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Designer Face Mask Detection Using Marker-Based Watershed Transform and YOLOv2 CNN Model

Designer Face Mask Detection Using Marker-Based Watershed Tr...

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Vyas, Arpita Sharma, Jankiballabh Rajasthan Tech Univ Dept Elect Engn Kota India

ISBN: (纸本)9789819984787;9789819984794

Face mask detection using artificial intelligence (AI) has become more challenging due to high variability in modern designer masks such as single color, multicolor, textile, and printed. This paper presents a designer face mask detection using marker-controlled watershed transform and YOLOv2 CNN model. In the first stage, the face images are preprocessed and segmented using marker-controlled watershed transform by setting mask color as foreground and face color as background marker. The segmented image is applied to the YOLOv2 CNN model for the detection of the face mask. Marker-controlled watershed transform is employed for segmentation and highlights the multicolor mask texture, to improve the classification efficiency of the YOLOv2 CNN model. Simulation performed using different types of designer masks gives an accuracy of 86.66% and an F1-score of about 0.91, which verifies the efficiency of the proposed scheme. The technique deployed in this paper can be used to develop automated systems for face mask detection, classification, and alarm systems.

关键词： Face mask detection YOLOv2 Watershed segmentation

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A Hybrid CNN-LSTM Approach for Sentiment Analysis 4th

A Hybrid CNN-LSTM Approach for Sentiment Analysis

引用

4th Congress on Intelligent systems (CIS)

作者： Ramirez-Alcocer, Ulises Manuel Tello-Leal, Edgar Hernandez-Resendiz, Jaciel David Romero, Gerardo Autonomous Univ Tamaulipas Multidisciplinary Acad Unit Reynosa Rodhe Reynosa 88779 Mexico Autonomous Univ Tamaulipas Fac Sci & Engn Victoria 87000 Mexico

ISBN: (纸本)9789819990399;9789819990405

The significant growth of microblogging in social media has caused companies, media outlets, and analysts to look for efficient methods to extract information about people's perceptions of their products and services. In this article, we propose a deep learning-based approach using a hybrid model that combines a convolutional neural network (CNN) and long short-term memory (LSTM) network to classify people's sentiments on a particular topic. Two datasets are used in the experimentation, the first with two polarities (positive or negative) and the second with three polarities (positive, neutral, or negative). The results of the CNN-LSTM hybrid model in the training and testing stages are acceptable. We calculate several parameters to measure the model's performance, such as accuracy, precision, recall, F1-score, and the area under the ROC curve. The classification results show that the proposed model exceeds 84 and 81% accuracy in the sentiment analysis for each dataset.

关键词： Sentiment analysis CNN LSTM Deep learning

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Comparison of Software, Programming Language and Framework for System Development in Institute of Higher Learning 13th

Comparison of Software, Programming Language and Framework f...

引用

13th Computer Science Online Conference

作者： Abd Rauf, Muhammad Fairuz Amran, Mohd Fahmi Mohamad Hassan, Wan Azlan Wan Adnan, Zuraidy Osman, Azilayati Wong, Rita Natl Def Univ Malaysia Fac Def Sci & Technol Kuala Lumpur 57000 Malaysia Univ Selangor Bestari Jaya 45600 Malaysia Natl Def Univ Malaysia Language Ctr Kuala Lumpur 57000 Malaysia

ISBN: (纸本)9783031702846;9783031702853

Software or programming language is one of the most crucial aspects in system development, especially in education institutions. Various software need to be considered from each angle, which includes pricing, after sales service, ease of integration and learnability. Model-View-Controller (VC) based software or programming language such as Laravel PHP is being considered since it is widely used by software house. Another software that is considered is Microsoft PowerApps because of its low code approach in system development. Finally, an application development framework that is considered is Corrad. Corrad is a local-based framework that has its own library which can reduce development time. After comparison have been conducted, Laravel PHPhave been chosen as the most suitable development framework. Some of the contributing factors include pricing, integration with existing platform and learnability.

关键词： System Development Application for Development Programming Language

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Away from Theory: A Cloud Storage Application with Public Key Searchable Encryption Feature 9th

Away from Theory: A Cloud Storage Application with Public Ke...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Senouci, Mohammed Raouf Senouci, Abdelkader Li, Fagen Busawon, Kumar K. Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 611731 Peoples R China Northumbria Univ Fac Engn & Environm Newcastle England Univ Mascareignes Fac Sustainable Dev & Engn Concorde Ave Roches Brunes Rose Hill Mauritius

ISBN: (纸本)9789819732883;9789819732890

Navigating the complex realm of secure cloud storage, our application offers a uniquely robust and user-friendly data storage solution, adeptly bridging AES-256 encryption and public key searchable encryption to safeguard user data while maintaining accessible retrieval. Specifically, the Searchable Encryption sub-module leverages the unaltered scheme proposed by Senouci et al. In J Syst Archit 119:102271 [1], foundational in enabling secure, efficient data searchability without necessitating decryption. Furthermore, detailed access control and comprehensive audit logging empower users with precise control and transparent oversight of their stored data, enhancing data security and user trust. With an architecture that synergizes stringent security protocols and user-centric design, the application presents a paradigm shift in secure cloud storage, achieving a harmonious balance between impenetrable data security and user accessibility, thereby setting a new benchmark in secure data storage and retrieval in cloud environments.

