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An Optimum Approach to Indian Sign Language Recognition using Efficient Convolution Neural Networks 4

An Optimum Approach to Indian Sign Language Recognition usin...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Kumar, Ritik Bhardwaj, Nikunj Kumar, N. Suresh Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9781665474368

the most important component of every discussion is language, and sign language is the most formal mode of communication for persons who are deaf or mute. Communication, as we all know, is one of the most important components of modern life. the importance of communication is increasing in tandem with our maturation in life. the purpose of this project is to develop a system capable of recognizing all of these signs and serving as a bridge for signers and non-signers to communicate and interpret sign meanings. Technology is rapidly evolving, and now that we have powerful systems, a wealth of data, and a diverse set of sources, we can design a system to assist people with disabilities. We will develop a user-independent framework for automatically recognizing Indian Sign Language in this project, which will allow for feature extraction, recognition, and interpretation of a variety of one-handed, dynamic isolated signals. the two most important and fundamental aspects of SLR research are isolated sign recognition and continuous sign recognition. Hand form, hand position, and so on are the primary hand traits that can be used in sign language. the extra-clung functionality can be implemented in two ways. Either one is tracking-based or it is not. this essay focuses on one such approach that we devised to overcome significant communication barriers. the technique is divided into three stages: pre-processing, texture extraction, and recognition. © 2022 IEEE.

关键词： Feature extraction

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Movie Recommendation System Using Machine Learning Techniques 4

Movie Recommendation System Using Machine Learning Technique...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Roy, Ritika Rai, Vandana Kumar, S. Rakesh Galgotias University School of Computing Science and Engineering India

ISBN: (纸本)9781665474368

Film Proposals outlines give a program to help clients in social affair clients with equivalent interests. this makes limited time structures a necessary piece of online locales and business applications. this work centers around music proposition programs whose fundamental object is to advance a proposed film however a supportive of based proposition program. this proposition system will gather information about the client's predisposition of the different movies two times, decidedly or expressly. Securing of client information frequently includes perceiving client conduct, like watching films. Of course, unequivocal insurance incorporates gathering evaluation or client *** paper talks about film proposals. the film's suggestion is significant in our public life in view of its power in giving better diversion. Such a framework can propose a bunch of motion pictures for clients in light of their inclinations, or fame films. the proposal framework is utilized to recommend things you can purchase or see. they direct clients towards them those things that can address their issues by removing a lot of data. Suggestion framework, or a proposal framework (some of the time it changes the 'framework' in a similar sense as a discussion or motor), is a little classification of data.A separating framework that looks to anticipate the "normal"or "inclinations"a client can appoint to an article. they are principally utilized in business applications. MOVREC likewise assists clients with tracking down motion pictures of their decision in view of film data of different clients in a powerful and productive manner without investing a ton of energy in pointless perusing. © 2022 IEEE.

关键词： Collaborative filtering

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Unsupervised Real-World Super-Resolution via Degradation Representations 4

Unsupervised Real-World Super-Resolution via Degradation Rep...

引用

4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Chen, Junhong Chen, Xuankun Zhang, Dongyu Sun Yat-sen University School of Computer Science and Engineering Guangzhou China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

Most current deep convolutional neural networks achieve great performance on single image super-resolution (SISR), trained with corresponding of high-resolution(HR) and low-resolution(LR) images. Conversely, the super-resolution performance of them is reduced testing in real-word super-resolution, since these methods create paired LR images by simple interpolation downsampling from HR images (e.g. bicubic) which is far more different from the natural degradation. In this paper, we design a novel unsupervised framework conditioned on degradation representations for real-world super-resolution. Our proposed method is composed of three stages: we first learn implicit degradation representations from real-world LR images and then acquire the LR images by downscaling network which would sharing a similar degradation with real-world images. Finally, we make paired data of the generated real LR images and HR images for training the SR network. Our model achieves better performance than recent SR methods on the NTIRE2020 real-world SR challenge Track1 dataset. © 2022 IEEE.

