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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Mareeswari V Vijayan R Ashish Shukla Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Department of Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Master of Computer Applications School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Bluetooth technology, which facilitates wireless communication between Billions of devices including smartphones, tablets, laptops, and Internet of Thing (IoT) devices, is a cornerstone of modern connectivity. Its importance lies in its ability to enable seamless data exchange and interaction across a wide range of applications, from personal gadgets to complex industrial systems. Despite its widespread adoption, Bluetooth is not immune to critical security vulnerabilities. Issues like Bluetooth Low Energy (BLE) vulnerabilities and denial-of-service (DoS) attacks can overwhelm devices with excessive traffic, while BLE Forced Connection can lead to unauthorized access, and eavesdropping exposes sensitive data being exchanged. We have discussed these vulnerabilities in detail, examining their mechanisms, potential impacts, and various implementation aspects. Additionally, we have added demonstrations to illustrate how these attacks can be executed and the potential consequences. To prevent these threats, we explored essential measures, including regular firmware updates, secure pairing protocols, and careful management of Bluetooth settings. Adopting best practices like disabling Bluetooth when not in use and monitoring connected devices can further enhance security, ensuring the reliable and safe operation of the vast and growing ecosystem of Bluetooth-enabled devices.

关键词： Wireless communication Ethics Protocols Ecosystems Denial-of-service attack Security Internet of Things Bluetooth Low Energy Microprogramming Guidelines

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Aspect-Based Sentiment Analysis on Amharic Text for Evaluating Ethio-Telecom Services 2

Aspect-Based Sentiment Analysis on Amharic Text for Evaluati...

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2nd International Conference on Emerging Trends in information Technology and engineering, ic-ETITE 2024

作者： Tesfa, Tarikwa Belete, Befikadu Abera, Samuel Mohapatra, Sudhir Kumar Das, Tapan Kumar Addis Ababa Science and Technology University Department of Software Engineering Addis Ababa Ethiopia Ethio Telecom Services Addis Ababa Ethiopia Sri Sri University Faculty of Emerging Technologies Cuttack India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

People are increasingly expressing their views and opinions about a company's goods or service on social media these days. For all types of businesses and organizations, sentiment analysis in text can be used to find prospective customers and obtain quick feedback on the services or goods they provided. As a result, the organization has a better chance and opportunity to meet the needs of the consumer. Using sentiment analysis, we may extract important information from the thoughts and emotions of an organization's supporters and clients. It examines natural language content produced about services and goods. Detailed opinion mining at the aspect/feature level to serve consumer and organizational needs. In this study, three different machine learning algorithms, these are Naïve Bayes (NB), Support Vector Machine (SVM), and K- Nearest Neighbor (KNN) are used to build the proposed aspect-based sentiment analysis model from the customer comments in Amharic text which is collected from Ethio-telecom official Facebook page. The collected data is annotated into sentiment polarity and aspect-based sentiment classes by the help of five annotators. After data annotation, different preprocessing tasks were implemented. Bag of words and TF-IDF word representation techniques were used to represent each unique word to their vector representation. The experiment was conducted on those three models and the result was validated. The labeled aspects were not balanced so that a SMOTE class imbalance handling technique was employed to the dataset. Finally, SVM model trained with TF-IDF word representation technique with SMOTE oversampled dataset has achieved the highest accuracy result of 98% as compared to NB and KNN. © 2024 IEEE.

关键词： Sentiment analysis

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Analysis the Research Hotspots and Key Technical of Intelligent Manufacturing 22

Analysis the Research Hotspots and Key Technical of Intellig...

