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Multi‐Task Residential Short‐Term Load Prediction Based on Contrastive Learning IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-16 Wuqing Zhang, Jianbin Li, Sixing Wu, Yiguo Guo
Load forecasting is crucial for the operation and planning of electricity generation, transmission, and distribution. In the context of short‐term electricity load prediction for residential users, single‐task learning methods fail to consider the relationship among multiple residential users and have limited feature extraction capabilities for residential load data. It is challenging to obtain sufficient
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Flow Behavior Characterization of DNA Molecules in Passive Nanofluidic Devices† IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-16 Franziska M. Esmek, Phil Grzybeck, Rukan Nasri, Sadhana Tiwari, Irene Fernandez‐Cuesta
This work aims to develop a method for analyzing the dynamic flow of single DNA molecules through nanochannels in fluidic chip which work passively. For this purpose, a two‐laser system was used, which is coupled into a fluorescence microscope and can detect labeled DNA molecules using a single photon counter for signal read‐out in real‐time. The two laser spots are focused at different points of the
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Fabrication of High‐Density Micro‐Bump Arrays for 3D Integration of MEMS and CMOS IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-16 Yunfan Shi, Zilin Wang, Rutian Huang, Jin Kang, Kai Zheng, Weihai Bu, Zheyao Wang
Cu‐Sn transient‐liquid‐phase bonding has a limit in achieving small diameter/high‐density bumps due to the extrusion of the melted Sn layer during bonding. This paper report a new method that can fabricate small diameter Cu‐Sn bumps with 5 μm diameter and 25 μm pitch based on a new thermal reflow and pre‐bonding method that enables solid‐state Cu‐Sn reaction for avoiding Sn extrusion. Using the new
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Bilayer Self‐Folding Method with High Folding Force and Angle by Suppressing Delamination of Shrink Layer IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-16 Yusuke Sato, Takashi Sato, Eiji Iwase
Heat‐shrinkable films commonly serve as active materials for self‐folding owing to their capability to fold all hinges upon heating. For origami‐based electronic devices, the self‐folding of the metal layer is necessary. Nevertheless, the self‐folding angle is low owing to the high bending stiffness of metal layers and the low adhesion of heat‐shrinkable films. Here, we introduce a bilayer self‐folding
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Self‐Stretchable Christmas‐Tree‐Shaped Ultraflexible Neural Probes† IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-14 Ye Tian, Cunkai Zhou, Kuikui Zhang, Huiran Yang, Zhaohan Chen, Yifei Ye, Zhitao Zhou, Xiaolin Wei, Tiger H. Tao, Liuyang Sun
This paper devised a novel Christmas‐tree structure for flexible neural probes, which features recording sites on side‐branches that can be folded along the shank of the probe by temporary encapsulation before implantation. This design reduces the size of the implant and minimizes the surgical footprint. Upon implantation, the temporary encapsulation dissolves in vivo, leading to self‐stretching of
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pvFed: Personalized Vertical Federated learning for Client‐Specific Tasks IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-12 Akihito Nishikawa, Tomu Yanabe, Yuiko Sakuma, Yuma Okuda, Hiroaki Nishi
Federated Learning (FL) is a distributed machine learning paradigm that enables multiple data holders to collaborate on building machine learning models while preserving the privacy of their data. FL can be categorized as horizontal or vertical, depending on the distribution characteristics of the data. Specifically, horizontal FL uses data partitioned in the sample space, whereas vertical FL uses
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HAPOVER: A Haptic Pronunciation Improver Device IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-09 Rıza Ilhan, Kadir Kaçanoğlu
This research article describes the HAPOVER (a haptic pronunciation improver device), which was produced to help second language learners' pronunciation skills as part of their foreign language learning process. The device comprises eight independent vibration motors connected to the fingers other than the thumb. The developed tactile feedback device was utilized to enhance pronunciation via speech
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Enhancing Incipient Fault Detection for Interface Converter Sensors through Signal Correlation Analysis IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-09 Chujia Guo, Qingqing Yang
