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11th International Conference on information and Communication technology, ICoICT 2023

作者： Kusuma, Wahyu Andhyka Hazri Bin Jantan, Azrul Mohd Norowi, Noris Binti Indriaty Admodisastro, Novia Universiti Putra Malaysi Informatics/Faculty of Computer Science and Information Technology Universitas Muhammadiyah Malang Malaysia Universiti Putra Malaysia Faculty of Computer Science and Information Technology Malaysia

ISBN: (纸本)9798350321982

Design solves the problem because the design positively correlates with performance improvement and simplifies some problems. Design thinking is a formal solution that solves problems creatively to increase product innovation. Frequently, to create solutions, developers will see from the perspective of products that are already on the market or use the latest technology to create design solutions;however, design thinking is a solution that uses the creativity of developers to create opportunities based on creativity from what already exists and can imagine the novelty of the product. The contradiction between solution and direction innovation emphasizes that both require variant design thinking practices. This research investigates several issues (i) the relationship between design thinking practices and constructs a value from a problem, and (ii) how to increase the value of this relationship to be moderated when the goal is determined to be solution innovation or direction innovation. This research contributes to providing increased value from the relationship between solution innovation and direction innovation according to the context of the problems faced. Moreover, developers can determine creative solutions that have value from a problem. By involving 137 freelance developers, researchers succeeded in proving that the UX Journey, a flexible design thinking-inspired model, can show that there is a positive relationship between the practice of user need elicitation and the value generated through design thinking is stronger for solution innovation than for direction innovation, with an average value of the solution is one (0.9136). © 2023 IEEE.

关键词： User experience

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Improved Accuracy of Decision Tree with XGBoost Technique in Cat Skin Disease Diagnosis 4

Improved Accuracy of Decision Tree with XGBoost Technique in...

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4th International Conference of science and information technology in Smart Administration, ICSINTESA 2024

作者： Safrina, Nanda Lydia, Maya Silvi Nasution, Benny Benyamin Universitas Sumatera Utara Master of Informatics Faculty of Computer Science and Information Technology Medan Indonesia Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia

ISBN: (纸本)9798350376111

This research aims to develop an expert system for initial diagnoses of skin diseases in cats using the Decision Tree method. It assists cat owners in identifying skin diseases based on observed symptoms. Data from expert veterinarian drh. Ismi Azima, including various types of cat skin diseases and their symptoms, were used. The research employs 80% training data and 20% testing data to develop the classification model. Testing results indicate the Decision Tree model achieves up to 90% average accuracy in diagnosing cat skin diseases based on 50 datasets. This expert system aids in diagnosis and provides treatment and prevention solutions, beneficial for cat owners, especially in areas with limited veterinary access. In conclusion, this Decision Tree-based expert system effectively provides initial diagnoses of skin diseases in cats with high accuracy. © 2024 IEEE.

关键词： Cat Skin Diseases Decision Tree Expert System XGBoost

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Optimized digital watermarking: Harnessing the synergies of Schur matrix factorization, DCT, and DWT for superior image ownership proofing

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Multimedia Tools and Applications 2025年第18期84卷 19817-19852页

作者： Al-Aiash, Issa Alquran, Rabee AlJamal, Mahmoud Alsarhan, Ayoub Aljaidi, Mohammad Al-Fraihat, Dimah Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa13133 Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa13110 Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman11622 Jordan

The contemporary context of abundant digital dissemination inherently gives rise to the need for media protection and the clear identification of ownership rights. This paper responded to this nagging issue of unauthorized media capture by developing a new digital watermarking approach uniting the Discrete Wavelet Transform DWT, Discrete Cosine Transform DCT, and Schur matrix factorization. The proposed watermark, which was a positive vector uniformly distributed, presented a high degree of robustness to several adversarial operating conditions, including histogram equalization, salt and pepper noise, ripple impact, smoothing attack, and cropping. The obtained results reveal the effectiveness of our approach. The correlation coefficient between watermarked and original images remains exceptionally high at 0.999998, ensuring minimal visual distortion. Mean Squared Error (MSE) graphs for both high-frequency (HH) and low-frequency (LL) domains demonstrate negligible changes after attacks, confirming the watermark's robustness. Notably, the watermark extraction process remains successful even after histogram equalization, as indicated by significantly lower MSE compared to random vectors. Moreover, the average processing times for different attacks are promising;Histogram Equalization and Salt and Pepper attacks each took 0.3 s, Ripple Attack required 0.28 s, Smoothing Attack completed in 0.29 s, and the Cropping Attack took 0.6 s. The robustness of our approach appears against the salt and pepper attack, which historically presented a vulnerability when employing Schur matrix factorization in image watermarking, indicating the novelty of and this contribution to improving media ownership verification. By combining disparate transformation methodologies, this technique offers a promising avenue for reinforcing the integrity and authenticity of digital media, thereby strengthening the foundations of intellectual property rights in the digital domain. © The Author(s), und

