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An Implementation of Answer Code Validation Program for Code Writing Problem in Java Programming Learning Assistant System

An Implementation of Answer Code Validation Program for Code...

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Information and Education Technology (ICIET), International Conference on

作者： Khaing Hsu Wai Nobuo Funabiki Soe Thandar Aung Khin Thet Mon Htoo Htoo Sandi Kyaw Wen-Chung Kao Dept. of Information and Communication Systems Okayama University Okayama Japan Dept. of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

To assist Java programming learning of novice students, we have developed the web-based Java Programming Learning Assistant System (JPLAS). It provides various exercise problems to cultivate code reading and code writing skills to support studies at various levels. The code writing problem (CWP) asks a student to write a source code to pass the given test code where the correctness is verified by running them on JUnit. Previously, we implemented the answer platform for students to solve CWP assignments with the automatic runs. However, the teacher needs to manually run them one by one to verify a lot of source codes from students. In this paper, we implement the answer code validation program that automatically verifies all the source codes for one test code and reports the number of tests that each code passed with the CSV file. For evaluations, we applied the program to a total of 999 source codes from 12-43 students for a total of 45 test codes that were assigned in the Java programming course in Okayama university, including for final examinations. The application results confirm the validity and effectiveness of the proposal.

关键词： Java Codes Source coding Education Writing Proposals Programming profession

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Ensuring Accurate Frequency in the Hardware Design of Grid-Forming (GFM) Inverter

Ensuring Accurate Frequency in the Hardware Design of Grid-F...

引用

Annual North-American Power Symposium

作者： Shuvangkar Chandra Das Paychuda Kritprajun Deepak Ramasubramanian Evangelos Farantatos Abhishek Banerjee Ulrich Muenz Dept. of ECE Clarkson University Potsdam New York Dept. of Electrical Engineering University of Tennessee Knoxville Knoxville Tennessee Grid Operation & Planning EPRI Knoxville Tennessee Grid Operation & Planning EPRI Palo Alto CA Autonomous Systems and Control Siemens Technology Princeton NJ

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

Accurate frequency generation is crucial for the hardware implementation of a grid-forming inverter (GFM). Unlike grid-following inverters (GFL), the phase angle and frequency generation in GFMs rely entirely on on-device computation and the crystal oscillator. Due to inaccuracies in the crystal oscillator and floating point quantization errors, the frequency of GFM inverters can drift. This drift can cause power sharing inequalities and interactions in multi-loop GFM control, leading to instability during operation. This issue applies to all microcontrollers and simulations that use 32-bit floating-point arithmetic for control algorithms. In this paper, we demonstrate a case study of frequency drifting in GFM inverters caused by floating point computation errors. We propose two solutions to solve the frequency drift issue in GFM. Finally, we present how the proposed GFM clock generators improve droop control power sharing and solve multi-loop GFM control interactions due to frequency drifting. Hardware and simulation results are provided to demonstrate the effectiveness of the proposed solutions.

关键词： Accuracy Microcontrollers Computational modeling Crystals Inverters Hardware Generators Stability analysis Oscillators Grid forming

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Improving ASTRO's Perception Capability for a more Natural Follow-Me Task

Improving ASTRO's Perception Capability for a more Natural F...

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Experiment@ International Conference (exp.at)

作者： Bruno Ferreira Alessandra Sorrentino Paulo Menezes Jorge Batista Jorge Dias Laura Fiorini Filipo Cavallo Dept. of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal Dept. of Industrial Engineering University of Florence Florence Italy Khalifa University Center for Autonomous Robotic Systems Khalifa University of Science and Technology Abu Dhabi UAE BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

Social assistive robots usually encompass a great compromise between the advanced perception models that one can use and their computing capabilities. The ideal approaches are always oriented towards low power consumption while maintaining a higher order of responsiveness to the surroundings. Therefore, we present in this paper, an improvement of the follow-me system on ASTRO. In detail, we propose the use of Mediapipe SDK for human detection and tracking, when ASTRO is meant to accompany someone that is walking. A study on the new velocity and distance profiles that the robot keeps from the individuals is presented and we have also evaluated how it affects their perception of being safe. The presented results show that our new approach allows the system to achieve real-time performance by becoming $\approx 9.1\times \mathbf{faster}$ , smoothing, and keeping a more natural distance from the user.

