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Cross-heterogeneous Domain Authentication Scheme Based on Blockchain

Journal of Artificial Intelligence and Technology 2021年第2期1卷 92-100页

作者： Jing Liu Yixin Liu Yingxu Lai Rongchen Li Siyu Wu Sami Mian College of Computer Science Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Shaanxi Key Laboratory of Network and System Security Xi’an 710071China Science and Technology on Information Assurance Laboratory Beijing 100072China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China Fan Gongxiu Honors College Beijing University of TechnologyBeijing 100124China University of Pittsburgh PittsburghPA 15260USA

With the rising popularity of the Internet and the development of big data technology,an increasing number of organizations are opting to cooperate across domains to maximize their *** organizations use public key infrastructure to ensure security in accessing their data and ***,with the continuous development of identity-based encryption(IBE)technology,small-and medium-sized enterprises are increasingly using IBE to deploy internal authentication *** solve the problems that arise when crossing heterogeneous authentication domains and to guarantee the security of the certification process,we propose using blockchain technology to establish a reliable cross-domain authentication *** the distributed and tamper-resistant characteristics of the blockchain,we design a cross-domain authentication model based on blockchain to guarantee the security of the heterogeneous authentication process and present a cross-domain authentication protocol based on *** model does not change the internal trust structure of each authentication domain and is highly ***,on the premise of ensuring security,the process of verifying the signature of the root certificate in the traditional cross-domain authentication protocol is improved to verify the hash value of the root certificate,thereby improving the authentication *** developed prototype exhibits generality and simplicity compared to previous methods.

关键词： public key infrastructure identity-based encryption cross-domain authentication blockchain

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Identifying common signatures and potential therapeutic biomarkers in COPD and lung cancer using miRNA-mRNA co-expression networks

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Informatics in Medicine Unlocked 2022年 34卷

作者： Fathinavid, Amirhossein Mousavian, Zaynab Najafi, Ali Nematzadeh, Sajjad Salimi, Mahdieh Masoudi-Nejad, Ali Department of Computer Engineering College of Engineering Hamedan Branch Islamic Azad University Hamedan Iran Laboratory of Systems Biology and Bioinformatics (LBB) Institute of Biochemistry and Biophysics University of Tehran Tehran Iran Department of Computer Science School of Mathematics Statistics and Computer Science University of Tehran Tehran Iran Molecular Biology Research Center System Biology and Poisoning Institute Tehran Iran Computer Engineering Department Architecture and Engineering Faculty Nisantasi University Istanbul Turkey Department of Medical Genetics Institute of Medical Biotechnology National Institute of Genetic Engineering and Biotechnology (NIGEB) Tehran Iran

The association between non-small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) is now well established, as people with COPD are more likely to develop lung carcinoma. However, the evidence for this relationship is inconclusive and there is currently little information on the underlying molecular mechanisms. MicroRNAs (miRNAs) are one of the regulatory factors in NSCLC and COPD that their functions are widely studied in many chronic diseases and cancers. In this study, we applied systems biology approaches to identify and predict miRNAs that potentially play regulatory roles between COPD and NSCLC. We performed differential expression analysis on public miRNA and mRNA expression datasets, for both of diseases, and then we reconstructed two miRNA-mRNA co-expression networks and merged these two co-expression networks into a community co-expression network. Results indicated the existence of very common miRNAs (ex. hsa-miR-326 and hsa-miR-1293) and mRNAs (such as FAT2, ALOX5AP, and LDB2) between the two mentioned diseases. Moreover, we discovered specific miRNAs (hsa-miR-574-3p) that targeted common mRNAs. We utilized drug-target interaction networks to identify candidate drugs for common mRNAs, which can be considered in the treatment of two diseases (e.g. iloperidone). Generally, our study highlighted common miRNAs between COPD and NSCLC that as new signatures or biomarkers for therapeutic purposes. Investigating the miRNA biomarkers in this study improves our understanding about the shared mechanisms between COPD and NSCLC. © 2022

关键词： Co-expression networks Community networks COPD miRNA-mRNA network Non-small cell lung cancer

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Students Online Exam Proctoring: A Case Study Using 360 Degree Security Cameras

Students Online Exam Proctoring: A Case Study Using 360 Degr...

