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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Haydar, Georgio Abou Telawi, Samer Borcsok, Josef Architecture and System Programming University of Kassel Department of Computer Kassel Germany

ISBN: (纸本)9798331529604

Ensuring the safety of human workers collaborating with industrial robots is paramount. This research work presents a novel approach by developing a safety-related intruder detection system for the operational zones of industrial robots, following the IEC 61508 standard and adopting the related redundant architecture. The hardware integrates light curtains and radar sensors in a dual-layer configuration, while the software utilizes a safety system-on-chip to implement real-time diagnostics and fault tolerance. Protecting employees and ensuring a smooth and safe work environment are significant concerns for all companies. As a result, numerous standards and regulations have been established to provide safe collaboration between humans and machines. However, despite these measures, accidents continue to occur, resulting in varying degrees of injuries. The proposed system is depicted through a comprehensive schematic, emphasizing the integration of safety measures within the robotic environment. The detailed prototype demonstrates practical application, show-casing the system's ability to detect intrusions, initiate emergency responses, and transition to fail-safe states during component failures. This research work advances safety protocols in human-robot collaboration within industrial settings, fostering a safe working environment through a well-defined safety framework. © 2025 IEEE.

关键词： Industrial robots

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LLM-based code generation and system migration in language-driven engineering

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International Journal on Software Tools for Technology Transfer 2025年 1-11页

作者： Busch, Daniel Bainczyk, Alexander Smyth, Steven Steffen, Bernhard Department of Computer Science Chair for Programming Systems TU Dortmund University Dortmund44227 Germany

This paper illustrates the power of extending Language Driven Engineering (LDE) with Domain-Specific Natural Languages (DSNLs) through a case study on two levels. Both cases benefit from the characteristic decomposition feature of LDE, resulting in tasks tailored to the application of domain-specific languages, here with a focus on the application of DSNLs supported by LLM-based code generation. In the first case study, we show how DSNL-supported LDE facilitates the development of point-and-click adventures, whereas the second case study focuses on migration: We demonstrate how the entire LDE scenario for point-and-click adventure games can be migrated to output TypeScript instead of JavaScript using LLM-based code generation exclusively, without manually writing any code. This migration not only infers the required types, but also preserves an important property of the original LDE scenario: generated web applications can be automatically validated by design via automata learning and subsequent model checking. Even better, this property can be exploited to automatically validate the correctness of the migration by learning so-called difference automata that characterize the behavioral differences between the generated JavaScript-based and Type-Script-based applications. © The Author(s) 2025.

关键词： Verification

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POD-BIN: A PROBABILITY OF DECISION BAYESIAN INTERVAL DESIGN FOR TIME-TO-EVENT DOSE-FINDING TRIALS WITH MULTIPLE TOXICITY GRADES

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Annals of Applied Statistics 2025年第1期19卷 147-168页

作者： Liu, Meizi Lin, Ji Mi, Gu Lorenzato, Christelle Chen, Xun Ji, Yuan Statistical and Quantitative Sciences Takeda Japan Department of Biostatistics and Programming Sanofi France Department of Public Health Sciences University of Chicago United States

We introduce a Bayesian framework centered on the “probability of decision” for designing dose-finding trials. The proposed PoD-BIN design evaluates the posterior predictive probabilities of up-and-down decisions. In PoDBIN, multiple grades of toxicity, categorized as mild toxicity (MT) and doselimiting toxicity (DLT), are simultaneously modeled, with the primary outcome being time-to-toxicity for both MT and DLT. This approach allows the enrollment of new patients while previously enrolled patients are still being monitored for toxicity, potentially reducing the trial duration. The Bayesian decision rules in PoD-BIN employ the probability of decisions to balance the trade-off between accelerating the trial and the risk of exposing patients to excessively toxic doses. Through numerical examples, we illustrate the trade-off between speed and safety of PoD-BIN and compare it with existing designs. PoD-BIN demonstrates the ability to control the frequency of risky decisions while simultaneously shortening trial duration in simulations. © Institute of Mathematical Statistics, 2025.