关键词： Discrete wavelet transforms

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A privacy and compliance in regulated anonymous payment system based on blockchain

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Journal of Ambient Intelligence and Humanized Computing 2024年第8期15卷 3141-3157页

作者： Elfadul, Issameldeen Wu, Lijun Elhabob, Rashad Elkhalil, Ahmed School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan250200 China Faculty of Computer Science and Information Technology Karary University Khartoum Sudan

Decentralized Anonymous Payment Systems (DAP), often known as cryptocurrencies, stand out as some of the most innovative and successful applications on the blockchain. These systems have garnered significant attention in the financial industry due to their highly secure and reliable features. Regrettably, the DAP system can be exploited to fund illegal activities such as drug dealing and terrorism. Therefore, governments are increasingly worried about the illicit use of DAP systems, which poses a critical threat to their security. This paper proposes Privacy and Compliance in Regulated Anonymous Payment System Based on Blockchain (PCRAP), which provides government supervision and enforces regulations over transactions without sacrificing the essential idea of the blockchain, that is, without surrendering transaction privacy or anonymity of the participants. The key characteristic of the proposed scheme is using a ring signature and stealth address to ensure the anonymity of both the sender and receiver of the transaction. Moreover, a Merkle Tree is used to guarantee government supervision and enforce regulations. Our proposed scheme satisfies most of the stringent security requirements and complies with the standards of secure payment systems. Additionally, while our work supports government regulations and supervision, it guarantees unconditional anonymity for users. Furthermore, the performance analysis demonstrates that our suggested scheme still remains applicable and effective even when achieving complete anonymity. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Blockchain

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Generative adversarial networks based motion learning towards robotic calligraphy synthesis

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CAAI Transactions on Intelligence technology 2024年第2期9卷 452-466页

作者： Xiaoming Wang Yilong Yang Weiru Wang Yuanhua Zhou Yongfeng Yin Zhiguo Gong Department of Computer and Information Science University of MacaoMacaoChina School of Software Beihang UniversityBeijingChina Department of Computer Science and Technology Faculty of Information TechnologyBeijing University of TechnologyBeijingChina School of Foreign Languages Guangzhou Huashang CollegeGuangzhouChina

Robot calligraphy visually reflects the motion capability of robotic *** traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters,this article presents a generative adversarial network(GAN)-based motion learning method for robotic calligraphy synthesis(Gan2CS)that can enhance the efficiency in writing complex calligraphy words and reproducing classic calligraphy *** key technologies in the proposed approach include:(1)adopting the GAN to learn the motion parameters from the robot writing operation;(2)converting the learnt motion data into the style font and realising the transition from static calligraphy images to dynamic writing demonstration;(3)reproducing high-precision calligraphy works by synthesising the writing motion data *** this study,the motion trajectories of sample calligraphy images are firstly extracted and converted into the robot *** robot performs the writing with motion planning,and the writing motion parameters of calligraphy strokes are learnt with *** the motion data of basic strokes is synthesised based on the hierarchical process of‘stroke-radicalpart-character’.And the robot re-writes the synthesised characters whose similarity with the original calligraphy characters is *** calligraphy characters have been tested in the experiments for method validation and the results validated that the robot can actualise the robotic calligraphy synthesis of writing motion data with GAN.

