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7th International Conference on Mathematics, Science, and Education 2020, ICMSE 2020

作者： Romli, R.N. Zolkipli, M.F. Osman, M.Z. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang26200 Malaysia

Android is designed for mobile devices and its open-source software. The growth and popularity of android platform are high compared to another platform. Due to its glory, the number of malware has been increasing exponentially. Android system used a permission mechanism to allow users and developers to manage their access to private information, system resources, and data storage required by Android applications (apps). It became an advantage to an attacker to violent the data. This paper proposes a novel framework for Android malware detection. Our framework used three major methods for effective feature representation on malware detection and used this method to classify malware and benign. The result demonstrates that the Random forest is with 23 features is more accurate detection than the other machine learning algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Open source software

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Design and Implementation of Intelligent Dustbin with Garbage Gas Detection for Hygienic Environment based on IoT

Design and Implementation of Intelligent Dustbin with Garbag...

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2022 International Conference on Advancement in Electrical and Electronic engineering, ICAEEE 2022

作者： Ahmed, Marzia Shaha, Rony Sarker, Kaushik Mahi, Rifat Bin Kashem, Mohammod Abul Daffodil International University Department of Software Engineering Dhaka Bangladesh Universiti Malaysia Pahang Faculty of Electrical and Electronics Engineering Pahang 26600 Malaysia Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh Duet Department of Computer Science and Engineering Gazipur Bangladesh

ISBN: (数字)9781665469449

ISBN: (纸本)9781665469449

Rapid population expansion necessitated increased resource use in everyday living. As a result, the pace of trash gen-eration has increased dramatically, affecting the environment's hygiene system and other health concerns. Waste overflows in public spaces, and improved management is necessary. The purpose of this study is to develop a model of an intelligent trashcan for usage in smart cities. Additionally, to identify dangerous gases emitted by dustbins for subsequent management operations, as well as to monitor the amount of trash in the waste bin and warn the municipality through SMS. This system includes two ultrasonic sonar sensors for measuring trash level, a GSM module for sending SMS, three gas sensors for detecting harmful garbage gas, an infrared sensor for counting garbage droplets, and an Arduino Uno for managing all activities. The system notifies you whether the bin is full or empty and can also be controlled by voice command. Additionally, released gas may be monitored to determine the severity of the impairment and to notify the appropriate authorities. Most significantly, it will identify a failed trash drop in the bin and alert the user through alarm for truly considering the reduction of spilled garbage surrounding bins while using the system. © 2022 IEEE.

关键词： Global system for mobile communications

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Data Fusion Architecture Empowered with Deep Learning for Breast Cancer Classification

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computers, Materials & Continua 2023年第12期77卷 2813-2831页

作者： Sahar Arooj Muhammad Farhan Khan Tariq Shahzad Muhammad Adnan Khan Muhammad Umar Nasir Muhammad Zubair Atta-ur-Rahman Khmaies Ouahada Faculty of Computing Riphah International UniversityIslamabad45000Pakistan Department of Forensic Sciences University of Health SciencesLahore54000Pakistan Department of Electrical and Electronic Engineering Science University of JohannesburgP.O.Box 524Johannesburg2006South Africa School of Computing Skyline University CollegeUniversity City SharjahSharjah1797United Arab Emirates Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Faculty of Artificial Intelligence&SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science Bahria UniversityLahore CampusLahore54000Pakistan Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia

Breast cancer(BC)is the most widespread tumor in females worldwide and is a severe public health *** is the leading reason of death affecting females between the ages of 20 to 59 around the *** detection and therapy can help women receive effective treatment and,as a result,decrease the rate of breast cancer *** cancer tumor develops when cells grow improperly and attack the healthy tissue in the human *** are classified as benign or malignant,and the absence of cancer in the breast is considered *** learning,machine learning,and transfer learning models are applied to detect and identify cancerous tissue like *** research assists in the identification and classification of *** implemented the pre-trained model AlexNet and proposed model Breast cancer identification and classification(BCIC),which are machine learning-based models,by evaluating them in the form of comparative *** used 3 datasets,A,B,and *** fuzzed these datasets and got 2 datasets,A2C and *** A2C is the fusion of A,B,and C with 2 classes categorized as benign and *** B3C is the fusion of datasets A,B,and C with 3 classes classified as benign,malignant,and *** used customized AlexNet according to our datasets and BCIC in our proposed *** achieved an accuracy of 86.5%on Dataset B3C and 76.8%on Dataset A2C by using AlexNet,and we achieved the optimum accuracy of 94.5%on Dataset B3C and 94.9%on Dataset A2C by using proposed model BCIC at 40 epochs with 0.00008 learning *** proposed fuzzed dataset model using transfer *** fuzzed three datasets to get more accurate results and the proposed model achieved the highest prediction accuracy using fuzzed dataset transfer learning technique.

