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2023 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2023

作者： Cleaver, Nathan Neshatian, Kourosh University of Canterbury Department of Computer Science and Software Engineering Christchurch New Zealand

ISBN: (纸本)9798350341072

Transfer learning is the ability to transfer knowledge from one context to another. This paper investigates, for the first time, the possibility of transfer learning on Monte Carlo Tree Search (MCTS). We use distributed parallel MCTS to construct game-playing models for one variant of chess and then transfer these models to another domain to play a different variant of chess. We also introduce a novel pruning mechanism for MCTS to cope with memory requirements of large game trees. Our results show that positive transfer learning in MCTS is possible, and in our case, highly successful. Transferred models significantly outperform models that have to be trained from scratch. © 2023 IEEE.

关键词： Monte Carlo methods

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PROGRESSIVE VORONOI DIAGRAM SUBDIVISION ENABLES ACCURATE DATA-FREE CLASS-INCREMENTAL LEARNING 11

PROGRESSIVE VORONOI DIAGRAM SUBDIVISION ENABLES ACCURATE DAT...

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11th International Conference on Learning Representations, ICLR 2023

作者： Ma, Chunwei Ji, Zhanghexuan Huang, Ziyun Shen, Yan Gao, Mingchen Xu, Jinhui Department of Computer Science and Engineering University at Buffalo United States Computer Science and Software Engineering Penn State Erie United States

Data-free Class-incremental Learning (CIL) is a challenging problem because rehearsing data from previous phases is strictly prohibited, causing catastrophic forgetting of Deep Neural Networks (DNNs). In this paper, we present iVoro, a novel framework derived from computational geometry. We found Voronoi Diagram (VD), a classical model for space subdivision, is especially powerful for solving the CIL problem, because VD itself can be constructed favorably in an incremental manner - the newly added sites (classes) will only affect the proximate classes, making the non-contiguous classes hardly forgettable. Furthermore, we bridge DNN and VD using Power Diagram Reduction, and show that the VD structure can be progressively refined along the phases using a divide-and-conquer algorithm. Moreover, our VD construction is not restricted to the deep feature space, but is also applicable to multiple intermediate feature spaces, promoting VD to be multilayer VD that efficiently captures multi-grained features from DNN. Importantly, iVoro is also capable of handling uncertainty-aware test-time Voronoi cell assignment and has exhibited high correlations between geometric uncertainty and predictive accuracy (up to ∼0.9). Putting everything together, iVoro achieves up to 25.26%, 37.09%, and 33.21% improvements on CIFAR-100, TinyImageNet, and ImageNet-Subset, respectively, compared to the state-of-the-art non-exemplar CIL approaches. In conclusion, iVoro enables highly accurate, privacy-preserving, and geometrically interpretable CIL that is particularly useful when cross-phase data sharing is forbidden, e.g. in medical applications. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Deep neural networks

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Early Diagnosis of Lung Tumors for Extending Patients’ Life Using Deep Neural Networks

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computers, Materials & Continua 2023年第7期76卷 993-1007页

作者： A.Manju R.Kaladevi Shanmugasundaram Hariharan Shih-Yu Chen Vinay Kukreja Pradip Kumar Sharma Fayez Alqahtani Amr Tolba Jin Wang Department of Computer Science and Engineering SRM Institute of Science and TechnologyRamapuramChennaiIndia Department of Computer Science and Engineering Saveetha Engineering CollegeChennaiIndia Department of Computer Science and Engineering Vardhaman College of EngineeringHyderabadIndia Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin 64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin 64002Taiwan Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Department of Computing Science University of AberdeenAberdeenUK Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh 12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh 11437Saudi Arabia School of Computer&Communication Engineering Changsha University of Science&TechnologyChangshaChina

