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2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019

作者： Ahmed, Suhaib Sadath, Lipsa Nagaria, Jumana Computer Science Engineering Amity University Dubai United Arab Emirates Faculty Software Engineering Amity University Dubai United Arab Emirates

ISBN: (纸本)9781538680100

There has been n number of software development designs and test patterns in software engineering. Frameworks are available on methods to calculate the time, effort and human power required to develop a software. Our work is a novel study on the basics of how proportional is the time required to test a software based on the LOCs (Lines of Codes) and the design used. The work aims to interlink the understanding between two kinds of structural testing. This basic study experiment was conducted using 20 different programs. We argue and prove that there is an interconnection between the design, Lines of Code (LOC) and testing. © 2019 IEEE.

关键词： software testing

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Deep Learning Approach for COVID-19 Identification

Deep Learning Approach for COVID-19 Identification

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Amin Ul Haq Jian Ping Li Riaz Ullah Khan Cobbinah Bernard Mawuli Bless Lord Y. Agbley Mordecai F. Raj Wang Zhou Jalaluddin Khan Abdul Haq Abdus Saboor Faiza Habib Zafar Khan School of Computer Science and Engineering University of Electronic Science and Tech. of China Chengdu China Yangtze River Delta Research Institute (Huzhou) University of Electronic Science and Tech. of China China School of Computer and Software Engineering Xihua University Chengdu Sichuan China Gomal University D.I. Khan Pakistan Hazzra University Manshera KPK Pakistan Faculty of Engineering and I.T Northern University Nowshera Pakistan

ISBN: (纸本)9781665413657

Accurate diagnostic system is significantly important for timely COVID-19 identification. Diagnosing COVID-19 from chest x-ray images employing the CNN model is recommended for accurate recognition of COVID-19. The existing diagnosis techniques of COVID-19 still lack high accuracy. To handle this problem in this work, we have proposed accurate detection method for COVID-19. In the proposed method, a CNN is incorporated for the diagnosis of COVID-19 using chest x-ray images data. The experimental results illustrate that our technique is good for COVID-19 accurate diagnosis and can be easily implemented in health care systems.

关键词： COVID-19 Deep learning Image recognition Computational modeling Medical services Information processing Media

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Green and Rapid and Instrumental One-Pot Method for the Synthesis of Imidazolines Having Potential Anti-SARS-CoV-2 Main Protease Activity

SSRN

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SSRN 2023年

作者： Azimi, Sabikeh Merza, Muna S. Ghasemi, Fathemeh Dhahi, Hasan Ali Baradarbarjastehbaf, Farid Moosavi, Mehdi Kargar, Pouya Ghamari Len, Christophe Department of Chemistry Faculty of Sciences University of Birjand Birjand97175-615 Iran Prosthetic dental Techniques Department Al-Mustaqbal University College Babylon51001 Iraq MSC in Software Engineering Kowsar The Institute of Higher Education Ministry of Science Research and Technology Computer Engineering Department Qazvin Iran National University of Science and Technology Dhi Qar Iraq Faculty of Pharmacy Department of Pharmaceutical Technology and Biopharmacy University of Pécs Pécs Hungary Department of Chemistry Faculty of Chemistry Mazandaran University Babolsar Iran Chimie ParisTech PSL University CNRS Institute of Chemistry for Life and Health Sciences 11 rue Pierre et Marie Curie ParisF-75005 France Peoples Friendship University of Russia [RUDN University 6 Miklukho Maklaya str. Moscow117198 Russia

The Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is responsible for ongoing epidemics in humans and some other mammals and has been declared a public health emergency of international concern. In this project, several small non-peptide molecules were synthesized to inhibit the major proteinase (Mpro) of SARS-CoV-2 using rational strategies of drug design and medicinal chemistry. Mpro is a key enzyme of coronaviruses and plays an essential role in mediating viral replication and transcription in human lung epithelial and stem cells, making it an attractive drug target for SARS-CoV. The antiviral potential of imidazoline derivatives as inhibitors of (SARS-CoV-2) Mpro was evaluated using in-silico techniques such as molecular docking simulation, molecular dynamics (MD) and ADMET prediction. The docking scores of these imidazoline derivatives were compared to that of the N3 crystal inhibitor and showed that most of these compounds, particularly compound E07, interacted satisfactorily in the active site of the coronavirus and strongly interacted with the residues (Met 165, Gln 166, Met 165, His 41, and Gln 189). Furthermore, the results were confirmed by MD simulations after exposure to long-term MD simulations and ADMET predictions. © 2023, The Authors. All rights reserved.