关键词： Breast cancer classification deep learning machine learning transfer learning learning rate

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A Systematic Survey on Mobile Internet of Things Security 14

A Systematic Survey on Mobile Internet of Things Security

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14th International Conference on Information Security and Cryptology, ISCTURKEY 2021

作者： Arat, Ferhat Akleylek, Sedat Samsun University Engineering Faculty Department of Software Engineering Samsun Turkey Ondokuz Mayis University Engineering Faculty Department of Computer Engineering Samsun Turkey

ISBN: (纸本)9781665407762

With its applicability and scope, IoT technology plays a role in facilitating daily life. Human independent interactions are become obligatory by technological innovations and connectivity. Mobile IoT represents the network structure created by customized smart devices with customized applications and personalized structure. Remote and simple management of industrial control systems and organizations in many different fields are became easier with M-IoT devices and network structure. M-IoT applications have emerged in all areas from smart home systems to health systems and remote access. Since M-IoT applications are characterized as the development and evolution of IoT networks, it inherits on the security issues and challenges of IoT networks. The fact that security and privacy solutions in traditional computer networks cannot be used in M-IoT networks and applications on account of many reasons, highlights the need for security solutions in this field. In this paper, we present an overview of M-IoT networks. M-IoT structure and application layer protocols are analyzed. Security challenges and vulnerabilities in M-IoT application layer and applications are emphasized. In addition, the application layer is examined and the security attacks are summarized. Furthermore, list of open problems in the literature are listed. © 2021 IEEE.

关键词： Internet of things

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The 5G Wireless Technology and a Significant Economic Growth and Sustainable Development

The 5G Wireless Technology and a Significant Economic Growth...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Alkholidi, Abdulsalam Alsharabi, Naif A. Hamam, Habib Alshammari, Talal Sarheed Canadian Institute of Technology Tirana Albania Sana'a University Faculty of Engineering Sana'a Yemen College of Computer Scinece and Engineering Univerity of Ha'il Comuter Engineering Ha'il55476 Saudi Arabia College of Engineering and It Amran University Yemen Université de Moncton Faculty of Engineering MonctonNBElA3E9 Canada Canadian Institute of Technology College Department of Software Engineering Moncton Canada

ISBN: (纸本)9798350347050

5G technology can create millions of new jobs in many economic and industry sectors. It needs an in-depth study between the engineering sector, business, moneymen, and economists to introduce new ideas and develop a road map to benefit from this technology. Also, learn from the experiences of pioneers in this sector. Mobile phone networks are no longer a means of social media, entertainment, narrow commerce, and commercial correspondence. They have become a new pillar in economic growth if they are optimally exploited. This paper aims at highlighting 5G mobile networks and economic growth by studying and analyzing prestigious research and technical and commercial related reports and raising important recommendations to the decision-makers to take advantage of it and adapt this modern technology to develop the economic sector and create new opportunities for young people and those interested. The most important recommendation of this study is the need to support a new generation of young people, especially in the least developed countries in the formation of their minor economic projects, taking advantage of the huge potential of 5G technology, as well as the localization of this technique in many medium and giant projects. One of the key recommendations of this study is to encourage young people to involve in this promising field and help them set up small businesses. © 2023 IEEE.

关键词： Decision making

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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Light-weight Sketch Recognition with Knowledge Distillation 6

Light-weight Sketch Recognition with Knowledge Distillation

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6th International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2023

作者： Huynh, Viet-Tham Nguyen, Tam.V Tran, Minh-Triet Software Engineering Laboratory Faculty of Information Technology University of Science VNU-HCM Viet Nam Vietnam National University Ho Chi Minh City Viet Nam University of Dayton Department of Computer Science United States

ISBN: (纸本)9798350327410

Recognizing hand-drawn sketches is a promising starting point for various applications, such as assisting artists in creating 3D environments for games or virtual environment scenes quickly and efficiently from concept arts. In addition, by understanding drawings, we can generate 3D models that can be used for further design and development. Thus, in this paper, we aim to develop a novel lightweight network that can accurately recognize sketch drawings. We propose a lightweight-yet-efficient neural network based on MobileNetV2 for sketch recognition and employ knowledge distillation to train the proposed model from EfficientNet-B4. To evaluate the accuracy of the proposed method, we collect a dataset of sketches comprising 1800 drawings in 12 categories, ranging from furniture to animals. The experimental results show that our network model achieves an accuracy of 96.7%, with 96.9% precision, 96.7% recall, and 96.7% F1-score. These results demonstrate that the proposed approach has great potential for practical sketch recognition applications, such as interior design or VR scene generation. © 2023 IEEE.