The medical community has more concern on lung cancer *** experts’physical segmentation of lung cancers is time-consuming and needs to be *** research study’s objective is to diagnose lung tumors at an early stage to extend the life of humans using deep learning ***-Aided Diagnostic(CAD)system aids in the diagnosis and shortens the time necessary to detect the tumor *** application of Deep Neural Networks(DNN)has also been exhibited as an excellent and effective method in classification and segmentation *** research aims to separate lung cancers from images of Magnetic Resonance Imaging(MRI)with threshold *** Honey hook process categorizes lung cancer based on characteristics retrieved using several *** this principle,the work presents a solution for image compression utilizing a Deep Wave Auto-Encoder(DWAE).The combination of the two approaches significantly reduces the overall size of the feature set required for any future classification process performed using *** proposed DWAE-DNN image classifier is applied to a lung imaging dataset with Radial Basis Function(RBF)*** study reported promising results with an accuracy of 97.34%,whereas using the Decision Tree(DT)classifier has an accuracy of 94.24%.The proposed approach(DWAE-DNN)is found to classify the images with an accuracy of 98.67%,either as malignant or normal *** contrast to the accuracy requirements,the work also uses the benchmark standards like specificity,sensitivity,and precision to evaluate the efficiency of the *** is found from an investigation that the DT classifier provides the maximum performance in the DWAE-DNN depending on the network’s performance on image testing,as shown by the data acquired by the categorizers themselves.

关键词： Lung tumor deep wave auto encoder decision tree classifier deep neural networks extraction techniques

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20 Years of EPICS at Butler University: Experiences and Lessons Learned 53

20 Years of EPICS at Butler University: Experiences and Less...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Johnson, Lucas Linos, Panagiotis Butler University Computer Science and Software Engineering Department IndianapolisIN United States

ISBN: (纸本)9798350336429

This research-to-practice full paper discusses experiences and lessons learned from our EPICS@BUTLER (engineering Projects in Community Service at Butler) program. The program, housed within the department of computer science and software engineering, is part of a college of Liberal Arts and sciences and serves a diverse population of students with multi-disciplinary backgrounds. The EPICS curriculum is driven by a team-based service-learning pedagogical model. EPICS teams learn how to work together effectively while addressing the immediate IT needs of our non-profit partner clients, navigating their budgetary restrictions, and coping with any lack of existing IT infrastructure. During the 2020/2021 academic year, we launched an empirical study to review and assess EPICS@BUTLER. The study's main goal was to learn from the past 20 years of running the EPICS program by soliciting input from all parties involved. We aimed to improve and expand our service-learning model within an LAS context. More specifically, this study included surveying alumni and current undergraduate students in order to understand the successes and areas of potential improvement within our program. In addition, we conducted one-on-one interviews with our community non-profit partners as well as volunteer team mentors to assess the program's effectiveness and community impact. Based on the empirical data we gathered and analyzed, we discuss how the existing curriculum is effective at providing fulfilling experiences which help our alumni secure jobs after graduation. In addition, we found that the practice of allowing supervised teams to navigate their own EPICS projects helps them improve their professional maturity and interpersonal skills. In summary, this paper discusses an empirical study and aims to leverage the results gathered from our surveys and interviews in order to present a plan for continuous improvement and modernization of our on-going EPICS program. In closing, our paper descri

关键词： Course assessment EPICS Service-Learning software engineering Teamwork

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Assessing Secure OpenID-Based EAAA Protocol to Prevent MITM and Phishing Attacks in Web Apps

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computers, Materials & Continua 2023年第6期75卷 4713-4733页

作者： Muhammad Bilal Sandile C.Showngwe Abid Bashir Yazeed Y.Ghadi College of Computer Science and Technology Zhejiang UniversityHangzhou310027China Department of Mathematical Statistics and Actuarial Science Faculty of Natural and Agricultural SciencesUniversity of the Free StateBloemfontein9301South Africa Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAbu DhabiUAE