Incipient faults in interface converters can potentially lead to catastrophic failures. Detection of incipient faults contributes to proactive fault management and predictive maintenance, which effectively improves system reliability. In this paper, a detection method in correlation space is proposed to address this problem, which is based on the inherent feature of correlation changes when a fault
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FDTD Analysis of Electric Field and Step Voltage in a Clay‐Wall House Struck by Lightning IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-08 Ken Uetsuhara, Yoshihiro Baba, Takeshi Kudo
The density of lightning flashes is quite high in Rwanda and its neighboring countries in Africa. In rural areas of these countries, there are still many clay‐wall houses. Sometimes people in clay‐wall houses are fatally injured by direct lightning strikes to the houses. In this paper, the electric field in a clay‐wall house and the step voltage on the floor, associated with a direct lightning strike
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All Ceramic Ion Sensor Using Dielectric BaTiO3 Transducer IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-08 Soichiro Suzuki, Satoko Takase, Youichi Shimizu
An all‐solid‐state impedance metric hydrogen‐phosphate ion sensor device has been tried to fabricate using BaTiO3 as a transducer and spinel‐type oxide receptor. AC impedance measurement was carried out using flow‐cell system with boric‐acid buffer solution with hydrogen‐phosphate ion The Co2RhO4/BaTiO3 sensor device was found to show impedance responses to hydrogen‐phosphate ion at 5 × 10−4 M and
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Equivalent Analytical Model of Magnetic Field in Parallel Magnetic Circuit Axial Flux Permanent Magnet Machines IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-07 Zhao Xiaoxiao, Wang Xiaoyuan, Gao Peng, Li Tianyuan
The axial flux permanent magnet (AFPM) machines with the parallel magnetic circuit (PMC) rotor can effectively improve its torque density. The PMC rotor consists of two sub‐rotors, radial Halbach array permanent magnet (PM) and tangential PM. The magnetic fields generated by two sub‐rotors are not in the same 2‐D analytical planes. In this paper, an equivalent analytical model of PMC‐AFPM machines
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Investigation of Calibration Methodology Using Mouth Airflow for Wearable Sensor Toward Quantitative Respiration Monitoring IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-03 Kenta Horie, Muhammad Salman Al Farisi, Yoshihiro Hasegawa, Miyoko Matsushima, Tsutomu Kawabe, Mitsuhiro Shikida
Present wearable sensors are able to measure the frequency of vital signs such as respiration rate and heartbeat rate, but unable to measure those quantitatively, e.g. respiratory volume and heartbeat strength. Meanwhile, airflow at mouth contains both the respiration and the heartbeat quantitative signals. In this study, we propose a calibration method for a wearable vital sensor attached on the chest
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Class-Relation Reasoning with Knowledge-Transfer for Few-Shot Object Detection IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-04 Xin Feng, Zhixian Zhang, Junjie Wang, Siping Wang, Xiaoning Jiao
Few-Shot Object Detection (FSOD) task involves accurately identifying target object classes using only a small set of labeled samples. Most of the current FSOD tasks independently predict class prototype features without considering class relationships and only rely on visual information. To address these challenges, we propose a novel Class-relational Reasoning Method with Knowledge-transfer (CRK-Net)
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Plasma‐Based Additive Manufacturing Method for MEMS Using APSLD (Atmospheric Pressure Sputtering Layer Deposition) Technology† IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-04 J. Bickel, Roland Gesche, Joachim Scherer, Reinhold Kovacs, Xiaodong Hu, Ha Duong Ngo
This paper reports a novel additive manufacturing technique for MEMS devices using newly developed APSLD (atmospheric pressure sputtering layer deposition) technology. It uses a microplasma at atmospheric pressure to deposit microstructures with defined properties, such as conducting or isolating directly at different surfaces additively without complex and time‐consuming manufacturing routes like
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Automated Correction of Eye‐Tracking Data for Detecting Difficult‐to‐Read Characters in Japanese Text IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-04 Yudai Ito, Chikako Ishizawa, Yoichi Kageyama
This paper proposes a new eye‐tracking data correction method for the development of an automatic detection system for difficult‐to‐read characters in Japanese text. The proposed method, which adjusts the x‐axis of the eye, was compared with existing methods that adjust only the y‐axis. Data correction was performed for each method, and the detection accuracy of difficult‐to‐read Japanese characters