关键词： Convolutional neural networks

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Joint Beam Pattern Selection and Power Control with Deep Reinforcement Learning in Wireless Mobile Networks 4

Joint Beam Pattern Selection and Power Control with Deep Rei...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Liu, JainShing Chang, Wan-Ling Lin, Chun-Hung Richard Providence University Computer Science and Information Engineering Taichung Taiwan Insurance Chaoyang University of Technology Taichung Taiwan National Sun Yat-sen University Computer Science and Engineering Kaohsiung Taiwan

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

To meet the huge data rate required in future wireless mobile networks, inter-cellular interference and inter-beam interference should be further reduced to achieve green communication while increasing the desired performance. For this aim, we study a joint design of beamforming and power control with interference coordination, and formulate it as a non-convex optimization problem. Specifically, the objective of this work is to maximize the overall system capacity while reducing the power consumption to realize the efficient and green communication expected. However, the non-convex problem is hard to solve even given certain optimization tools. To obtain its solution online, we develop a deep reinforcement algorithm based on deep deterministic policy gradient (DDPG) that is applicable for continuous states to realize the continuous power allocation, eliminating the curse of dimensionality due to the discrete action space only solvable for the conventional Q-learning algorithm. In our simulations, the proposed DDPG algorithm is shown to outperform the Q-learning algorithm, and the utility of the former would be 1.5 times higher than that of the latter at most. © 2022 IEEE.

关键词： Reinforcement learning

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Novel Approach for the System Identification of a Non linear Industrial Process 4

Novel Approach for the System Identification of a Non linear...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Indumathi, S.K. Ramachandraiah, Uppu Hindustan Institute of Technology and Science Department of Mechatronics Engineeering Chennai India School of Electrical Sciences Hindustan Institute of Technology and Science Chennai India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Controlling the flow and level of the liquid in the process is a critical issue in every sector. In various sectors, the conical tank method is frequently employed. the conical tank's design causes non-linearity, and controlling liquid level in the conical tank process is the most difficult difficulty. As a result, the process' output may be influenced from time to time. the level control of the conical process has been the subject of numerous studies. In several process industries, a conical bottomed tank is employed for complete fluid drainage, with nonlinearity limited to the bottom. If the tank is totally conical, the drainage efficiency can be improved even more. However, the tank's continual change makes it very nonlinear, making liquid level control challenging in such a process. Colloidal mills, food processing industries, leaching extractions in pharmaceutical and chemical industries, petroleum industries, molasses, liquid feed and liquid fertilizer storage, chemical holding & mix tank, Biodiesel processing and reactor tank are all examples of conical shaped tank systems. Conical tanks are used to prevent sludge and settlement in storage and holding tanks. Modeling and controller design on a single conical tank are carried out in this research using traditional modeling (transfer function modeling), system identification, and data-based methods. the performance of the designed controllers is evaluated using time domain specifications. Controllers designed using data based method is proved to be better than the other two methods. To model and design a controller, MATrix LABoratory (MATLAB) platform is used. © 2022 IEEE.

关键词： Controllers

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Multiple targets localization and micro deformation monitoring 4

Multiple targets localization and micro deformation monitori...

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4th international conference on Information science, Electrical, and Automation Engineering, ISEAE 2022

作者： Cai, Min Li, Wenjie Lian, Wenbin Lv, Yansong Jiang, Fan Zhu, Guofu Guangdong Provincial Highway Construction Co. Ltd. Guangzhou510623 China CCCC Road and Bridge Construction Co. Ltd. Beijing101107 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Hunan Taikang Electronic Information Technology Co. Ltd. Changsha410012 China

ISBN: (纸本)9781510655157

Micro deformation monitoring technology can be used in surface subsidence, slope, building deformation detection and other emergency fields. A micro deformation monitoring method for multiple targets by exploiting a mmWave radar are proposed. the proposed method takes advantage of employing higher-order cumulant (HOC) to localize targets and extracting the phase by differentiate and cross multiply (DACM). the measured data in real scene have validated the proposed method. It is convenient to be applied in real engineering practice with a high accuracy and a low computing complexity. © 2022 SPIE.

关键词： Deformation

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A Systematic Study on methods of Spatiotemporal Hotspot Detection and Evaluation metrics 4

A Systematic Study on methods of Spatiotemporal Hotspot Dete...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Jain, Rishabh Bhat, Aruna Delhi Technological University Department of Computer Science New Delhi India

ISBN: (纸本)9781665474368

A Spatial hotspot is a confined region/space inside a geographical area which has a higher concentration of activity points than outside the hotspot region within the study area. With technological breakthroughs in spatial data collection and increased computation capabilities, several research publications presented novel methods for Spatial Hotspot detection. the relationship between Spatial Hotspots and time (temporal effect) has also been investigated by various researchers, expanding the horizon of the spatial hotspot to spatiotemporal hotspot. the idea of Spatiotemporal hotspot detection gained considerable interest among researchers because of its practical utility in public health, public safety, traffic volume analysis, crime zone analysis, and other essential applications. However, it is also vital to analyze the research literature. Our research aims to organize the existing comprehensive literature into a well-organized hierarchical framework to comprehend better the various methodologies widely adopted around the world. We propose a framework that suitably categorizes the research effort of various scholars into several appropriate categories based on their differences in primary algorithmic approaches. Furthermore, we also present an extensive analysis of the widely utilized evaluation measures adopted in this research domain. © 2022 IEEE.