关键词： Legged locomotion Smoothing methods Power demand Computational modeling Robot vision systems Pose estimation Cameras

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Anomaly Detection With Quantified Explanations for Multivariate Time Series Networking Data

Anomaly Detection With Quantified Explanations for Multivari...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Panagiotis Marantis Kostas Ramantas Christos Verikoukis Industrial Systems Institute Patras Greece Iquadrat Informatica S.L Barcelona Spain Dept. of Computer Engineering and Informatics University of Patras Patras Greece Athena Research Center Athens Greece

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Next-generation telecommunication networks provide vast amounts of Multivariate Time Series monitoring data during their operation. Using these data to automatically detect anomalous system behavior is of critical importance to operators and Internet Service Providers, in order to analyze the network state and take mitigating actions to resolve possible faults. For the output of this Anomaly Detection process to be trusted, comprehensive and accurate explanations must be provided. These explanations are essential to make critical decisions that affect the network state. In this paper, we present a framework that utilizes reconstruction-based Deep Neural Network models to perform the anomaly detection task, while also using an explainability module that provides explanations of the results. The quality of the explanations is quantified through the use of interpretation labels. In addition, we provide a comparative analysis, performing Anomaly Detection on three different open-source datasets from the mobile networking domain, while testing multiple Deep Learning models and comparing their performance. The presented results show that our framework accurately detects various types of anomalies that can be present in mobile networks, while offering the flexibility to identify and select the model that offers the best performance for each dataset, in both the Anomaly Detection and explainability tasks.

关键词： Deep learning Time series analysis Web and internet services Data models Communications technology Global communication Anomaly detection Next generation networking Monitoring Testing

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Key Exchange in the Quantum Era: Evaluating a Hybrid System of Public-Key Cryptography and Physical-Layer Security

Key Exchange in the Quantum Era: Evaluating a Hybrid System ...

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Annual Conference on Information Sciences and systems (CISS)

作者： Paul Staat Meik Dörpinghaus Azadeh Sheikholeslami Christof Paar Gerhard Fcllwcis Dennis Goeckel Max Planck Institute for Security and Privacy Bochum Germany Vodafone Chair Mobile Communications Systems Technische Universität Dresden Dresden Germany Math and Computer Science Department Suffolk University Boston Dept. Electrical and Computer Engineering University of Massachusetts Amherst USA

ISBN: (数字)9798331513269

ISBN: (纸本)9798331513276

Today's information society relies on cryptography to achieve security goals such as confidentiality, integrity, authentication, and non-repudiation for digital communications. Here, public-key cryptosystems play a pivotal role to share encryption keys and create digital signatures. However, quantum computers threaten the security of traditional public-key cryptosystems as they can tame computational problems underlying the schemes, i.e., discrete logarithm and integer factorization. The prospective arrival of capable-enough quantum computers already threatens today's secret communication in terms of their long-term secrecy when stored to be later decrypted. Therefore, researchers strive to develop and deploy alternative *** this work, we evaluate a key exchange protocol based on combining public-key schemes with physical-layer security, anticipating the prospect of quantum attacks: If a powerful quantum attacker cannot immediately obtain a private key, legitimate parties have a window of short-term secrecy to perform a physical-layer jamming key exchange (JKE) to establish a long-term shared secret. Thereby, the protocol constraints the computation time available to the attacker to break the employed public-key cryptography. In this paper, we outline the protocol, discuss its security, and point out challenges to be resolved.

关键词： computers Protocols Quantum computing Quantization (signal) Non-repudiation Public key cryptography Security Time factors Jamming Signal resolution

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Deep-Learning Enabled Assessment of Neurocognitive Performance in Object Following in Mixed Reality

Deep-Learning Enabled Assessment of Neurocognitive Performan...

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IEEE International Conference on Connected Health: Applications, systems and engineering Technologies (CHASE)

作者： Ansh Sharma Keerthana Nallamotu Mukhilshankar Umashankar Shenlong Wang Inki Kim Dept. of Computer Science University of Illinois Urbana-Champaign USA Dept. of Computer Engineering University of Illinois Urbana-Champaign USA Health Care Engineering Systems Center University of Illinois Urbana-Champaign USA

ISBN: (数字)9781450394765

The objective of this article is to develop a deep learning model to construct a comprehensive, machine-learnable representation of human performance that spans visual, cognitive, and motor-control abilities associated with an object-following task in mixed reality (MR). Compared to direct observations by trained clinical staffs, which is the current standard for clinical diagnosis, a deep learning approach is expected to detect subtle signs of neurocognitive abilities and/or impairment. If successful, the resultant representation will bring a new opportunity to be shared and communicated with humans, a first step to collaborative workflows between clinical staffs and artificial intelligence (AI) specialists for diagnosis.

