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Predicting Monthly Household Water Consumption

Predicting Monthly Household Water Consumption

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IEEE international conference on Research, Innovation and Vision for the Future

作者： Minh Thanh Vo Duong Vu Ham Nguyen Huong Bui Tuong Le Faculty of Information Technology HUTECH University Ho Chi Minh City Vietnam University of Information Technology Vietnam National University HCMC Ho Chi Minh City Vietnam Department of Information Technology FPT University Ho Chi Minh City Vietnam Laboratory for Artificial Intelligence Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Vietnam

ISBN: (纸本)9781665461672

The monthly household water consumption prediction is an interesting and practical problem in predicting the volume of water use of a residential area. Therefore, this study develops a hybrid approach between a Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory networks (Bi-LSTM) named CBLSTM model for predicting the monthly household water consumption. The experiments are conducted on a dataset collected in Can Tho city, Vietnam in three years from 2018 to 2020 (named by MWC-CT dataset). We compared the proposed model with the two state-of-the-art models for time series prediction which are the LSTM and Stacked LSTM models. Evaluation of experimental results on the MWC-CT dataset indicates that CBLSTM performs better than the comparative models.

关键词： Computational modeling Urban areas Time series analysis Predictive models data models Communications technology Convolutional neural networks

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The Integration of Connectivity and System Integrity Approaches using Internet of Things (IoT) for Enhancing Network Security

The Integration of Connectivity and System Integrity Approac...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Shashidhar Sonnad Manoj Sathe D. Khalandar Basha Vipul Bansal Rajesh Singh Devesh Pratap Singh Department of Electronics & Communication Engineering Sharnbasva University Kalaburagi Karnataka India PES Modern Institute of Business Studies Pune Maharashtra India Department of ECE Institute of Aeronautical Engineering Dundigal Hyderabad India Department of Information Technology Kurukshetra University Haryana India Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

Machine learning, this same Internet of Things, and other emerging digital technologies aid in improving military uses and aid management in efficiently gathering, analysing, manipulating, and storing enormous volumes of data. Additionally, these technologies help with the storage of information that may be recovered later. However, this poses a serious risk to the organization’s ability to protect the data that is needed to properly increase the network security. It has been stated that IoT may help safeguard the organisation from various cyber-hacks, necessitating the use of various ways to raise security levels. Additionally, the expanded use of IoT improves cooperation and integration across diverse systems and processes in commercial *** order to improve network security, this research is primarily concerned with identifying the critical factors that relate here to integration of connections and system integrity techniques. The scholars used both inferential and descriptive statistics to conduct the study, and it has been further recognised that all the IoT causal factors support strengthening network level of security. The paper is classified in outlining the crucial aspect on which the entity needs to concentrate when using IoT to enhance security by protecting the data.

关键词： Productivity Knowledge engineering Technological innovation Target tracking Sensitivity Machine learning Network security

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Monitoring and Forecasting Water Environment Parameters for Smart Aquaculture Using LSTM

Monitoring and Forecasting Water Environment Parameters for ...

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IEEE international conference on Research, Innovation and Vision for the Future

作者： Phat Nguyen Huu Dinh Dang Dang Minh Nguyen Khai Hieu Nguyen Trong Pha Pham Ngoc Quang Tran Minh Hanoi University of Science and Technology Hanoi Vietnam Salisbury School Connecticut United States National Institute of Patent and Technology Exploitation (NIPTECH) Hanoi Vietnam HoChiMinh City University of Technology HoChiMinh Vietnam Vietnam National University HoChiMinh City HoChiMinh Vietnam

ISBN: (纸本)9781665461672

The goal of the paper is to develop a system capable of automatically updating the parameters of the water environment periodically on the website and providing forecasts of water parameters for users. The system is simple to use and can be applied in many places. It has been partially built, including measuring parameters (pH, temperature, salinity, dissolved oxy-gen concentration (DO)), displaying, storing locally, and sending data to the website. This paper focuses on the analysis and design of sensor signal processing circuits and builds an algorithm to predict water parameters using long short-term memory (LSTM) model. The experiment results show that the circuit has worked to meet the requirements and the environmental parameters have been measured with 90% accuracy. This result shows that the system is feasible when applied in practice.

