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Brain-computer Interface System Based on Common Spatial Patterns for Inner Speech Recognition from Electroencephalography Signal by Using a Convolutional Neural Networks

Brain-Computer Interface System Based on Common Spatial Patt...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Abdalla, Hussna Elnoor M. Al-Haddad, Syed Abdul Rahman Basri, Hamidon Bin Aris, Ishak Bin Yusofv, Abdul Hanif Khan Bin Neyaz, Hisham University Putra Malaysia Malaysia & Sudan International University Sudan University Putra Malaysia Department of Computer and Communication System Engineering Malaysia University Putra Malaysia Faculty of Medicine and Health Sciences Department of Medicine Malaysia University Putra Malaysia Department of Electrical and Electronic Engineering Malaysia University Putra Faculty of Medicine and Health Sciences Department of Medicine Malaysia

ISBN: (纸本)9781665410205

Inner speech recognition is a modern advancement in Brain computer interfaces (BCI) that facilitates a communication between the computer and the brain in a direct way. It is particularly beneficial for individuals who face communication issues due to speech disability. In this research, an end-to-end brain-computer interface system was developed that uses Electroencephalography (EEG) signals to recognize inner speech straight from the brain. The study utilized an open-access dataset presented on four Spanish words from ten participants. The proposed system involved preprocessing to clean and enhance the signal. Common Spatial Pattern (CSP) was utilized to extract features to improve the discrimination between the selected four words. A Convolutional Neural Networks (CNNs) deep learning model was used to enhance the inner speech recognition performance from spatial features. The result shows that the model can decode the inner speech with an average accuracy of 81.40% for the un-seeing dataset and 89.80% for the entire dataset, indicating that the proposed method outperforms previous works that used the same dataset. © 2024 IEEE.

关键词： Convolutional neural networks

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Secure Encryption and Decryption Circuit on 8T1C Structure-Based Charge Accumulation and Dissipation

Secure Encryption and Decryption Circuit on 8T1C Structure-B...

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International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Shutong Zhang Pengjun Wang Ziyu Zhou Yuejun Zhang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (数字)9798331509453

ISBN: (纸本)9798331520243

To solve the large resource overhead and risk problems of traditional encryption and decryption technologies. This paper presents a secure computing scheme of 8T1C structure based on charge accumulation and dissipation which is used to implement low-cost encryption and decryption circuits. Firstly, the scheme uses the characteristics of capacitor charge accumulation and dissipation to complete the XOR encryption. Decryption of data is performed by dynamically charging and discharging the load capacitor. Secondly the 8T1C SRAM unit structure is designed in combination with the Static Random-Access Memory Physical Unclonable Function (SRAM PUF) structure. The encryption and decryption operations are built into the storage unit to reduce the hardware resource overhead, by integrating additional MOS tubes and capacitors. Finally, the encrypted data is reshaped by the sense amplifier and stored in the same unit. The function of safe data storage is realized through hardware reuse of circuit resources. The security encryption and decryption circuit is simulated and verified In the TSMC 65nm process. The experimental results show that the designed encryption and decryption circuit structure can confuse the traces of the original data and recover the original information content in the decryption process. PUF key uniqueness is 50.31%, randomness is 99.9%, and it has passed the NIST randomness test. Under the working environment of -50 °C~125°C and 0.8V to 1.5V, the worst bit error rate is 7.6%, which can be applied to the security encryption field of the Internet of Things.

关键词： Integrated circuits Micromechanical devices Circuits Capacitors Random access memory NIST Physical unclonable function Reliability engineering Hardware Encryption

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Power Budget Calculation and Sensitivity Enhancement for N×25 Gbps TDM-PON Configuration 3

Power Budget Calculation and Sensitivity Enhancement for N×...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Feituri, Ahmed B Abdullah, M.F.L. Swedan, Abdulhameed Almabrok Suliman, Hager A Universiti Tun Hussen Onn Malaysia Faculty of Electrical and Electronic Engineering Batu Pahat Malaysia The Electronic and Communication Research Center Applied Research and Development Authority Tripoli Libya University of Misurata Department of Computer Science Misurata Libya

