检索结果-内蒙古大学图书馆

Developing capabilities for responsible research and innovation (RRI)

Journal of Responsible Technology 2023年 15卷

作者： Ogoh, George Akintoye, Simisola Eke, Damian Farisco, Michele Fernow, Josepine Grasenick, Karin Guerrero, Manuel Rosemann, Achim Salles, Arleen Ulnicane, Inga School of Computer Science University of Nottingham Nottingham United Kingdom Centre for Research Ethics & Bioethics (CRB) Uppsala University Uppsala Sweden Biogem Biology and Molecular Genetics Research Institute AV Ariano Irpino Italy Department of Bioethics and Medical Humanities University of Chile Santiago Chile Centre for Law Faculty of Business and Law Justice and Society De Montfort Law School De Montfort University Leicester United Kingdom Centre for Computing and Social Responsibility Faculty of Computing School of Computer Science and Informatics Engineering and Media De Montfort University Leicester United Kingdom

This paper examines the notion of capability development through the lens of Responsible Research and Innovation (RRI). It describes how RRI capabilities can be promoted and developed through capacity-building activities by drawing on a reflection of the experiences of some members of the Ethics and Society team of the EU-funded Human Brain Project (HBP) who have contributed to the development of an extensive RRI capacity building programme for HBP researchers, EBRAINS research infrastructure developers and users, as well as interested external audiences. It also highlights some of the outcomes of the RRI capacity-building exercise and the challenge of assessing the impact of such activities. © 2023

关键词： Capability development Capacity building Ethics Research and innovation RRI

来源：评论

学校读者我要写书评

暂无评论

Identifying Gamified Teaching Elements in Computer Science Course

Identifying Gamified Teaching Elements in Computer Science C...

引用

International Conference on Platform Technology and Service (PlatCon)

作者： Hasnah Tanalol Hazmi Hashim Punitha Turumogan Noorsidi Aizuddin Mat Noor Aslina Baharum Farhana Diana Deris Preparatory Center for Science & Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Computing and Informatics University Malaysia Sabah Kota Kinabalu Malaysia Department of Computing and Information Technology Tunku Abdul Rahman University of Management and Technology Penang Malaysia Real Estate Department Mass Appraisal Housing and Planning Research Group Centre for Real Estate Studies Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Bahru Johor Malaysia Computing and Information System School of Engineering and Technology Sunway University Bandar Sunway Selangor Malaysia Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Universiti Malaysia Sabah Johor Bahru Johor Malaysia

Traditional education methods, having said, lack motivation and self-regulation. The 5G and 6G technology have improved education; one such is gamification. Gamification applies gaming mechanisms to non-gaming platforms. Sadly, the use of gamification is still limited, especially in Malaysia. Gamification affects user experience, so it is intriguing to see if it can solve education problems. A study was conducted to identify elements of gamification. A systematic literature review (SLR) determines the gamification elements. Results show the list of identified 30 elements as guidelines for developing gamified teaching in Computer Science Courses. Thus, it is hoped that the improved teaching and learning process can affect students' performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Evaluating Security of MQTT Protocol in Internet of Things

Evaluating Security of MQTT Protocol in Internet of Things

引用

Canadian Conference on Electrical and Computer engineering (CCECE)

作者： Ayman Al-Ani Wong Kang Shen Ahmed K. Al-Ani Shams A. Laghari Omar E. Elejla Cybersecurity Research Group Faculty of Computing and Informatics Universiti Malaysia Sabah Jalan UMS Kota Kinabalu Sabah Malaysia School of Computing and Data Science Xiamen University Malaysia Sepang Selangor Malaysia School of Engineering Technology and Applied Science Centennial College Toronto Ontario Canada National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia (USM) Gelugor Penang Malaysia Department of Computer Science Al-Aqsa University Gaza Palestine