关键词： Coronavirus

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Modeling and analysis of COVID-19 new deaths using tree-based ensemble

TechRxiv

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TechRxiv 2021年

作者： Hashem, Ibrahim Abaker Targio Usmani, Raja Sher Afgun Shah, Asad Ali Almazroi, Abdulwahab Ali Bilal, Muhammad College of Computing and Informatics Department of Computer Science University of Sharjah Sharjah27272 United Arab Emirates Department of Software Engineering Faculty of Computing and Information Technology University of Sialkot Pakistan Department of Computing School of Electrical Engineering & Computer Science National University of Sciences and Technology Pakistan Department of Information Technology College of Computing and Information Technology at Khulais University of Jeddah Jeddah Saudi Arabia Department of Computer Science FAST National University of Computer and Emerging Sciences Islamabad44000 Pakistan

The COVID-19 pandemic has emerged as the world's most serious health crisis, affecting millions of people all over the world. The majority of nations have imposed nationwide curfews and reduced economic activity to combat the spread of this infectious disease. Governments are monitoring the situation and making critical decisions based on the daily number of new cases and deaths reported. Therefore, this study aims to predict the daily new deaths using four tree-based ensemble models i.e., Gradient Tree Boosting (GB), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Voting Regressor (VR) for the three most affected countries, which are the United States, Brazil, and India. The results showed that VR outperformed other models in predicting daily new deaths for all three countries. The predictions of daily new deaths made using VR for Brazil and India are very close to the actual new deaths, whereas the prediction of daily new deaths for the United States still needs to be improved. © 2021, CC BY.

关键词： COVID-19

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software Architecture for Quantum Computing Systems - A Systematic Review

arXiv

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arXiv 2022年

作者： Khan, Arif Ali Ahmad, Aakash Waseem, Muhammad Liang, Peng Fahmideh, Mahdi Mikkonen, Tommi Abrahamsson, Pekka M3S Empirical Software Engineering Research Unit University of Oulu Oulu90014 Finland School of Computing and Communications Lancaster University Leipzig Germany School of Computer Science Wuhan University Wuhan China School of Business University of Southern Queensland QLD Australia Faculty of Information Technology University of Jyväskylä JyvaskylaFI-40014 Finland

Quantum computing systems rely on the principles of quantum mechanics to perform a multitude of computationally challenging tasks more efficiently than their classical counterparts. The architecture of software-intensive systems can empower architects who can leverage architecture-centric processes, practices, description languages to model, develop, and evolve quantum computing software (quantum software for short) at higher abstraction levels. We conducted a Systematic Literature Review (SLR) to investigate (i) architectural process, (ii) modeling notations, (iii) architecture design patterns, (iv) tool support, and (iv) challenging factors for quantum software architecture. Results of the SLR indicate that quantum software represents a new genre of software-intensive systems;however, existing processes and notations can be tailored to derive the architecting activities and develop modeling languages for quantum software. Quantum bits (Qubits) mapped to Quantum gates (Qugates) can be represented as architectural components and connectors that implement quantum software. Tool-chains can incorporate reusable knowledge and human roles (e.g., quantum domain engineers, quantum code developers) to automate and customize the architectural process. Results of this SLR can facilitate researchers and practitioners to develop new hypotheses to be tested, derive reference architectures, and leverage architecture-centric principles and practices to engineer emerging and next generations of quantum software. © 2022, CC BY.

关键词： Modeling languages

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Employing derivatives for creating texture masks for digital images

引用

AIP Conference Proceedings 2024年第1期2898卷

作者： Taha Basheer Taha Ruzelita Ngadiran Dujan B. Taha IT Department Faculty of Applied Science Tishk International University Erbil Kurdistan Region Iraq Faculty of Electronic Engineering Technology Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Centre of Excellence Advanced Computing (AdvComp) Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Software Engineering Department College of Computer Science and Mathematics Mosul University Mosul Iraq

Texture masking has been used as a significant factor in creating perceptual maps that simulates human vision system in observing noise in digital images. In this paper, the possibility of creating texture masks using first and second derivatives is investigated and tested. Results shows that after applying the derivatives, areas of higher texture were highlighted and recognized, which will lead to simple implementation of texture masks using numerical analysis.

