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arXiv 2023年

作者： Zhai, Shengfang Dong, Yinpeng Shen, Qingni Pu, Shi Fang, Yuejian Su, Hang School of Software and Microelectronics Peking University China Department of Computer Science & Technology Tsinghua University China ShengShu Beijing China School of Software and Microelectronics National Engineering Research Center for Software Engineering PKU-OCTA Laboratory for Blockchain and Privacy Computing Peking University Beijing100871 China Dept. of Comp. Sci. and Tech. Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Beijing100084 China

With the help of conditioning mechanisms, the state-of-the-art diffusion models have achieved tremendous success in guided image generation, particularly in text-to-image synthesis. To gain a better understanding of the training process and potential risks of text-to-image synthesis, we perform a systematic investigation of backdoor attack on text-to-image diffusion models and propose BadT2I, a general multimodal backdoor attack framework that tampers with image synthesis in diverse semantic levels. Specifically, we perform backdoor attacks on three levels of the vision semantics: Pixel-Backdoor, Object-Backdoor and Style-Backdoor. By utilizing a regularization loss, our methods efficiently inject backdoors into a large-scale text-to-image diffusion model while preserving its utility with benign inputs. We conduct empirical experiments on Stable Diffusion, the widely-used text-to-image diffusion model, demonstrating that the large-scale diffusion model can be easily backdoored within a few fine-tuning steps. We conduct additional experiments to explore the impact of different types of textual triggers, as well as the backdoor persistence during further training, providing insights for the development of backdoor defense methods. Besides, our investigation may contribute to the copyright protection of text-to-image models in the future. Our Code: https://***/sf-zhai/BadT2I. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Graph Theory for Dimensionality Reduction: A Case Study to Prognosticate Parkinson's 11

Graph Theory for Dimensionality Reduction: A Case Study to P...

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11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020

作者： Maitra, Shithi Hossain, Tonmoy Hasib, Khan Md. Shishir, Fairuz Shadmani Sheba.xyz Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Software Engineering Team InsideMaps Inc. Dhaka Bangladesh

ISBN: (纸本)9781728184166

In the present world, the commotion centering Big Data is somewhat obscuring the craft of mining information from smaller samples. Populations with limited examples but huge dimensionality are a common phenomenon, otherwise known as the curse of dimensionality-especially in the health sector-Thanks to the recently-discovered potential of data mining and the enthusiasm for feature engineering. Correlated, noisy, redundant features are byproducts of this tendency, which makes learning algorithms converge with greater efforts. This paper proposes a novel feature-pruning technique relying on computational graph theory. Restoring the appeal of pre-AI conventional computing, the paper applies Disjoint Set Union (DSU) on unidirectional graphs prepared basis thresholded Spearman's rank correlation coefficient, r. Gradual withdrawal of leniency on Spearman's r caused a greater tendency in features to form clusters, causing the dimensionality to shrink. The results-extracting out finer, more representative roots as features-have been k-fold cross-validated on a case study examining subjects for Parkinson's. Qualitatively, the method overcomes Principal Component Analysis's (PCA) limitation of inexplicit merging of features and Linear Discriminant Analysis's (LDA) limitation of inextendibility to multiple classes. Statistical inference verified a significant rise in performance, establishing an example of conventional hard computing reinforcing modern soft computing. © 2020 IEEE.

关键词： Graph theory

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Genetic Algorithm-Based Feature Selection for Accurate Breast Cancer Classification

Genetic Algorithm-Based Feature Selection for Accurate Breas...

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IT and Industrial Technologies (ICIT), International Conference on

作者： Attia Shabbir Raja Hashim Ali Muhammad Zeeshan Shabbir Zain Ul Abideen Talha Ali Khan Ali Zeeshan Ijaz Nisar Ali Muhammad Imad Muhammad Abu Bakar Faculty of Computer Science & Engineering GIK Institute of Engg. Sciences & Technology Topi Pakistan Dept. of Technology & Software Engineering University of Europe for Applied Sciences Berlin Germany Department of Electrical Engineering University of Engineering & Technology (UET) Lahore Pakistan BCMaterials Basque Center for Materials Applications & Nanostructure Leioa Basque Country Spain Faculty of Electronic Systems Engineering University of Regina Regina Canada

Breast cancer is a significant global healthcare challenge, particularly in developing and underdeveloped countries, with profound physical, emotional, and psychological consequences, including mortality. Timely diagnosis and accurate treatment are crucial in addressing this issue. We propose the utilization of a feature selection technique to identify the most relevant features from among all features for breast cancer diagnosis, and show that Genetic Algorithms are impressive for this task. The study compares the results of GA with no selection and an alternative method, Principle Component Analysis (PCA). Three machine learning models, all based on supervised learning with data split into training and test data, are employed for binary classification using the selected feature subset. The evaluation metrics employed encompass accuracy, precision, recall, and F1-score. Among the selected models, Random Forest demonstrates the most favorable outcomes, achieving an accuracy score of 0.96, precision score of 0.96, recall value of 0.98, and an F1-score of 0.97. These results underscore the effectiveness of GA in feature selection for breast cancer diagnosis. Consequently, the integration of Genetic Algorithms (GA) with Random Forest showcases the superior performance among the evaluated models.