关键词： Temperature measurement Signal processing algorithms Prediction algorithms Stability analysis Time measurement Circuit stability Forecasting

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Design and Implementation of Low-Cost Smart Contactless Thermometer with Polynomial Regression Model

Design and Implementation of Low-Cost Smart Contactless Ther...

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Smart and Sustainable technologies in Energy and Power Sectors (SSTEPS), international conference on

作者： M Naresh Ajitha G Samineni Peddakrishna Prashanth Kumar Avtar Singh School of Electronics Engineering VIT-AP University Amaravati India Department of Electronics and Communication Engineering Institute of Aeronautical Engineering Hyderabad India School of Electronics Engineering Vellore Institute of Technology Chennai India School of Electrical Engineering & Computing Adama Science and Technology University Adama Ethiopia

Body temperature is an important measure of a person's health. It is used to diagnose a variety of disorders. Core temperature measurement takes some time and puts patients under strain. To measure temperature in real-time and without contact. We proposed a contactless thermometer that can be calibrated by deriving the ambient and body temperatures from thermometer readings. We analyze this accuracy using second-order polynomial linear regression. After getting the actual body temperature of 124 subjects, we achieved 99% prediction temperature accuracy and linearity with gold standard reference temperature sensors. Additionally, the application has been developed to save the readings. This application can be connected through either OTG or Bluetooth depending on the user's preference. They will have the option to save multiple people's temperature data in separate excel sheets. Following that, the user can access the data and share the link to the data using any of the shareable platforms.

关键词： Temperature measurement Temperature distribution Thermometers Bluetooth Linear regression Linearity Real-time systems

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Teaching and Learning Concepts of Audio Modulation Using Tangible User Interfaces 5th

Teaching and Learning Concepts of Audio Modulation Using Tan...

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5th international conference on Advanced computing and Intelligent Engineering, ICACIE 2020

作者： Wong Suk Hee, Ah-Kwet Rémi Halfani, Hadija Ramadhani Bekaroo, Girish School of Science and Technology Middlesex University Mauritius Flic en Flac Mauritius

ISBN: (纸本)9789813342989

Digital technologies form an integral part of sound production. To meet industry requirements, audio processing and modulation are taught in computer science-related courses within modules such as multimedia, data communications and science, technology, engineering, and mathematics (STEM). However, due to the complexity of the subject, teaching and learning audio modulation within traditional settings involves challenges, thereby adversely impacting student engagement. The use of tangible user interfaces (TUI) can potentially improve student experience during teaching and learning, although this type of user interface has not been much explored in the area of sound processing and modulation. As such, this paper investigates the application of a novel TUI-based system to assist in teaching and learning concepts of audio modulation. Using an TUI evaluation framework, the proposed solution was evaluated in order to assess five key constructs, notably learnability, interaction, tangibility, enjoyment, and intention for future use. During the evaluation process, 29 students practically utilized the solution and provided feedback on the constructs assessed. Results revealed an inclination towards agreement for the different constructs investigated, although some limitations were identified. Based on these limitations, recommendations are provided towards improving design of such systems. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Modulation

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E-Voting System Using Blockchain Technology

E-Voting System Using Blockchain Technology

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Nagesh H R Guru Prasad M S Shivaraj B G Dhawal Jain Puneeth B R M Anadkumar Dept. of Computer Science & Engg. Sahyadri College of Engg. & Management Mangaluru India Dept. of Computer Science & Engg. Graphic Era (Deemed to be University) Dehradun India Dept. of Computer Science & Engg. Mangalore Institute of Technology & Engg. Moodabidri India Dept. of Computer Science & Engg. SDM Institute of Technology Ujire India Department of MCA Nitte NMAM Institute of Technology (NMAMIT) Nitte (Deemed to be University) Karnataka India Dept. of Computer Applications Graphic Era (Deemed to be University) Dehradun India