The Internet of Things (IoT) has revolutionized the way people interact, communicate, and perform daily activities in various domains ranging from households to industries and cities. MQTT is one of the commonly adopted protocols for implementing IoT. However, IoT systems that are connected through MQTT are susceptible to security breaches as MQTT was not originally designed with security as a priority. The credentials and messages transmitted in plaintext by default, thereby compromising data confidentiality and integrity. This study presents a comprehensive analysis of the MQTT protocol, including experimentation on an MQTT system using various cryptographic implementations, such as AES-CBC, RSA, and ECC AES Hybrid Scheme, to assess the processing time and message size. The findings indicate that payload encryption increases processing time and message bytes. Among the cryptographic implementations, RSA incurs the highest processing time, followed by ECC AES Hybrid Scheme and AES- CBC. Furthermore, the study demonstrates the effectiveness of attack prevention between standard MQTT and secured MQTT implementations by simulating various IoT attacks, such as black-box penetration attack, identity spoofing, DoS attack, and MITM attack. The results and subsequent discussion provide insights that answer the research question, revealing the cryptographic algorithms that result in the most overhead on the standard MQTT implementation and their capacity to resist common attacks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Discrepancy and Thematic Bibliometric Analyses of the Remaining Limitations in Artificial Intelligence

Discrepancy and Thematic Bibliometric Analyses of the Remain...

引用

computing (ICOCO), IEEE International Conference on

作者： Mahayaudin M. Mansor Nurain Ibrahim Noor Fadhilah Ahmad Radi Nadirah Abdul Rahim Syarul Heiry Yahaya Mohd Aftar Abu Bakar Roslinazairimah Zakaria School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia Institute of Big Data Analytics and Artificial Intelligence Universiti Teknologi MARA Malaysia Department of Electrical and Computer Engineering Kuliyyah of Engineering International Islamic University Malaysia Department of Science Computer and Mathematics Universiti Teknologi MARA (Penang Campus) Malaysia Department of Mathematical Sciences Faculty of Science & Technology Universiti Kebangsaan Malaysia Centre for Mathematical Sciences Universiti Malaysia Pahang Al-Sultan Abdullah Malaysia

ISBN: (数字)9798331530303

ISBN: (纸本)9798331530310

As artificial intelligence (AI) advances, it is essential to continuously comprehend its limitations to optimise the integration of AI into autonomous systems that empower humans. The first objective of this study is to highlight the key capabilities of both humans and AI, focusing on the differences and identifying limitations of AI from the literature. Through discrepancy analysis, this study uses a Venn diagram to visualise the remaining limitations of AI into five key domains: (i) emotional intelligence, (ii) consciousness and awareness, (iii) creative imagination, (iv) communication, and (v) ethical decision-making. Furthermore, this study employs thematic bibliometric analysis to provide a more detailed examination of each AI limitation as the second objective. This study has identified underdeveloped and emerging research themes with potential for future development, such as emotion recognition, human-computer interaction, digital health, and situational awareness, which may require further research. Additionally, this study commends the ongoing efforts to harness AI’s computational power and algorithmic innovations to enhance AI’s overall performance and applicability.

关键词： visualization Technological innovation Ethics Emotion recognition Bibliometrics Decision making Focusing Electronic healthcare Object recognition Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Hypothyroidism Prediction and Detection Using Machine Learning

Hypothyroidism Prediction and Detection Using Machine Learni...

引用

International Conference on engineering Technology and their Applications (IICETA)

作者： Hebatullah Mohammad Almahshi Esraa Abdallah Almasri Hiam Alquran Wan Azani Mustafa Ahmed Alkhayyat Department of Biomedical Engineering Jordan University of Science and Technology Irbid Jordan Biomedical Systems and Medical Informatics Engineering Yarmouk University Irbid Jordan Faculty of Electrical Engineering Technology Univerisiti Malaysia Perlis (UniMAP) Pauh Putra Campus Arau Perlis Malaysia Advanced Computing Centre of Excellence Univerisiti Malaysia Perlis (UniMAP) Pauh Putra Campus Arau Perlis Malaysia Faculty of Engineering The Islamic University Najaf Iraq

