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Texture and Orientation-based Feature Extraction for Robust Facial Expression Recognition 21

Texture and Orientation-based Feature Extraction for Robust ...

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21st IEEE/ACIS International Conference on software engineering Research, Management and Applications, SERA 2023

作者： Khan, Sajid Ali Bin Abdulrahman Alawairdhi, Mohammed Al-Akhras, Mousa Foundation University Islamabad Department of Software Engineering Islamabad Pakistan Saudi Electronic University College of Computing and Informatics Saudi Arabia The University of Jordan Amman King Abdullah II School for Information Technology Computer Information Systems Department Jordan

ISBN: (纸本)9798350345889

Facial expressions are the most effective way to characterize people's motives, emotions, and feelings. Several new methods are proposed each year;however, the accuracy of facial expression recognition still needs to be improved especially in uncontrolled conditions. In this paper, we propose a hybrid facial expression model that considers both texture and orientation features to classify expressions. Two types of descriptors namely Local binary pattern and Weber local descriptor are used to preserve the local intensity information and orientation of edges. In the next step, computing the Histograms of oriented gradients (HOG) features from the Local binary pattern and Weber local descriptor images to capture micro-expressions. Then, the AdaBoost feature selection algorithm is utilized to choose the best features from the combined HOG features. The results of the experiments demonstrate that the method proposed in this study performs better than existing methods. © 2023 IEEE.

关键词： Local binary pattern

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Impersonated Human Speech Chatbot with Adaptive Frequency Spectrum 3

Impersonated Human Speech Chatbot with Adaptive Frequency Sp...

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3rd International Conference on Intelligent Communication and Computational Techniques, ICCT 2023

作者： Chettiar, Gautam Shukla, Amogh Nalwaya, Preet Sethi, Karman Prakash, Surya Vellore Institute of Technology Dept. of Communication Engineering Vellore India Department of Software Systems Vellore Institute of Technology Vellore India Indian Institute of Information Technology Allahabad Department of Electronics and Communication Engineering Prayagraj India

ISBN: (纸本)9781665453578

Recent trends in artificial intelligence and natural language processing models have led to the generation of highly efficient and versatile intelligent chatbot models., which have the potential to supplant human speech to the level of conversational proficiency. The proposed method creates a chatbot model that trains itself on open conversation datasets and aims to impersonate without compromising the emotional sentiments in the voice. These datasets extract from the applications such as WhatsApp., Telegram., Messenger., or any other chatting platform. Datasets convert to a machine-readable format., which is dynamically updated in real-time during the conversation., and then using speech conversion algorithms convert the reply into the desired individual's voice. The proposed model's conversational ability depends on the amount of conversation data., which gives the output in the person's voice frequency. By using an NLP-based chatbot trained on personalized data using KNN., and handling misses by pipelining the chatbot inputs to the GPT-2 model., the model can generate human-like replies even if there is data insufficiency. The natural replies are complemented with matching human voice and tone characteristics by using the vocoder model., which matches the spectral characteristics of the target voice onto the required voice. This opens a plethora of commercial and therapeutic applications that provide excellent insights into implementing natural communication models for humanoid and robotics innovations. © 2023 IEEE.

关键词： Sentiment analysis

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Don't Forget the Exception! : Considering Robustness Changes to Identify Design Problems 20

Don't Forget the Exception! : Considering Robustness Changes...

