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International Conference on software engineering (ICSE)

作者： M. Orsted Software Development Engineer Microsoft Sandyford Industrial Estate Dublin Ireland

This paper is a position statement. There are important requirements on software development engineers that go beyond the normal academic qualifications and technical skills, and which quite often receive a lower priority in education and training. Some of the soft skills that are listed in the job descriptions for software development engineers at Microsoft are: change management; self-development; composure and stress management; problem-solving skills; drive for results; communication skills; and interpersonal skills. This paper focuses on the first four of these. The exact description of the soft skills needed changes depending on the level of the position.

关键词： Programming Computer industry Qualifications engineering management Industrial training Management training Design engineering software design Stress Career development

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software development engineer in Microsoft: a subjective view of soft skills required 00

Software development engineer in Microsoft: a subjective vie...

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Proceedings of the 22nd international conference on software engineering

作者： Martin Orsted Software Development Engineer Microsoft Blackthorne Road Sandyford Industrial Estate Dublin 18 Ireland

ISBN: (纸本)9781581132069

关键词： soft skills

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Design of Flexure Robotic Hand for Teleoperation 6th

Design of Flexure Robotic Hand for Teleoperation

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6th Joint International Conference on Multibody System Dynamics and 10th Asian Conference on Multibody Systems, IMSD-ACMD 2020

作者： Zubair, Mohammad Bhandari, Shubham Chatterjee, Indranath Department of Mechanical Engineering Adamas University Kolkata India Software Development Engineer-I HashedIn by Deloitte Bengaluru India Department of Computer Science Manchester Metropolitan University Manchester United Kingdom

ISBN: (纸本)9789819775248

Robots are getting deployed at home and in industries, becoming an integral part of our daily lives. Sophisticated mechanisms are required to make the joints of the robots compact and simple. In this paper, we have developed a flexure joint for the fingers of the robotic hand. The flexure joint is arranged in series to make a three-DOF underactuated finger. Five fingers are arranged to make a robotic hand. Castigliano’s theorem is used to develop the deformation related to the applied loads, using the equation the flexure mechanism was designed. Pseudo-rigid model is developed to determine the stiffness of the flexure mechanism. A virtual model of the flexure mechanism is developed in a CAD environment. Finite Element (FE) simulation is conducted to the different loading conditions to evaluate the performance of the flexure mechanism. It was seen that the flexure mechanism is flexible about the rotational axis and stiff about the other axes. The stiffness model developed using the pseudo-rigid model has a good correlation with the FE simulation model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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MSPAt-CNN: Multi Spectral Recurrent Primal Dual Attention Based Deep Learning Model for Intrusion Detection System with Mitigation

MSPAt-CNN: Multi Spectral Recurrent Primal Dual Attention Ba...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： Rupal K Panchal Rupal Snehkunj Vinaykumar V Panchal Department of Computer Science Sarvajanik University Surat Gujarat Software Development Engineer (work done outside Amazon)

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

Intrusion detection systems are the majorly used tools for defending various cyber-attacks in the real time scenarios. Deep learning-based methods have achieved remarkable success for early intrusion detection, besides, the existing techniques have experienced certain limitations including improper security, not timely response, and also providing a high false positive rate. To eliminate aforementioned challenges, the research proposes a multi spectral recurrent primal dual attention based convolutional neural network (MSP At-CNN) model for effective intrusion detection. The proposed model associates the MSP At module to focus on the deep features of the input data, which improves accuracy and robustness. Moreover, the MSPAt-CNN model provides automatic feature extraction using convolution blocks, which reduces complex computation and alleviates vanishing gradient problems. In addition to that, a mitigation system is included in the proposed framework, which recognizes malicious events and excludes cyber attacks. Furthermore, the performance results of the MSP At-CNN model show stability, as well as interpretability and offer proper security, therefore the proposed model attains maximum of 98.23% accuracy, 97.92% precision, and 98.54% recall using the CICIDS dataset compared to other conventional methods.

关键词： Adaptation models Accuracy Computational modeling Prevention and mitigation Intrusion detection Feature extraction Stability analysis Robustness Real-time systems Cyberattack

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Adaptive Deep Reinforcement Learning-based Resource Management for Complex Decision Making in Industry Internet of Things Applications 4

Adaptive Deep Reinforcement Learning-based Resource Manageme...