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Technical Debt Management: The Road Ahead for Successful software Delivery

Technical Debt Management: The Road Ahead for Successful Sof...

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software engineering: Future of software engineering (ICSE-FoSE), IEEE/ACM International Conference on

作者： Paris Avgeriou Ipek Ozkaya Alexander Chatzigeorgiou Marcus Ciolkowski Neil A. Ernst Ronald J. Koontz Eltjo Poort Forrest Shull Dept. of Computing Science University of Groningen Groningen The Netherlands Software Engineering institute Carnegie Mellon University Pittsburgh PA USA Dept. of Applied informatics University of Macedonia Thessaloniki Greece QAware GmbH München Germany Department of Computer Science University of Victoria Victoria Canada The Boeing Company Mesa AZ USA CGI Rotterdam The Netherlands

Technical Debt, considered by many to be the ‘silent killer’ of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to “bankrupt” those systems. software engineers and organizations that develop software-intensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt; we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence.

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EdgeMatrix: A Resources Redefined Edge-Cloud System for Prioritized Services

arXiv

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arXiv 2022年

作者： Ren, Yuanming Shen, Shihao Ju, Yanli Wang, Xiaofei Wang, Wenyu Leung, Victor C.M. TANKLab College of Intelligence and Computing Tianjin University Tianjin China Shanghai Zhuichu Networking Technologies Co. Ltd. China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Dept. of Electrical and Computer Engineering The University of British Columbia Vancouver Canada

The edge-cloud system has the potential to combine the advantages of heterogeneous devices and truly realize ubiquitous computing. However, for service providers to guarantee the Service-Level-Agreement (SLA) priorities, the complex networked environment brings inherent challenges such as multi-resource heterogeneity, resource competition, and networked system dynamics. In this paper, we design a framework for the edge-cloud system, namely EdgeMatrix, to maximize the throughput while guaranteeing various SLA priorities. First, EdgeMatrix introduces Networked Multi-agent Actor-Critic (NMAC) algorithm to redefine physical resources as logically isolated resource combinations, i.e., resource cells. Then, we use a clustering algorithm to group the cells with similar characteristics into various sets, i.e., resource channels, for different channels can offer different SLA guarantees. Besides, we design a multi-task mechanism to solve the problem of joint service orchestration and request dispatch (JSORD) among edge-cloud clusters, significantly reducing the runtime than traditional methods. To ensure stability, EdgeMatrix adopts a two-time-scale framework, i.e., coordinating resources and services at the large time scale and dispatching requests at the small time scale. The real trace-based experimental results verify that EdgeMatrix can improve system throughput in complex networked environments, reduce SLA violations, and significantly reduce the runtime than traditional methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

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A Comprehensive Framework for Measuring and Improving API Usability

A Comprehensive Framework for Measuring and Improving API Us...

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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Jeff Tian Abdullah Bokhary Sultan Alanazy Dept of Computer Science Southern Methodist University Dallas Texas USA Dept of Software Engineering College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

ISBN: (纸本)9781665458429

In this paper, we develop a comprehensive framework for measuring and improving API usability, consisting of both a comprehensive measurement framework and an analysis/modeling framework. Our measurement framework consists of both a set of direct measurements of API usability and a set of indirect measurements of factors that may influence API usability. Our analysis/modeling framework validates the measurement framework empirically and establishes predictive relations between its two sets of measurements. Such predictive relations can help us improve API usability through recommended actions applied on its influence factors. Examples from a preliminary case study are included to demonstrate the viability and potential effectiveness of our approach.

关键词： Analytical models Scientific computing Computational modeling Usability Computational intelligence

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Reversing obfuscated control flow structures in android apps using ReDex optimizer 9

Reversing obfuscated control flow structures in android apps...

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9th International Conference on Smart Media and Applications, SMA 2020

作者： You, Geunha Kim, Gyoosik Park, Jihyeon Cho, Seong-Je Park, Minkyu Dept. of Computer Science and Engineering Dankook University Korea Republic of Dept. of Convergence Technology Korea Telecom Korea Republic of Dept. of Software Science Dankook University Korea Republic of Dept. of Software Technology Konkuk University Korea Republic of

ISBN: (纸本)9781450389259

Code obfuscation is a technique that makes programs harder to understand. Malware writers widely the obfuscation technique to evade detection from anti-malware software, or to deter reverse engineering attempts for their malicious code. If we de-obfuscate the obfuscated code and restore it to the original code before obfuscation was applied, we can analyze the obfuscated malware effectively and efficiently. In this paper, we apply ReDex optimizer for reversing the control-flow obfuscation performed by the Obfuscapk system on open-source Android applications. We then analyze the effectiveness and limitations of ReDex in terms of its deobfuscation ability to reverse the control-flow obfuscation of Android apps. The experimental results show that ReDex can recover 1089 of 1108 apps obfuscated with control-flows obfuscation techniques of Obfuscapk obfuscator. During the process of optimizing bytecode, ReDex reduces the number of methods and fields significantly while it has a limitation in removing dead codes related to both useless goto statements and random nop instructions. © 2020 ACM.

