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Adversarial Guided Gradient Estimation Hashing for Cross-modal Retrieval 8

Adversarial Guided Gradient Estimation Hashing for Cross-mod...

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8th ieee international conference on Cloud Computing and Intelligence systems, CCIS 2022

作者： Lu, Kangkang Liang, Meiyu Xue, Zhe Cao, Xiaowen Yin, Mengran Zhao, Zehua Beijing University of Posts and Telecommunications Beijing Key Laboratory of Intelligent Communication Software and Multimedia School of Computer Science National Pilot Software Engineering School Beijing100876 China

ISBN: (纸本)9781665477352

Due to low storage cost and fast query speed, deep hashing methods are widely used in cross-modal retrieval. However, the 'heterogeneous gap' between multi-modal data is still a challenge. Moreover, a major difficulty in deep hashing lies in the discrete constraints imposed on the network output. Existing solutions usually use relaxation techniques, but this inevitably produces quantization error, leading to sub-optimal hash code. In this paper, we propose Adversarial Guided Gradient Estimation Hashing (AGEH). Firstly, in order to bridge the heterogeneous gap between different modal data, a cross-modal adversarial feature learning network is constructed to learn cross-modal semantic associations. Secondly, to solve the discrete optimization problem of hash code, we propose a hashing optimization strategy based on gradient estimation for sign function, which strictly uses sign function to maintain discrete constraints in forward propagation, while in back propagation, the gradient is directly transmitted to the previous layer and thus avoid quantization error. Extensive experiments conducted on two cross-modal benchmark datasets show that our proposed AGEH outperforms several state-of-the-art methods. © 2022 ieee.

关键词： Backpropagation

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UA-HGAT: Uncertainty-aware Heterogeneous Graph Attention Network for Short Text Classification 15

UA-HGAT: Uncertainty-aware Heterogeneous Graph Attention Net...

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2022 ieee Congress on Cybermatics: 15th ieee international conferences on Internet of things, ithings 2022, 18th ieee international conferences on Green Computing and Communications, GreenCom 2022, 2022 ieee international conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th ieee international conference on Smart Data, SmartData 2022

作者： Kong, DeYan Ji, ZhenYan Sang, Yanjuan Dong, Wei Yang, Yanyan Beijing Jiaotong University School of Software Engineering Beijing China Blueintelligence Technology Co.Ltd. R&d Department Wuhan China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing100190 China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

During the last decade, deep learning has played a significant role in improving text classification which is widely applied in question answering systems, comment extraction, sentiment analysis, etc. Considering that few labeled training data are available, semi-supervised short text classification needs to be studied urgently. Existing works focus on long texts and cannot achieve satisfactory performance on short texts due to the sparsity, non-standardization, and insufficient labeled data. In this paper, we propose a novel uncertainty-aware heterogeneous graph attention network for semi-supervised short text classification (UA-HGAT), which makes full use of limited labeled data and large amounts of unlabeled data via exploiting an uncertainty-aware mechanism. In the model, entity description from Wikipedia is introduced to empower short texts, and word-level information is acquired by Word2Vec. the entity description and word-level information are combined with topic information to address the issue of short text sparseness. In particular, we introduce uncertainty-aware mechanism and negative sample learning to relieve the erroneous high confidence predictions from poorly calibrated models, so that it can offer enough pseudo-label samples for the model training. Extensive experiments show that our model significantly outperforms the SOTA methods on AGNews and Snippets datasets. © 2022 ieee.

关键词： Sentiment analysis

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A Density-based Controller Placement Algorithm for software Defined Networks 15

A Density-based Controller Placement Algorithm for Software ...

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作者： Chen, Jue Xiong, Yujie He, Dun Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

software Defined Network (SDN) is a new type of network structure, which decouples the data plane from the control planes, and improves network flexibility. However, this separation creates a problem called Controller Placement Problem (CPP), that is, how many controllers are required and where they should be placed. In this paper, we propose an improved Density-based Controller Placement Algorithm (DCPA), which can obtain the required number of controllers through traversing candidate values of radius, and then divide the entire network into multiple sub-networks. In each sub-network, the controllers are deployed with the purpose of minimizing the average propagation latency and worst-case propagation latency between controllers and switches simultaneously. We conduct experiments on 100 real network topologies from the Internet Topology Zoo to evaluate the performance of algorithm, and the results verify that DCPA can always find out the controller placement scheme with a low time consumption to reduce the propagation latency for different network scales, with a less than 10% margin from the optimal solution. © 2022 ieee.

