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4th International Conference on Innovations in computer Science, ICONICS 2024

作者： Shaikh, Akhlaq Ahmed Awan, Samia Masood Zahid, Mahnoor Fahad, Muhammad NED University of Engineering and Technology Department of Computer Science and Information Technology Karachi Pakistan

ISBN: (纸本)9798331504342

The E-commerce industry has seen significant growth over the past few years and many people prefer to purchase their goods online, but with this advancement and growth many fraudulent activities and scams have also gained a hike. Due to this the customers have shown significant concerns and worries while using any such platforms such as deception by vendors by selling fake products or their products getting counterfeit during the delivery process because the supply chain of their ordered product is often veiled in secrecy. This paper presents Commercio, a comprehensive solution that enables individuals with an understanding of how their products are transferred, managed, stored, and delivered to their doorsteps. Our application aims to tackle these challenges by creating an innovative e-commerce platform. This platform will serve as a dynamic marketplace and will connect sellers with customers who prioritize authenticity and dependability. Additionally, it will redefine supply chain management by offering unparalleled transparency and security. Moreover, incorporating blockchain-based payment systems will also improve transaction integrity hence delivering a trustworthy buying experience. © 2024 IEEE.

关键词： Marketplaces

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A fast and distributed C4.5 algorithm for urban big data

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Intelligent Data Analysis 2023年第5期27卷 1379-1408页

作者： Cheng, Wan-Shu Huang, Peng-Yu Huang, Jheng-Yu Chen, Ju-Chin Lin, Kawuu W. Department of Computer Science and Information Management Providence University Taichung Taiwan Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

The amount of information nowadays is rapidly growing. Aside from valuable information, information that is unrelated to a target or is meaningless is also growing. Big data and broader digital technologies are considered the primary components of smart city governance and planning. Big data analysis is considered to define a new era in urban planning, research, and policy. Effective data mining and pattern detection techniques are becoming very important these days. Processing such a large amount of data entails the use of data mining, a technique that clarifies the association between valid information and excludes irrelevant data to implement a practical decision tree. A large amount of data affects processing time and I/O costs during data mining. This study proposes to distribute data among multiple clients and distribute a large amount of data computation equally to improve the resource cost problem of exploration. Following that, the main server consolidates the computation results and generates the survey results. Experiment results show that the proposed algorithm is superior, thus allowing a larger amount of data to be processed while producing high-quality results. © 2023 - IOS Press. All rights reserved.

关键词： Data mining

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Human Age Prediction Based on Gender Image Recognition 5

Human Age Prediction Based on Gender Image Recognition

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Vignesh, Bowgikar Keerthan, A V K Sai Shyamsunder, Bonkuru Satheesh Kumar, S. Computer Science and Information Technology Institute of Aeronautical Engineering Hyderabad India

ISBN: (纸本)9798331518097

Facial age and gender classification is a fundamental task for many applications, such as social media, security and personalized user experience. This project provides a detailed approach to age and gender classification based on CNNs, including model training and evaluation using the UTK Face dataset. The diversity and granularity of the datasets offered an excellent basis for training and evaluating models. Normalization and augmentation were added in our preprocessing pipeline to enhance the generalizability of this model among a wide variety of conditions, mitigating overfitting risks. Breathable CNN Model ArchitectureThe CNN model was designed in a deep architecture to incorporate several convolutional layers, pooling layerone after other. It helps the model to learn detailed complex patterns of face at different levels. We introduced techniques like batch normalization and dropout to improve training stability and mitigate overfitting. The CNN was shown to be correlated and robust by demonstrating a 95% accuracy for gender classification and an MAE of 95.04 for age estimation. The performance of the model was evaluated in a comprehensive manner using standard metrics like accuracy, precision, recall and F1-score. Ethics and Bias - This project also explored the ethics of using age and gender classifiers, investigating fairness in model performance across different demographic groups to identify potential biases. To summarize, this project demonstrates the use of CNNs for age and gender classification utilizing the UTK Face dataset, a practical approach with significant scope for real-world application. Future work will focus on refining the model to address even more diverse datasets and exploring seamless integration into real-time applications. © 2024 IEEE.

关键词： Face recognition

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A Spatial Phase Unwrapping Method Guided by a Unidirectional Neighbor Edge Index Chain List Strategy 9

A Spatial Phase Unwrapping Method Guided by a Unidirectional...

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9th International Conference on Intelligent Informatics and BioMedical Sciences, ICIIBMS 2024

作者： Yang, Wenhua Shao, Yao Xu, Ao Yang, Du Shanghai Institute of Technology School of Computer Science and Engineering of Information Technology Shanghai China

ISBN: (纸本)9798350363043

In response to the issues of processing speed and storage associated with the quality map-guided method in classical spatial phase unwrapping techniques, this paper proposes a spatial phase unwrapping method guided by a unidirectional neighbor edge index chain list strategy. The proposed method pertains to the field of optical threedimensional measurement. This approach does not require the acquisition of additional images, enabling rapid data collection. Furthermore, the short chain list pointed to by a pixel node pointer in the main index chain list includes only the neighboring pixels of that pixel node, with quality values decreasing from left to right and from top to bottom. This significantly reduces the length of the chain list, shortens the traversal time of the chain list, and greatly reduces the time for sorting and allocating points, thereby enhancing the measurement speed. (Abstract) © 2024 IEEE.

