Memristor-based feature learning for pattern classification by Tuo Shi, Lili Gao, Yang Tian, Shuangzhu Tang, Jinchang Liu, Yiqi Li, Ruixi Zhou, Shiyu Cui, Hui Zhang, Yu Li, Zuheng Wu, Xumeng Zhang, Taihao Li, Xiaobing Yan, Qi Liu

“…We propose that innovations in hardware physics could create an intriguing solution for intelligent models by balancing model complexity and performance.…”
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A hybrid model for smart grid theft detection based on deep learning by Yinling LIAO, Jincan LI, Bing WANG, Jun ZHANG, Yaoyuan LIANG

“…A hybrid deep learning model was proposed to effectively detect electricity theft in smart grids.The hybrid model employed a deep learning convolutional neural network (AlexNet) to tackle the curse of dimensionality, significantly enhancing data processing accuracy and efficiency.It further improved classification accuracy by differentiating between normal and abnormal electricity usage using adaptive boosting (AdaBoost).To resolve the issue of class imbalance, undersampling techniques were utilized, ensuring balanced performance across various data classes.Additionally, the artificial bee colony algorithm was used to optimize hyperparameters for both AdaBoost and AlexNet, effectively boosting overall model performance.The effectiveness of this hybrid model was evaluated using real smart meter datasets from an electricity company.Compared to similar models, this hybrid model achieves accuracy, precision, recall, F1-score, Matthews correlation coefficient (MCC), and area under the curve-receiver operating characteristic curve (AUC-ROC) scores of 88%, 86%, 84%, 85%, 78%, and 91%, respectively.The proposed model not only increases the accuracy of electricity usage monitoring, but also offers a new perspective for intelligent analysis in power systems.…”
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Study on Cold Chain Transportation Model of Fruit and Vegetable Fresh-Keeping in Low-Temperature Cold Storage Environment by Xiaolong Jiao, Wen Xu, Lintong Duan

“…Due to the limitation of later stage intelligent algorithms, the fruit and vegetable fresh-keeping cold chain transportation scheme did not meet the expectation and could not achieve the dual objectives of the shortest time and the lowest consumption at the same time. …”
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Gear Fault Diagnosis Based on APIT-SA-MEMD and FLLE by Ji Haofei, Liu Huiling, Dong Jiaqiang

“…To solve this problem, an intelligent fault diagnosis method based on adaptive projection intrinsically transformation sine-assisted multivariate empirical mode decomposition (APIT-SA-MEMD) and Floyd local linear embedding (FLLE) algorithm is proposed. …”
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Space-air-ground integrated networks:review and prospect by Xuemin(Sherman) SHEN, Nan CHENG, Haibo ZHOU, Feng LYU, Wei QUAN, Weisen SHI, Huaqing WU, Conghao ZHOU

“…With the advance of the information technologies,the scale of the information services gradually expands,from ground services,to aerial,maritime,and spatial services,with the soaring requirements on multi-dimensional comprehensive information resources.The space-air-ground integrated networks (SAGINs) are envisioned to provide seamless network services to spatial,aerial,maritime,and ground users,satisfying the future network requirements on all-time,all-domain,and all-space communications and interconnected networking.Firstly,we reviewed the current research development of SAGINs,discussing the research trends on the low-earth orbiting (LEO) satellite constellation and space-ground network integration.Then,the reinforcement learning (RL) framework was proposed in SAGINs to address the problems of complex architecture,high dynamics,and resource constraints in SAGINs,which facilitated efficient and fast network design,analysis,optimization,and management.As a case study,the method of applying deep RL (DRL) was showed for the intelligent access network selection in SAGINs.To improve the RL training efficiency,a comprehensive SAGINs simulation platform was established,through which the agent-environments interaction was accelerated and training samples could be obtained more cost-effectively.Finally,some open research directions were presented.…”
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Realization of Wireless-Controlled Gear Shifter for Shaft-Driven Bicycle Gearbox by Hsiung-Cheng Lin, Elangovan Chelliah

“…The traditional bicycle depends on a chain driving mechanism to move forward (This paper is an extended version of our paper published in The 16th Intelligent Living Technology Conference, Taichung, Taiwan, 2 June 2022). …”
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Resilient routing in ad hoc wireless sensor networks by Tehmina Karamat Khan, Taimur Karamat, Asad Ullah Shah, Umair Aitimad

“…This paper has devised an algorithm for identifying reliable routes for efficient and intelligent packet transmission in wireless network topology. …”
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Operation and Control of an Active Power Collector for Roadside Feeding Electric Road System by Saleh A. Ali, Volker Pickert, Mohammed A. Alharbi, Handong Li, Haris Patsios

“…Dynamic conductive road charging (DCRC) of EVs at high speed has the potential to overcome the technical limitations of existing static charging methods. An intelligent motorway system for EVs called tracked electric vehicle (TEV) was proposed to incorporate the latest technologies of dynamic road charging, autonomous driving, and smart city data into transport infrastructure. …”
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Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases by Mahmood Deypir, Amirhossein Mohammadpour

“…In other words, the purposes of test selection methods is to reduce the number of test cases after changing the code and focus on identifying the modified parts of the program. Intelligent methods such as regression improve the accuracy of tests in software projects, and the use of optimization algorithms to find the optimal amount of test cases can be useful in terms of time and speed, and according to research by examining and optimizing this algorithm in the system. …”
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…In order to solve the problems of high energy consumption and high reliance on manual annotation data of traditional intelligent attack detection methods in UAV networks, a lightweight UAV network online anomaly detection model based on a double-layer memory-enhanced autoencoder integrated architecture was proposed. …”
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Smart Shift Decision Method Based on Stacked Autoencoders by Zengcai Wang, Yazhou Qi, Guoxin Zhang, Lei Zhao