关键词： Controllers

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Identification of fake currency

Identification of fake currency

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8th international conference on Computing in engineering and Technology (ICCET 2023)

作者： K. Sivanagi Reddy B. Jyothika R. Shravya G. AathmajaSai Department of Electronics and Communication Engineering India

Currency fraud now possess a serious risk to both people's livelihoods and the nation's economy. Due to im-provements, in printing and scanning technology, currency duplication is still a growing worry for governments. Although banks have many note-detecting systems; but are expensive and frequently wrong. this problem has the potential to be considerably solved by the disciplines of machine vision, neural networks, and image processing. Although there are fake cash detectors, they are only used in banks and corporate offices, leaving the general public and small companies at risk. In order To detect and invalidate fraudulent Indian currency, we will develop a software-based system in this project using cutting-edge image processing and computer vision techniques. First, we will analyze the many security character-istics of Indian currency. this currency authentication system was created entirely in the Jupyter Notebook environment using the Python programming language.

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Fusion BASED AGV Robot Navigation Solution Comparative Analysis and Vrep Simulation 8

Fusion BASED AGV Robot Navigation Solution Comparative Analy...

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8th international Iranian conference on Signal Processing and Intelligent systems, ICSPIS 2022

作者： Moshayedi, Ata Jahangir Zanjani, S. Mohammadali Xu, Dangling Chen, Xi Wang, Guijiang Yang, Shuxin Jiangxi University of Science and Technology School of Information Engineering Jiangxi Ganzhou China Islamic Azad University Smart Microgrid Research Center Najafabad Branch Najafabad Iran Islamic Azad University Department of Electrical Engineering Najafabad Branch Najafabad Iran

ISBN: (纸本)9781665476232

Today, Automated Guided Vehicle (AGV) robots are integral to many factories. One of the basic problems of these robots is accurate navigation, which, in addition to creating security in performing tasks, it helps the robot to manage the battery power and energy and move on a predetermined path. Over the various method, the visions are based on good performance, recently been widely used. In this research, a simple but effective fusion method as the combination of vision(camera) and infrared (IR) sensors with the minimum number of sensors is proposed and implemented. the proposed method has been simulated and evaluated using the Vrep simulator with real dimensions of our previous design AGV system named Hongma and the Python API. In the simulation, the proposed method was carried out. In the experiment, five paths named Circle, Elliptical, Spiral,8 shapes, and Special path, different paths with different complexity were tested, and the experiment aimed to find the maximum speed at which the proposed algorithm and the vision sensor (camera sensors) can track the path with a 100% success rate. the results obtained in the experiment show the fusion method's effectiveness over the five mentioned scenarios in tracking the planned path compared to the routine vision method. © 2022 ieee.

关键词： computer software

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Modeling and Design of FPGA-Based Power Quality Analyzer 8th

Modeling and Design of FPGA-Based Power Quality Analyzer

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8th international conference on Microelectronics, Circuits, and systems, Micro 2021

作者： Balasubbareddy, M. Sri Ram, Kondapalli Venkata Sangu, Ravindra Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad India Department of Electrical and Electronics Vasireddy Venkatadri Institute of Technology Namburu India

ISBN: (纸本)9789819904112

this paper deals with the modeling and design of power quality analyzer. the power quality analyzer (PQA) is essential in today’s world to give quality power uninterruptedly. We discussed about the hardware design of PQA and the software used. It is used to measure all the powers (P, Q, and S) in three phases. Voltage profiles, %thD, power factor, harmonic profile, and load curves can be obtained with this type of analyzer at cheaper cost. this equipment can be used to analyze the output of any machine like alternators transformers and transmission lines. through the harmonic profile, we can measure which order of harmonic is more in the output of these machines. It uses Hall sensors (HE055T01) for current sensing and PT (230/9 V) for voltage stepping down and 7840 IC voltage sensing. these sensed along signals are converted to digital signals with help of ADC (AD7366). these digital signals are given to Field Programmable Gate Array (FPGA)-SPARTAN 6 model. FPGA processes these signals based on FIFO algorithm, and through USB port, it is connected to personal computer. Key sight VEE pro is the software used to analyze the power signals. We can measure active, reactive and apparent powers, thD of all three phase and also live load variations tracking through this software. this analyzer costs very less when compared to Fluke power quality analyzer. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Power quality

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Selecting Embedded Feature Modeling with software Product Line for Smart Home Applications 8

Selecting Embedded Feature Modeling with Software Product Li...