关键词： Searchable encryption Cloud computing Data outsourcing Sequence diagram Flowchart diagram Privacy

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Anomaly Prediction in Real-Time Water Flow Data-Machine Learning Versus Statistical Models 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Anand, V. Simha, J. B. Agarwal, Rashmi REVA Univ RACE Bangalore Karnataka India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

Industries are at the vanguard of the looming catastrophe in a time of growing worries about resource depletion and water scarcity. Additionally, the enormous financial outlays needed to secure water sources and treatment methods highlight the underlying cost of water. Industries must optimize their water consumption to reduce this mounting financial burden and the negative environmental effects of excessive water use. This study is highly significant since it takes a novel technique to predict anomalies in industrial water use. This research paper focuses on a thorough comparative study to assess two popular approaches for anomaly prediction in real-time water flow data: statistical models and machine learning models. This research makes use of dynamic machine learning models as opposed to conventional techniques, which concentrate on establishing a single static threshold value. These models adjust to the constantly shifting circumstances in industrial operations. Water usage can vary significantly in dynamic industrial activities, such as those in the Food and Beverage (F&B) sector, depending on output levels, seasonal conditions, or even unplanned equipment failures. As a result, choosing a single threshold number is frequently insufficient since it ignores the subtle patterns and trends in the data. The dataset being looked at comes from an electromagnetic water flow meter that has an Internet of Things (IoT) device attached, allowing for easy data transmission to the cloud. With the help of a high-quality dataset, effectiveness of several models is investigated, including the well-known statistical approaches with Weighted Moving Average (WMA), Simple Moving Average (SMA), Exponential Weighted Moving Average (EWMA), Auto-Regressive Integrated Moving Average (ARIMA), that are known for their skill in identifying time-series anomalies. Parallel to this, we make use of machine learning models like K-Nearest Neighbors (KNNs), Isolation Forest (IF), Support Vector

关键词： Anomaly prediction Real-time data Statistical models Machine learning models IoT

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Model-Free Adaptive Fault-Tolerant Control for Offshore Wind Turbines 1

引用

Computing Conference

作者： Lam, Yat Ping Simani, Silvio Univ Ferrara Dept Engn Ferrara Italy Shibaura Inst Technol Toyosu Campus Koto Tokyo 1358548 Japan

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

Floating offshore wind turbines have increased in popularity owing to their adaptability for deep water applications and high power generation efficiency. The control of floating offshore wind turbines, on the other hand, is very complex. The main challenges are the difficulty in precisely modeling floating offshore wind turbines and the higher failure rate of components. As a consequence, this study proposes a model-free adaptive fault-tolerant control system for blade root moment sensor failures. A model-free adaptive control approach is used to construct an individual pitch controller and a fault compensation to avoid mathematical modeling of floating offshore wind turbines. The proposed fault-tolerant control technique removes the need for fault detection and isolation by converting the fault dynamic compensation process into a real-time control issue for nonlinear systems. The fatigue, aerodynamics, structures, and turbulence code simulates and tests the proposed control strategy, and the results show that the proposed strategy can not only keep the wheel bearing load balanced, but also reduce the movement of the floating platform and significantly reduce the bearing load of the floating offshore wind turbines. Furthermore, the output power is closer to the rated power, proving the strategy's high fault tolerance in the face of repeated blade root moment sensor faults.

关键词： Floating offshore wind turbines Individual pitch control Fault-tolerant control Model-free adaptive control Blade root moment sensor fault

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A Research-Led Contribution of Engineering Education for a Sustainable Future 21st

A Research-Led Contribution of Engineering Education for a S...

引用

21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Block, Brit-Maren Guerne, Marie Gillian Leuphana Univ Univ Allee 1 D-21335 Luneburg Germany

ISBN: (纸本)9783031618901;9783031618918

In order to optimally support engineering students and prepare them for future challenges, the integration of education for sustainable development (ESD) with a linking of technical and sustainability-oriented topics within the curriculum is essential. This paper contributes in two ways. On the one hand, a systematic literature analysis will focus on existing modules integrate sustainability aspects into engineering education and revealed framework conditions for successful implementation. Framework conditions such as the learning objectives of a course, the possible main topics, the didactic methods used, the challenges and obstacles to implementation and examples of good practice were identified. On the other hand, determined aspects were used developing an exemplary teaching-learning concept and putting it into practice. The proposed concept consists of a tripartite module structure, including a content level, a methodological-didactic concept and an individual process level for anchoring sustainability aspects in the teaching of engineering and strengthening student awareness.