关键词： Machine learning

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Identification of Fake News Using Machine Learning Approach 4

Identification of Fake News Using Machine Learning Approach

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Singh, Gurupraksh Yadav, Brijendra Kumar Singh, Bhuvnesh Pratap Sharama, Shelja Galgotias College of Engineering and Technology UP Greater Noida India Galgotias College of Engineering and Technology Department of Computer Science and Engineering UP Greater Noida India

ISBN: (纸本)9781665474368

In today's world everyone is using internet and Social media platforms like Instagram, Twitter, Facebook etc. In such scenario fake news spreads very rapidly and reaches to millions of user in a short span of time. Riots during election, riots between different religious groups are consequences of these fake news. Many political parties utilize false information to boost their vote totals. Machine learning is important for classification of data, but it has limitations. On the basis of the kaggle dataset, a model has been suggested to classify fake and authentic news in this project. Our technology will be programmed to discern between fake and legitimate news from various social media platforms. It also aims to distinguish genuine news from a variety of sources. Our research looks into several textual qualities that can be used to tell the difference between phoney and real content. We use machine learning algorithms, such as the Passive Aggressive classifier using TF-IDF, to train our model utilizing those properties. © 2022 IEEE.

关键词： Machine learning

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Early Warning Algorithm for thermal Fault Diagnosis of Electrical Equipment based on Dynamic Early Warning threshold 4

Early Warning Algorithm for Thermal Fault Diagnosis of Elect...

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4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Zhou, Feng Li, Wenqiang Wang, Xiaoting Hu, Heng Jiang, Peng Hao, Ting Shandong University of Science and Technology Qingdao China Heilongjiang Electric Power Co. Ltd. UHV Company Harbin China State Grid Heilongjiang Electric Power Company Limited Harbin China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

For electrical equipment in the thermal fault warning due to alarm thresholds in any case is static and lead to leakage, false alarm problem. An early warning algorithm for thermal fault diagnosis of electrical equipment based on dynamic warning thresholds is proposed. the temperature prediction model based on BP neural network is established by considering load current, ambient temperature and other influencing factors, and the normal operating temperature is accurately predicted by training and calibrating the measured data in normal operation at different ambient temperature and load current. Using the relative temperature difference method, the corresponding dynamic early warning threshold is determined by the thermal fault defect standard, and the early warning for different fault degrees is realized according to the dynamic threshold. this paper effectively solves the problem of false alarms and omissions caused by traditional static thresholds, improve the accuracy of temperature monitoring and fault warning of electrical equipment and reduce the workload of maintenance workers, Moreover, it lays the foundation for realizing the intelligence of thermal fault diagnosis and fault warning of electrical equipment, and provides a guarantee for the safety, reliability and continuous and stable operation of electrical equipment. © 2022 IEEE.

关键词： Failure analysis

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Traffic improvisation by identifying the accident locations using ML/data mining approaches 4

Traffic improvisation by identifying the accident locations ...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Goswami, Nitish Giri Sharma, Pranav Arora, Aditi Singh, Nidhi Abes Engineering College Department of Computer Science U.P. Ghaziabad India Abes Engineering College U.P. Ghaziabad India Krishna Engineering College U.P. Ghaziabad India

ISBN: (纸本)9781665474368

Road Traffic Accident Prediction is really widely necessary element that affects the premature death of lots of people and also have the losses of property which is either public or private. Traffic road safety basically is a word which is related to the proper planning and the executing the various approaches to reduce the cause of road traffic accidents. Road traffic accident survey is really most essential to pick out diverse elements connected with road accidents that can surely help in decreasing the accident rate. the homogeneity of road traffic accident data is major problem in traffic road safety survey. Primarily in this paper we are using decision tree, random forest classifier on a current traffic road accident data. Although, in these defined procedures they are efficiently fitted to pull out homogeneity of road traffic accident data. Several studies center on procedure of road accidents. Other elements put in weather and light conditions of the road. Road accident harshness keeps on changing over a period of time and also expand infinitely. Hence in this study we basically examined latest works, data mining methodologies and tools that were demonstrated better in accident factual data analysis and prediction. We also made a web app using flask to deploy our machine learning model and use this app to predict and send a message to alert the user. © 2022 IEEE.

关键词： data mining

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