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8th international conference on Contemporary Information Technology and Mathematics, ICCITM 2022

作者： Hasan, Mohammed Zaki Al-Rizzo, Hussain Allawi, Manar Mozahim Univeristy of Mosul College of Computer Science Mosul Iraq University of Arkansas Dcstem College System Engineering Dept Little RockAR United States

ISBN: (纸本)9798350334869

Internet of things (IoT) for environmental applications such as smart homes, campuses, cities, and health care systems are used to connect various wireless devices. Despite the use of the same devices, the reusability of these applications enables developers and software engineers to make enhancements to the development process according to the requirements of end users. However, the large number of variations in IoT technologies makes it hard for the developers or software engineers to select the default features in each application because of compatibility issues among devices. In this paper, software Product Line (SPL) approach is proposed to design and manage the variabilities and commonalities among smart home applications. An embedded feature selection mechanism is proposed to classify the services by selecting the optimal subset feature. the selected subset features are those that are highly correlated and consistent with other features. the dataset is generated using open smart home simulator (OpenSHS) for daily activities within the virtual environment. the subset of features is evaluated by the level of consistency in each service. Weka data mining tool is used to find the classifier such as Bayes network and decision table which achieve the best accuracies on the dataset obtained in order to support services for residents in smart home applications. the approach adopted is based on a set of predefined performance metrics in order to compare the results for each classifier in terms of its ability to classify the services. It has been found that the Bayes network achieves an accuracy over 84.0% while the decision table achieved an accuracy over 83.0%. © 2022 ieee.

关键词： Feature Selection

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Development of Boost Converter System with Solar Charging Controller for Electrical Equipment

Development of Boost Converter System with Solar Charging Co...

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ieee international conference on engineering Technologies and Applied Sciences (ICETAS)

作者： Babul Salam Ibrahim Dur Muhammad Soomro Sharman Sundarajoo Mohd Fakhrul Shahirin Electrical and Computer Engineering Department Gulf University for Science & Technology Kuwait Faculty of Electrical and Electronic Engineering Universiti Tun Hussein onn Malaysia Johor Malaysia

there are numerous DC to DC energy alteration utilizations where the origin voltage needs to be transformed to a larger resulting voltage. Boost converters utilization includes energy equipment for semiconductor manufacturing supplies, ultrasound instruments, X-ray devices, solar systems, and mercury ion motors. Notably, this type of converter is used to step up the photovoltaic generator's voltage to the required load voltage in solar systems. Hence, this study's principal interest is to form and compose a boost converter and a solar charging controller circuit. this system aims to change the uncontrolled input of DC to a regulated output of DC with the wanted level of voltage. there are three critical procedures involved to produce a boost converter. the first process was to design. Next was to simulate, and the final process was to construct the boost converter and a solar charging controller circuit. the operational frequency was configured at 20 kHz, and a duty cycle of 50% was employed. In this study, the OrCAD PSpice, Multisim, and Proteus software environments were used to simulate the develop the circuit to obtain results. Every parameter value was obtained from the hardware. the values obtained were compared with the calculation, simulation, and hardware results from the boost converter circuit as a validation procedure.

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Beyond 100 Ethical Concerns in the Development of Robot-to-Robot Cooperation 15

Beyond 100 Ethical Concerns in the Development of Robot-to-R...

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作者： Rousi, Rebekah Vakkuri, Ville Daubaris, Paulius Linkola, Simo Samani, Hooman Makitalo, Niko Halme, Erika Agbese, Mamia Mohanani, Rahul Mikkonen, Tommi Abrahamsson, Pekka School of Marketing and Communication University of Vaasa Finland Faculty of Information Technology University of Jyv¨skyl¨a Finland Department of Computer Science University of Helsinki Finland School of Engineering Computing and Mathematics University of Plymouth United Kingdom

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

this paper investigates ethical issues implicated in multi-robot cooperation development. the authors explore the possibilities of applying ECCOLA - a tool and method for ethical AI software development in the context of robot-to-robot cooperation. the method entailed a workshop of researchers (N=10) who ideated multi-robot ethical concerns (N=149). these were analysed by an external researcher and emergent themes were compared to the ECCOLA framework. the results show the need for expansion of the ECCOLA framework. the paper makes three important contributions: 1) application of ECCOLA in multi-robot cooperation;2) identification of ethical concerns for robot-to-robot cooperation;and 3) urgency for attention towards mutual cooperation and confrontation in multi-robot cooperation. © 2022 ieee.

关键词： Multipurpose robots

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eBFP: A Processing-in-Memory Storage Method with Parallel Computing and Low Latency

eBFP: A Processing-in-Memory Storage Method with Parallel Co...

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international conference on computers, Communications, and systems (ICCCS)

作者： Jiehao Miao Jizhou Bai Bingbin Huang Jingrui Li Kaixuan Bao Wei Xu School of Information Science and Engineering Southeast University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

With the development of the sixth Generation (6G) mobile communication, big data and deep learning, new requirements for latency and computational complexity have been put forward. therefore, in this paper, we propose a new floating-point storage called extended block floating-point (eBFP). this article first briefly introduces the storage method of the ieee Standard for Floating-point Arithmetic (ieee-754) floating-point numbers and its shortcomings, and then details the storage method of the eBFP operator and its specific operation logic. Finally, a simulation comparison with ieee-754 floating-point number shows the advantage of eBFP to better trade-off accuracy and complexity.

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