关键词： Reverse engineering

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A Pico-Second Timing System on a Chip (SoC) for Magnetostrictive Displacement Sensors (MDSs)

A Pico-Second Timing System on a Chip (SoC) for Magnetostric...

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Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)

作者： Qin Ke Zhouji Du Hang Yu Yan Li Xinchao Zhong Haiquan Li Binjie Ge Daoming Xi Shenzhen iOT Lab of IC Design College of Computer Science and Software Engineering Shenzhen University Shenzhen China Dept. of Computer Science The University of Auckland Auckland Central Auckland New Zealand Runyu Sensor Technology Co. Ltd Xinhui City Jiangmen China Dept. of Electronics and Computer Engineering SHENZHEN MCU-BIT University Shenzhen China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

Based on the Wiedemann effect, Magnetostrietive Displacement Sensors (MDSs) can measure displacement without contact so that it is free of wear. Therefore, compared with other displacement sensors, the MDSs has a longer service life and is more adaptable to harsh environments. The MDSs are getting more attention and are widely used in industry control system. Precision time interval is the key aspect of the MDSs. In this paper, a pico-second timing system on chip (SoC) is designed in a 180 nm CMOS process for the MDSs applications. SoC is proposed for the MDSs applications. The chip integrates a high speed comparator and a time-to-digital converter (TDC) to build a fine time measurement chain. A 32-MHz microcontroller unit (MCU) realized by RISC-V core with two-stage pipeline is realized for system control. Test results show that the comparator temporal noise is around 1 mV and the TDC achieves a resolution of 156 ps.

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Explaining Agent Behavior in Agent-Based Modeling Using Subgroup Discovery

SSRN

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SSRN 2023年

作者： Romero, Elena Carmona del Jesús, Cristóbal José Cordón, Oscar del Jesus, María José Damas, Sergio Chica, Manuel Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Dept. of Computer Science and Artificial Intelligence DECSAI University of Granada Granada18071 Spain Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Jaen Jaen23071 Spain Leicester School of Pharmacy De Montfort University LeicesterLEI 9BH United Kingdom Dept. of Computer Science University of Jaen Jaen23071 Spain Dept. of Software Engineering University of Granada Granada18071 Spain School of Electrical Engineering and Computing The University of Newcastle CallaghanNSW2308 Australia

Agent-based modeling (ABM) is a popular tool for simulating complex systems. In addition to the key performance indicators ABM provides as main outputs of the modeling process, it also generates valuable information about the agents' roadmap, but the large volume of generated data is difficult to analyze and understand. Explainable Artificial Intelligence (XAI) techniques can improve the transparency and interpretability of these models. Subgroup Discovery (SD) is a useful tool for XAI that can facilitate the analysis of the data with respect to a variable of interest. In this contribution, we propose a methodology for applying SD to ABM for extracting useful knowledge of agents behavior from the model output. We compare the performance of different SD algorithms and show the effectiveness of our methodology through a case study in the marketing area. We analyze the obtained set of rules from the point of view of a marketing expert. The results show that our methodology can provide a deeper understanding of consumer behavior and market dynamics, providing potential areas of opportunity for marketers. © 2023, The Authors. All rights reserved.

关键词： Consumer behavior

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Assistive and rehabilitation robotics for upper limb impairments in post-stroke patients: Evaluation criteria for the design and functionality

Assistive and rehabilitation robotics for upper limb impairm...

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2020 Advances in science and engineering Technology International Conferences, ASET 2020

作者： Karam, Aliaa Alnajjar, Fady Gochoo, Munkhjargal College of Engineering Dept. of Biomedical Engineering University College Dublin Ireland College of Information Technology UAE University Dept. Computer Science and Software Engineering Al Ain United Arab Emirates

ISBN: (纸本)9781728146409

Rehabilitation and assistive robotics are beneficial for chronic and subacute stroke patients with upper limb impairments. Rehabilitation robotics is the use of robotic machinery and devices during therapy sessions to motivate and optimize the patient's upper limb motor functions. While assistive robotics is the use of portable robotic devices, which can assist the post stroke user with their upper limb movements along their daily tasks. Assistive robotic devices may also allow patients to 'in-directly' improve their motor functions through encouraging them to utilize their affected limb on daily basis. Thus, an assistive device is seen to be essential complementary to a rehabilitation device. Before marketing these two types of devices, they should undergo evaluation studies and clinical trials. This process will not only ensure patient's safety and optimal outcomes, but also help to overcome challenges in promoting the final product. The aim of this short article is to provide a brief review of current rehabilitation and assistive robotics, highlighting how they are complementary to each other, and how they can be evaluated and improved. © 2020 IEEE.

关键词： Robotics

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