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4th International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Karne, Niharika Ramagundam, Chandra Shekar Patnala, Ranga Rao Ramagundam, Shashishekhar Tadiboina, Sai Nitisha Sr. Principal Systems Engineer in C&RS Platform Services University of South Alabama Department of Electrical Engineering Masters in Electrical Engineering Amtrak DT United States Software Engineer in Cloud Platform Services City of Philadelphia Pennsylvania United States Vice President Neuberger Berman United States Software Development & Engineering in Content Discovery & AI Troy University Department of Computer Science Masters in Computer Science AL Comcast Montgomery Campus United States Department of Information Technology GEICO - Chevy Chase Chevy ChaseMD20815 United States

An independent industrial system may transform into a connected network through the assistance of Industrial Internet of Things (IIoT). The deployed sensors in the IIoT maintain surveillance of the industrial machinery and equipment. As a result, safety and reliability emerge as the primary concerns in IIoT. This presents a variety of well-known and increasing issues related to the industrial system. The IIoT devices are exposed to a wide range of malware, threats, and assaults. To prevent the IIoT devices from malware effects, effective protection plans must be implemented. But adequate security mechanisms are not be incorporated in IIoT devices with limited resources. It is essential to ensure the accuracy and dependability of information gathered by IIoT devices. Decisions taken with incomplete or inaccurate data might be devastating. To overcome these difficulties deep learning with reinforcement learning for complex decision-making in industry applications is developed in this research work. In this developed model, an Adaptive Deep Reinforcement learning (ADRL)-based resource management is performed to reduce the operation cost associated with IIoT deployments. Energy efficiency is essential in IIoT ecosystem, particularly for the devices that run on batteries. Through dynamic resource allocation based on workload needs and energy limits, ADRL-based resource management optimizes the usage of energy. The reliability of the designed model is enhanced by fine-tuning the parameters from DRL using the Ship Rescue Optimization (SRO) algorithm. Thus, ADRL-based resource management systems make real-time decisions based on current environmental conditions and system requirements. This helps the IIoT systems to react quickly to change demands and optimize resource allocation. Finally, the experimental analysis is performed to find the success rate of the developed resource management system via various metrics. Throughout the validation, the statistical analysis of the

关键词： Deep reinforcement learning

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Developing a Blockchain-Based AI-IoT Platform for Industrial Automation and Control Systems 1

Developing a Blockchain-Based AI-IoT Platform for Industrial...

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1st International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Dalal, Aryendra Sareddy, Mohan Reddy Santharam, Vinoth Thoguluva Bhattacharjee, Partha Pratim Barboza-Sanchez, Luis Jesus Sahoo, Deepali Rani Middle Georgia State University GA United States Orasys LLC TX United States Software Development Engineer 5 Comcast Chennai India National Institute of Technology Mizoram India Jr. Centenario 156 Lima La Molina15026 Peru Symbiosis Law School Noida India Pune India

ISBN: (纸本)9798331518578

Blockchain, artificial intelligence (AI), and the internet of things (IoT) come together to offer a transformative opportunity to increase automation, effectiveness, and security across a variety of industries. Blockchain ensures decentralised trust, data integrity, and safe transactions, while AI enables analytics in real time, predictive insights, and intelligent decision-making. IoT enables smooth communication among the digital and physical worlds by connecting and gathering enormous volumes of data from smart devices. By combining these innovations, a synergistic ecosystem is produced in which AI safely analyses data provided by the Internet of Things and stores it on blockchain networks, guaranteeing transparency and immutability. Smart cities, healthcare, supply chain management, and autonomous systems are just a few of the many fields where this incorporation can be used to promote innovation and operational resilience. To fully utilise this trinity, however, issues like flexibility, compatibility, and privacy concerns need to be resolved. This study examines the advantages, drawbacks, and potential avenues for further research of the synergy amongst blockchain, AI, and the IoT. © 2025 IEEE.