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Parallel Monte Carlo Integration Algorithm Based on GPU 14

Parallel Monte Carlo Integration Algorithm Based on GPU

引用

14th IEEE International Conference on Intelligent Systems and Knowledge engineering, ISKE 2019

作者： Zong, Hui Hua, Renfeng Zhao, Jianyang Cao, Zining Huaiyin Institute of Technology Faculty of Computer and Software Engineering Huaian China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China

ISBN: (纸本)9781728123486

Big data comes with the increasing maturity of computer network technology and its application popularity. How to process big data and mine its potential value is a hot issue today. Artificial intelligence is one of the main sources of algorithms for dealing with big data, while parallel computation is the only choice to improve computing performance. Monte Carlo method plays an important role in the application of artificial intelligence, such as computer game AlphaGo, and it requires a lot of random data to calculate, so we use it, in this paper, to explore the general method of parallel processing big data. According to Monte Carlo method, the calculation time of the algorithm will increase exponentially with the increase of the calculation accuracy. As the calculation accuracy will increase accordingly when the number of points increases. In order to improve the computing performance, a Monte Carlo parallel algorithm based on GPU-CUDA programming model is designed. The quality of the random number generator is the key factor affecting the accuracy of Monte Carlo calculation, so the higher quality Mersenne Twister random number algorithm is chosen. Taking \pi and e as examples, the experimental results show that the GPU-based Monte Carlo parallel algorithm is effective. This method improves both the calculation performance and the calculation accuracy. © 2019 IEEE.

关键词： Monte Carlo methods

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Markov switching model for driver behavior prediction: Use cases on smartphones

arXiv

引用

arXiv 2021年

作者： Zaky, Ahmed B. Khamis, Mohamed A. Gomaa, Walid Benha University Cairo11240 Egypt Big Data Institute College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518060 China New Borg El-Arab City Alexandria21934 Egypt Faculty of Engineering Alexandria University Alexandria21544 Egypt

Several intelligent transportation systems focus on studying the various driver behaviors for numerous objectives. This includes the ability to analyze driver actions, sensitivity, distraction, and response time. As the data collection is one of the major concerns for learning and validating different driving situations, we present a driver behavior switching model validated by a low-cost data collection solution using smartphones. The proposed model is validated using a real dataset to predict the driver behavior in short duration periods. A literature survey on motion detection (specifically driving behavior detection using smartphones) is presented. Multiple Markov Switching Variable Auto-Regression (MSVAR) models are implemented to achieve a sophisticated fitting with the collected driver behavior data. This yields more accurate predictions not only for driver behavior but also for the entire driving situation. The performance of the presented models together with a suitable model selection criteria is also presented. The proposed driver behavior prediction framework can potentially be used in accident prediction and driver safety systems. © 2021, CC BY.

关键词： Smartphones

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Correction to: Enhancing lung cancer diagnosis with data fusion and mobile edge computing using DenseNet and CNN

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Journal of Cloud Computing 2024年第1期13卷 1-1页

作者： Zhang, Chengping Aamir, Muhammad Guan, Yurong Al-Razgan, Muna Awwad, Emad Mahrous Ullah, Rizwan Bhatti, Uzair Aslam Ghadi, Yazeed Yasin Mechanical and Electrical Engineering College Hainan Vocational University of Science and Technology Haikou China College of Computer Science Huanggang Normal University Huanggang China Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Department of Electrical Engineering College of Engineering King Saud University Riyadh Saudi Arabia Faculty of Engineering Chulalongkorn University Bangkok Thailand Bangkok Thailand School of Information and Communication Engineering Hainan University Haikou China Department of Computer Science Al Ain University Al Ain UAE

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Scenario-Based Learning Exemplification with a Dynamic Video Retrieving Tool for the Second Language Teaching 2nd

Scenario-Based Learning Exemplification with a Dynamic Video...

引用

2nd International Conference on Innovative Technologies and Learning, ICITL 2019

作者： Wang, Kun-Te Lu, Lele Sun, Qiao Huang, Tien-Chi Faculty of Computer and Software Engineering Huaiyin Institute of Technology Hangzhou China National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9783030353421

In most second language teaching environments, the traditional teaching instruction tends to focus on language elements, grammatical rules, and vocabulary memorizing rather than learning on the language in meaningful discourse for successful communication. A simple memory of abstract language elements in a context-free learning environment will make language learning a very difficult task and often frustrate teachers in providing examples of relevant contexts with phrases and sentences. This study describes an interactive video retrieval tool that helps English teachers provide the authentic material of a particular language element which can be viewed in different environments. The tool allows students to access 110 video clips containing examples of contextualized language elements to help them build their perception of the target language. Besides, the tool analyzes the emotional polarity of each subtitle. The result shows that 5814/6000 words could be found by using the tool for Chinese CET-6 training, and the repetition rate the examples was 85% (CET-4) and 87% (CET-6). In a short time, the tool is designed to give teachers access to many dynamic examples from a multimedia corpus, and the choice of teachers can be easily used as a teaching resource for students. The design of this study not only reveals the importance of using dynamic instances in the classroom, but also provides an effective strategy for English teachers to present and explain new vocabulary to students. © Springer Nature Switzerland AG 2019.

关键词： Students

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