ISBN: (纸本)9798350319897

Passive Optical Network (PON) standards relied on Time Division Multiplexing (TDM) and Wavelength Division Multiplexing (WDM) methods to maximize data rate. The latest 25GS-PON specifications were declared by Multi-Source Agreement (MSA) group in 2022. The current work stacks two and four 25-Gb/s TDM-PON downstream (DS) channels. The simulation, evaluation, and outcomes are completed using various versions of *** software. O-band wavelength plan as well as Continuous-Wave (CW) laser with Non-Return-to-Zero/On-Off-Keying (NRZ-OOK) format support the system to mitigate Chromatic Dispersion (CD) and upgrade the system capacity. The power budget of 31.1 dB is suitable for Optical Distribution Network (ODN) standards, and the standard value of receiver sensitivity (-24.1 dBm) is achieved. The transmitted power of 1, 4, and 7 dBm are needed for 32, 64, and 128 users/λ, respectively. The transmission is successful for 512 subscribers and 20 km optical reach without the use of amplifiers, Forward Error Correction (FEC), and compensation techniques. The effect of four-wave mixing (FWM) is solved by the wavelength space of 0.8 nm as well as the slight increase in transmitted power from 7 to 7.8 dBm. The open and clear eye diagrams prove the quality of received signals. The simplicity of structure is high because of utilizing basic components and Intensity Modulation/Direct Detection (IM/DD) strategy without amplification and equalization. FEC and compensation techniques are recommended for future work. © 2023 IEEE.

关键词： Passive optical networks

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Leaf Guard: Detecting the Diseases in Banana Leaf 5

Leaf Guard: Detecting the Diseases in Banana Leaf

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Yathurshan, K. Barathy, S. Karini, G. Sajitha, P. Abeygunawardhna, Pradeep Rajapakse, Kaushalya Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Engineering Electrical & Electronic Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

This research paper introduces 'Leaf Guard,' a mobile app designed for disease detection and management in banana trees, specifically tailored for Sri Lanka's agricultural landscape. Through the amalgamation of image processing, deep learning, and customized chemical recommendations, this app proficiently identifies early-stage diseases, offering tailored remedies. Catering to farmers and agricultural experts, 'Leaf Guard' provides an intuitive tool, revolutionizing disease management and bolstering sustainable banana cultivation practices. By seamlessly integrating these cutting-edge technologies, this research significantly advances disease detection methods, paving the way for environmentally friendly and economical interventions. The study's findings not only enrich the realm of disease detection technology but also hold promise for future innovations, fostering sustainable approaches to enhance banana cultivation. © 2023 IEEE.

关键词： Cultivation

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A Defense Against Rowhammer Attacks Based on Dual-Layer RRAM Counting Method

A Defense Against Rowhammer Attacks Based on Dual-Layer RRAM...

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International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Zhuo Ruan Yuejun Zhang Shuaicheng Guo Pengjun Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (数字)9798331509453

ISBN: (纸本)9798331520243

The security issues in high-density memory have attracted increasing attention, and how to defend Row Hammer (RH) has become a research hotspot. To address the issue of significant storage overhead in defending RH attacks, this paper proposes a defense method based on dual-layer counting with Resistive Random Access Memory (RRAM). Initially, this method investigates the transition from low-resistance state to high-resistance state in RRAM, and utilizes the resistance variation process of RRAM to represent the number of row activations, achieving the functionality of counting row activations using a single RRAM; Secondly, a group counter is formed by an RRAM that one end connected to multiple memory rows and a sensitive amplifier that monitors the resistance variation of the RRAM. This group counter completes the aggregated counting of the row groups formed by multiple memory rows, completing the aggregation counting of the row groups composed of multiple memory rows; Finally, a row counter is constructed using RRAM and a sensitive amplifier placed at the end of a single memory row to accurately count the memory rows that exceed the counting range of the previous stage, achieving protection against RH. The dual-layer counter composed of row counter and group counter is connected to DRAM and tested under TSMC28nm technology. The experimental results demonstrate that the two counters can work together to protect against RH attacks without affecting the original Dynamic Random Access Memory (DRAM) timing logic.

