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Defining Short- and Long-Term programming Requirements in Patients Treated With 10-kHz Spinal Cord Stimulation

NEUROMODULATION 2024年第6期27卷 1045-1054页

作者： Provenzano, David A. Leech, Jozef E. Bendersky, Marina Azalde, Rose Pain Diagnost & Intervent Care 301 Ohio River BlvdSte 203 Sewickley PA 15143 USA Nevro Corp Redwood City CA USA

Objectives: High-frequency spinal cord stimulation (10-kHz SCS) has been shown to be an effective treatment for refractory low back pain and neck pain with and without limb pain in clinical trial and real-world studies. However, limited information is available in the literature on the type and frequency of programming parameters required to optimize pain relief. Materials and Methods: Retrospective trial and postimplant clinical and system device data were analyzed from consecutive patients with neck pain and low back pain, with and without limb pain, from a single clinical site, including both thoracic and cervical lead placement. Best bipole, stimulation parameters, and outcomes, including pain relief, change in opioid medication use, sleep, and daily function, were analyzed. Results: Of the 92 patients in the trial, 70 received a permanent implant. Of these, the mean duration of follow-up was 1.8 +/- 1.3 years. Pain relief of >= 50% at the last follow-up was achieved by 64% of patients implanted;in addition, 65% reduced their opioid medication use;65% reported improved sleep, and 71% reported improved function. There was some consistency between the "best" bipole at trial and permanent implant, with 82% of patients within one bipole location, including 54% of permanent implants who were using the same best bipole as at trial. After permanent implant, device reprogramming was minimal, with <= one reprogramming change per patient per quarter required to maintain pain outcomes. Conclusions: In the study, 10-kHz SCS was an effective therapy for treating chronic pain, whereby a high responder rate (>= 50% pain relief) was achieved with short time to pain relief in trial and maintained with limited device programming after permanent implant. The data presented here provide insight into the programming required during the trial and implant stages to obtain and maintain therapeutic efficacy.

关键词： 10 kHz neuromodulation pain programming SCS

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Difference of Convex Functions programming With Machine-Learning Prior for the Imaging Problem in Electrical Capacitance Tomography

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第12期53卷 7535-7547页

作者： Lei, Jing Liu, Qibin North China Elect Power Univ Sch Energy Power & Mech Engn Beijing 102206 Peoples R China Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China

The electrical capacitance tomography technology has potential benefits for the process industry by providing visualization of material distributions. One of the main technical gaps and impediments that must be overcome is the low-quality tomogram. To address this problem, this study introduces the data-guided prior and combines it with the electrical measurement mechanism and the sparsity prior to produce a new difference of convex functions programming problem that turns the image reconstruction problem into an optimization problem. The data-guided prior is learned from a provided dataset and captures the details of imaging targets since it is a specific image. A new numerical scheme that allows a complex optimization problem to be split into a few less difficult subproblems is developed to solve the challenging difference of convex functions programming problem. A new dimensionality reduction method is developed and combined with the relevance vector machine to generate a new learning engine for the forecast of the data-guided prior. The new imaging method fuses multisource information and unifies data-guided and measurement physics modeling paradigms. Performance evaluation results have validated that the new method successfully works on a series of test tasks with higher reconstruction quality and lower noise sensitivity than the popular imaging methods.

关键词： Imaging Image reconstruction Dimensionality reduction Relevance vector machines Physics programming Convex functions Difference of convex functions programming problem electrical capacitance tomography inverse problem non-negative matrix factorization relevance vector machine visualization measurement

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Estimation and Expansion of Vehicle Stability Region With Sums of Squares programming

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2023年第5期28卷 2820-2831页

作者： Hu, Xiao Chen, Hong Ren, Qiao Gong, Xun Wang, Ping Hu, Yunfeng Jilin Univ Sch Artificial Intelligence Changchun 130012 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China Frontiers Sci Ctr Intelligent Autonomous Syst Shanghai 201210 Peoples R China Jilin Univ Sch Artificial Intelligence Changchun 130012 Peoples R China Jilin Univ State Key Lab Automot Simulat & Control Changchun 130012 Peoples R China Jilin Univ Sch Commun Engn Dept Control Sci & Engn Changchun 130012 Peoples R China