关键词： Distillation

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Exploring the Impact of Data Augmentation Techniques on Emotional Speech Recognition

Exploring the Impact of Data Augmentation Techniques on Emot...

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Telecommunications Forum (TELFOR)

作者： Jovan Galić Slavko Šajić Branko Marković Department of Telecommunications Faculty of Electrical Engineering University of Banja Luka Banja Luka Bosnia and Herzegovina Department of Computer and Software Engineering Faculty of Technical Sciences University of Kragujevac Čačak Serbia

ISBN: (数字)9798350391060

ISBN: (纸本)9798350391077

Automatic Speech Recognition (ASR) systems are known to perform poorly in recognition of atypical speech, which certainly includes emotional speech. The labor-intensive nature of developing comprehensive speech databases for training purposes has led to the widespread adoption of synthetic speech data generation, utilizing existing natural speech, in numerous research studies. This paper examines the impact of standard data augmentation techniques, including pitch shifting, time stretching and volume adjustment on the accuracy of isolated-word recognizer of emotional speech. The experiments carried out indicate a significant increase in accuracy achieved through a single augmentation based on pitch-shifting for all emotional states.

关键词： Training Emotion recognition Accuracy Speech recognition Data augmentation Robustness Telecommunications Speech synthesis Standards Synthetic data

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Characterizing Discussion Trend on Blockchain Development by Mining Stack Overflow

SSRN

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SSRN 2023年

作者： Ze, Xue Zhao, Tianyu Hao, Isabella Wei, Lili Department of Electrical and Computer Engineering Faculty of Engineering McGill University MontrealQC Canada Department of Software Engineering Faculty of Engineering McGill University MontrealQC Canada

Context: The importance of blockchain knowledge is becoming more apparent as the technology continues to grow and expand. With the increasing interest in web3-related technology and the hype of the metaverse, more people are seeking to understand blockchain and its potential applications. Thus, characterizing blockchain-related concerns on Stack Overflow, one of the most popular question-and-answer (Q&A) sites for programmers, is important for the concerned software development. Several research projects have explored the technological obstacles confronted by users. However, there is no existing study that analyzes the trend and change in blockchain-related discussions over the years. There is also a paucity of information on the community itself, the Stack Overflow users, and the important topics to ***: In this study, we investigated the developers' concerns associated with blockchain development by leveraging the Latent Dirichlet Allocation (LDA) technique. We also characterized the changing trend of blockchain discussions over the ***: We first collected 6,340 blockchain-related questions from Stack Overflow. Leveraging LDA, we discerned the most relevant topics and prevalent challenges encountered by blockchain developers. Subsequently, we depicted these findings using pie charts and embarked on a manual analysis to elucidate the trends in topic changes over the ***: The findings of our investigation reveal a predilection among users to post topics closely associated with "Hyperledger Fabric", "Blockchain Mechanism", and "Smart Contract". Notably, a pronounced surge in user engagement and the proliferation of discussions have been observed from 2018 to ***: Utilizing the LDA methodology, we have discerned a transformation in the scope of blockchain-related topics under discussion by users on Stack Overflow (SO) over the course of the year. Furthermore, our analysis has shed light on the evolving trends and the array o

关键词： Smart contract

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A High-Resolution Approach for Dynamic Traffic Police Gestures Recognition Based on Spatial Context and Temporal Features Fusion 8

A High-Resolution Approach for Dynamic Traffic Police Gestur...

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8th International Conference on Image, Vision and Computing, ICIVC 2023

作者： He, Jian Jiang, Shengsheng Wei, Xin Zhang, Cheng Dong, Ruihai Beijing Engineering Research Center for IOT Software and Systems Beijing University of Technology Beijing China Beijing University of Technology Faculty of Information Technology Beijing China School of Computer Science University College Dublin Dublin Ireland

ISBN: (纸本)9798350335231

According to the requirement of recognizing traffic police gestures for driver assistance systems and intelligent vehicles, a universal model for dynamic traffic police gesture recognition is firstly introduced, of which can accurately present the spatial context (such as the relative lengths of skeletons, the angles between each skeleton w. r. t. gravity, and part features) of the traffic police gestures. Secondly, an architecture which can respectively extract spatial context and temporal features of dynamic traffic police gesture is proposed. Meanwhile, deep neural network and LSTM are introduced to build a high-resolution traffic police gestures recognizer (namely HRTPGR). At last, the open Police Gesture Dataset is used to train and test TPGR, and the experimental results show that the TPGR achieves a state-of-the-art accuracy with 98.7% for dynamic traffic police gestures recognition, and has strong anti-interference ability to light, background and gesture shape changes. © 2023 IEEE.

关键词： Gesture recognition

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