关键词： Resistance Micromechanical devices Integrated circuits Resistive RAM Timing Logic Security Protection Monitoring

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A 7nm-Based Decodable Self-Resetting Regfile Circuit 15

A 7nm-Based Decodable Self-Resetting Regfile Circuit

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Zhao, Wanlong Zhang, Yuejun Ren, Mingze Wen, Liang Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo University Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China China Coast Guard Academy Department of Electronic Technology Ningbo China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

This paper presents a novel design scheme for a decodable self-resetting Regfile circuit that aims to reduce the power consumption caused by massive data and high computing power. The scheme consists of three steps: first, it analyzes the working principle and the energy consumption process of the decoding circuit;second, it proposes a self-resetting decoding circuit structure that uses the clock to control the decoding state and automatically resets when the clock is low, thus avoiding the extra power consumption due to the inversion of the memory cell state during the non-working period of the decoding circuit;third, it implements a two-read, two-write, decodable self-resetting Regfile circuit using a full-custom design method under the TSMC 7nm FinFET process. The experimental results demonstrate that the circuit has an area of 5593μm2 and an energy-delay product of 0.41pJ•nS, and it can operate stably at 4GHz under various temperatures and process corner conditions. © 2023 IEEE.

关键词： 7nm process high speed low power consumption Regfile circuit

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Green Machine Learning Approach for QoS Improvement in Cellular Communications 2

Green Machine Learning Approach for QoS Improvement in Cellu...

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2nd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2022

作者： Saeed, Mamoon M. Saeed, Rashid A. Azim, Mohammad Abdul Ali, Elmustafa Sayed Mokhtar, Rania A. Khalifa, Othman Faculty of Engineering Communications and Electronics Engineering Department Yemen Taif University College of Computers and Information Technology Department of Computer Engineering Taif21944 Saudi Arabia Asian University for Women Department of Computer Science Bangladesh Department of Electrical Electronic Engineering Port Sudan Sudan College of Electronics Engineering Khartoum Sudan International Islamic University Malaysia Faculty of Engineering Dept of Electrical and Electronics Engineering Malaysia

ISBN: (数字)9781665479189

ISBN: (纸本)9781665479189

Green cellular communications are becoming an important approach due to large-scale and complex radio networks. Due to the dynamic cellular network behaviors related to interference distribution, traffic bottlenecks, congestion points, and hotspots, there is a need to evaluate the dynamic processes in cellular systems in addition to ensuring spectrum availability. The delay, loss rate, and SNR are the most issues that may affect cellular communication performance. Artificial intelligent algorithms such as machine learning (ML) enable to detection of the dynamics in cellular networks by analyzing the complex cellular network processes and evaluating the spectrum and links qualities. It enables the extraction of spectrum knowledge from the network autonomously. The extracted information helps to know about every dynamic change in wireless parameters, related to frequency, modulation, route selection, etc. This paper provides details about the use of ML in green cellular networks to efficiently upgrade the communications and enhances different related approaches including quality of services (QoS), signal traffic load, and energy efficiency, which are critical issues of green cellular communication paradigms. The paper also presents the technical concept of green ML approaches to solve significant problems in cellular communications, in addition to future aspects and considerations for energy consumption minimization using the green ML approach in cellular radio communications. © 2022 IEEE.

关键词： Energy efficiency

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Loss Analysis Towards Developing a Digital Twin Model of a PMSG-Based Powertrain for Wind Turbine System

Loss Analysis Towards Developing a Digital Twin Model of a P...