In every nation, democratic elections are a momentous and weighty occurrence, and the voting system that is now in place requires the use of ballots or electronic voting machines (EVM). Transparency, poor turnout, vote manipulation, distrust of electoral organizations, fabrication of unique IDs (voting party IDs), and delays in posting results are some of the issues that arise as a result of these procedures. The matter of safety is of the utmost importance. When considering the installation of a computerized voting system, voter confidentiality has always been one of the most important concerns. There is no question regarding the system's capability to secure itself in contrast to prospective assaults and safeguard data in the face of such big choices. Utilization of blockchain technology is one approach that might be taken to resolve security concerns. The blockchain technology has an endless number of different uses that might be implemented. The technology known as blockchain is a distributed ledger that makes it possible for peer-to-peer networks all over the world to handle digital assets. In this context, distributed ledger technology represents an intriguing development. A grouping of all transactions is referred to as a block. Immutability, decentralisation, security, transparency, and anonymity are some of the outstanding properties offered by blockchain technology. The combination of blockchain technology with smart contracts has shown promise as a viable option for the development of trustworthy and open-source electronic voting systems. In this article, we demonstrate how to use blockchain technology with the help of a wallet and the Solidity programming language to build an electronic voting application. The programme was designed as a smart contract for the Ethereum network. In order to avoid having the same person vote twice, the user's wallet will only hold a certain number of tokens (gas), which will be depleted each time the user casts a vote. Thi

关键词： Fabrication Distributed ledger Smart contracts Organizations Blockchains Safety Peer-to-peer computing

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Cluster-based under-sampling using farthest neighbour technique for imbalanced datasets 10th

Cluster-based under-sampling using farthest neighbour techni...

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10th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2019 and 9th World Congress on Information and Communication technologies, WICT 2019

作者： Rekha, G. Tyagi, Amit Kumar Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Hyderabad India School of Computing Science and Engineering Vellore Institute of Technology Chennai Campus ChennaiTamilnadu600127 India

ISBN: (纸本)9783030493387

In domain of data mining, learning from imbalanced class distribution datasets is a challenging problem for conventional classifiers. The class imbalance exists when the number of samples of one class is much lesser than the ones of the other classes. In real-world classification problems, data samples often have unequal class distribution. This problem is represented as a class imbalance problem. However, many solutions have been proposed in the literature to improve classifier performance. But recent works entitlement that imbalanced dataset is not a problem in itself. The degradation of classifier performance is also linked with many factors like small sample size, sample overlapping, class disjunct and many more. In this work, we proposed cluster-based under-sampling based on farthest neighbors. The majority class samples are selected based on the average distance to all minority class samples in the cluster are farthest. The experimental results show that our cluster-based under-sampling approach outperform with existing techniques in the previous studies. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Classification (of information)

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Reinforcement Learning Based Scheme for On-Demand Vehicular Fog Formation and Micro Services Placement

Reinforcement Learning Based Scheme for On-Demand Vehicular ...

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international Wireless Communications and Mobile computing conference, IWCMC

作者： Ahmad Nsouli Azzam Mourad Wassim El-Hajj Department of Computer Science American University of Beirut Lebanon Division of Science New York University Abu Dhabi UAE Department of Computer Science Lebanese American University Lebanon

The high need of real-time vehicular applications for self-driving cars to maintain service availability and reachability, and to process huge amount of generated data within a small amount of time, rise the need to improve the vehicular network infrastructure. Fog computing has been introduced to reduce the amount of data sent to cloud by bringing processing power near the edge and reducing latency. In this paper, we overcome the aforementioned limitations by taking advantage of the evolvement of On-Board Units, Reinforcement Learning, Kubeadm Clustering, Docker Containerization, Istio service mesh, and micro-services technologies. We propose in our scheme (1) a service mesh architecture that manages communication between multiple micro services across different clusters and tackle inter-service communication, (2) a Reinforcement Learning model deployed on RSUs to predict on-demand placement of microservices. Experiments and simulations show that our method is more efficient in deploying microservices using the reinforcement learning model than other current strategies in the literature. Given that only needed microservices are deployed in limited resource cluster, mesh network shows an improvement in the deployment time and inter-service communication across clusters.