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Fabrication and Evaluation of MUT-Type Acoustic Metamaterial for Impedance Matching IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-03 Hiroki Tanaka, Shuntaro Machida, Mitsuhiko Nanri
A micromachined ultrasonic transducer (MUT)-type acoustic metamaterial that achieved acoustic impedance matching between materials with different acoustic impedances was successfully fabricated. The fabricated device consisted of a thin membrane that vibrated when acoustic waves impinged on the surface of the device, along with tapered trench structures located beneath the membrane. The device fabrication
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Research on Detection and Defense Methods for Software‐Defined Network Architecture after Hybrid Attack by Distributed Denial of Service IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-03-01 Hongfei Xiao, Tao Xiang, Shiqi Tang
The architecture of software‐defined network (SDN)enhances the openness of the network by separating the control and forwarding functions, but the centralized SDN control form is susceptible to distributed denial of service (DDoS) attacks. In this paper, entropy value and back‐propagation neural network (BPNN) were applied to the DDoS attack detection of SDN, and then the two detection algorithms were
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QoS-Based Bi-Level Demand Response for Data Center to Facilitate Renewable Energy Integration IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-27 Bin Li, Wangzhang Cao, Tianyue Tang, Bing Qi, Jianli Zhao, Chuan Liu
Scheduling workload is a demand response strategy for data centers to reshape electricity usage, which provides an opportunity for them to utilize renewable energy. Enhancing the flexibility of workload scheduling would promote the data center to integrate renewable energy. Considering that the improvement of flexibility in workload scheduling is tightly related to the Quality of Service (QoS) required
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Colorimetric Readout Based Photoionization Detector for Gas Chromatographs IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-27 Jingqin Mao, Longze Liu, Yahya Atwa, Junming Hou, Hamza Shakeel
This paper presents a new scheme for readout of a photoionization detector (PID) that utilizes the ionization luminescence of target gases in helium plasma to generate an output signal. Our signal readout method is based on processing the recorded video and correlating the light peak intensity with the sample injection time and concentration. We successfully demonstrated the feasibility of a colorimetric
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A Proposal of a Novel Automatic Checkout System Reducing Additional Item Information Relearning Cost IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-25 Daisuke Hanamitsu, Kimihiro Mizutani
Recently, a retail industry has trended to adopt automatic checkout systems for enhancing customer sales. Typically, an automatic checkout system employs an object detection technique (i.e., image processing) based on a commonly used deep learning model (e.g., Faster R-CNN and YOLO) that has been trained for items. Therefore, it takes much time to relearn the model whenever an item is added to the
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Improved Sequential Model Predictive Control of Cascaded H‐Bridge Multilevel Converter IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-26 Risheng Qin, Hua Kuang, He Jiang, Hui Yu, Hong Li, Zhuan Li
The cascaded H‐bridge (CHB) converter can achieve rich functions, such as active rectification, active power filtering, distributed energy storage, etc. The control of the CHB converter is a multiobjective optimization problem. Finite control set model predictive control (FCS‐MPC) is an effective method developed in recent years to solve this problem. However, because of the large amount of calculation
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Theoretical and Experimental Analysis on Liquid Metal Droplets Fiber Fabrication Via co‐Flow Microfluidic System IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-26 Xu Gao, Wei Wang
In this work, liquid metal was introduced into a simple co‐flow microfluidic system, and we successfully fabricated the liquid metal droplets fiber by solidifying the continuous phase. The law of liquid metal droplet generation was discussed by theoretical analysis, simulations and experiment results, which is a critical guidance for fabricating liquid metal droplets fibers with various parameters
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Combining Fourier Fractional GM(1,1|sin) Model with Rat Swarm Optimizer for Employment Rate Prediction IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-23 Lulu Cai, Dongge Lei, Fei Wu, Aihua Guo