关键词： Deep learning Visualization Mixed reality Collaboration Virtual reality Transformers Clinical diagnosis

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Applying Deep Learning to Autonomous Vehicles: A Survey 4

Applying Deep Learning to Autonomous Vehicles: A Survey

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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Ren, Jing Gaber, Hossam Al Jabar, Sk Sami Ontario Tech University Dept. of Electrical and Computer Engineering OshawaON Canada Ontario Tech University Faculty of Energy Systems and Nuclear Science OshawaON Canada

ISBN: (纸本)9780738131702

Autonomous vehicles will revolutionize the future automotive industry by reducing or eliminating human errors and increasing vehicle safety. The design of autonomous vehicles will bring together many modern technologies such as control, computer vision, path planning, sensor fusion and fault diagnosis. Although traditional algorithms can be used to implement these technologies, in the last decade, deep learning has been proposed to challenge traditional algorithms and excels in many applications and research areas. Deep learning has shown its significant use in the design and operation of autonomous vehicles. In this paper, we will review the application of deep learning in five major research areas of autonomous vehicles i.e. path planning, control, computer vision, sensor fusion and fault diagnosis. Recent advances of the deep learning in autonomous vehicles will be reviewed and discussed. © 2021 IEEE.

关键词： Failure analysis

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Advanced Visual Interfaces and Interactions in Cultural Heritage (AVICH 2024) 24

Advanced Visual Interfaces and Interactions in Cultural Heri...

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Proceedings of the 2024 International Conference on Advanced Visual Interfaces

作者： Tsvi Kuflik Berardina Nadja De Carolis Cristina Gena Antonio Origlia Julia Sheidin Information Systems The University of Haifa Israel Department of Computer Science dipartimento di informatica universita' di bari Italy Computer Science Department of Computer Science University of Torino Italy Dept. of Electrical Engineering and Information Technology URBAN/ECO Research Center ?Federico II? University Naples Italy Italy Information Systems Braude College Israel

ISBN: (纸本)9798400717642

Cultural Heritage (CH) is a challenging domain of application for novel Information and Communication Technologies (ICT), where visualization plays a major role in enhancing the visitors’ experience, whether onsite or online. Technology-supported natural human-computer interaction is a key factor in enabling access, both on-site and online, to CH assets. Recent advances in ICT enhance visitors’ access to online collections as well as their CH experience onsite, bringing even wider audiences than those who visit the physical museums. The range of visualization devices – from tiny smartwatch screens, through large situated public displays, to the latest generation of immersive Head-Mounted Displays – together with the increasing availability of real-time 3D rendering technologies for online and mobile devices and, recently, Internet of Things (IoT) approaches, Social Robotics, requires exploring how they can be applied successfully in CH. Following the successful workshops at AVI 2016, AVI 2018, AVI 2020, AVI 2022 and AVI 2024 and a large number of recent events and projects focusing on CH, the goal of the workshop is to bring together researchers and practitioners interested in presenting and discussing the potential of state of the art advanced visual interfaces in enhancing our daily cultural heritage experience. This year the workshop theme will be: AVI for accessibility in CH.

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Ensuring Safety for UAVs Through Event-Triggered Predictive control

Ensuring Safety for UAVs Through Event-Triggered Predictive ...

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Mediterranean Conference on control and Automation (MED)

作者： Sotirios N. Aspragkathos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens Athens Greece Dept. of Informatics and Telecommunications University of Thessaly Lamia Greece Engineering Division and Center for AI & Robotics (CAIR) New York University Abu Dhabi UAE

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

This paper presents a control system for un-manned aerial vehicles (UAVs) that track deformable objects. Using Event-Triggered (ET) principles and Image Moments-Based Nonlinear Model Predictive control (NMPC), the suggested approach improves flexibility by triggering control changes in response to specific occurrences. The incorporation of Barrier Functions (BFs) enforces safety requirements, which are critical for negotiating uncertain terrains. The framework's implementation and testing on a UAV tracking deformable coastlines are intended to demonstrate its effectiveness in adapting to dynamic situations while adhering to safety limitations.

关键词： Coastlines Target tracking Streaming media Aerodynamics Visual servoing Safety Vehicle dynamics

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Strategic Airlift Operationalizing Constructive Simulations

Strategic Airlift Operationalizing Constructive Simulations

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2020 Spring Simulation Conference, SpringSim 2020

作者： Barwell, Rob Wainer, Gabriel Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (纸本)9781565553705

Large organizations now use Modeling and Simulation (MS) for complex systems. This evolution has also resulted in a lack of simple tools and processes to define models and experiments which hinders wide scale user adoption of MS to solve many real-world problems. By exploring the Arctic logistical support base problem, we will illustrate how a simple MS process and system can be used by operators with limited knowledge of MS. This will be demonstrated by determining a temporary logistical support base for re-supplying military operations in the Canadian Arctic. © 2020 SCS.

关键词： Military operations

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