关键词： Wireless communication Mesh networks Image edge detection Microservice architectures Intrusion detection Reinforcement learning Predictive models

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Development of Low-Cost Surgical Simulator for Neuroendoscopy using Unity3D and HTC VIVE

Development of Low-Cost Surgical Simulator for Neuroendoscop...

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international conference on Open Source Systems and technologies (ICOSST)

作者： Aimen Fatima Faisal Bukhari Waheed Iqbal Department of Computer Science Faculty of Computing and Information Technology University of the Punjab Lahore Pakistan Department of Data Science Faculty of Computing and Information Technology University of the Punjab Lahore Pakistan

ISBN: (纸本)9781665464789

Neuroendoscopy is being utilized more frequently to treat brain tumors and hydrocephalus brought on by tumors. Neuroendoscopy is a minimally invasive operation that requires a lot of skills. Complete training is needed in hospitals to perform this procedure in the operating room. Simulators are necessary to train doctors due to the deficiency of time, resources, cost, and potential risks. With advancements in computer technology, it is becoming more common to simulate and plan surgery using a VR-based simulation. We have created and developed a surgical simulator to provide endoscopic training for the ETV procedure. A method to use multimedia capabilities for learning is to create a virtual 3D simulator using a game engine and render it using VR technology. The user-friendly collaborative environment of the Unity3D game engine offers good features. We have demonstrated how a simplex mesh depiction in a game-based simulator may effectively deform a soft body in actuality. We have successfully developed a method employing Position Based Dynamics to simulate the actual deformation of TM the cancerous brain. According to our study, the HTC Vive is a suitable VR technology for ETV training because it offers excellent precision, quick tactile feedback, a fast frame rate, and a wide field of vision. In the future, this practical tool might replace more costly training simulators.

关键词： Training Three-dimensional displays Minimally invasive surgery Tactile sensors Games Real-time systems Engines

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Analysis on Fake News Detection with Novel Bert Algorithm and Random Forest

Analysis on Fake News Detection with Novel Bert Algorithm an...

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Advanced technologies in Intelligent Control, Environment, computing & Communication Engineering (ICATIECE), international conference on

作者： Heena Khera Sanjai Kumar Srivastava Department of Computer Science and Engineering Galgotias University Greater Noida India Department of Media Studies Jaipur National University Jaipur India

ISBN: (纸本)9781665493970

As opposed to random forest algorithms, the objective of this study is to increment expectation rate involving a clever model of bidirectional encoder portrayals for transformers (BERT). The viability of Novel BERT and Random Forests are stood out utilizing a dataset from a size of 1100. A structure for recognizing fake news in electronic media networks is advanced utilizing Random Forest. The structure decides an example size of 20 for clinical. The Clever Bert algorithm beats Random Forest as far as Precision rate by 8.33%. BERT accomplishes a pace of 0.002, which is fundamentally higher than the random forest algorithm. In this review, it was found that the clever BERT algorithm performed greater at anticipating fake news than Random Forest. With a novel bidirectional encoder portrayal for transformers (BERT) model rather than the random forest algorithm, this study looks to expand the expectation rate. The viability of Novel BERT and Random Forests are stood out utilizing a dataset from a size of 1100. A structure for distinguishing fake news in electronic media networks is advanced utilizing Random Forest. The structure decides an example size of 20 for clinical. The Clever Bert algorithm beats the Random Forest algorithm as far as Precision rate by 8.33%. BERT accomplishes a pace of 0.002, which is fundamentally higher than the random forest algorithm. The consequence of this study is that the clever BERT algorithm performs better compared to Random Forest anticipating of fake data.

关键词： Social networking (online) Face recognition Bit error rate Entertainment industry Channel estimation Forestry Transformers

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