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4th International Conference on Management science and Industrial engineering, MSIE 2022

作者： Cai, Yu Wu, Jiahao Zaheer, Muhammad Department of Computer Software Engineering Institute of Guangzhou Guangzhou51098 China College of Computer Information and Engineering Nanchang Institute of Technology Nanchang330044 China Southern University of Science and Technology Shenzhen518000 China

ISBN: (纸本)9781450395816

Intelligent manufacturing is one of the keys to open up the future of life, and multidisciplinary interactions have shown its strong vitality. This study conducts a scientometric review of the global research published since 1987 on intelligent manufacturing, through citation, keyword, clustering and keywords burst analysis. A total of 3994 research documents are taken as data sources, which are retrieved from the Web of science Core Collection database from 1987 to 2021. Using the CiteSpace analysis tool, this paper discussed the development process of the relevant years of intelligent manufacturing, analyzed the research hotspots and their technology, presented the emerging models and techniques, and identified the latest research evolution and trends. The results will provide reference for scientific scholars in future research in the field of intelligent manufacturing. © 2022 ACM.

关键词： Industrial research

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Train a Robot to Climb Staircase Using Vision-Base System 10

Train a Robot to Climb Staircase Using Vision-Base System

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10th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2022

作者： Jayawardana, J.T.H. Dilshan, H.V.V. Wijethilaka, R.G.K.H Balasooriya, T.D. Rajapaksha, U.U.S. Harshanath, S.M.B. Jayawardena, Chandimal Sri Lanka Institute of Information Technology Dept. Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. Information Technology Malabe Sri Lanka

ISBN: (数字)9781665401562

ISBN: (纸本)9781665401562

Currently, robots are used for different types of work, such as the manufacturing industry, healthcare, and the hotel industry. According to the current epidemic situation, the usage of robots was increased because of the need to reduce human interaction. As a result, they have to walk around the workplace, because of that, they may have to climb staircases. The world has many types of robots. Here the selected robot is a humanoid. This proposal is concerned with how to detect the staircase, count steps, get dimensions of it, and move the robot on it by keeping body balance. First, want to know what the objects are, then walk. The identified images from the image sensors will get as input. The technology stack that is used for image analysis is a method related to computer vision in deep learning. Other than that, while climbing the stairs robot needs to identify whether the staircase is over or not. Here we introduce a new concept: get the number of steps required to climb before climbing the stairs. It is related to how humans identify things by seeing and making decisions. The need to take the dimensions of the stairs is that when considering the stairs, they have their height, width, and range. Therefore, it is imperative to calculate the dimensions of each staircase separately. Creating a balance system similar to human balance is a great advantage in robotics. To implement such a system, there is an upright pose controller to allow the robot to walk stably by preventing tilting of the robot during walking on uneven floor. In general, for us to do that we need to calculate the global inclination of the floor is a key factor. It can be measured with a 2-axis accelerator meter, and it is installed in the inertial sensor. © 2022 IEEE.

关键词： Stairs

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Cocopal - A Deep Learning Based Intelligent System to Certify and Standardize the Quality of Coconut Based Products 4

Cocopal - A Deep Learning Based Intelligent System to Certif...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Gunawardana, K.H.R. Hemachandra, M.G.S.P. Hettiarachchi, N.M. Deshan, M.P.N. Ganegoda, Devanshi Weerasinghe, Lokesha Dept. of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Dept. of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

The procedure of certifying and standardizing the quality of the coconut-based products is done manually in Sri Lanka at precent. It is a time consuming and labor- intensive task and is conducted by experts. In most cases, the quality is decided solely by visual inspections by buyers and suppliers, with no scientific basis. The paper reports the capacity of bringing modern technology solutions such as Artificial Intelligence (AI), Machine Learning (ML), Image Processing (IP), and decentralized storage to aid in the certification and standardization of the quality of raw *** showed that the accuracy of the proposed system is in the 86% to 90% range and showed that this technique could beimproved and used as an alternative to manual techniques. © 2022 IEEE.

关键词： Deep learning

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A Comprehensive Approach to Identify Stroke based on Real-time Medical Data 1

A Comprehensive Approach to Identify Stroke based on Real-ti...