The vehicle stability region can be used to evaluate vehicle stability performance and lay the foundation for vehicle safety improvement. It can be obtained via the region of attraction (RoA) based on sums of squares (SOS) programming. However, it is usually conservative, and the computational burden is large. This article focuses on the above issues and proposes a well-developed method for RoA estimation, with application to the estimation and expansion of the vehicle stability region. For RoA estimation, an improved SOS program is formulated, and its optimization objective combined with the customized algorithm significantly reduces conservatism. In addition, the feasibility prejudgment strategy and the dynamic search range are proposed in the algorithm. As a result, the computational burden is greatly reduced, which also indirectly helps reduce conservatism. Then, a more accurate vehicle stability region is obtained with less time consumption, and a map-based controller is proposed to improve vehicle stability. Better stability performance and larger stability regions are guaranteed under different scenarios due to the adaptive adjustment of controller gains. Finally, simulations and hardware-in-the-loop experiments with an embedded vehicle controller are performed to verify the effectiveness of our method.

关键词： Thermal stability Heuristic algorithms Estimation Stability criteria Vehicle dynamics programming Optimization Lyapunov methods nonlinear dynamical systems region of attraction vehicle safety vehicle stability region

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Six Opportunities for Scientists and Engineers to Learn programming Using AI Tools Such as ChatGPT

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COMPUTING IN SCIENCE & ENGINEERING 2023年第3期25卷 73-78页

作者： Guo, Philip J. Univ Calif San Diego Cognit Sci La Jolla CA 92093 USA

This article demonstrates how scientists and engineers can use modern artificial intelligence (AI) tools such as ChatGPT and GitHub Copilot to learn computer programming skills that are relevant to their jobs. It begins by summarizing common ways that AI tools can already help people learn programming in general and then presents six new opportunities catered to the needs of scientists and engineers: 1) create customized programming tutorials for one's own domain of work, 2) learn complex data visualization libraries, 3) learn to refactor exploratory code into more maintainable software, 4) learn about inherited legacy code, 5) learn new programming languages on demand within the context of one's workflow, and 6) question the assumptions that one's scientific code is making. Taken together, these opportunities point toward a future where AI can help scientists and engineers learn programming on demand within the context of their existing real-world workflows.

关键词： Computer languages Codes Data visualization Tutorials programming Chatbots Software

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A Multi-Step Inertial Proximal Peaceman-Rachford Splitting Method for Separable Convex programming

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IEEE ACCESS 2023年 11卷 30859-30872页

作者： Li, Hongyan Yu, Dongmei Gao, Leifu Liaoning Tech Univ Sch Business Adm Huludao 125105 Peoples R China Liaoning Tech Univ Inst Optimizat & Decis Analyt Fuxin 123000 Peoples R China

In this paper, we propose a multi-step inertial proximal Peaceman-Rachford splitting method (abbreviated as MIP-PRSM) for solving the two-block separable convex optimization problems with linear constraints, which is a unified framework for such Peaceman-Rachford splitting methods (PRSM)-based improved algorithms with inertial step. Furthermore, we establish the global convergence of the MIP-PRSM under some assumptions. Finally, some numerical experimental results on the least squares semidefinite programming (LSSP), LASSO, the convex quadratic programming problem (CQPP), total variation (TV) based denoising and medical image reconstruction problems demonstrate the efficiency of the proposed method.