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European Conference on Power electronics and Applications

作者： Abdullah Shawier Shady Gadoue Kamyar Mehran School of Electronic Engineering and Computer Science Queen Mary Univierty of Lonodn London UK Faculty of Engineering Alexandria Univerity Alexandria Egypt

ISBN: (数字)9798350364446

ISBN: (纸本)9798350364453

Wind turbine energy plays a vital role in the transition towards a cleaner energy environment. The ever-growing demand on wind turbine systems (WTS) necessitates the exploration of new technologies that offer higher reliability and efficiency. Digital twin (DT) technology has emerged as a leading trend for WTS. In this regard, this work aims to carry out a comprehensive losses analysis for the powertrain of a PMSG-based WTS to develop an accurate DT model for efficiency maximization. Leveraging finite element analysis, this study analyzes various loss components across stator, rotor, magnet, and converter under both passive and active rectifier configurations. The influence of current waveform and operating conditions on these loss components and torque ripple is also examined. The findings will contribute to training the DT model and further enhance the efficiency and performance optimization of WTS.

关键词： Wind speed Switching frequency Core loss Rectifiers Europe Mechanical power transmission Iron Wind turbines Digital twins Torque measurement

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A Reliable Current Starved Inverter PUF Based on SRAM Memory Structure

A Reliable Current Starved Inverter PUF Based on SRAM Memory...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Mingze Ren Pengjun Wang Yuejun Zhang Shutong Zhang Zhikang Chen Tengfei Yuan Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

This paper presents a current starved inverter physically unclonable function (PUF) based on static random memory (SRAM) structure. By improving the SRAM cell structure, the PUF cell is biased in the subthreshold region to form a current starved inverter PUF, and the DIBL effect amplifies the voltage distribution of the switching threshold in current starved inverter PUF. Meanwhile, the proposed PUF is monostable, which provides higher reliability compared to the conventional SRAM PUF and retains the storage function of conventional SRAM. We simulate and verify the proposed PUF circuit at 65nm process. The simulation results show that the proposed PUF exhibits superior uniqueness and randomness with an average inter-chip Hamming distance of 50.17% and a standard deviation of 0.0639, which passes the NIST 800–22 randomness test. The worst BER is 3.27% and 2.05 % over the temperature variation range of −20°C–80°C and the voltage variation range of 1V-l.4V, respectively.

关键词： Temperature distribution Simulation Random access memory Switches SRAM cells Physical unclonable function Inverters Threshold voltage Integrated circuit reliability Standards

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Automated Artificial Intelligence Empowered White Blood Cells Classification Model

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computers, Materials & Continua 2023年第4期75卷 409-425页

作者： Mohammad Yamin Abdullah M.Basahel Mona Abusurrah Sulafah M Basahel Sachi Nandan Mohanty E.Laxmi Lydia Faculty of Economics and Administration King Abdulaziz UniversityJeddahSaudi Arabia Department of Management Information Systems College of Business AdministrationTaibah UniversityAl-MadinahSaudi Arabia E-commerce Department College of Administrative and Financial SciencesSaudi Electronic UniversityJeddahSaudi Arabia School of Computer Science&Engineering(SCOPE) VIT-AP UniversityAmaravatiAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information Technology(Autonomous)VisakhapatnamAndhra Pradesh530049India

White blood cells (WBC) or leukocytes are a vital component ofthe blood which forms the immune system, which is accountable to fightforeign elements. The WBC images can be exposed to different data analysisapproaches which categorize different kinds of WBC. Conventionally, laboratorytests are carried out to determine the kind of WBC which is erroneousand time consuming. Recently, deep learning (DL) models can be employedfor automated investigation of WBC images in short duration. Therefore,this paper introduces an Aquila Optimizer with Transfer Learning basedAutomated White Blood Cells Classification (AOTL-WBCC) technique. Thepresented AOTL-WBCC model executes data normalization and data augmentationprocess (rotation and zooming) at the initial stage. In addition,the residual network (ResNet) approach was used for feature extraction inwhich the initial hyperparameter values of the ResNet model are tuned by theuse of AO algorithm. Finally, Bayesian neural network (BNN) classificationtechnique has been implied for the identification of WBC images into distinctclasses. The experimental validation of the AOTL-WBCC methodology isperformed with the help of Kaggle dataset. The experimental results foundthat the AOTL-WBCC model has outperformed other techniques which arebased on image processing and manual feature engineering approaches underdifferent dimensions.

关键词： White blood cells cell engineering computational intelligence image classification transfer learning

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