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检索条件"任意字段=2022 International Conference on Algorithms, Network and Computer Technology, ICANCT 2022"

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network Communication Technologies and its Role in Enabling Effective Communication 6

Network Communication Technologies and its Role in Enabling ...

引用

6th international conference on Trends in Electronics and Informatics, ICOEI 2022

作者： Shamsan, Abdullah Haider Balu Raskar, Sandeep Saha, Supratim Suleimenova, Kymbat Madkar, Shankar Sagybekova, Akmaral Administration Sana'a University Department of Business Yemen Computer Engineering Terna Engineering college University of Mumbai India Swami Vivekanand Subharti University Department of ECE India International Education Corporation Department of Design Almaty Kazakhstan College of Engineering Maharashtra Pune India Tymarkul Muzdybayeva L.B. Goncharov Kazakh Automobile and Road Institute Almaty Kazakhstan

ISBN: (纸本)9781665483285

network-communication technologies have brought significant changes in ways each individual in an organisation connects and communicates with each other. Different types of network-communication technologies include wearable computers, IRDA interfaces, WAN technology, wireless LAN, IRDA interfaces. With these technologies, organisations improve communication with different stakeholders including suppliers, employees, vendors, partners and so on. LAN is used for connecting computers in different locations through a common path of communication, which makes it easy to communicate across the organisational communication channels irrespective of the locations of the stakeholders. This study is aimed at analysing the role of network-communication technologies in enhancing communication amongst the organisational employees, suppliers or other stakeholders. The literature-review chapter has included concepts regarding the role of Intranet and other network-technologies in enhancing communication efficiency of organisations. This section has also analysed possible security risks that organisations should consider before adopting network-communication technologies, Further, it has provided understanding of the application of these technologies in different sectors for improving communication. Methodology-chapter of this study has included a detailed understanding of the ways data has been collected in the study. The findings and discussion chapter includes different themes based upon objectives of the study that has helped in establishment of relationships amongst different variables included in this study. This section has found that network-communication technologies have helped different organisations in achieving their strategic objectives through proper communication amongst different individuals associated with the organisations. © 2022 IEEE.

关键词： Wide area networks

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Research on Machine Learning-based Nowcasting Method for Low Visibility Weather in Urumqi Airport 4

Research on Machine Learning-based Nowcasting Method for Low...

引用

4th international conference on Advances in computer technology, Information Science and Communications, CTISC 2022

作者： Li, Jing Wang, Fan Xue, Kang Hao, Yusong Chengdu China Urumqi International Airport Operation Management Committee of Xinjiang Airport Group Urumqi China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

This paper takes Urumqi Airport as an example, to analyze the visibility of the airport and its impact on normal flight. For the purpose of analysis, the airport's real-time meteorological observation and numerical forecast data is regarded as the analysis field after full consideration of the meteorological observation conditions of the airport, combined with the advantages and disadvantages of mainstream research methods at home and abroad, so that the temporal and spatial characteristic factors causing the low visibility weather at the airport in nowcasting period can be obtained through the analysis and matching of the airport and satellite observation data, to prospect a nowcasting model for low visibility weather in the airport using machine learning algorithms. Due to the addition of multi-channel satellite data, the nowcasting model proposed in this paper can access the visibility evolution information of large scale in space, which provides the basis for the fine monitoring of visibility at the airport. According to the video image monitoring data of airport flight area, the multidimensional and high-frequency quantitative inversion data about the airport visibility can be obtained, which makes up for the lack of low visibility weather monitoring at airport in azimuth and time. © 2022 IEEE.

关键词： Visibility

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international Roughness Index (IRI) prediction using various machine learning techniques on Flexible Pavements 2

International Roughness Index (IRI) prediction using various...