“…Experimental results demonstrate that using the SAE intelligent shift control strategy to determine shift timing not only is feasible and accurate but also saves time and development costs.…”
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Recent Progress in Self-Healing Triboelectric Nanogenerators for Artificial Skins by Guoliang Li, Zongxia Li, Haojie Hu, Baojin Chen, Yuan Wang, Yanchao Mao, Haidong Li, Baosen Zhang

“…Future research should focus on advanced material development, scalable fabrication, and intelligent system integration to unlock the full potential of self-healing TENGs. …”
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MODELING AND SIMULATION OF COAL-ROCK RECOGNITION SYSTEM OF SHEARER BASED ON CYBER-PHYSICAL SYSTEM (MT) by ZHAO LiJuan, SI HuanHuan, SHI Lei, JIN Xin, ZHANG MeiChen

“…In order to solve the problem of intelligent identification of coal-rock interface of shearer in fully mechanized coal mining face, a CPS-based coal-rock identification system structure of shearer is proposed. …”
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Design and Implementation of BIM-Based Construction Supervision Platform for Hydraulic Engineering by YANG Chuhua, RAO Fanwei, FU Zhihao, LIAO Xiangjun

“…With the continuous promotion of high-quality development of water conservancy in the new era,it has become an inevitable trend to make full use of information technologies such as BIM,digital twins,and simulations to integrate and innovate with the water conservancy industry.In hydraulic engineering,an intelligent management system focusing on “BIM+a whole life cycle” has been gradually formed.Centering on the construction stage of hydraulic engineering,this study uses the new generation of information technologies such as BIM,big data,3S,and three-dimensional (3D) visualization to build an advanced,practical,and safe construction supervision platform for hydraulic engineering that can integrate the basic and overall construction process information resources.It is expected that the platform can greatly reduce the risks and solve the problems such as insufficient cooperation among institutions,difficult information collection,poor data sharing and consistency,and low construction management efficiency. …”
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Advanced load balancing techniques using MIMO fuzzy logic: A panel distribution case study at state polytechnic of Malang by Ika Noer Syamsiana, Harry Hassidiqi, Wijaya Kusuma, Anang Dasa Novfowan, Arwin Datumaya Wahyudi Sumari, Chandra Wiharya

“…The objective of this research is to make a significant contribution to improving the efficiency, reliability, and scalability of the power distribution system, with the ultimate goal of maximizing the use of electrical equipment.It will facilitate the implementation of more intelligent and adaptive decision-making processes. …”
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Customer service complaint work order classification based on matrix factorization and attention multi-task learning by Yong SONG, Zhiwei YAN, Yukun QIN, Dongming ZHAO, Xiaozhou YE, Yuanyuan CHAI, Ye OUYANG

“…The automatic classification of complaint work orders is the requirement of the digital and intelligent development of customer service of communication operators.The categories of customer service complaint work orders have multiple levels, each level has multiple labels, and the levels are related, which belongs to a typical hierarchical multi-label text classification (HMTC) problem.Most of the existing solutions are based on classifiers to process all classification labels at the same time, or use multiple classifiers for each level, ignoring the dependence between hierarchies.A matrix factorization and attention-based multi-task learning approach (MF-AMLA) to deal with hierarchical multi-label text classification tasks was proposed.Under the classification data of real complaint work orders in the customer service scenario of communication operators, the maximum Top1 F1 value of MF-AMLA is increased by 21.1% and 5.7% respectively compared with the commonly used machine learning algorithm and deep learning algorithm in this scenario.It has been launched in the customer service system of one mobile operator, the accuracy of model output is more than 97%, and the processing efficiency of customer service agent unit time has been improved by 22.1%.…”
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Validation and Calibration of an Agent-Based Model: A Surrogate Approach by Yi Zhang, Zhe Li, Yongchao Zhang

“…In this paper, we present a surrogate analysis method for calibration by combining supervised machine-learning and intelligent iterative sampling. Without any prior assumptions regarding the distribution of the parameter space, the proposed method can learn a surrogate model as the approximation of the original system with a relatively small number of training points, which will serve the needs of further sensitivity analysis and parameter calibration research. …”
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Displacement-Based Back-Analysis of the Model Parameters of the Nuozhadu High Earth-Rockfill Dam by Yongkang Wu, Huina Yuan, Bingyin Zhang, Zongliang Zhang, Yuzhen Yu

“…The parameters of the constitutive model, the creep model, and the wetting model of materials of the Nuozhadu high earth-rockfill dam were back-analyzed together based on field monitoring displacement data by employing an intelligent back-analysis method. In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. …”
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High-Performance Wireless Piezoelectric Sensor Network for Distributed Structural Health Monitoring by Shang Gao, Xuewu Dai, Zheng Liu, Guiyun Tian

“…In addition to hardware, embedded signal processing and distributed data processing algorithm are designed as the intelligent “brain” of the proposed wireless monitoring network to extract features of the PZT signals, so that the data transmitted over the wireless link can be reduced significantly.…”
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Application of Perceptual Filtering Models to Noisy Speech Signals Enhancement by Novlene Zoghlami, Zied Lachiri

“…Using objective tests based on the perceptual quality PESQ score and the quality rating of signal distortion (SIG), noise distortion (BAK) and overall quality (OVRL), and subjective test based on the quality rating of automatic speech recognition (ASR), we demonstrate that our speech enhancement approach using filter banks modeling the human auditory system outperforms the conventional spectral modification algorithms to improve quality and intelligibility of the enhanced speech signal.…”
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