关键词： Spatial variables measurement

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MTLS: Making Texts into Linguistic Symbols

MTLS: Making Texts into Linguistic Symbols

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Fei, Wenlong Wang, Xiaohua Hu, Min Zhang, Qingyu Li, Hongbo School of Computer Science and Information Engineering HeFei University of Technology China

ISBN: (纸本)9798891761643

In linguistics, all languages can be considered as symbolic systems, with each language relying on symbolic processes to associate specific symbols with meanings. In the same language, there is a fixed correspondence between linguistic symbol and meaning. In different languages, universal meanings follow varying rules of symbolization in one-to-one correspondence with symbols. Most work overlooks the properties of languages as symbol systems. In this paper, we shift the focus to the symbolic properties and introduce MTLS: a pre-training method to improve the multilingual capability of models by Making Texts into Linguistic Symbols. Initially, we replace the vocabulary in pre-trained language models by mapping relations between linguistic symbols and semantics. Subsequently, universal semantics within the symbolic system serve as bridges, linking symbols from different languages to the embedding space of the model, thereby enabling the model to process linguistic symbols. To evaluate the effectiveness of MTLS, we conducted experiments on multilingual tasks using BERT and RoBERTa, respectively, as the backbone. The results indicate that despite having just over 12,000 pieces of English data in pre-training, the improvement that MTLS brings to multilingual capabilities is remarkably significant. © 2024 Association for Computational Linguistics.

关键词： Semantics

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High Dynamic Range Imaging for Dynamic Scenes Based on Multi-Level Spike Camera

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 5394-5406页

作者： Zhu, Zhenkun Xiong, Ruiqin Zhao, Jing Zhao, Rui Fan, Xiaopeng Zhu, Shuyuan Huang, Tiejun Peking University School of Computer Science Beijing100871 China Harbin Institute of Technology Department of Computer Science and Technology Harbin150001 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China

Spike camera is a retina-inspired neuromorphic camera which can capture dynamic scenes of high-speed motion by firing a continuous stream of spikes at an extremely high temporal resolution. The limitation in the current design is that each spike only represents the arrival of a fixed amount of photons. It can not deal with strong light areas in which the amount of accumulated photons reaches the pre-specified threshold multiple times within a single readout interval. In this paper, we propose a new spike camera model of high-speed imaging for high dynamic range scenarios. In this scheme, each pixel accumulates the incoming photons persistently and generates a new type of spike stream in which each spike symbol may be associated with different levels, indicating the arrival of different amounts of photons since the last readout. This enables the camera to support dynamic scenes with wider dynamic range. To achieve this, we propose a two-level buffer mechanism, one for photon accumulation and one for spike-firing encoding. We use a register to hold the number of spike-firings which has not been read out yet. At each readout time, the major part in the counter is read out via a carefully designed exponential encoding and the counter is updated. Such encoding and readout strategy enables a very efficient expansion of the dynamic range using a small number of encoding bits. Furthermore, we propose an image reconstruction scheme for the proposed camera, utilizing both spike intervals and spike levels to recover the light intensity. We incorporate Mamba and propose a temporal-spatial selective scan mechanism to extract temporal-spatial correlation within spike streams. We employ a pyramid adaptive filtering and alignment module to achieve coarse-to-fine feature alignment. Experimental results show that the proposed scheme can achieve better imaging quality and outperform the existing spike camera in high dynamic range scenarios. © 1991-2012 IEEE.

关键词： Adaptive filtering

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An Improved Dense Crowd Detection Model Based on YOLOv8 18

An Improved Dense Crowd Detection Model Based on YOLOv8

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18th IEEE International Conference on Anti-Counterfeiting, Security, and Identification, ASID 2024

作者： Lin, Zewei Xu, Huarong Xiamen University of Technology Department of Computer and Information Engineering Xiamen China

ISBN: (纸本)9798331505639

With the increase of crowd monitoring and management needs, dense crowd detection has become an important research direction in the field of computer vision, mainly using target detection methods to detect the position and number of pedestrians in pictures and videos. Aiming at the problem of missed detection and misdetection due to the occlusion between pedestrians or the target pedestrians being too small in dense crowd scenes, this paper proposes an improved detection algorithm CscSCA-YOLOv8 based on YOLOv8. Firstly, the Conv-SPD-Conv module is used instead of each convolutional step and each pooling layer in the trunk and the neck, to prevent the loss of fine-grained information and the less efficient feature representation Learning. Then the SCAMix hybrid attention mechanism is introduced into the YOLOv8 network architecture to utilize the global perception capability of self-attention and capture local features via CoordAttention to improve detection in dense scenes. Experimental results show that this paper's method achieves 74.1% and 46.6% for mAP50 and mAP50-95 on the WiderPerson dataset, respectively, and improves 3.6% and 2.8% compared with the original YOLOv8n. © 2024 IEEE.