关键词： Blockchain

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An SLS Launched Titan Balloon Spacecraft Mission

An SLS Launched Titan Balloon Spacecraft Mission

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Donahue, Benjamin Ziglar, Matt Van Sambeek, Justin Horsewood, Jerry Cupples, Mike Internal Research and Development The Boeing Company HuntsvilleAL35758 United States Exploration Systems The Boeing Company HuntsvilleAL35758 United States Guidance and Trajectory Design Engineer Exploration Systems The Boeing Company HuntsvilleAL35758 United States Developer of Mane Software Space Flight Solutions Corporation ColumbusNC United States Modelling Simulation and Mission Design Raytheon-retired SandpointID United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper describes the delivery of a spacecraft to Saturn's moon Titan. Once captured at Titan and deployed, a Zeppelin type spacecraft would ride the moon's stratified and dynamic wind currents, operating for several years. The inflatable spacecraft and science package would flyover and survey large segments of the surface of Titan including its poles, mountains, valleys and liquid lakes. The NASA Space Launch System (SLS) is capable of injecting a 24.1-mt payload to an injection energy (C3) of 29 km2/s2, required for launch in 2035. Flight time to Saturn will be 7.8-years. Carried with the spacecraft will be trailing tethers, deployable probes, and drones that descend through the clouds and the various layers of the atmosphere to the surface. The SLS Block 1 vehicle successfully flew its first mission in late 2022. The SLS is being upgraded to the new Block 2 configuration with the addition of a new large Exploration Upper Stage (EUS). The EUS will substantially increase SLS payload capability, making robust, high science outer planet missions like this mission to Titan a reality © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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Adaptive Deep Reinforcement Learning-based Resource Management for Complex Decision Making in Industry Internet of Things Applications

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Procedia Computer Science 2025年 252卷 231-240页

作者： Niharika Karne Chandra Shekar Ramagundam Ranga Rao Patnala Shashishekhar Ramagundam Sai Nitisha Tadiboina Sr. Principal Systems Engineer in C&RS Platform services DT Amtrak USA University of south alabama Department of electrical engineering Masters in electrical engineering Senior Software Engineer in Cloud platform services City Of Philadelphia Pennsylvania USA Vice president Neuberger Berman US Software Development & Engineering in Content Discovery & AI Comcast USA Troy University Montgomery Campus AL. Department of computer Science Masters In Computer Science Department of Information Technology GEICO - Chevy Chase Chevy Chase MD 20815 United States

关键词： Resource Management Industrial Internet of Things Applications Complex Decision Making Adaptive Deep Reinforcement Learning Ship Rescue Optimization

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Developing a Blockchain-Based AI-IoT Platform for Industrial Automation and Control Systems

Developing a Blockchain-Based AI-IoT Platform for Industrial...

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Aryendra Dalal Mohan Reddy Sareddy Vinoth Thoguluva Santharam Partha Pratim Bhattacharjee Luis Jesus Barboza-Sanchez Deepali Rani Sahoo Middle Georgia State University Georgia USA Orasys LLC Texas USA Software Development Engineer 5 Data Analytics Comcast Chennai India National Institute of Technology Mizoram India Business Advisor Business Banking La Molina Lima Peru Symbiosis Law School Noida Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

关键词： Industries Technological innovation Automation Data security Decision making Supply chains Real-time systems Blockchains Internet of Things Artificial intelligence

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Large storm relief tunnel for basement flood protection

Large storm relief tunnel for basement flood protection

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Proceedings of the 1st International Conference on Water Resources. Part 1 (of 2)

作者： Bouchard, Greg P. Q.C. Engineer and Software Development Winnipeg Canada

In Winnipeg, Manitoba, providing relief of collector sewer backwash into neighborhood basements during spring snow melt has always been a high priority. When spring rain water combines with accumulated winter snow, both the Red River and Assiniboine River basins send melt water flowing toward the city. This increases ground water and river levels substantially throughout the area. During the 1950's, a floodway was constructed to divert major flood levels from the Red River around the city. For upstream backwater damage reasons, however, system gates are only raised when predictions indicate that river banks through the city will be compromised. When heavy spring rain combines with large amounts of accumulated snow, temporary storage tunnels may be an excellent method to help solve urban water table control problems. The purpose of this paper is to provide project details concerning melt water relief and construction logistics for the large tunnel contract.

关键词： Sewer tunnels

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