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20th IEEE/ACM International Conference on Mining software Repositories, MSR 2023

作者： Oliveira, Anderson Correia, Joao Sousa, Leonardo Assuncao, Wesley K. G. Coutinho, Daniel Garcia, Alessandro Oizumi, Willian Barbosa, Caio Uchoa, Anderson Pereira, Juliana Alves Informatics Department - Pontifical Catholic Rio de Janeiro Brazil Carnegie Mellon University Department of Electrical and Computer Engineering Pittsburgh United States Institute of Software Systems Engineering Linz Austria Itapajé Brazil

ISBN: (纸本)9798350311846

Modern programming languages, such as Java, use exception-handling mechanisms to guarantee the robustness of software systems. Although important, the quality of exception code is usually poor and neglected by developers. Indiscriminate robustness changes (e.g., the addition of empty catch blocks) can indicate design decisions that negatively impact the internal quality of software systems. As it is known in the literature, multiple occurrences of poor code structures, namely code smells, are strong indicators of design problems. Still, existing studies focus mainly on the correlation of maintainability smells with design problems. However, using only these smells may not be enough since developers need more context (e.g., system domain) to identify the problems in certain scenarios. Moreover, these studies do not explore how changes in the exceptional code of the methods combined with maintainability smells can give complementary evidence of design problems. By covering both regular and exception codes, the developer can have more context about the system and find complementary code smells that reinforce the presence of design problems. This work aims to leverage the identification of design problems by tracking poor robustness changes combined with maintainability smells. We investigated the correlation between robustness changes and maintainability smells on the commit history of more than 160k methods from different releases of 10 open-source software systems. We observed that maintainability smells can be worsened or even introduced when robustness changes are performed. This scenario mainly happened for the smells Feature Envy, Long Method, and Dispersed Coupling. We also analyzed the co-occurrence between robustness and maintainability smells. We identified that the empty catch block and catch throwable robustness smells were the ones that co-occurred the most with maintainability smells related to the Concern Overload and Misplaced Concern design problems. T

关键词： Maintainability

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A study of media texts in the Slovak language

A study of media texts in the Slovak language

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Zooming Innovation in Consumer Electronics International Conference (ZINC)

作者： Given Igor Stupavský Given Valentino Vranić Faculty of Informatics and Information Technologies Institute of Informatics Information Systems and Software Engineering Brastislava 4 Slovakia

ISBN: (数字)9781665483742

ISBN: (纸本)9781665483759

Nowadays, it is difficult to determine the veracity of the information obtained. Communication takes place through websites, discussions, social networks, and the like. Using various anti-social behavior tips, such as fake news, their disseminates want to gain various benefits or convince the recipient of “their truth.” The theoretical part of the work is focused on different approaches to the detection of antisocial behavior. In the experimental part of this work, we will deal with the analysis of the statuses of opinion-forming dailies in the Slovak language, which we obtained from the social network Facebook. NLP message analysis is not accurate enough, and we create an algorithm that is better identifies POS tags.

关键词： Technological innovation Social networking (online) Conferences Data collection Tagging Behavioral sciences Fake news

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Threat Modeling to Design a Decentralized Health Data Management Application

Threat Modeling to Design a Decentralized Health Data Mana...

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International Conference on information Technology and systems, ICITS 2023

作者： Erler, Christina Hu, Shanshan Danelski, Alexa Stork, Wilhelm Sunyaev, Ali Gersch, Martin Embedded Systems and Sensors Engineering FZI Research Center for Information Technology Karlsruhe76131 Germany Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Information Systems Free University of Berlin Berlin14195 Germany Institute for Information Processing Technologies Karlsruhe Institute of Technology Karlsruhe76131 Germany

ISBN: (纸本)9783031332609

Decentralized applications are increasingly recognized as efficient tools to overcome security challenges in the management of highly sensitive health information. However, research still lacks the understanding of how to address the complex security challenges in the design of health data management applications (HDMAs). In this study, we structurally analyzed security requirements of health data management systems to improve the efficiency of their design. We leveraged threat modeling to inform the design of HDMAs and proposed the system architecture accordingly to facilitate the security of interorganizational health data exchange. Our results contribute to the exaptation of threat modeling to the innovative design of decentralized applications for health data management and to the exploration of benefits of decentralization for healthcare. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： information management

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State-based Sandbox Tool for Distributed Malware Detection with Avoid Techniques 13

State-based Sandbox Tool for Distributed Malware Detection w...