关键词： Network architecture

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Fatigue Detection System for Extracting Driver's Eye Features 7

Fatigue Detection System for Extracting Driver's Eye Feature...

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7th International Conference on Advanced Algorithms and Control engineering, ICAACE 2024

作者： Chen, Weihang Zhang, Xuebai Chen, Sigan School Of Computer And Information Engineering Xiamen University Of Technology Xiamen China

ISBN: (纸本)9798350361445

Traffic safety remains one of the most concerning issues for humans, with people dying in traffic accidents every moment, and nearly half of them being related to fatigue driving. When drivers feel fatigued, the eyes undergo significant changes. In this study, eye movement characteristics were utilized to detect the fatigue state of drivers, and a fatigue detection system was developed, combining the PERCLOS algorithm and the EAR algorithm, which were validated through experiments to assess system usability. The system was developed and designed based on traditional image processing algorithms in OpenCV and the facial feature recognition capabilities of the Dlib library. By using the 68-dimensional facial landmark detection model in the Dlib library, facial feature points were extracted, and eye tracking functionality was achieved through the feature points of the eyes. Subsequently, the PERCLOS algorithm, EAR algorithm, and a combination of the PERCLOS and EAR algorithms were employed. In this experiment, thresholds were set separately for the EAR and PERCLOS algorithms to compare the accuracy of eye movements. The system sets a threshold of 0.4 for PERCLOS, classifying it as fatigue when the proportion of closed eye time exceeds 0.4, and collects 20 sets of EAR data from the subject using an average value threshold of 0.2 to determine eye closure actions. Finally, through experiments monitoring the driver's eyes, the presence of fatigue state was determined, and the advantages and disadvantages of the three algorithms were summarized based on the experimental results. The experiment demonstrated that the Combined method algorithm has a more comprehensive detection capability compared to the PERCLOS and EAR algorithms, improving the fatigue detection performance. © 2024 IEEE.

关键词： Fatigue testing

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Asymmetrical Fault Current Calculation Method and Influencing Factors Analysis of Droop-Controlled Inverters

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 562-573页

作者： Huimin Zhao Zhikang Shuai Jun Ge An Luo Weimin Wu Z.John Shen College of Electrical and Information Engineering Hunan UniversityChangsha 410006China Electrical Engineering Department Shanghai Maritime UniversityShanghai 201306China Department of Electrical and Computer Engineering Ilinois Institute of TechnologyChicagoIL 60616 USA

Since the fault dynamic of droop-controlled inverter is different from synchronous generators (SGs), protection devices may become invalid, and the fault overcurrent may damage power electronic devices and threaten the safety of the microgrid. Therefore, it is imperative to conduct a comprehensive fault analysis of the inverter to guide the design of protection schemes. However, due to the complexity of droop control strategy, existing literatures have simplified asymmetric fault analysis of droop-controlled inverters to varying degrees. Therefore, accurate fault analysis of a droop-controlled inverter is needed. In this paper, by analyzing the control system, an accurate fault model is established. Based on this, a calculation method for instantaneous asymmetrical fault current is proposed. In addition, the current components and current characteristics are analyzed. It was determined that fault currents are affected by control loops, fault types, fault distance and nonlinear limiters. In particular, the influences of limiters on the fault model, fault current calculation and fault current characteristics were analyzed. Through detailed analysis, it was found that dynamics of the control loop cannot be ignored, the fault type and fault distance determine fault current level, and part of the limiters will totally change the fault current trend. Finally, calculation and experimental results verify the correctness of the proposed method.

关键词： Asymmetrical fault analysis droop control fault current calculation method limiter transient fault characteristics

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A Deep Reinforcement Learning Approach with Heuristic Optimization for Resource-Efficient Task Offloading in Mobile Edge Computing 6

A Deep Reinforcement Learning Approach with Heuristic Optimi...

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6th International Conference on Electronics and Communication, Network and computer technology, ECNCT 2024

作者： Liu, Yanggai Hou, Zeyu Lin, Ke Li, Lin School of Computer and Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9798350366143

Mobile edge computing (MEC) environments are characterized by limited computational resources, posing a significant challenge to achieving optimal task allocation and processing. To address this challenge, this study proposes a novel Hybrid Deep Reinforcement Learning approach (HARL) that integrates heuristic algorithms with deep reinforcement learning. HARL exhibits swift adaptation to diverse environmental states, enabling more precise resource allocation and task offloading decisions. The algorithm optimizes the hyperparameters of the Deep Q-Network (DQN) using a genetic algorithm. This enhances the exploration capabilities of DQN within the search space, allowing it to potentially discover superior strategies and improve system performance and efficiency. Experimental results demonstrate that the HARL method can achieve a significant reduction in energy consumption exceeding 5.11% compared to traditional reinforcement learning algorithms. © 2024 IEEE.

关键词： Deep reinforcement learning

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