Accurate prediction of employment rate of graduated students can greatly help education authorities to make informed decisions as well as for universities to adjust their teaching plans. Unfortunately, prediction of the employment rate of graduated students is still a difficult problem because the historical employment rate data exhibits fluctuations. In this paper, a new method is proposed for employment
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Error Analysis of XY Model Equivalent Circuit Based on Finite Element Simulation IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-23 Yalong Tu, Qingchuan Xu, Bo Jiang, Shengkang Wang, Fuchang Lin, Yangze Lu, Yunhao Qiu
The XY model is a simplified insulation model for transformers that aims to connect the frequency spectrum of major insulation, insulation paper, and oil. It enables the calculation of the paper's frequency spectrum, facilitating a quantitative evaluation of the transformer's insulation status. Given the scarcity of research addressing the accuracy of the XY model and its corresponding equivalent circuit
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Evaluation of Voltage Unbalance Definitions for Voltage Control in Distribution Systems with Photovoltaic Penetration IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-21 Akito Nakadomari, Narayanan Krishnan, Masahiro Furukakoi, Ashraf Mohamed Hemeida, Tomonobu Senjyu
This paper examines the impact of different voltage unbalance definitions on voltage control in unbalanced distribution systems. Traditional voltage regulation methods for unbalanced systems rely on a single voltage unbalance definition with inconsistent adoptions. In such a situation, voltage control performance can vary between definitions, and improper choice leads to control failures. In this study
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Security Enhancement of mmWave MIMO Wireless Communication System Using Adversarial Training IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-22 Mehak Saini, Surender K. Grewal
Millimeter wave MIMO wireless communication systems are deployed in 5G and next‐generation networks. The effectiveness of deep learning models for improving the performance of these systems has been proven in the literature. However, several deep learning models are vulnerable to security threats, such as adversarial attacks. Therefore, for the deployment of these systems, it is essential to make them
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Pitot Tube Sensor Probe System for Simultaneous Airflow and Pressure Measurement of Expiration Inside Pulmonary Airway IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-21 Aoi Miyawaki, Muhammad Salman Al Farisi, Yoshihiro Hasegawa, Miyoko Matsushima, Tsutomu Kawabe, Mitsuhiro Shikida
Respiratory diseases, including the cronic obstructive pulmonary disease (COPD) are among the leading causes of death worldwide. To date, there is no physical examination procedure that can quantify important parameters within a specific lesion area inside the lung. In this study, we propose a novel sensor probe system consisting of a basket forceps and 2 pressure sensors to simultaneously measure
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Three‐Phase Unbalance Reduction and Energy Optimization for Active Distribution Network Using Flexible Multi‐State Switch IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-21 Yixuan Jin, Moduo Yu, Nengling Tai, Ruochen Duan, Chao Lu
Active distribution network is integrated with a large number of renewable energy sources and flexible loads such as electric vehicles(EVs). The unstable output of distributed generation and the random access to different phases cause three phase unbalance in the distribution network, which increase the energy loss and carbon emissions. Three phase unbalance reduction requires high real‐time dispatch
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Recognition of Fiber Optic Vibration Signals Based on Laplace Wavelet Transform and Deep Learning IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-19 Jinshui Qi, Jiaqing Mo, Yasen Niu, Yiteng Cui
Convolutional neural networks possess the capability of feature learning and nonlinear mapping, which has significant advantages in classifying and recognizing optical fiber vibration signals. In order to further enhance the recognition rate of vibration signals, this paper combines wavelet transform with convolutional neural networks and designs a convolutional layer based on parameterized wavelets
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Hybrid 3D Printing of Molten Metal Microdroplets and Polymers for Prototyping of Printed Circuit Boards Featuring Interdigitated 3D Capacitors IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-17 Zeba Khan, Dheepesh Gururajan, Peter Koltay, Sabrina Kartmann, Roland Zengerle, Zhe Shu