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2020 International Conference on Emerging Technology in Computing, Communication and Electronics, ETCCE 2020

作者： Turani, Aiman A Alkhateeb, Jawad H Alsewari, AbdulRahman A. Taibah University Information System Department AlMadinah Almunawarah Saudi Arabia Taibah University Computer Science Department AlMadinah Almunawarah Saudi Arabia Faculty of Computing Software Engineering Department Pekan Pahang Malaysia

ISBN: (纸本)9781665419628

Online courses, online exams and online certificates are conducted by various universities and Information Technology (IT) institutes worldwide. Delivery tools have been created for conducting the exams from any place. Applying this will lead saving time and travelling cost. Nowadays, due to the COVID-19 pandemic, there is a big demand on the online courses and exams. This paper introduces a new approach for exam proctoring using 360-degree security camera. Mainly, online exams' security is a major concern. Thus, a delivery tools must not only ensure the identity of a test-taker but also the overall test integrity. In this paper, the usage of the 360-degree security camera over the traditional webcam was investigated in order to enhance the exam security and to minimize the stressful restrictions. To verify this goal, a case study on a group of volunteer students within the college of computer science and engineering was made. In addition, an automated proctoring model that will eliminate the need for a real-time proctoring and remove any scheduling constraints in order to prevent cheating is proposed in this paper. The machine learning algorithms is exploited to enrich the proposed system. A secure frame work using the biometric is applied in order to ensure authentication and running the online exam smoothly. © 2020 IEEE.

关键词： Students

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Research and implementation of complex task based on DMP 9

Research and implementation of complex task based on DMP

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Jia, Jie Wang, Yucan Zuo, Guoyu Cao, Yilin Yu, Naigong Beijing University of Technology Faculty of Information Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China University of Science and Technology School of Computer and Communication Engineering Beijing China

Aiming at the problem of poor task versatility in the strategy learning of complex tasks and cannot be generalized to obstacle environments, a method for robots learning from demonstration based on Dynamic Movement Primitive (DMP) is proposed. This method divides the demonstration task into several subtasks, and uses DMP to model each subtask. We utilize the local weighted regression algorithm to learn the corresponding weight of each subtask. Then the task trajectory is obtained by sequentially combining the generated subtask trajectory. The obstacle avoidance coupling item is added to the DMP framework to generate the obstacle avoidance task trajectory. The UR5 robotic arm is used to perform grasp and place tasks on the simulation platform as a demonstration task to verify the method in this article. © 2020 IEEE.

关键词： Trajectories

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Employee performance assessment system based on smart method (case study: Banda Aceh Military Court I-01)

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AIP Conference Proceedings 2023年第1期2484卷

作者： Zalfie Ardian Arifah Che Alhadi Gusti Mas Panji 1Department of Information System Faculty of Computer Science Universitas Ubudiyah Indonesia Indonesia 2Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia 3Department of Informatics Engineering Faculty of Computer Science Universitas Ubudiyah Indonesia Indonesia

Employee performance assessment is the evaluation of the employee's performances recorded at the end of every month. This approach is currently used at the Military Court Office I-01 Banda Aceh. The main aim of this assessment is to measure employee's performances in achieving their targets. The results will be used as the measuring key, where an employee is only eligible to receive the allowance, if the targets are successfully fulfilled. At this moment, the assessment form has to be filled in manually by each employee, and they will be later assessed manually by the assessors. This manual process undeniably has many disadvantages, especially in terms of accuracy and efficiency. To solve this problem, the Employee Performance Information system was designed using the SMART (Simple Multi Attribute Technique). The assessments were based on eight indicators, i.e; performance, attendance, the proportion of performance targets, behavioral scores, number of tasks, services, overtime, and monthly rewards earned. The weights for each variable were assessed, and keyed into the system. The values for each variable were compared, and results were generated. In SMART, the weighting is measured as a scale between 0 and 10, thus it is easier to make calculations and comparison. The obtained results (SI-TUKIN) indicated that the system is capable of evaluating and analysing the employee's performances, quickly and effectively.