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2nd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Pandit, Wasique Haleem Sharma, K.P. Sharma, Nonita Dr. B. R. Ambedkar National Institute of Technology Department of Computer Science and Engineering Jalandhar India Indira Gandhi Delhi Technical University for Women Department of Information Technology Delhi India

ISBN: (纸本)9781665437899

Pavement performance is an essential factor for companies to shape their strategies for maintenance, repair, and sometimes reconstruction of damaged roads. Pavement roughness is a crucial indicator for performance measurement. The international roughness index (IRI) represents pavement roughness. Over the last decade, researchers have been working on linking pavement roughness to other performance indicators. In India, no IRI (international Roughness Index) research has been conducted that considers the characteristics and parameters of Indian road conditions. This paper explores the possibility of using different models to determine the characteristic of traffic and the structural parameters of the road. Using the data set collected from the Central Road Research Institute of India (CRRII) database, different machine learning models were applied to effectively predict the IRI to determine the pavement condition. IRI using ANN (Artificial Neural network) and XGB-Regressor gave the lowest mean absolute percentage error in terms of data analysis compared to the other models used. © 2022 IEEE.

关键词： Fatigue of materials

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Spam Recognition Model Based on TextCNN 3

Spam Recognition Model Based on TextCNN

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3rd international conference on Pattern Recognition and Machine Learning, PRML 2022

作者： Yixuan, Gao Yuanyuan, Zhang Ye, Cheng Fuzhou University Maynooth International Engineering College Fuzhou China Fuzhou University College of Computer and Data Science Fuzhou China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

With the advancement of modern Internet technology, email is widely used in people's daily lives and has become one of the common communication tools. However, at the same time, email-based spam has also been widely spread, flooding people's lives and not only wasting public resources but also infringing on people's legitimate rights and interests. Based on this, we propose a Spam recognition model based on TextCNN by combining Convolutional Neural network and Natural Language Processing, where natural language processing techniques are used to pre-process the text in the spam corpus to obtain text features, which are then imported into the constructed Convolutional Neural network analysis model. A CNN spam recognition model is then designed and analyzed hierarchically using the TensorFlow framework. After extracting the features from the email dataset, the model was fed into the convolutional neural network again for several iterations of training. The results indicated that the model achieved an accuracy of 97.7% in spam recognition, which is an exceptionally significant improvement in accuracy and stability compared to the SVM model used previously, demonstrating good filtering performance. © 2022 IEEE.

关键词： Convolutional neural networks

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An Improved Particle Swarm Optimization Algorithm Based on Simulated Annealing for Large-Scale Node Location of WSN 4

An Improved Particle Swarm Optimization Algorithm Based on S...

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4th IEEE international conference on Civil Aviation Safety and Information technology, ICCASIT 2022

作者： Li, Yitao Chongqing University of Posts and Telecommunications International College Chongqing China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Location-based service (LBS) is one of the most potential applications in the Internet of Things (IoT) and providing reliable node location information has become an important indicator to measure the technical standards of the IoT. However, node location in wireless sensor network (WSN) is a non-convex optimization problem, as well as the dynamic and large amount of data in the IoT, traditional node location algorithms have encountered severe challenges in solving such problems. In this paper, an improved particle swarm optimization (PSO) algorithm based on simulated annealing (SA) algorithm (SA-PSO) was proposed to locate nodes in the IoT. Using the probabilistic search characteristics of the SA algorithm in the "optimization"and "deterioration"directions, the particle iteration of the PSO is optimized and adjusted to avoid the "premature convergence"phenomenon that the PSO algorithm is prone to. At the same time, an adaptive inertia weight is introduced for dynamic calculation, thereby effectively improving the coverage of node location. Experimental results show that, compared with the traditional PSO algorithm, the algorithm proposed in this paper can effectively improve the coverage rate and solving speed of node location, and has more accurate location results in large-scale WSN location. © 2022 IEEE.

关键词： Internet of things

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Analysis and Design of Low Power Consumption 8T and 10T Full Adder CMOS technology 13

Analysis and Design of Low Power Consumption 8T and 10T Full...