To secure web applications from Man-In-The-Middle(MITM)and phishing attacks is a challenging task *** this purpose,authen-tication protocol plays a vital role in web communication which securely transfers data from one party to *** authentication works via OpenID,Kerberos,password authentication protocols,***,there are still some limitations present in the reported security *** this paper,the presented anticipated strategy secures both Web-based attacks by leveraging encoded emails and a novel password form pattern *** proposed OpenID-based encrypted Email’s Authentication,Authorization,and Accounting(EAAA)protocol ensure security by relying on the email authenticity and a Special Secret Encrypted Alphanumeric String(SSEAS).This string is deployed on both the relying party and the email server,which is unique and *** first authentication,OpenID Uniform Resource Locator(URL)identity,is performed on the identity provider side.A second authentication is carried out by the hidden Email’s server side and receives a third authentication *** Email’s third SSEAS authentication link manages on the relying party(RP).Compared to existing cryptographic single sign-on protocols,the EAAA protocol ensures that an OpenID URL’s identity is secured from MITM and phishing *** study manages two attacks such as MITM and phishing attacks and gives 339 ms response time which is higher than the already reported methods,such as Single Sign-On(SSO)and *** experimental sites were examined by 72 information technology(IT)specialists,who found that 88.89%of respondents successfully validated the user authorization provided to them via *** proposed EAAA protocol minimizes the higher-level risk of MITM and phishing attacks in an OpenID-based atmosphere.

关键词： Secure user authentication SSO OpenID phishing attack MITM attack

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Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

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China Communications 2024年第7期21卷 135-148页

作者： Qasim Jan Yin Chao Pan Zhiwen Muhammad Furqan Zakir Ali You Xiaohu National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211100China Department of Computer Science National University of Computer and Emerging Sciences Peshawar Campus 25100Pakistan Department of Software Engineering Capital University of Science and Technology(CUST)Islamabad 44000Pakistan Department of Computer Sciences Bahria University Lahore CampusPakistan

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and *** alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update *** modified CS is further utilized for the identification of error-prone *** proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)*** gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),*** addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

关键词： belief propagation bit-flipping concatenated codes LDPC-CRC-Polar codes polar codes

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Optimization of Heterogeneous Coded Distributed Computing with Nonuniform Input File Sizes

Optimization of Heterogeneous Coded Distributed Computing wi...

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2024 IEEE International Performance, Computing, and Communications Conference, IPCCC 2024

作者： Liang, Jiasheng Zhang, Siyu Deng, Yong Lakehead University Department of Software Engineering Canada Binghamton University Department of Computer Science New York United States

ISBN: (纸本)9798350367942

This work considers the optimal design of MapReduce-based coded distributed computing (CDC) with nonuniform input file sizes. We propose an efficient heterogeneous CDC (HetCDC) scheme capable of handling an arbitrary number of files of nonuniform sizes. We further jointly optimize the file placement and coded shuffling strategies of the proposed HetCDC by formulating an integer linear programming (ILP) problem. Finally, the performance of the optimized HetCDC is verified by numerical studies. © 2024 IEEE.

关键词： Integer linear programming

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Use of Audience Response Systems to Enhance Student Engagement in Online Synchronous Environments: An Exploratory Study 27

Use of Audience Response Systems to Enhance Student Engageme...

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27th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2023

作者： Nesbit, Trevor Department of Computer Science and Software Engineering University of Canterbury Christchurch New Zealand

ISBN: (纸本)9781713880325

Many higher education institutions adapted to the Covid-19 pandemic by switching their teaching into online mode making use of online synchronous sessions using technologies such as Zoom. It was common for lecturers to find it disconcerting that many students were not turning on their cameras and microphones and how this made it difficult to ascertain whether their students were engaged in the sessions at all. This paper examines the experiences of teaching staff in eight courses relating to the use of audience response systems (ARS) to improve the experiences of students and teaching staff when conducting synchronous online teaching sessions or hybrid sessions when they had some face-face students and some online students joining sessions synchronously. Literature is examined that shows the benefits relating to the use of ARS in synchronous online teaching sessions to include anonymity of student responses;enhancement of feedback between teaching staff and students;and teaching staff getting a better sense of student engagement during a session. An analysis of the eight cases presented confirms these benefits in the literature from the perspective of the teaching staff. The findings apply irrespective of the ARS being used and will be of relevance and interest to any teaching staff seeking to improve the experiences of students and teaching staff involved in synchronous online teaching sessions. © 2023 Proceedings of World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI. All rights reserved.