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13th International Conference on Dependable systems, Services and Technologies, DESSERT 2023

作者： Rehida, Pavlo Markowsky, George Sachenko, Anatoliy Savenko, Oleg Khmelnytskyi National University Department of Computer Engineering and Information Systems Khmelnytskyi Ukraine Kennesaw State University Department of Software Engineering and Game Development Marietta United States Kazimierz Pulaski University of Technology and Humanities Department of Informatics Radom Poland Research Institute for Intelligent Computer Systems West Ukrainian National Unversity Ternopil Ukraine

ISBN: (纸本)9798350396119

This paper deals with the problem of detecting the malware by using emulation approach. Modern malware include various avoid techniques, to hide its anomaly actions. Advantages of using sandbox and emulation technologies are described. Various anti-emulation techniques that are used in modern malware considered. Obfuscation as one primary approach to hide malware malicious actions described and discussed. State of emulator is presented, and the advantages of its usage are covered. Distributed model for malware detection is considered. Basic emulator and its current capabilities presented. Prepared files that represent malware are described. Experimental results for developed files that differs with included avoid techniques are presented. Disadvantages of proposed approach is described. Future research and sandbox improvement are described. © 2023 IEEE.

关键词： anti-emulation techniques malware detection obfuscation techniques sandbox

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RobFL: Robust Federated Learning via Feature Center Separation and Malicious Center Detection 40

RobFL: Robust Federated Learning via Feature Center Separati...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Zhou, Ting Liu, Ning Song, Bo Lv, Hongtao Guo, Deke Liu, Lei National University of Defense Technology Science and Technology Laboratory on Information Systems Engineering Changsha China School of Software Shandong University Jinan China Shandong Research Institute of Industrial Technology Jinan China

ISBN: (纸本)9798350317152

In recent years, the integration of federated learning and deep learning technologies has become increasingly prevalent in privacy-preserved scenarios, such as smart health applications and automatic financial support. However, the inherent robustness issue in deep learning poses potential risks to federated learning systems when subjected to various attack methods. These attacks can inflict damage during the training and testing phases, perturbing models and inputs. To enhance the robustness of existing federated learning systems, we propose a novel framework called RobFL. This framework incorporates a unique feature learning module -feature center separation learning -that is specifically designed to increase the margins between different classes in the feature space, thereby augmenting the difficulty of attacks employing imperceptible perturbations on inputs. Furthermore, we design a malicious center detection method to detect malicious clients and mitigate their adverse impact. Extensive experiments substantiate the robustness of our proposed framework, RobFL, demonstrating its resilience against both evasion attacks and poisoning attacks. © 2024 IEEE.

关键词： Anomaly detection

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Common Code Quality Issues of Novice Java Programmers: A Comprehensive Analysis of Student Assignments 15

Common Code Quality Issues of Novice Java Programmers: A Com...

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15th International Conference on Computer Supported Education, CSEDU 2023

作者： Kohlbacher, Christina Julia Vierhauser, Michael Groher, Iris Institute of Business Informatics - Software Engineering JKU Business School Johannes Kepler University Linz Austria LIT Secure and Correct Systems Lab Johannes Kepler University Linz Austria

ISBN: (纸本)9789897586415

Starting to learn programming is often perceived as being quite tedious by students at the bachelor level. Many programming courses thus face high drop-out rates and moderate results for those who pass. This problem is exacerbated when teaching programming to students enrolled in non-computer science curricula. To overcome these issues, we have developed a novel didactic concept based on peer learning, tutoring, dedicated teaching, and learning material that supports individuality and competency-based learning. Our current focus lies on teaching basic programming principles, but to further support our students and foster a positive learning experience, we want to learn more about the difficulties they are facing, particularly with respect to best practices, coding conventions, and code quality. We, therefore, performed a static code analysis of homework assignments of students participating in our introductory programming course for two consecutive years. We analyzed over 13,000 Java files and more than 400,000 lines of Java code to identify common code quality issues faced by our students. Our analysis shows that the majority of rule violations are related to coding style. The violations do not differ much with respect to the topics covered in the homework assignments, and hardly change over time. The more lines of code the students write, the more rules are violated. Based on our findings we present concrete recommendations on how to support novice programmers in improving their code quality. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Students