关键词： and phrases. Dose limiting toxicity equivalence interval latent probit regression moderate toxicities phase I trial time to toxicity

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An Improved Numerical Solution of Modified Regularized Long Wave Equation by Quartic Trigonometric B-Spline

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International Journal of Applied and Computational Mathematics 2025年第2期11卷 1-17页

作者： Kırlı, Emre Mersin, Mehmet Ali Department of Mathematics Aksaray University Aksaray 68000 Türkiye Computer Programming Aksaray University Aksaray 68000 Türkiye

This study presents the application of a numerical method specifically designed to solve the Modified Regularized Long Wave equation, a crucial model in the analysis of non-linear wave dynamics. The proposed method employs a Quartic Trigonometric B-spline approach for spatial discretization, which ensures smooth and accurate interpolation across the spatial domain, while temporal integration is conducted using the well-established fourth-order Runge–Kutta (RK4) scheme, known for its stability and precision. To evaluate the performance of the method, it is applied to three test problems: the propagation of a single solitary wave, the interaction between two and three solitary waves. The invariant quantities are computed for all test cases. To ensure the stability of the method, a stability analysis is performed through the computation of eigenvalues. The results demonstrate that the proposed method achieves a high degree of accuracy in preserving the invariant properties and produces minimal error, highlighting its efficiency and reliability. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Modified regularized long wave Quartic trigonometric B-spline Runge Kutta Solitary wave

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A fault-tolerant scheduling strategy through proactive and clustering techniques for scientific workflows in cloud computing

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Soft Computing 2025年第2期29卷 755-781页

作者： Farhood, Suha Mubdir Khorsand, Reihaneh Hussein, Nashwan Jasim Ramezanpour, Mohammadreza Branch Islamic Azad University Isfahan Iran Department of Programming Collage of Information Technology University of Babylon Hillah Iraq Department of Computer Engineering Mobarakeh Branch Islamic Azad University Mobarakeh Isfahan Iran

Cloud computing offers solutions for various scientific and business applications. Large-scale scientific applications, which are organized as scientific workflows, are carried out using cloud computing. However, the higher failure rates in cloud computing can be attributed to the numerous servers and components dealing with intense workloads. This study presents a fault-tolerant scheduling approach using proactive and clustering methods for scientific workflows in cloud computing. Initially, the task clustering issue is addressed by consolidating multiple short-duration tasks into a single job to improve the runtime performance of workflow executions. Subsequently, an automated workflow scheduling strategy is outlined with four key stages: monitoring, analysis, planning, and execution. During monitoring, clustered jobs and the capacities of available cloud resources are observed. In the analysis phase, the accuracy of failure prediction is enhanced by employing the Group Method of Data Handling (GMDH) neural network prior to any faults or failures. The planning stage introduces a novel hybrid multi-objective algorithm, MOPSO-aSA, based on MOPSO and adaptive simulated annealing (SA), to streamline workflow scheduling in error-prone execution environments. Moreover, the reliability of application execution is maintained through re-clustering and migration techniques following any faults or failures. Finally, based on the experimental findings, it is evident that the proposed strategy surpasses other methods in terms of makespan, total cost, energy consumption, and failure rate. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Simulated annealing

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A charged hadronic string model within the R.P. Feynman proper time paradigm and vacuum field theory approach 14

A charged hadronic string model within the R.P. Feynman prop...

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14th Biennial Conference on Classical and Quantum Relativistic Dynamics of Particles and Fields, IARD 2024

作者： Bogolubov, Nikolai N. Prykarpatski, Anatolij K. ICTP Trieste Italy Department of Applied Mathematics The Cracov University of Technology Kraków Poland Department of Computational Mathematics and Programming The Lviv Polytechnic National University Lviv Ukraine

We study a novel charged hadronic string model within the least action principle and the vacuum field theory approach based on the classical R.P. Feynman’s proper time paradigm. It is stated that the hadronic string model allows the conformal local coordinates, with respect to which the resulting string dynamics is described by means of the linear second order elliptic equation under the Dirac type constraint, suitable for the canonical quantization and demonstrating a related gauge type invariance of the model. The related Lagrangian and Hamiltonian aspects of the string model, interacting with ambient both electrical and electromagnetic potential fields, are analyzed in detail. © 2025 Institute of Physics Publishing. All rights reserved.

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Renal Tumor Classification and Detection Based on Artificial Intelligence 3

Renal Tumor Classification and Detection Based on Artificial...