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1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Maragatharajan, M. Shanmugapriya, S. Sudhan, M.B. Deeptha, R. Paramasivam, Sankar Muthu Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh Kothrikalan India Kalasalingam Academy of Research and Education School of Computing Department of Computer Science and Engineering Tamilnadu Srivilliputhur India Srm Institute of Science and Technology Department of Computer Science and Engineering RamapuramTamilnadu Chennai India Srm Institute of Science and Technology Department of Information Technology RamapuramTamilnadu Chennai India Palo Alto Networks Inc Distinguished Software Engineer 3000 Tannery Way Santa ClaraCA United States

ISBN: (纸本)9798350372748

Strokes or cardiovascular disorders continue to be a major global health concern. Proactive intervention and timely detection greatly reduce the morbidity and death related to strokes. The goal of this research is to build a prediction model using machine learning techniques to assess a person's risk of stroke based on a variety of sociodemographic and health characteristics. The dataset used in this study consists of a large collection of medical records. It contains important details including age, gender, BMI, smoking habits, heart disease, hypertension, and the type of residential property. Using this information, a Decision Tree Classifier is trained to predict the likelihood of strokes, enabling early detection and customized treatment plans. A Decision Tree Classifier with a predetermined maximum depth is used in the proposed methodology's rigorous data preprocessing, which includes handling missing values, encoding categorical features, and developing models. Both the training and testing datasets are used to evaluate the model's performance using evaluation measures including accuracy, precision, and recall. The model's insights provide important characteristics that influence the prediction of stroke risk, assisting medical professionals in focused risk assessment and preventive intervention. The proposed method has the potential to improve healthcare practices by facilitating prompt interventions and personalized treatment for stroke risk individuals. The proposed model has resulted in 86.78% accuracy for this dataset by using the traditional machine learning algorithms. This work highlights the value of predictive modelling in the healthcare industry by demonstrating how it may improve early detection techniques and lessen the impact of strokes on public health. © 2024 IEEE.

关键词： Forecasting

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TRIPORA: Intelligent Machine Learning Solution for Sri Lanka Touring Access and Updates 4

TRIPORA: Intelligent Machine Learning Solution for Sri Lanka...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Legrand, T.R. Bandara, K.M.R.A.I. Stefania Crishani, J.A.D. Uvindu, L.W.P. Amarasena, Nelum Kasthurirathna, Dharshana Department of Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Sri Lanka is one of the top tourist destinations in the world. However, tourists face various inconveniences due to the obsolescence of facilities. There are various tools designed to solve such problems. But they are scattered in different places and users have to use different tools. The biggest issue in the tourist sector is that travelers are unable to get the most out of their tours since there may be days when a large number of people visit the same location, causing the location to become overcrowded, and preventing tourists from enjoying their visit as anticipated. There are seasons when natural disasters occur, as well as human-centered crises. Also, there are situations when travelers feel helpless because they are unable to find the best tour guide for them. We developed a cost-effective, automatic, and efficient Machine Learning-based recommendation system as a result of this research. Based on past data on tourists and data received from the SLTDA, this research can provide the best trip plan with the tour guide and provide destination news alerts on regular basis. Furthermore, in order to achieve the best accuracy through the system, unique machine learning approaches were used in this study. © 2022 IEEE.

关键词： Obsolescence

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Exact Quantum Sensing Limits for Bosonic Dephasing Channels

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PRX Quantum 2024年第2期5卷 020354-020354页

作者： Zixin Huang Ludovico Lami Mark M. Wilde School of Mathematical and Physical Sciences Centre for Quantum Software and Information Faculty of Engineering and Information Technology Science Park 123 Amsterdam 1098 XG the Netherlands Korteweg–de Vries Institute for Mathematics Institute for Theoretical Physics School of Electrical and Computer Engineering

Dephasing is a prominent noise mechanism that afflicts quantum information carriers, and it is one of the main challenges toward realizing useful quantum computation, communication, and sensing. Here, we consider discrimination and estimation of bosonic dephasing channels, when using the most general adaptive strategies allowed by quantum mechanics. We reduce these difficult quantum problems to simple classical ones based on the probability densities defining the bosonic dephasing channels. By doing so, we rigorously establish the optimal performance of various distinguishability and estimation tasks and construct explicit strategies to achieve this performance. To the best of our knowledge, this is the first example of a non-Gaussian bosonic channel for which there are exact solutions for these tasks.