关键词： Students

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Dm-Health App:Diabetes Diagnosis Using Machine Learning with Smartphone

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computers, Materials & Continua 2022年第7期72卷 1713-1746页

作者： Elias Hossain Mohammed Alshehri Sultan Almakdi Hanan Halawani Md.Mizanur Rahman Wahidur Rahman Sabila Al Jannat Nadim Kaysar Shishir Mia Department of Software Engineering Daffodil International UniversityDhaka1207Bangladesh Department of Computer Science Najran UniversityNajran55461Saudi Arabia Department of Computer Science and Engineering Rajshahi University of Engineering and TechnologyRajshahi6204Bangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversitySantoshTangail1902Bangladesh Department of Computer Science and Engineering BRAC UniversityDhaka1212Bangladesh Department of Computer Science and Engineering World University BangladeshDhaka1230Bangladesh

Diabetes Mellitus is one of the most severe diseases,and many studies have been conducted to anticipate *** research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic,pre-diabetic,or non-diabetic without the assistance of any physician or medical *** study’s methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture *** Diabetes Prediction Approach uses a novel approach,Light Gradient Boosting Machine(LightGBM),to ensure a faster *** Proposed System ArchitectureDesign has been combined into sevenmodules;the Answering Question Module is a natural language processing Chabot that can answer all kinds of questions related to *** Doctor Consultation Module ensures free treatment related to *** this research,90%accuracy was obtained by performing K-fold cross-validation on top of the K nearest neighbor’s algorithm(KNN)&*** evaluate the model’s performance,Receiver Operating Characteristics(ROC)Curve and Area under the ROC Curve(AUC)were applied with a value of 0.948 and 0.936,*** manuscript presents some exploratory data analysis,including a correlation matrix and survey ***,the proposed solution can be adjustable in the daily activities of a diabetic patient.

关键词： Machine learning diabetes-prediction support vector machine(SVM) LightGBM eHealth ROC-AUC

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A Method to Evaluate User-Centered Self-Adaptive Systems for Smart Environments 10

A Method to Evaluate User-Centered Self-Adaptive Systems for...

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10th International Conference on eDemocracy and eGovernment, ICEDEG 2024

作者： Avila, Marcelo Quito, Christian Valdez, Wilson Cardenas-Delgado, Paul Cedillo, Priscila Universidad de Cuenca Computer Science Department Cuenca Ecuador University of Szeged Software Engineering Department Szeged Hungary

ISBN: (纸本)9798350365535

With the advent of Industry 4.0, Ambient Intelligence, and other related technologies, self-Adaptation has been seen in modern systems. In this sense, Human-computer Interaction (HCI) requires an approach focused on the user and the environment, which facilitates and enhances the use of the systems. In this context, the quality of Self-Adaptive Systems (SAS) is essential for their adoption, dissemination, and service. Thus, this study introduces a detailed evaluation method to analyze the quality of HCI in SAS, providing a solution applicable to various contexts aligned with the standard ISO/IEC 25040. This study also presents a quality model aligned with the ISO/IEC 25010 standard. The quality evaluation method allows the objective definition for the measurement application through specific metrics that determine the degree of functional adequacy and interaction capability. Finally, this study demonstrates how to perform a detailed evaluation of the quality of HCI in SAS, using as an example the evaluation of the Spotify system as a case study, applying metrics to evaluate functional adequacy and interaction capacity aligned with ISO/IEC 25040 and 25010 standards. © 2024 IEEE.

关键词： ISO Standards

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