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

The world is facing an increase in the incidence of thyroid diseases, including in Jordan as well, especially hypothyroidism. This condition can be diagnosed through blood samples to know the percentage of hormones (TSH, T3, and T4) and take the appropriate decision after that. The major goal of this study is to make diagnosis easier and reduce the risk of misdiagnosis, which happens all too often. Methods: The use of machine learning in the prediction of disease is a crucial step in the process of data analysis. This paper presents an analysis and classification model that takes into account the various factors involved in the prediction of disease. We applied a number of machine learning algorithms like support vector machine (SVM), Nave Bayes, decision trees, and ensemble to get the best prediction. The decision tree algorithm showed the highest accuracy and lowest cost with a percentage of 97.6 percent and 90, respectively. The results appeared in the form of three classes (compensated hypothyroidism, primary hypothyroidism, and negative). Conclusion: The best results were obtained at the milestone point in computer-aided diagnosis of hypothyroidism. Future work is considered to increase the number of cases that can be detected and diagnosed using machine learning.

关键词： Support vector machines Solid modeling Machine learning algorithms Databases Machine learning Medical services Predictive models

来源：评论

学校读者我要写书评

暂无评论

Chronic Kidney Disease Detection Using Machine Learning Technique

Chronic Kidney Disease Detection Using Machine Learning Tech...

引用

International Conference on engineering Technology and their Applications (IICETA)

作者： Rama Al-Momani Ghada Al-Mustafa Razan Zeidan Hiam Alquran Wan Azani Mustafa Ahmed Alkhayyat Department of Biomedical Engineering Jordan University of Science and Technology Irbid Jordan Biomedical Systems and Medical Informatics Engineering Yarmouk University Irbid Jordan Faculty of Electrical Engineering Technology Univerisiti Malaysia Perlis (UniMAP) Pauh Putra Campus Arau Perlis Malaysia Advanced Computing Centre of Excellence Universiti Malaysia Perlis (UniMAP) Pauh Putra Campus Arau Perlis Malaysia Faculty of Engineering The Islamic University Najaf Iraq

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

chronic kidney disease is a disorder that disables normal kidney function. The WHO has shown that CKD is a serious disease, ranked as one of the top twenty causes of death. It is recognized that2 million people worldwide suffer from kidney failure and the number of patients diagnosed with CDK continues to expand at a rate of 5-7% annually. late diagnosis of this disease is a life-threatening problem, which, often occurs in remote areas due to the lack of specialized medical personnel, in addition to the high cost of diagnosis. This paper aims at early detection of CDK using machine learning algorithms Artificial Neural Network, Support Vector Machine, and k-Nearest Neighbor. The importance of AI is reflected in the importance of identifying these typically fatal ailments. This study looks at a data set consisting of 400 samples and 13 features. The three classification techniques were evaluated by applying them to the data. The results show that the ANN classifier achieved the best accuracy at 99.2%.

关键词： Machine learning algorithms Costs Support vector machine classification Artificial neural networks Machine learning Personnel Kidney

来源：评论

学校读者我要写书评

暂无评论

A New 4-D Multistable Hyperchaotic Two-Scroll System, its Bifurcation Analysis, Synchronization and Circuit Simulation 1

A New 4-D Multistable Hyperchaotic Two-Scroll System, its Bi...