This paper presents layer-by-layer additive manufacturing (AM) of molten metal microdroplets and dielectric materials to fabricate multilayer hybrid circuit boards featuring interdigitated 3D capacitors. The printed metal lines have a low resistance of 5 mΩ/mm, 12 times lower than state-of-the-art conductive inks. Exploiting the advantages of Sn-based oxide as an ideal candidate for Electrical Energy
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Experimental Analysis of Rayleigh and Sezawa Modes Resonance Frequencies in SAW Devices Manufactured on Sc0.3Al0.7N/Si† IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-15 Alexandra Nicoloiu, George Boldeiu, Claudia Nastase, Monica Nedelcu, Cristina Ciornei, Ioana Zdru, George Stavrinidis, Dan Vasilache, Antonis Stavrinidis, Adrian Dinescu, George Konstantinidis, Alexandru Müller
GHz operating single port SAW resonators have been manufactured on Sc0.3Al0.7N/Si substrate. The thickness of the ScAlN thin layer was 0.8 μm. Advanced nano-lithographic techniques have been developed for devices manufacturing. Rayleigh and Sezawa modes have been evidenced on Sc0.3Al0.7N/Si structure. The targeted applications are temperature sensors for harsh environmental operations. The sensitivity
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A Two‐Stage Method for Order Selection in Model‐Free Predictive Control IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-19 Pratvittaya Jiravit, Shigeru Yamamoto
One of the primary advantages of model‐free predictive control over conventional methods is that it does not use any mathematical models and relies only utilizes measured input/output data from the storage. The capability of model‐free predictive control has been already demonstrated in nonlinear systems using linear and polynomial regression for data storage. However, identifying the appropriate order
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Treatment Temperature and Magnetic Field Distribution for Magnetic Hyperthermia Using Magnetic Nanoparticles IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-15 Takayuki Kagami, Akihiro Kuwahata, Shin Yabukami
A minimally invasive cancer treatment method utilizing magnetic nanoparticles (MNPs) and magnetic coils, magnetic hyperthermia, generates heat locally inside the body to degenerate cancer cells. The uniformity of the coil's magnetic field is a crucial factor in enhancing the therapeutic effect. In this study, we evaluated the temperature distribution of MNPs on induction heating experiments at various
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Dialogue System for Casual and Continuous Word Learning IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-14 Yosuke Seki
Facilitating causal and continuous learning in individuals with low motivation presents a formidable challenge owing to the diverse methods and systems available for vocabulary acquisition. Therefore, this study developed a non-task-oriented dialogue system to facilitate casual and continuous word learning. Specifically, dialogue systems capable of processing text-based inputs, encompassing words registered
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Improved Compound Vibration Suppression Control for Magnetic Levitation Motor IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-13 Dan Zhang, Baonan Wang
The magnetic levitation motor is high efficiency, energy saving and environmental protection, which integrates magnetic levitation bearing and permanent magnet motor into the traditional motor. Two key technologies of its stable operation are vibration suppression control of magnetic bearing and speed sensorless chattering suppression control of motor. The innovative research has been studied from
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TriClick: Interactive Dermoscopic Image Segmentation with Triangle Map IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-13 Shuofeng Zhao, Chunzhi Gu, Jun Yu, Takuya Akashi, Chao Zhang
Lesion segmentation is a fundamental task that has been widely studied in biomedicine. State-of-the-art methods still struggle with the inherent challenges of dermoscopic images such as uncertain boundaries or severe occlusion. In this study, we argue that this task can be better resolved by introducing user interaction and proposing a deep interactive framework for lesion segmentation. Our method
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Design of Motion Attitude Measurement System and Correction Method in Semi-Airborne Frequency Domain Electromagnetic Detection IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-12 Changsheng Liu, Yang Su, Chunfeng Zhang, Shuxu Liu
In the semi-airborne frequency domain electromagnetic detection, strong noise will be generated due to the attitude change of the receiving coil sensor. However, the existing attitude measurement system cannot be directly used in the semi-airborne frequency domain electromagnetic system because of the requirement on the volume and accuracy of the instrument. In order to reduce the effect of attitude
