Controlling multiple multi-joint fish-like robots has long captivated the attention of engineers and biologists,for which a fundamental but challenging topic is to robustly track the postures of the individuals in rea...
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Controlling multiple multi-joint fish-like robots has long captivated the attention of engineers and biologists,for which a fundamental but challenging topic is to robustly track the postures of the individuals in real *** requires detecting multiple robots,estimating multi-joint postures,and tracking identities,as well as processing fast in real *** the best of our knowledge,this challenge has not been tackled in the previous *** this paper,to precisely track the planar postures of multiple swimming multi-joint fish-like robots in real time,we propose a novel deep neural network-based method,named *** TAB part fuses the top-down and bottom-up approaches for vision-based pose estimation,while the IOL part with long short-term memory considers the motion constraints among joints for precise pose *** satisfying performance of our TAB-IOL is verified by testing on a group of freely swimming fish-like robots in various scenarios with strong disturbances and by a deed comparison of accuracy,speed,and robustness with most state-of-the-art ***,based on the precise pose estimation and tracking realized by our TAB-IOL,several formation control experiments are conducted for the group of fish-like *** results clearly demonstrate that our TAB-IOL lays a solid foundation for the coordination control of multiple fish-like robots in a real working *** believe our proposed method will facilitate the growth and development of related fields.
The generative pre-trained transformer (GPT) is a notable breakthrough in the field of artificial intelligence, as it empowers machines to effectively comprehend and engage in interactions with humans. The GPT exhibit...
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The generative pre-trained transformer (GPT) is a notable breakthrough in the field of artificial intelligence, as it empowers machines to effectively comprehend and engage in interactions with humans. The GPT exhibits the capacity to enhance inclusivity and accessibility for students with learning disabilities in the context of higher education, hence potentially facilitating substantial advancements in the field. GPT can provide personalized and diverse solutions that successfully cater to the distinct requirements of students with learning disabilities. This motivated us to conduct an extensive review to assess the effectiveness of GPT in enhancing accessibility and inclusivity in higher education for students with learning disabilities. This review offers a comprehensive analysis of the GPT and its significance for enhancing inclusivity in the field of higher education. In this research, we also examined the possible challenges and constraints associated with the integration of GPT into inclusive higher education, along with potential solutions. Overall, this review is intended for educators, students with and without learning disabilities, policymakers, higher education institutes, researchers, and educational technology developers. This review aims to provide a comprehensive understanding of GPT in promoting inclusive higher education for people with various learning disabilities, its impacts on inclusive higher education, emerging challenges, and potential solutions. Copyright 2025 Gadekallu et al.
Communication and coordination between OSS developers who do not work physically in the same location have always been the challenging *** pull-based development model,as the state-of-art collaborative development mec...
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Communication and coordination between OSS developers who do not work physically in the same location have always been the challenging *** pull-based development model,as the state-of-art collaborative development mechanism,provides high openness and transparency to improve the visibility of contributors'***,duplicate contributions may still be submitted by more than one contributors to solve the same problem due to the parallel and uncoordinated nature of this *** not detected in time,duplicate pull-requests can cause contributors and reviewers to waste time and energy on redundant *** this paper,we propose an approach combining textual and change similarities to automatically detect duplicate contributions in pull-based model at submission *** a new-arriving contribution,we first compute textual similarity and change similarity between it and other existing *** then our method returns a list of candidate duplicate contributions that are most similar with the new contribution in terms of the combined textual and change *** evaluation shows that 83.4%of the duplicates can be found in average when we use the combined textual and change similarity compared to 54.8%using only textual similarity and 78.2%using only change similarity.
Fault localization techniques are originally proposed to assist in manual debugging by generally producing a rank list of suspicious *** the increasing popularity of automated program repair,the fault localization tec...
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Fault localization techniques are originally proposed to assist in manual debugging by generally producing a rank list of suspicious *** the increasing popularity of automated program repair,the fault localization techniques have been introduced to effectively reduce the search space of automated program *** developers who mainly focus on the rank information,current automated program repair has two strategies to use the fault localization information:suspiciousness-first algorithm(SFA)based on the suspiciousness accuracy and rank-first algorithm(RFA)relying on the rank ***,despite the fact that the two different usages are widely adopted by current automated program repair and may result in different repair results,little is known about the impacts of the two strategies on automated program *** this paper we empirically compare the performance of SFA and RFA in the context of automated program ***,we implement the two strategies and six well-studied fault localization techniques into four state-of-the-art automated program repair tools,and then use these tools to perform repair experiments on 60 real-world bugs from *** study presents a number of interesting findings:RFA outperforms SFA in 70.02%of cases when measured by the number of candidate patches generated before a valid patch is found(NCP),while SFA performs better in parallel repair and patch diversity;the performance of SFA can be improved by increasing the suspiciousness accuracy of fault localization techniques;finally,we use SimFix that deploys SFA to successfully repair four extra Defects4J bugs which cannot be repaired by SimFix originally using *** observations provide a new perspective for future research on the usage and improvement of fault localization in automated program repair.
This paper presents an approach to extract high-level patterns from traces of programmable logic control (PLC) programs recorded with a deterministic replay debugging tool. Our deterministic replay debugging works by ...
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ISBN:
(纸本)9781450301374
This paper presents an approach to extract high-level patterns from traces of programmable logic control (PLC) programs recorded with a deterministic replay debugging tool. Our deterministic replay debugging works by recording an application run in real-time with minimal overhead so that it can be reproduced afterwards. In a subsequent phase, the application is replayed in offline mode to produce a more detailed trace log with additional information about the application run. A software developer can replay the program in a debugger and use debugger features to analyze the program run and locate errors. However, due to the vast amount of data and the complex behavior of reactive control programs, a normal debugger is usually only a poor support in comprehending the program behavior. In this paper we present an approach to analyze recorded program runs of PLC applications. We present a technology to visualize the reactive behavior of a program run and find recurring high-level execution patterns in long-running applications. We give an overview of possible application scenarios to support program comprehension, testing, and debugging.
Cloud computing provides the essential infrastructure for multi-tier Ambient Assisted Living(AAL) applications that facilitate people's lives. Resource provisioning is a critically important problem for AAL applic...
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Cloud computing provides the essential infrastructure for multi-tier Ambient Assisted Living(AAL) applications that facilitate people's lives. Resource provisioning is a critically important problem for AAL applications in cloud data centers(CDCs). This paper focuses on modeling and analysis of multi-tier AAL applications, and aims to optimize resource provisioning while meeting requests' response time constraint. This paper models a multi-tier AAL application as a hybrid multi-tier queueing model consisting of an M/M/c queueing model and multiple M/M/1 queueing models. Then, virtual machine(VM) allocation is formulated as a constrained optimization problem in a CDC, and is further solved with the proposed heuristic VM allocation algorithm(HVMA). The results demonstrate that the proposed model and algorithm can effectively achieve dynamic resource provisioning while meeting the performance constraint.
Domain-specific languages aim to present software in the notations of domain experts and allow a straightforward mapping of application concepts to software solutions. In this paper, we present a domain-specific langu...
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Deterministic Replay Debugging is an approach to finding field failures in application runs. It records an application run so that it can be replayed deterministically in a development system for debugging purposes wi...
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The Knowledge Acquisition Support Environment (KASE) and some case studies on expert system development are described. DiPROS is a diagnostic expert system building tool, which has a knowledge base editor and an infer...
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