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Image-based Freeform Handwriting Authentication with Energy-oriented Self-Supervised Learning

arXiv

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arXiv 2024年

作者： Wang, Jingyao Mou, Luntian Zheng, Changwen Gao, Wen The University of Chinese Academy of Sciences Beijing100049 China The National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing100086 China Beijing Institute of Artiicial Intelligence Faculty of Information Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Multimedia and Intelligent Software Technology Beijing100124 China The School of Electronics Engineering and Computer Science Peking University Beijing100871 China

Freeform handwriting authentication verifies a person’s identity from their writing style and habits in messy handwriting data. This technique has gained widespread attention in recent years as a valuable tool for various fields, e.g., fraud prevention and cultural heritage protection. However, it still remains a challenging task in reality due to three reasons: (i) severe damage, (ii) complex high-dimensional features, and (iii) lack of supervision. To address these issues, we propose SherlockNet, an energy-oriented two-branch contrastive self-supervised learning framework for robust and fast freeform handwriting authentication. It consists of four stages: (i) pre-processing: converting manuscripts into energy distributions using a novel plug-and-play energy-oriented operator to eliminate the influence of noise;(ii) generalized pre-training: learning general representation through two-branch momentum-based adaptive contrastive learning with the energy distributions, which handles the high-dimensional features and spatial dependencies of handwriting;(iii) personalized fine-tuning: calibrating the learned knowledge using a small amount of labeled data from downstream tasks;and (iv) practical application: identifying individual handwriting from scrambled, missing, or forged data efficiently and conveniently. Considering the practicality, we construct EN-HA, a novel dataset that simulates data forgery and severe damage in real applications. Finally, we conduct extensive experiments on six benchmark datasets including our EN-HA, and the results prove the robustness and efficiency of SherlockNet. We will release our code and dataset at https://***/WangJingyao07/SherlockNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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Development of heterogeneous database synchronization algorithm based on entity relationship model approach

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AIP Conference Proceedings 2023年第1期2484卷

作者： Ayu Helinda Zuhar Musliyana Teuku Yuliar Arif Zalfie Ardian Zuriana Abu Bakar Zulaida Rahmi Mutiawati 1Informatic Engineering Department Faculty of Computer Science Ubudiyah Indonesia University Indonesia 2Information System Department Faculty of Computer Science Ubudiyah Indonesia University Indonesia 3Electrical and Computer Engineering Department Faculty of Engineering Syiah Kuala University Indonesia 4Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia 5Faculty of Education Science Ubudiyah Indonesia University Indonesia

Nowadays, database technology keeps evolving and available on various platforms. However, the use of heterogeneous database had a limitation because each database only provides a synchronization method for similar types of databases. Therefore, the utilization of various types of databases becoming a problem since the entire data among the databases need to be integrated. Previous research had examined heterogeneous database synchronization algorithms on mobile devices using message digest. Nevertheless, this algorithm requires a longer synchronization time because necessity to check the hash value of each data record. Thus, this study investigates the development of a multi-platform database synchronization algorithm using the Entity Relationship (ER) model. This model is based on the data relationships in each table. ER model implementation is executed by creating a temporary table that stores the primary key of each data record in a table that has changed or consist new data. The synchronization process flow is determined based on the type of transaction by selecting data from the source table based on the relationship from the temporary table data to the destination database. The results of this study indicates that the proposed ER model could be a new method in the heterogeneous database synchronization process and is able to shorten the synchronization process time.

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Mobile Malaysian Sign Language Application

Mobile Malaysian Sign Language Application

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Advancement in Data science, E-learning and Information systems (ICADEIS), International Conference on

作者： Lye Chee Hao Ryan Adhitya Nugraha Mohd Farhan Md Fudzee Mohd Norasri Ismail Dedy Syamsuar Che Samihah Dalim Deden Witarsyah Norhalina Senan Iis Kurnia Nurhayati Maria Apsari Sugiat Faculty of Computer Science and IT Universiti Tun Hussein Onn Malaysia Parit Raja MALAYSIA School of Industrial Engineering Telkom University Bandung INDONESIA School of Information System Bina Nusantara University Jakarta INDONESIA School of Communication and Business Telkom University Indonesia Bandung INDONESIA Faculty of Economics and Business Telkom University Indonesia Bandung INDONESIA

ISBN: (纸本)9781665463881

Due to the Covid-19 plague, children with hearing misfortune have experienced challenges in learning and practicing sign language due to need of educational services and learning assets. The next considerations for creating an educational mobile learning application to help deaf kids learn Malaysian Sign Language (MSL). The investigation was conducted through gatherings based on inquire about and interviews with subject matter experts. Instructors recommend that within the current circumstance, versatile learning application are the foremost reasonable stage for understudies to memorize or as an extra learning strategy in arrange to educate them well. This research was conducted through research-based and interview sessions with subject matter experts and followed the Multimedia Mobile Content Development (MMCD) methodology as it was shown to help accelerate development activities and ensure that the application would work and execute as planned. Once the application is developed, students from Sekolah Kebangsaan Silabukan in Lahad Datu, Sabah, will participate in beta testing. Based on the results of user acceptance tests, the application has received positive reviews from its target users. As such, the project's goals are said to have been achieved. At the conclusion of the study, the advantages, limitations and future work of Pocket Sign Language were also identified.