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3rd International Conference on Communications, Information System, and Data Science, CISDS 2024

作者： Al-Taie, Raflaa Hilmi Hussein, Nashwan J. Physiology and Organ Functions Department College of Medicine University of Babylon Iraq Department of Electrical Power Engineering AL-Hussain University College Department of Programming Collage of Information Technology University of Babylon Iraq

ISBN: (数字)9781510688322

ISBN: (纸本)9781510688315

The kidney is a crucial organ in the human body, co-operating billions of pipelines to cleanse the body's water. Kidney failure, renal tumor happens when cells divide uncontrollably and form an aberrant collection of cells surrounding or within the kidney. This cell type has the ability to disrupt regular kidney activity and destroy healthy cells. The prompt diagnosis of renal tumor is critical since they can be fatal if left untreated. Because it is dependent on the skill of the person analyzing the images, the traditional approach of manually checking the MR image may not be very accurate. The study concentrated on the diagnosis of normal and normal renal tumor. To enhance accuracy and expedite diagnosis, using publicly accessible individual records, the present research used methodologies for machine learning, involving support vector machine learning (SVM), adaptive optimization (AO), as well as gradient enhancement (GE). It uses an approach for making the dataset reduced multidimensional. Image feature extraction is a data preprocessing method that minimizes the time required to train the proposed algorithm. The accuracy rates of the algorithms for diagnosing normal and up normal are reported to be 88.8 % for GB, 83.8 % for ADA, 86.1 % for SVM and 93.3% for KNN and for up normal diagnosis tumor are reported to be 55.3 % for GB, 55.4 % for SVM, 55.3 % for ADA and 51.0% for KNN. © 2025 SPIE.

关键词： Image enhancement

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Analyzing a Transportation Problem with Reliability Under the Shadowed Environment

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Operations Research Forum 2025年第2期6卷 1-38页

作者： Bera, Raj Kumar Mondal, Shyamal Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

The concept of reliability is crucial in assessing the ability of a transportation network to provide the continuity in operation. Because of this, in the recent transportation business, sources are being pressurized to deliver items reliably and cost-effectively. In such a direction, a classical transportation problem has been modified to a reliable transportation problem by incorporating the transportation reliability along with cost. Also, the main objective of this study is to minimize the cost and maximize the reliability of the proposed problem simultaneously. Here, the transportation reliability has been considered based on the deterioration of items and failure of the transportation mode. It is noted that both the cost and reliability of each path are assigned through negotiation at the beginning of the business; therefore, both data are uncertain. Also, to properly cover the uncertainty, the model has been formulated under the shadowed environment. To solve the proposed model, various methodologies are developed such as a weighted-based de-shadowed procedure to convert the uncertain model into an equivalent deterministic model, a weighted sum method to convert the multi-objective model into a single objective model, the lingo solver to find the optimal result, and a method to find the most efficient pareto optimal result. To justify the impact and significance of the proposed model in the real world, some numerical studies have been done. The variation of results due to uncertainty has been presented. In addition, the effect of negotiation on the uncertainty has been discussed.

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Fostering Attachment to the Community by Discovering of Local Resources using Location-Based System 19

Fostering Attachment to the Community by Discovering of Loca...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Honda, Ken Itoga, Chiharu Hattori, Akira Faculty of Technology International Professional University of Technology Tokyo Japan Department of Sound Programming SITE LLC Osaka Japan Faculty of Global Media Studies Komazawa University Tokyo Japan

ISBN: (纸本)9798331507817

In Japan, population decline and the depopulation of local regions have become social issues. Various municipalities are working to discover and promote the unique attractions of their regions. Identifying the local resources can help foster attachment to the region, potentially reducing population outflow and increasing the number of new residents. In this paper, we propose a location-based system to discover local resources and their associated stories to foster attachment to the local community. To evaluate whether this system effectively identifies local attractions and cultivates attachment to the community, we organized a town walking event in collaboration with local municipalities and members of local community groups in the event area. © 2025 IEEE.

关键词： Depopulation Local Resources Location-based System Tourism Informatics Town Walking Event

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

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Control, Automation, and Instrumentation (IC2AI), International Conference on

作者： Georgio Abou Haydar Samer Telawi Josef Börcsök Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

关键词： Service robots Intrusion detection Prototypes Human-robot interaction Industrial robots Manipulators Safety System-on-chip IEC Standards Standards

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