关键词： Convergence programming Convex functions Linearization techniques Linear programming Iterative algorithms Biomedical imaging Convex optimization convergence analysis multi-step inertial technique Peaceman-Rachford splitting method

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Human Morality Difference when programming and Actually Operating Autonomous Machines

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TSINGHUA SCIENCE AND TECHNOLOGY 2025年第4期30卷 1648-1658页

作者： Yi, Wenfeng Wu, Wenhan Chen, Maoyin Zheng, Xiaoping Tsinghua Univ Dept Automat Beijing 100084 Peoples R China China Univ Petr Coll Informat Sci & Engn Beijing 102249 Peoples R China

Autonomous machines (AMs) are poised to possess human-like moral cognition, yet their morality is often pre-programmed for safety. This raises the question of whether the morality intended by programmers aligns with their actions during actual operation, a crucial consideration for a future society with both humans and AMs. Investigating this, we use a micro-robot swarm in a simulated fire scenario, with 180 participants, including 102 robot programmers, completing moral questionnaires and participating in virtual escape trials. These exercises mirror common societal moral dilemmas. Our comparative analysis reveals a "morality gap" between programming presets and real-time operation, primarily influenced by uncertainty about the future and heightened by external pressures, especially social punishment. This discrepancy suggests that operational morality can diverge from programmed intentions, underlining the need for careful AM design to foster a collaborative and efficient society.

关键词： Ethics Uncertainty Decision making programming Real-time systems Safety Stakeholders Mirrors Machinery Stress moral machines moral level autonomous machines (AMs) emergency evacuation robot crowd

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DSSDPP: Data Selection and Sampling Based Domain programming Predictor for Cross-Project Defect Prediction

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2023年第4期49卷 1941-1963页

作者： Li, Zhiqiang Zhang, Hongyu Jing, Xiao-Yuan Xie, Juanying Guo, Min Ren, Jie Shaanxi Normal Univ Sch Comp Sci Xian 710119 Peoples R China Engn Lab Teaching Informat Technol Xian 710119 Shaanxi Peoples R China Univ Newcastle Sch Elect Engn & Comp Callaghan NSW 2308 Australia Zhejiang Sci Tech Univ Sch Comp Sci & Technol Hangzhou 310018 Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210093 Jiangsu Peoples R China Wuhan Univ Sch Comp Sci Wuhan 430072 Hubei Peoples R China Guangdong Univ Petrochem Technol Sch Comp Maoming 525011 Guangdong Peoples R China

Cross-project defect prediction (CPDP) refers to recognizing defective software modules in one project (i.e., target) using historical data collected from other projects (i.e., source), which can help developers find defects and prioritize their testing efforts. Unfortunately, there often exists large distribution difference between the source and target data. Most CPDP methods neglect to select the appropriate source data for a given target at the project level. More importantly, existing CPDP models are parametric methods, which usually require intensive parameter selection and tuning to achieve better prediction performance. This would hinder wide applicability of CPDP in practice. Moreover, most CPDP methods do not address the cross-project class imbalance problem. These limitations lead to suboptimal CPDP results. In this paper, we propose a novel data selection and sampling based domain programming predictor (DSSDPP) for CPDP, which addresses the above limitations. DSSDPP is a non-parametric CPDP method, which can perform knowledge transfer across projects without the need for parameter selection and tuning. By exploiting the structures of source and target data, DSSDPP can learn a discriminative transfer classifier for identifying defects of the target project. Extensive experiments on 22 projects from four datasets indicate that DSSDPP achieves better MCC and AUC results against a range of competing methods both in the single-source and multi-source scenarios. Since DSSDPP is easy, effective, extensible, and efficient, we suggest that future work can use it with the well-chosen source data to conduct CPDP especially for the projects with limited computational budget.

关键词： Data models Prediction algorithms Measurement Predictive models Tuning Transfer learning programming Cross-project defect prediction domain programming predictor data selection data sampling transfer learning software quality assurance

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Distributed Interval Optimization Over Time-Varying Networks: A Numerical programming Perspective

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IEEE ACCESS 2023年 11卷 122541-122553页

作者： Wang, Yinghui Wang, Jiuwei Song, Xiaobo Hu, Yanpeng Univ Sci & Technol Beijing Sch Automati & Elect Engn Key Lab Knowledge Automat Ind Proc Minist Educ Beijing 100083 Peoples R China Univ Sci & Technol Beijing Beijing Engn Res Ctr Ind Spectrum Imaging Sch Automat & Elect Engn Beijing 100083 Peoples R China Univ Chinese Acad Sci Acad Math & Syst Sci Beijing 100049 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Beijing 100190 Peoples R China