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Quantum-Behaved Particle Swarm Optimization Based on Concentration Selection Probability Assignment Weights for Power System Economic Dispatch IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-12 Miao Wang, Zhiao Cao, Yuchun Li
The economic dispatch (ED) problem is very important in the economics of power systems, and a suitable dispatch algorithm can help power plants save huge amounts of money and use energy efficiently. To ensure the economics of the power system dispatch strategy, this paper proposes a quantum-behaved particle swarm improvement algorithm for solving the ED problem. First, the algorithm addresses the problem
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A Dendritic Architecture-Based Deep Learning for Tumor Detection IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-12 Shibo Dong, Zhipeng Liu, Haotian Li, Zhenyu Lei, Shangce Gao
Brain tumor detection typically involves classifying various tumor types. Traditional classifiers, based on the McCulloch-Pitts model, have faced criticism due to their oversimplified structure and limited capabilities in detecting brain tumor images with complex features. In this study, we propose a multiclassification model inspired by dendritic architectures in neurons, which leverages synaptic
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Transfer Learning Using Musical Instrument Audio for Improving Automatic Singing Label Calibration IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-11 Xiao Fu, Xijian Rui, Hangyu Deng, Jinglu Hu
Automatic Singing Label Calibration (ASLC) aims to enhance the labeling accuracy of coarse singing labels through the analysis of raw audio. However, the ASLC model faces limitations due to the challenges and costs associated with generating or augmenting real-world songs. To address this problem, we propose a novel approach to strengthen limited singing audio using easily available musical instrument
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Measurement of Three-Dimensional Bubble distributionVia Single-Directional Capture Using a Light Field Camera IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-11 Manabu Kodama, Shuichiro Hirai
In water electrolysis, which converts electricity into hydrogen, the distribution of bubbles affects ion transport in the electrolyte. Therefore, measuring the three-dimensional distribution of bubbles in the electrolysis cell can be effective in improving efficiency. However, the electrolysis cell contains electrodes and membranes, making it difficult to use conventional stereo photography to measure
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Design and Analysis of a Cooling System for the REBCO Coil Based on GM/JT Cycle IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-11 Jingxin Zheng, Junjie Li
High-field magnets have been used in a wide range of scientific and industrial areas. REBCO (REBa2Cu3Ox, where RE = Rare Earth) coated superconductors (CCs) have been gaining increasing interest due to the potentialities of using them in high-field magnets. However, the thermal stability of the REBCO CCs coils is limited by longitudinal heat conduction inside the coils and bubbles generated by evaporating
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In-Situ Fabrication Process of Bacterial Cellulose compositesfor Soft Robots IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-03 Motonori Uchimura, Fujio Tsumori
Bacterial cellulose (BC) produced by acetic acid bacteria is a promising biomaterial that exhibits exceptional mechanical strength, biocompatibility, and biodegradability. In this study, we have successfully fabricated BC composites with various materials such as alumina fibers, zirconia particles, carbon nanotubes, and magnetic particles by adding each material to the culture medium. We also demonstrate
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Rail-Lane Extraction Based on Cutting-Edge Deep Neural Networks and Graph-Based Segmentation IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-02 Noboru Yasue, Takuya Futagami
This study aims to enhance the accuracy of rail-lane extraction, which determines the rail lane and its background at a pixel-wise level from an ego-perspective image captured by the front camera of a train. For this purpose, cutting-edge deep neural network (DNN)-based semantic segmentation models, MANet and UNet++, were applied. In addition, a method that effectively enlarges the rail lane extracted
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A Novel Hybrid Deep Learning Model for Photovoltaic Power Forecasting Based on Feature Extraction and BiLSTM IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-01 Wenshuai Lin, Bin Zhang, Renquan Lu