关键词： Non-gaussian quantum states Quantum channels Quantum fluctuations & noise Quantum information theory Quantum parameter estimation Quantum sensing

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Task and Process Capturing Toolkit using GUI Automation 4

Task and Process Capturing Toolkit using GUI Automation

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4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Perera, Ravindu Lakshan Bellanthudawa, Hiruni Piyumika Hevavitharana, Nipun Dimantha Ariyasinghe, Kavindu Malshan Wickramarathne, Jagath Perera, Jeewaka Sri Lanka Institute of Information Technology Dept.Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665468350

Automation is one of the best ways to make easier everyone's day-to-day life. When considering the industry, if someone could be able to automate the mechanism of solving computer software issues, that will be helpful to every company. Because most companies are facing difficulties when it comes to giving IT support. Some companies are suffering from a lack of IT supporters because they have to solve the same problem on different computers at the same time. This most likely reduces the efficiency of the company and affects its performance as well. Without the proper knowledge of technology, employees tend to get a lot of technical issues while working with the technology. Here comes the opportunity to automate the IT-related problem-solving mechanism. That will save a lot of time and increase the company's efficiency as well. While carrying out the background research we thought, by automating the IT-related problem it will reduce the allocation of human power and that will directly affect company efficiency. The research team came up with the idea of creating a software product that can export an executable file by capturing selected tasks of the user's screen and its' relevant processes. Task and process capturing toolkit is a software product called the 'ClickMe toolkit'. It can capture relevant processes that are happening in any computer which runs on Windows 10 platform, then make a script called 'ClickMe script', and convert it into an executable file. It can be run on any Windows 10 Platform. © 2022 IEEE.

关键词： Graphical user interfaces

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Mobile and Simulation-based Approach to reduce the Dyslexia with children Learning Disabilities 10

Mobile and Simulation-based Approach to reduce the Dyslexia ...

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10th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2022

作者： Muthumal, S.A.D.M. Neranga, K.T. Harshanath, S.M.B. Sandeepa, V.D.R.P. Lihinikaduwa, D.N.R. Rajapaksha, U.U.S.K. Sri Lanka Institute of Information Technology Department of Information System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (数字)9781665401562

ISBN: (纸本)9781665401562

Learning disabilties are frequently overlooked while treating various limitations. The primary causes for such a dropout might be a lack of awareness of the risks and access to adequate medical care. Because Learning Disabilities are neurological illnesses, their etiology is unknown. Learning Disabilities do not have a therapy or a cure. Dyslexia, Dysgraphia and Dyscalculia are the most common types of Learning Dis-abilities among school children. There are numerous approaches for diagnosing and treating this ailment available today. The optimal method is to make use of a mobile application. Existing applications either do not adequately handle the problem or have minor limitations in terms of meeting genuine expectations. We can mitigate this dysfunction by utilizing mobile and simulation-based technologies. Furthermore, earlier research has not given contact and curiosity among children a significant emphasis and children have not interacted with robots. Therefore, this paper, introduces interactive and collaborative mobile appli-cation called 'Helply' with a robotic based simulation that may foster learning and help children improve and encour-age Color identification skills, Reading skills and Short-term memory skills the learning process while reducing their other dyslexic disorders. Also, NAO Robot is used to taking inputs as voice clip using voice recognition technology and images using image processing technology which embedded in NAO robot. We constructed three models for three distinct disorders and obtained accurate findings. CNN model for colour disorder had a training accuracy of 93%, FFNN model for short-term memory disorder had a training accuracy of 98%, and CNN model for reading disorder had a training accuracy of 94%. © 2022 IEEE.

关键词： Diagnosis

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