关键词： Sustainable Learning Engineering Education Research Engineering Education of the Future

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A Simulation Based Staff Scheduling Analysis for Call Centers in Cargo Industry

A Simulation Based Staff Scheduling Analysis for Call Center...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Kandaz, Omer Faruk Ozcan, Tuncay Istanbul Tech Univ TR-34467 Istanbul Turkiye

ISBN: (纸本)9783031671913;9783031671920

Call centers play a crucial role in terms of customer satisfaction. In the cargo industry, it holds even more importance than many others, not only for B2B but also for B2C deliveries. Long waiting times in queues cause re-dials or call abandonments, negatively affecting overall service delivery. The term "call center staff scheduling" mainly refers to the effective use of resources while meeting customer demands to prevent customer dissatisfaction. The aim of this study is to illustrate the existing state of the operating system in a cargo call center to ultimately manage staff scheduling effectively and efficiently, using the ARENA simulation program. Within this context, related data on call center operations for different processes is collected. After conducting pre-processing of the data to identify relevant best-fit distributions, a simulation model is formed using the ARENA simulation program, employing discrete event simulation techniques. Additionally, bottleneck analysis is carried out aiming to further improve the system. Moreover, based on the results, scenario analysis is implemented to compare and propose different alternative solutions that improve the system.

关键词： Simulation Staff Scheduling Call Center Bottleneck Analysis Cargo Industry

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Enhancing the Immersion of Augmented Reality Through Haptic Feedback 21st

Enhancing the Immersion of Augmented Reality Through Haptic ...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Grodotzki, Joshua Mueller, Benedikt Tobias Tekkaya, A. Erman TU Dortmund Univ Inst Forming Technol & Lightweight Components D-44227 Dortmund Germany

ISBN: (纸本)9783031618901;9783031618918

Mobile multi-actoric force feedback gloves (bHaptics Tactgloves) have been coupled with a mobile holographic display device (HoloLens 2). The communication is realized using open programmable interfaces, while the gloves are paired with a laptop. The holographic device, which must be connected to the internet, sends information via a network protocol to the cloud. This information is read by a program on the laptop and converted into actions sent to the gloves. The intensity and duration of the force-feedback can be modulated depending on the action the user is currently performing. Clicking a holographic button triggers a low-intensity, short-duration pulse at the fingertip while moving the entire hand into an area of potential danger causes all fingers and wrist motor to vibrate at maximum intensity as long as the user does not remove the hand from that area. First tests have shown that for novice users and users familiar with Augmented Reality, the additional sensory feedback through haptics offers a significantly higher level of immersion. While previously holograms could only be interacted with by hands without any haptic feedback, they now report that they have a sense of being able to touch and feel the holograms. The feedback gloves are viewed to be bulky and stiff, hence further development is needed on the hardware side, similar to the holographic devices themselves. Overall, connecting force-feedback gloves with Augmented Reality shows large potential in the fields of manufacturing, maintenance and education, as the level of immersion is further increased.

关键词： Haptic Feedback Augmented Reality Immersion Immersivity

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Integrated Information Theory with PyPhi: Testing and Improvement Strategies 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Enith Guerrero, Luz Arango-Lopez, Jeferson Fernando Castillo, Luis Moreira, Fernando Univ Caldas Fac Ingn Dept Sistemas & Informat Calle 65 26-10Edificio Parque Manizales Caldas Colombia Univ Portucalense IJP REMIT Rua Dr Antonio Bernardino Almeida 541-619 P-4200072 Porto Portugal Univ Aveiro IEETA Aveiro Portugal

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

The study of consciousness has increased in relevance in recent years in the scientific community. In the same line, integrated information theory (IIT) is making inroads into the understanding of consciousness. However, the enormous computational costs required make it difficult to apply IIT to experimental data. In this work we intend to explore and design efficient computational algorithms applying techniques such as Divide and Conquer and parallel computation that can provide some kind of solution to the challenges proposed by IIT based on optimizations and approximations used by PyPhi toolbox to reduce the complexity of the calculations. This software package allows users to easily study cause-effect structures of discret dynamical systems of binary elements, for causal analysis, serves as an up-to-date reference implementation of the formalisms of integrated information theory, and has been used in our research on efficient algorithms.

关键词： IIT MIP PyPhi Improvement Strategy integrated information Phi efficient algorithms

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