In this paper, a hybrid photovoltaic power forecasting model is proposed based on bidirectional long-short-term memory network. Firstly, the photovoltaic power and meteorological data are decomposed by ensemble empirical mode decomposition. Secondly, key features in the meteorological subsequences are extracted by kernel principal component analysis method to eliminate the correlation and redundancy
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A Proposal of a Method to Determine the Appropriate Learning Period in Stock Price Prediction Using Machine Learning IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-02-01 Ryuya Shirata, Taku Harada
In this study, we propose a method to determine the appropriate learning period for each stock and the prediction period by considering stock price fluctuations for stock price prediction using machine learning. Our proposed method uses historical volatility as an indicator of the turning point to determine the learning period based on the policy that the fluctuations in the period after the major
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YVG-SLAM: Dynamic Feature Removal SLAM Algorithm Without A Priori Assumptions Based on Object Detection and View Geometry IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-31 Juan Li, Qi Wei, Xuerong Cui, Bin Jiang, Shibao Li, JianHang Liu
Visual SLAM algorithms can obtain a large amount of texture information from the environment and usually perform very well in static scenes, but there are a large number of irregular dynamic points when running in dynamic scenes, which can lead to increased error in SLAM feature point matching and loss of tracking localization. To address this challenge this paper proposes a SLAM system (YVG-SLAM)
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Area Day-Ahead Photovoltaic Energy Generation Forecasting by Auto-Encoder Inputting Images of Multiple Meteorological Elements IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-28 Yusuke Mori, Shinji Wakao, Hideaki Ohtake, Takahiro Takamatsu, Takashi Oozeki
Photovoltaics (PV), which is one of variable renewable energies, have been installed largely. In the environment of largely installed PV, the output fluctuates of PV influences on the operation of power gird network adversely. Therefore, PV energy generation forecasting is valid for power grid operation and management and needs the reduction of large forecast error as well as average error. Due to
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A Novel Method for Operation Monitoring of Thyristor Converter Based on Real-Time Virtual Measurement of Valve Current in LCC-HVDC IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-28 Yuchen He, Xiaohua Li, Shanshan Yin, Hao Li, Zexiang Cai
The thyristor converter is a core equipment for AC/DC hybrid power grids of high-voltage direct current (HVDC) where overheating does harm to its reliability. In reality, overheating is closely related to the broken three-phase symmetry when the AC side is disturbed. Particularly, when commutation failures occur, the valve forced to reconduct will suffer from severe short-circuit current for a long
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The Heterogeneous Packaging of A 3 × 3 Mini-LED Array for Smart Contact Lens Display Applications IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-24 Cheng-Wei Tsai, Guan-Ting Yeh, Shun-Hsi Hsu, Shin-Ho Wu, Yu-Hsuan Huang, Herming Chiueh, Jin-Chern Chiou
For the needs of augmented reality (AR), virtual reality (VR) and mixed reality (MR), smart contact lenses (SCL) have become an important platform as a display source in the future consumer market. Accordingly, this paper demonstrates a display device based on contact lenses. This device integrates a 3 × 3 Mini-LED display array, a micro antenna, and a driver and transmission chip and is packaged in
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High Efficiency Actuation Conversion Mechanism for High-Output Bending Motion of a Soft Inflatable Microactuator IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-24 Yuto Hori, Seiji Suzuki, Tatsumi Katsura, Satoshi Konishi
The actuation conversion efficiency of a pneumatic inflatable microactuator can be improved by 4.8 times that of conventional microactuators which generated a Newton-level high force generation via the same conversion mechanism. The inflatable force of the balloon was converted into a bending motion using a conversion film. An adaptive deformation film with force-receiving plates were designed as the
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Evaluation-Number Constrained Optimization Problem and its Solution Strategy IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-22 Kenichi Tamura
This paper addresses optimization problems subject to an objective function's evaluation-number constraint arbitrarily given in advance. These problems are practical for black-box objective functions which cost much money and/or time per evaluation because money and/or time constraints are typically applicable in real-world projects. This paper suggests a new solution strategy that can be used to adapt