引用

1st Paris Van Java International Seminar on Computer, Science, engineering, and Technology, PVJ ISComSET 2020

作者： Vaidyanathan, Sundarapandian Sambas, Aceng Mujiarto Mamat, Mustafa Wilarso Mada Sanjaya, W.S. Sutoni, Akhmad Gunawan, I. Research and Development Centre Vel Tech University Avadi Chennai India Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia Department of Mechanical Engineering Sekolah Tinggi Teknologi Cileungsi Indonesia Department of Physics Universitas Islam Negeri Sunan Gunung Djati Bandung Indonesia Department of Industrial Engineering Universitas Suryakancana Cianjur Indonesia Universitas Langlangbuana Bandung Indonesia

A new 4-D hyperchaotic two-scroll system with three quadratic nonlinearities and a cubic nonlinearity is proposed in this paper. The dynamical properties of the new hyperchaotic system are described in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, symmetry, dissipativity, etc. We also establish that the new hyperchaotic system has multistability with coexisting attractors. As a control application, we use integral sliding mode control for active self-synchronization of the new hyperchaotic systems as master-slave systems. As an engineering application, an electronic circuit design of the new hyperchaotic two-scroll system is developed in MultiSIM, which confirms the feasibility of the system. © Published under licence by IOP Publishing Ltd.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

引用

Computer Systems Science & engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Deep-Motion-Net: GNN-based volumetric organ shape reconstruction from single-view 2D projections

arXiv

引用

arXiv 2024年

作者： Wijesinghe, Isuru Nix, Michael Zakeri, Arezoo Hokmabadi, Alireza Al-Qaisieh, Bashar Gooya, Ali Taylor, Zeike A. Centre for Computational Imaging and Simulation Technologies in Biomedicine School of Mechanical Engineering University of Leeds Leeds United Kingdom Institute of Medical and Biological Engineering School of Mechanical Engineering University of Leeds Leeds United Kingdom Department of Medical Physics and Engineering St James’s University Hospital Leeds Teaching Hospitals NHS Trust Leeds United Kingdom Division of Informatics Imaging and Data Sciences Faculty of Biology Medicine and Health University of Manchester Manchester United Kingdom School of Medicine and Population Health University of Sheffield Sheffield United Kingdom School of Computing Science University of Glasgow Glasgow United Kingdom

We propose Deep-Motion-Net: an end-to-end graph neural network (GNN) architecture that enables 3D (volumetric) organ shape reconstruction from a single in-treatment kV planar X-ray image acquired at any arbitrary projection angle. Estimating and compensating for true anatomical motion during radiotherapy is essential for improving the delivery of planned radiation dose to target volumes while sparing organs-at-risk, and thereby improving the therapeutic ratio. Achieving this using only limited imaging available during irradiation and without the use of surrogate signals or invasive fiducial markers is attractive. The proposed model learns the mesh regression from a patient-specific template and deep features extracted from kV images at arbitrary projection angles. A 2D-CNN encoder extracts image features, and four feature pooling networks fuse these features to the 3D template organ mesh. A ResNet-based graph attention network then deforms the feature-encoded mesh. The model is trained using synthetically generated organ motion instances and corresponding kV images. The latter is generated by deforming a reference CT volume aligned with the template mesh, creating digitally reconstructed radiographs (DRRs) at required projection angles, and DRR-to-kV style transferring with a conditional CycleGAN model. The overall framework was tested quantitatively on synthetic respiratory motion scenarios and qualitatively on in-treatment images acquired over full scan series for liver cancer patients. Overall mean prediction errors for synthetic motion test datasets were 0.16±0.13 mm, 0.18±0.19 mm, 0.22±0.34 mm, and 0.12±0.11 mm. Mean peak prediction errors were 1.39 mm, 1.99 mm, 3.29 mm, and 1.16 mm. © 2024, CC BY-SA.

关键词： Radiotherapy

来源：评论

学校读者我要写书评

暂无评论

Modelling, Control Methods and Applications of Chaotic Oscillators

引用

Discrete Dynamics in Nature and Society 2023年第1期2023卷

作者： Vaidyanathan, Sundarapandian Sambas, Aceng Lien, Chang-Hua Mamat, Mustafa Centre for Control Systems Vel Tech University 400 Feet Outer Ring Road Chennai 600062 India Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak 21300 Terengganu Malaysia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Jawa Barat 46196 Indonesia Department of Marine Engineering National Kaohsiung University of Science and Technology Kaohsiung 81157 Taiwan

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：