关键词： calligraphy synthesis generative adversarial networks Motion learning robot writing

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Copy-Right protection of color videos using robust watermarking based geometrically invariant moments of fractional orders and logistic sine cosine chaotic map

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Multimedia Tools and Applications 2024年 1-26页

作者： Alsahafi, Yousef S. Darwish, Mohamed M. Hosny, Khalid M. Department of Information Technology Khulis College University of Jeddah Jeddah Saudi Arabia Department of Computer Science Faculty of Computers and Information Assiut University Assiut Egypt Department of Computer Science University College of Al Wajh University of Tabuk Tabuk Saudi Arabia Department of Information Technology Faculty of Computers and Informatics Zagazig University Zagazig Egypt

Digital video watermarking research has yielded numerous promising breakthroughs in recent years. As more people grow interested in videos, the copyright protection of videos has become an urgent issue that must be addressed. Digital video watermarking is a significant method for copyright protection of videos because of the growing need to safeguard video data’s intellectual property. Some existing works cannot resist geometric attacks effectively, while others fail to address the balance between robustness and visual imperceptibility. Significant progress has been made in studying fractional orthogonal moments due to their geometric invariance and beneficial image description capabilities. For these reasons, this paper proposes a robust watermarking algorithm for color video using accurate quaternion fractional Gegenbauer moments (QFrGMs), which are constructed relying on a combination of quaternion theory and accurate fractional Gegenbauer moments (FrGMs). The proposed algorithm is designed to address existing deficiencies in some related works and improve resilience. This algorithm is imperceptibly invisible and resistant to various kinds of attacks. In the proposed algorithm, the watermark information is embedded into accurately selected coefficients of QFrGMs for the selected frame of the cover video. This algorithm is robust to geometric attacks due to the outstanding geometric invariance of QFrGMs. To ensure security and improve the suggested algorithm’s security, we employed a chaotic map termed a one-dimensional Logistic Sine Cosine (LSC) map with superior chaotic characteristics to scramble the watermark. Numerical experiments were performed regarding imperceptibility and robustness to test the effectiveness. The experimental results demonstrated that the proposed method provides high visual quality and robustness against common signal processing, geometric, frame averaging, frame swapping, and frame dropping attacks. Furthermore, the proposed algorithm e

关键词： Image watermarking

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RELIANCE: Reliable Ensemble Learning for information and News Credibility Evaluation 20

RELIANCE: Reliable Ensemble Learning for Information and New...

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20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Ramezani, Majid Mohammad-Shahi, Hamed Daliry, Mahshid Rahmani, Soroor Asghari, Amirhossein Faculty of Computer Science and Information Technology Zanjan Iran

ISBN: (纸本)9798350383942

In the era of information proliferation, discerning the credibility of news content poses an ever-growing challenge. This paper introduces RELIANCE, a pioneering ensemble learning system designed for robust information and fake news credibility evaluation. Comprising five diverse base models, including Support Vector Machine (SVM), naïve Bayes, logistic regression, random forest, and Bidirectional Long Short Term Memory Networks (BiLSTMs), RELIANCE employs an innovative approach to integrate their strengths, harnessing the collective intelligence of the ensemble for enhanced accuracy. Experiments demonstrate the superiority of RELIANCE over individual models, indicating its efficacy in distinguishing between credible and non-credible information sources. RELIANCE, also surpasses baseline models in information and news credibility assessment, establishing itself as an effective solution for evaluating the reliability of information sources. © 2024 IEEE.

关键词： Learning systems

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A Comparison Study of Prominent International University Ranking Systems: Exploring the Potential of Yemeni Universities for Rankings 1

A Comparison Study of Prominent International University Ran...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Hagree, Salah Al-Shalabi, Ahmed Abdullah Al-Sanabani, Maher Al-Majma, Nashwan Ahmed Abdulrazzak, Fuaad Hasan Al-Gaphari, Ghaleb Al-Dilami, Redwan Alawdi, Ala'a Computer Science Department Faculty of Computer and Information Technology Sana’a University Yemen Computer Science Department Faculty of Sciences Ibb University Yemen Aljazeera University Yemen Computer Science Department Faculty of Computer and Information Technology Sana’a University Sana’a Yemen Computer Science Department Faculty of Computer and Information Technology Thamar University Yemen Faculty of Computing and IT University of Science and Technology Sana’a Yemen