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13th IEEE Annual Information technology, Electronics and Mobile Communication conference, IEMCON 2022

作者： Bin Abd Majid, Mohamed Ibrahim Sahak, Rohilah Subramaniam, Krishnan Zainuddin, Ahmad Anwar Rahman, Siti Husna Abdul Puzi, Asmarani Ahmad Mansor, Ahmad Fairuzabadi Mohd Yunos, Muhammad Farhan Affendi Mohamad Svpk, Satya Devu Manipal International University Negeri Sembilan Malaysia International Islamic University Malaysia Multimedia University Cyberjaya Malaysia Silverseeds Lab Network Gombak Malaysia

ISBN: (数字)9781665463164

ISBN: (纸本)9781665463164

All designers and engineers are familiar with the significance of adder subsystems. Therefore, engineers continue to perform research on them by integrating creative design ideas to boost the speed of the circuit and decrease its power consumption. In numerous digital data processing applications, such as microprocessors, and digital signal processors, adder logic cells are utilized. To implement Complementary Metal Oxide Semiconductor (CMOS) design techniques, many logic styles are employed. One example is the full adder, which is at the heart of every central processing unit and is essential to the way every type of computer processor works. In this paper, a design of 8 transistors and 10 transistors was developed using DSCH 3.5. Full adders are fundamental components of the ALU, which is the microprocessors' and Digital Signal Processing's logical and arithmetic unit. The Micro wind 3.5 tool is used to conduct simulation of the generated full adder design while operating at room temperature. The proposed 8T design shows $71.742\mu \mathrm{W}$ power consumption, the time delay is O.880ns and has 1.15 GHZ speed. The lOT design has less power consumption than 8T design. According to the findings of the investigation, the 8T design demonstrates superior speed efficiency and reduced power consumption when compared to the lOT design methodologies that were taken into consideration. © 2022 IEEE.

关键词： Adders

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Prediction of Protein-Protein Interactions through Deep Learning Based on Sequence Feature Extraction and Interaction network

Prediction of Protein-Protein Interactions through Deep Lear...

引用

2022 IEEE Biomedical Circuits and Systems conference, BioCAS 2022

作者： Le, Nguyen Quoc Khanh Kha, Quang Hien Taipei Medical University Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei Taiwan

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

Protein-protein interaction (PPI) is an important molecular process in the cell, which is vital to the function of the cell in the biochemical process. This study focuses on human protein. It uses protein information and the relationship of protein interaction network structure to predict PPI. Deep neural network model is implemented to realize PPI prediction. Through five-fold cross-validation, a high performance in the prediction accuracy is produced. The accuracy rate on the test set is 92.45%. To further evaluate the performance of this method, we compared it with other machine learning algorithms. The experimental results show that the method based on neural network is significantly better than the others on the same dataset. It also shows a superior performance compared to previous predictors in this field on PPI prediction. © 2022 IEEE.

关键词： Proteins

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Convolutional Neural network Based Partial Face Detection 7

Convolutional Neural Network Based Partial Face Detection

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7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Islam, Md. Towfiqul Ahmed, Tanzim Raihanur Rashid, A.B.M. Islam, Taminul Rahman, Md. Sadekur Tarek Habib, Md. Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665421683

Due to the massive explanation of artificial intelligence, machine learning technology is being used in various areas of our day-to-day life. In the world, there are a lot of scenarios where a simple crime can be prevented before it may even happen or find the person responsible for it. A face is one distinctive feature that we have and can differentiate easily among many other species. But not just different species, it also plays a significant role in determining someone from the same species as us, humans. Regarding this critical feature, a single problem occurs most often nowadays. When the camera is pointed, it cannot detect a person's face, and it becomes a poor image. On the other hand, where there was a robbery and a security camera installed, the robber's identity is almost indistinguishable due to the low-quality camera. But just making an excellent algorithm to work and detecting a face reduces the cost of hardware, and it doesn't cost that much to focus on that area. Facial recognition, widget control, and such can be done by detecting the face correctly. This study aims to create and enhance a machine learning model that correctly recognizes faces. Total 627 Data have been collected from different Bangladeshi people's faces on four angels. In this work, CNN, Harr Cascade, Cascaded CNN, Deep CNN & MTCNN are these five machine learning approaches implemented to get the best accuracy of our dataset. After creating and running the model, Multi-Task Convolutional Neural network (MTCNN) achieved 96.2% best model accuracy with training data rather than other machine learning models. © 2022 IEEE.