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Systematic Face Pareidolia Generation Method Using Cycle-Consistent Adversarial Networks IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-22 Yoshitaka Endo, Rinka Asanuma, Shinsuke Shimojo, Takuya Akashi
Pareidolia is a psychological tendency of perceiving a face in non-face stimulus. As a majority of people globally experience this tendency, it has been extensively studied and measured in terms of tendencies, such as frequencies. However, no study has investigated the systematic manipulation of stimulus owing to the lack of a systematic image-generation method. Therefore, herein, we generated face
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A Method of Field Elevation Measurement in Distribution Network Work Based on Combination of Barometric Altimetry and Motion Detection IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-22 Ying-Chun Yang, Li-Jun Tang, Xu Zhao, Tian-Xi Han
Accurate detection of violations in the process of high-altitude operation plays an essential role in improving the safety production level of distribution network work. The basis of detecting violations in work at high altitude is to accurately measure the ground height of relevant workers and tools. Therefore, in this study, a method of on-site elevation measurement in distribution network based
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A Semi-Passive Smart Contact Lens with on-Lens Power Storage Element IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-15 Cheng-Wei Tsai, Shun-Hsi Hsu, Yu-Chieh Huang, Guan-Ting Yeh, Yu-Hsuan Huang, Cheng-Yu Hsu, Chun-Yu Wu, Jhu-Jyun Yang, Xuan-Wei Zhang, Jin-Chern Chiou
This paper presents a semi-passive smart contact lens platform for sensor and actuator applications. It focuses on design improvements made prior to human clinical trials involving basic considerations on comfort and safety, which are verified through animal studies. Observations of tissue temperature variation and post-trial surgery examinations confirm that the 50 μW on-lens wireless power delivery
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Dual Model Predictive Control Strategy of Direct-Drive PMSM Based on Sliding Mode Disturbance Observer IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-16 Zhaoyue Sun, Cao Tan, Bo Li, Aijuan Song, Peng Yu, Mingji Hao
Aiming at the current control steady-state error caused by sampling delay, parameters mismatch of direct-drive permanent magnet synchronous motor (PMSM). This paper proposed a method of dual model predictive control (MPC) of direct-drive PMSM based on sliding mode disturbance observer (SMDO). Deadbeat predictive current control (DPCC) is used for current loop, a SMDO is proposed to observe the system
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Multipurpose Optimization Method for Energy Storage System Specification Using Measurement Data of DC Traction Substations IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-13 Sho Nakamura, Takahiro Fukuda, Yasuhiro Kodama, Yasuhiro Hayashi, Hitoshi Hayashiya
The peak demand for railway power occurs when trains operate at full capacity, which calls for the need of facilities that can handle such peaks. These expansive railway power facilities, which cover vast areas, result in increased maintenance and management costs while affecting the power supply to traction substations (TSs). Herein, we investigated the load leveling of TSs using energy storage systems
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Color Change Analysis of Raw Chicken Breast over Different Timestamps Using CNNs IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-10 Min Zou, Yoichi Kageyama, Aihong Yuan
In this study, the potential of a novel method based on an artificial neural network was investigated to analyze the color change of raw chicken breasts during refrigeration. As edible meat for people, chicken breasts have high nutrients and low-fat content. Therefore, people consume it as a safe and high-value food in their daily diet. The investigation of chicken breast freshness is proposed as a
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MEMS-Based Ultra-High Frequency Wireless 10 × 10 QCM Sensor Array for Biochemical Sensing Applications IEEJ Trans. Electr. Electron. Eng. (IF 1.0) Pub Date : 2024-01-09 Fumihito Kato, Junki Shinohara, Manabu Yoshino, Manabu Suzuki, Hirotsugu Ogi
The quartz crystal microbalance (QCM) biosensor is one of the devices that enables label-free evaluation of biomolecular reactions. Commercial QCM biosensors have less than 10 channels for detection and are not suitable for the screening. The sensitivity of the QCM biosensor increases as the quartz thickness becomes thinner; however, the limit of thinning is 60–330 μm. In this study, applying micromachining