evaluation Codes Linux Conferences Debugging Complex networks Routing

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Performance Enhancement and Secrecy Analysis of Hybrid RF/FSO Communication Links Under Combined κ-μ Fading and Exponential Turbulence Conditions 2

Performance Enhancement and Secrecy Analysis of Hybrid RF/FS...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Upadhyay, Deepak Prakhar Moray, Rashmy Sharma, Rashmi Venu, Nookala Shukla, Shipra Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of CSE Roorkee Institute of Technology Pune India A constituent of Symbiosis International Deemed University India Nagpur Campus Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798331530389

In this study, the secrecy performance evaluation of hybrid RF/FSO communication systems over κ-μ fading and exponential turbulence channels are conducted. We analyse the secure information rate and evaluate the throughput and secrecy capacity of the system through simulations. The results indicate that the proposed hybrid system improves reliability and security by combining adaptive modulation, beamforming, and encryption to combat interference and secure data transmission. Geographical heat maps help to visualize the influence of environmental factors on system performance. Federated learning in hybrid RF/FSO systems have been investigated in detail through simulations and numerical results to show the considerable improvements in communication reliability and performance that the increased redundancy and robustness of the hybrid scheme provides. This helps gain valuable insights into a better design of wireless networks in the future by highlighting the benefits of hybrid communication techniques and simulation-driven design to enhance performance and security across diverse complex environments and conditions. © 2025 IEEE.

关键词： Adaptive modulation

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Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry

Monitoring and Forecasting Quality Indicators of Predough Pr...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Andrii Zhyltsov dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of electromagnetic systems The Institute of Electrodynamics of the National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them.

关键词： Force Process control Production Machine learning Quality control Humidity Predictive models Stability analysis Monitoring Thermal stability

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