关键词： Face recognition

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Using Image Processing and Optical Character Recognition to Recognise ID cards in the Online Process of Onboarding

Using Image Processing and Optical Character Recognition to ...

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2022 international conference on Smart Information Systems and Technologies, SIST 2022

作者： Gulnara, Bektemyssova Yerassyl, Akhmer International Information Technology University Almaty Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

A broad range of computer vision studies have been conducted on the recognition of identity documents using mobile devices. A portfolio of techniques and algorithms for solving problems like face recognition, document detection and correction, text field recognition, and so on has been developed, and the lack of data sets has become a critical challenge. The electronic ID card has been commonly used to verify or recognize an individual since its discovery in 2011. Take note of several issues, such as high requirements for detecting the id-card field and challenges recognizing the data in the id-card. In this research, we realized an approach for identifying electronic ID cards using image detection and Optical Character Recognition (OCR). This paper provides a short outline of how banking institutions and other fintech companies utilize highly developed OCR tools to automate their processes, enhancing not just service quality, as well as the precision, speed, and protection of their transaction data. As an outcome of our image processing and OCR techniques, we can achieve 99 percent ID detection. This research was based on the interface of a mobile application, such as those owned by one of Kazakhstan's banks. © 2022 IEEE.

关键词： Optical character recognition

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8th international Symposium on Ubiquitous networking, UNet 2022

8th International Symposium on Ubiquitous Networking, UNet 2...

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8th international Symposium on Ubiquitous networking, UNet 2022

ISBN: (纸本)9783031294181

The proceedings contain 21 papers. The special focus in this conference is on Ubiquitous networking. The topics include: Deep Reinforcement Learning to Improve Vehicle-to-Vulnerable Road User Communications in C-V2X;Pervasive Computing for Efficient Intra-UAV Connectivity: Based on Context-Awareness;road Accident Analysis of Dhaka City Using Counter Propagation network;reinforcement Learning for Protocol Synthesis in Resource-Constrained Wireless Sensor and IoT networks;Distributional Reinforcement Learning for VoLTE Closed Loop Power Control in Indoor Small Cells;reinforcement Learning Aided Routing in Tactical Wireless Sensor networks;a Green and Scalable Clustering for Massive IoT Sensors with Selective Deactivation;threat Mitigation Model with Low False Alarm Rate Based on Hybrid Deep Belief network;on Feature Selection algorithms for Effective Botnet Detection;Low Profile CPW Fed Tri-Band Millimeter Wave Antenna Design for Future 5G Application;A Novel Hybrid Deep Learning Model for Crop Disease Detection Using BEGAN;Multivariate Skewness and Kurtosis for Detecting Wormhole Attack in VANETs;trading Off Controlled System Energy and Wireless Communication Energy;statistical Moments of the Temporal Spectrum of Electromagnetic Waves in the Equatorial Ionosphere;Towards Facilitating URLLC in UAV-enabled MEC Systems for 6G networks;resource Allocation and Power Control for Heterogeneous Cellular network and D2D Communications;optimized network Coding with Real-Time Loss Prediction for Hybrid 5G networks;TCP-RTA: Real-time Topology Adaptive Congestion Control Strategy in TCP;Rio_DSA: Redirecting I/O Scheme for Dynamic Storage Allocation on Docker Container.

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