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Predicting the Performance of ATL Model Transformations 23

Predicting the Performance of ATL Model Transformations

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14th Annual ACM/SPEC International Conference on Performance engineering, ICPE 2023

作者： Groner, Raffaela Bellmann, Peter Höppner, Stefan Thiam, Patrick Schwenker, Friedhelm Tichy, Matthias Institute of Software Engineering and Programming Languages Ulm University Ulm Germany Institute of Neural Information Processing Ulm University Ulm Germany Institute of Medical Systems Biology Ulm University Ulm Germany

ISBN: (纸本)9798400700682

Model transformation languages are special-purpose languages, which are designed to define transformations as comfortably as possible, i.e., often in a declarative way. Typically, developers create their transformations based on small input models which systematically cover the language of the input models. This makes it difficult for the developers to estimate how the transformations would perform for a large and diverse set of input models. Hence, developers would benefit from an approach for predicting the performance of model transformations based on just abstract characteristics of input models. Regression approaches based on machine learning lend themselves well to such predictions. However, it is currently unknown, whether and which regression approach is suitable in this context as well as how a model should be abstractly characterized for this purpose. We conducted several experiments to analyze how well different machine learning methods predict the execution time of model transformations defined in the Atlas Transformation Language (ATL) transformations for distinct sets of model characteristics. As possible methods, we have investigated linear regression, random forests and support vector regression using a radial basis function kernel. The results of our experiments show that support vector regression is the best choice in terms of usability and prediction accuracy for the model transformation modules covered in our experiments and is thus suited for a prediction approach. In addition, simple model characterizations based only on the number of model elements, the number of references, and the number of attributes are a suitable way to easily describe a model and to achieve decent prediction accuracy. © 2023 Owner/Author.

关键词： Forecasting

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An Exploratory Case Study on Effort Estimation in Microservices 49

An Exploratory Case Study on Effort Estimation in Microservi...

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49th Euromicro Conference on software engineering and Advanced Applications, SEAA 2023

作者： Unlu, Huseyin Hacaloglu, Tuna Omural, Neslihan Kucukates Caliskanel, Neslihan Leblebici, Onur Demirors, Onur Izmir Institute of Technology Computer Engineering Izmir Turkey Atilim University Information Systems Engineering Ankara Turkey Middle East Technical University Informatics Institute Ankara Turkey Univera Inc. Izmir Turkey

ISBN: (纸本)9798350342352

software project management plays an important role in producing high-quality software, and effort estimation can be considered as a backbone for successful project management. Size is a very significant attribute of software by being the only input to perform early effort estimation. Even though functional size measurement methods showed successful results in effort estimation of traditional data-centric architectures such as monoliths, they were not designed for today's architectures which are more service-based and decentralized such as microservices. In these new systems, the event concept is highly used specifically for communication among different services. By being motivated by this fact, in this study, we looked for more microservice-compatible ways of sizing microservices using events and developed a method accordingly. Then, we conducted an exploratory case study in an organization using agile methods and measured the size of 17 Product Backlog Items (PBIs) to assess how this proposed method can be useful in effort estimation in microservices. The implication from the case study is that despite performing a more accurate effort estimation using the proposed size measurement than COSMIC, we were unable to significantly outperform using the total number of events. However, our suggested approach demonstrated to us a different way to use software size in terms of events, namely, to determine the coupling complexity of the project. This finding can be beneficial specifically when evaluating the change requests. © 2023 IEEE.

关键词： Project management

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