In this study, we investigate a distributed interval optimization problem involving agents linked by a time-varying network, optimizing interval objective functions under global convex constraints. Through scalarization, we first reformulate the distributed interval optimization problem as a distributed constrained optimization problem. The optimal Pareto solutions to the reformulated problem are then illustrated. We establish a distributed subgradient-free algorithm for the distributed constrained optimization problems by generating random differences of reformulated optimal objective functions, and the optimal solutions of the distributed constrained optimization problem are equivalent to Pareto optimal solutions of the distributed interval optimization problem. Moreover, we demonstrate that a Pareto optimal solution can be reached over the time-varying network using the proposed algorithm almost surely. FInally, we conclude with a numerical simulation to demonstrate the effectiveness of the proposed algorithm.

关键词： Optimization Pareto optimization Linear programming Convergence Topology Random variables programming Time-varying systems Distributed interval optimization time-varying network Pareto optimal solution subgradient-free algorithm

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Exploring the Balance Between Computational Thinking and Learning Motivation in Elementary programming Education: An Empirical Study With Game-Based Learning

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IEEE TRANSACTIONS ON GAMES 2023年第1期15卷 95-107页

作者： Liu, Huizhong Wu, Zengqing Lu, Yili Zhu, Ling Shanghai Univ Finance & Econ Shanghai 200433 Peoples R China China Welf Inst Comp Ctr Childrens Palace Shanghai 200040 Peoples R China Osaka Univ Osaka 5650871 Japan Chuo Univ Tokyo 1920393 Japan Univ Minnesota Minneapolis MN 55455 USA

Computational thinking (CT) skills are generally regarded as a basic ability for problem-solving and are gradually filtering down to younger age groups. Existing research has attempted to increase interaction and enhance the learning interest of elementary school students through block-based programming environments represented by Scratch. However, criticism suggests that this approach has potential long-term constraints on CT education. Therefore, this study designed a game-based project to investigate students' learning motivation and CT performance in different programming environments. A total of 108 fifth-grade students participated in the experiment and were divided into two experimental groups (EG1 and EG2) and a control group (CG). The students in experimental groups all undertook game-based learning, while EG1 students used C++ and EG2 students used Scratch;CG students used C++ for traditional algorithm-based learning. Findings suggest that traditional programming languages with game-based learning can also substantially improve learning interest, which can promote the efficiency of improving CT for students who already have some motivation and foundation for learning. But for students who still lack motivation, are also encouraged to develop an interest in a block-based programming environment. Teachers can choose the most appropriate approach for students to find the best balance between learning efficiency and long-term interest.

关键词： Computational thinking (CT) elementary education game-based learning learning motivation programming

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VID2XML: Automatic Extraction of a Complete XML Data From Mobile programming Screencasts

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2023年第4期49卷 1726-1740页

作者： Alahmadi, Mohammad D. Univ Jeddah Coll Comp Sci & Engn Dept Software Engn Jeddah 21959 Saudi Arabia

Developers often refer to video-hosting online platforms to find screencasts that provide a step-by-step guide to help them solve a programming task at hand or learn a new concept. More specifically, developers search for resources that help them design and implement effective mobile graphical user interfaces (GUI) using XML. Although mobile programming screencasts contain a vast amount of XML data at developers' disposal, they cannot be easily found and copied-pasted due to the image nature of videos. Given that the most common task developers perform online is copy-pasting, mobile programming screencasts must support that and be complemented with XML data in a textual format. To overcome this challenge and aid developers, this paper presents vid2XML, which is a three-phase approach that leverages both visual and textual information of video frames to locate XML region in video frames, locate the currently opened file, and extract XML data for each file presented in video frames. We evaluated each phase of vid2XML in a comprehensive empirical evaluation on videos collected from YouTube. The results reveal that vid2XML is able to accurately (i) locate XML regions, outperforming four previous work, (ii) locate the bounding box of the selected file, and (iii) extract, fix, and merge XML data for each file opened/created in a video.

关键词： Videos XML Data mining programming Codes Feature extraction Optical character recognition software programming screencasts computer vision Android programming programming video tutorials video mining

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