ISBN: (纸本)9798331533557

Specifically targeting Yemeni universities, the focus lies on their potential to enter these rankings and enhance their positions such as Quacquarelli Symonds (QS) World University Ranking (QS), Academic Ranking of World Universities (ARWU), Webometrics Ranking, Times Higher Education (THE) World University Ranking, and SCImago Institutions (SIR) Rankings. Its objective is to encourage Yemeni universities to prioritize the criteria outlined in these rankings and view them as a means to access other international rankings. The research tackles the challenge of comprehending the criteria and application process required for Yemeni universities to participate in these rankings, as well as the rankings they have achieved. The study underscores the importance of this research by providing Yemeni university administrators with valuable insights into the criteria used for international rankings and the rankings obtained by Yemeni universities. This understanding can facilitate efforts to enhance the quality of higher education within these institutions. The findings of the study reveal that there are two Yemeni universities listed in the QS. The University of science and technology, ranks 151-170, while Thamar University, ranks 171-200 for 2023. While in 2024, the University of science and technology ranked first locally and the University of Aden ranked second. This paper investigates the participation of Yemeni universities in global ranking systems such as ARWU, THE, QS, and SIR, with the aim of enhancing their international standing. It highlights the challenges and opportunities for Yemeni universities to meet ranking criteria, offering insights that can help improve the quality of higher education. © 2024 IEEE.

关键词： Quacquarelli Symonds Ranking Yemen research Yemeni Universities

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Big Data Analysis using Elasticsearch and Kibana: A Rating Correlation to Sustainable Sales of Electronic Goods

HighTech and Innovation Journal

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HighTech and Innovation Journal 2023年第3期4卷 583-591页

作者： Henderi, Henderi Irawatia, Ranty Indra, Indra Dewi, Deshinta Arrova Kurniawan, Tri Basuki Department of Informatics Engineering University of Raharja Indonesia Informatics Technical Department Universitas Budi Luhur Indonesia Faculty of Data Science and Information Technology INTI International University Nilai Malaysia Faculty of Science and Technology Universitas Bina Darma Indonesia Faculty of Technology and Information Science Universiti Kebangsaan Malaysia Malaysia

Big data collection involves enormous amounts of raw data. To boost the sustainability of corporate value and support business intelligence and decision-making systems, in-depth data analysis is necessary. The data storage, analysis, and visualization methods, as well as the discovery of patterns and linkages, all depend on extensive data analysis. This study aims to process datasets to learn things like how ratings impact market sales transactions and how much of an impact factor connected to consumers and items have on ratings. Elasticsearch and Kibana were used for the dataset processing. This study evaluated traits related to the test parameters using a variety of test procedures. The product is scored as a representation of the product types involved in the sales transaction, and the name is assessed as a reflection of the customer. Kibana and Elasticsearch, a full-text search engine, were used in this work to do extensive data analysis on data sets. It is a visualization tool that is employed in a controlled environment to evaluate how ratings impact market exchanges for electronic goods, and it offers suggestions. The study found a substantial relationship between electronic product sales on the Amazon marketplace from 2012 to 2018. It suggested the importance of buyer constituents as users and how different product categories relate to ratings in business transactions. © 2023, Ital Publication. All rights reserved.

关键词： Decision making

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Hybrid Feature Selection Method for Predicting Alzheimer’s Disease Using Gene Expression Data

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computers, Materials & Continua 2023年第3期74卷 5559-5572页

作者： Aliaa El-Gawady BenBella S.Tawfik Mohamed A.Makhlouf Department of Information Systems Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Faculty of Computer Science Nahda UniversityBeni SuefEgypt

Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many *** machine learning(ML)in the prediction of many diseases based on GE data has been a flourishing research ***,some diseases,like Alzheimer’s disease(AD),have not received considerable attention,probably owing to data scarcity *** this work,we shed light on the prediction of AD from GE data accurately using *** approach consists of four phases:preprocessing,gene selection(GS),classification,and performance *** the preprocessing phase,gene columns are preprocessed *** the GS phase,a hybrid filtering method and embedded method are *** the classification phase,three ML models are implemented using the bare minimum of the chosen genes obtained from the previous *** final phase is to validate the performance of these classifiers using different *** crux of this article is to select the most informative genes from the hybrid method,and the best ML technique to predict AD using this minimal set of *** different datasets are used to achieve our *** predict AD with impressive values forMultiLayer Perceptron(MLP)classifier which has the best performance metrics in four datasets,and the Support Vector Machine(SVM)achieves the highest performance values in only one *** assessed the classifiers using sevenmetrics;and received impressive results,allowing for a credible performance *** metrics values we obtain in our study lie in the range[.97,.99]for the accuracy(Acc),[.97,.99]for F1-score,[.94,.98]for kappa index,[.97,.99]for area under curve(AUC),[.95,1]for precision,[.98,.99]for sensitivity(recall),and[.98,1]for *** these results,the proposed approach outperforms recent interesting *** these results,the proposed approach outperforms recent interesting results.

关键词： Gene expression gene selection machine learning classification Alzheimer’s disease

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