关键词： Gesture recognition Games Assistive technologies Data science Mobile learning Object recognition Interviews

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2D Mobile Vocab Library Learning Application

2D Mobile Vocab Library Learning Application

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Advancement in Data science, E-learning and Information systems (ICADEIS), International Conference on

作者： Heng Seng Zhou Ryan Adhitya Nugraha Mohd Farhan Md Fudzee Muhammad Fakri Othman Dedy Syamsuar Azizan Ismail Deden Witarsvah Suriawati Suparjoh Iis Kurnia Nurhayati Maria Apsari Sugiat Faculty of Computer Science and IT Universiti Tun Hussein Onn Malaysia Parit Raja MALAYSIA School of Industrial Engineering Telkom University Bandung INDONESIA School of Information System Bina Nusantara University Jakarta INDONESIA School of Communication and Business Telkom University Indonesia Bandung INDONESIA Faculty of Ecomonics and Business Telkom University Indonesia Bandung INDONESIA

ISBN: (纸本)9781665463881

Technology is continuously evolving nowadays, and learners are exposed to digital devices at an early stage. It will lead learners to use digital devices to learn or play with instead of using books or traditional puzzle games. Thus, this project will develop an English Language vocabulary learning application using 2D learning content applying an information- based learning and quiz approach, and 2D gamification approach in the game module and executed on the Android platform. Furthermore, the Multimedia Mobile Content Development (MMCD) methodology is selected and used to develop the V ocab Library application is to ensure that the development process can run smoothly and efficiently as planned. This paper is based on the research from online journals and the questionnaire that had distributed. The Vocab Library application is appropriate for 7-year-old target users to learn English vocabulary on a mobile platform, based on the good feedback received from the target users. Lastly, this learning application is designed to help today's children understand and learn English vocabulary, which will benefit children's future.

关键词： Vocabulary Electronic learning Operating systems Personal digital devices Games Data science Libraries

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Deep Learning Based Application To Detect Face Masks For Health Protocol Surveillance During The Covid-19 Pandemic

Deep Learning Based Application To Detect Face Masks For Hea...

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Information Technology International Seminar (ITIS)

作者： Yisti Vita Via Eva Yulia Puspaningrum Dicky Giancini Arwindo Kurniawan Salamun Rohman Nudin Nurfiana Mochammad Syahrul Munir Department of Informatics Faculty of Computer Science Universitas Pembangunan Nasional Veteran Jawa Timur Surabaya Indonesia Departement of Informatics Faculty of Engineering Universitas Negeri Surabaya Surabaya Indonesia Department of Computer System Faculty of Computer Science Institut Informatika dan Bisnis Darmajaya Lampung Indonesia Departement of Tata Laksana Studio Produksi Akademi Komunitas Negeri Pacitan Pacitan Indonesia

ISBN: (纸本)9781665408080

As part of preventing the rapid spread of the COVID-19 virus, masks should be used besides physical distancing, avoiding crowds, setting good ventilation, cleaning hands, and more. In fact, there are still many people who do not use masks in public places. Security officers usually carry out the supervision system for the use of masks in public places. Direct interaction between security officers and many visitors in the long term will trigger a high risk of being infected. It is better if there is a system that can monitor the use of masks automatically and continuously. In this study, a deep learning algorithm with YOLOv3 architecture is applied to a web-based mask detection system. YOLOv3 is one of the best algorithms that has been widely applied and optimized by researchers for object detection. This system has been tested in two scenarios using different data sets, namely without augmentation and with augmentation. For each scenario, three experiments were carried out using varying amounts of training data, namely 10, 100, and 800. The best mAP and confidence values were obtained from experiments using 800 training data with augmentation. This mAP value is 0.99 with a confidence value range between 0.9 to 1.

关键词： COVID-19 Training Deep learning Face recognition Surveillance Training data Streaming media

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