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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Tsilikas, Ioannis Tsirigotis, Aris Deligiannidis, Stavros Tsigaridas, Georgios N. Bogris, Adonis Mesaritakis, Charis National Technical University of Athens Dept. Physics Iroon Polytechniou 9 Zografou Athens15772 Greece University of the Aegean Dept. Information and Communication Systems Engineering Palama 2 str. 83200 Karlovasi Samos Greece University of West Attica Dept. Informatics and Computer Engineering Ag. Spiridonos Egaleo12243 Greece

ISBN: (纸本)9798350345995

In this work, we investigate the compression capabilities of a photonic neuromorphic accelerator relying on an optical spectrum slicing technique [1], following a high-flow 1D imaging cytometry setup, able to image 62000 particles/sec. The utilized image scheme relies on a technique, where spatial information is transfered to the spectrum and subsequently through dispersion to the temporal domain. Therefore, it can replace high speed spectrometers with a single photodetector [2]. On the other hand, the elevated image acquisition rate, trigger the generation of a staggering amount of data, which can cause a processing backlog at the digital backend. In this context, we explore, for the first time, the use of a photonic neuromorphic pre-processing unit, following the cytometer that can reduce the number of trainable parameters at a lightweight digital backend by a factor of 2.5, while at the same time, it can project incoming data to a high dimensional space boosting accuracy. © 2023 IEEE.

关键词： Photonics

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Power and Rate Allocation for Energy-Efficient Rate-Splitting Multiple Access via Deep Q-Learning

Power and Rate Allocation for Energy-Efficient Rate-Splittin...

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IEEE Globecom Workshops

作者： Maria Diamanti Georgios Kapsalis Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

Rate-Splitting Multiple Access (RSMA) has recently emerged as an effective technique for increasing network capacity by smartly controlling the tradeoff between decoding and treating interference as noise. In this paper, aligned with the need for sustainable wireless networks, we study the energy-efficient power and rate allocation of the common and private messages in the downlink of a network where rate-splitting is adopted. The corresponding energy efficiency maximization problem is transformed into a multi-agent Deep Reinforcement Learning (DRL) problem, based on which each private stream transmitted in the downlink constitutes a different DRL agent. The formulated DRL problem is solved by using Deep Q-Learning (DQL) algorithm and training a single Deep Q-Network (DQN) from the cumulative experiences gained from the DRL agents and their exploration of the environment, i.e., the exploration of different private-message power allocations. Numerical results obtained via modeling and simulation verify the effectiveness of the proposed DQL algorithm, demonstrating that it concludes solutions that outperform existing approaches from the literature in the achieved energy efficiency.

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Multiband Microstrip Patch Antenna Operating at Five Distinct 5G mm-Wave Bands

Multiband Microstrip Patch Antenna Operating at Five Distinc...

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2021 International Conference of Technology, Science and Administration, ICTSA 2021

作者： Saeed, Osama Y. A. Saeed, Ahmed A. A. Gaid, Abdulguddoos S. A. Aoun, Amjad M. H. Sallam, Amer A. Taiz University Faculty of Engineering and IT Dept. of Communication and Computer Engineering Taiz Yemen Taiz University Faculty of Engineering and IT Dept. O F Computer Networks and Distributed Systems Taiz Yemen

ISBN: (纸本)9781665428620

A novel mm-Wave multiband microstrip patch antenna for 5G wireless communication is designed and presented in this paper. The proposed design is an H-shaped with inset feed and a rectangular slit in the upper side of the radiating patch. The 5G mm-Wave antenna resonates at frequencies of 23.2, 40.3, 59.3, 86.9 and 104.3 GHz with a maximum bandwidth of 1.1, 2.8, 18.1, 7.7 and 10.7 GHz respectively. The antenna has sufficient realized gains of 6.4882, 7.1198, 7.9062, 8.1804 and 9.8156 dBi at the resonant frequencies respectively. Furthermore, the antenna covers the most interest 5G mm-Wave spectrum with a total bandwidth of 40.4 GHz. The proposed multiband antenna is designed using microstrip technology with features such as light weight, low cost, low profile, high gain and efficiency. The 5G antenna is designed using a high frequency structure simulator software (HFSS). It has a small form factor of 7.5 × 8.5 × 0.55 mm3. The antenna is compact enough to incorporate into smart devices and used for various 5G applications. © 2021 IEEE.

关键词： Bandwidth

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Building Collaborative Learning: Exploring Social Annotation in Introductory Programming

Building Collaborative Learning: Exploring Social Annotation...

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Software engineering: Software engineering Education and Training (ICSE-SEET), IEEE/ACM International Conference on

作者： Francisco Gomes De Oliveira Neto Felix Dobslaw Dept. of Computer Science and Engineering Chalmers and the University of Gothenburg Gothenburg Sweden Dept. of Quality Mngmt Communication and Inf. Systems Mid Sweden University Östersund Sweden

ISBN: (数字)9798400704987

ISBN: (纸本)9798350352115

The increasing demand for software engineering education presents learning challenges in courses due to the diverse range of topics that require practical applications, such as programming or software design, all of which are supported by group work and interaction. Social Annotation (SA) is an approach to teaching that can enhance collaborative learning among students. In SA, both students and teachers utilize platforms like Feedback Fruits, Perusall, and Diigo to collaboratively annotate and discuss course materials. This approach encourages students to share their thoughts and answers with their peers, fostering a more interactive learning environment. We share our experience of implementing social annotation via Perusall as a preparatory tool for lectures in an introductory programming course aimed at undergraduate students in Software engineering. We report the impact of Perusall on the examination results of 112 students. Our results show that 81% of students engaged in meaningful social annotation successfully passed the course. Notably, the proportion of students passing the exam tends to rise as they complete more Perusall assignments. In contrast, only 56% of students who did not participate in Perusall discussions managed to pass the exam. We did not enforce mandatory Perusall participation in the course. Yet, the feedback from our course evaluation questionnaire reveals that most students ranked Perusall among their favorite components of the course and that their interest in the subject has increased.

关键词： Training Software design Annotations Federated learning Buildings Programming profession Software engineering

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Building Collaborative Learning: Exploring Social Annotation in Introductory Programming

arXiv

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arXiv 2024年

作者： de Oliveira Neto, Francisco Gomes Dobslaw, Felix Chalmers The University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden Mid Sweden University Dept. of Quality Mngmt Communication and Inf. Systems Östersund Sweden

关键词： Students

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Photonic Neuromorphic Accelerator Combined with an Event-Based Neuromorphic Camera for High-Speed Object Classification

Photonic Neuromorphic Accelerator Combined with an Event-Bas...

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Tsirigotis, Aris Tsilikas, Ioannis Sozos, Kostas Bogris, Adonis Mesaritakis, Charis University of the Aegean Dept. Information and Communication Systems Engineering Palama 2 str. Karlovasi Samos83200 Greece National Technical University of Athens Dept. Applied Physics and Mathematics Iroon Polytechniou 9 Zografou Athens15772 Greece University of West Attica Dept. Informatics and Computer Engineering Ag. Spiridonos Egaleo12243 Greece

ISBN: (纸本)9798350345995

In this work, we demonstrate the impact of an unconventional convolutional photonic accelerator, based on an optical spectrum slicing (OSS) [1], on the classification accuracy of objects, generated through a high-frame rate neuromorphic event-based camera [2]. The experimental setup is depicted in Fig.1a. Ιt consists of a 5 mW-632 nm-LED source, two objective lenses with NA=0.65 that concentrate the light beam into a 100 μmX100 μm channel. In our experiments, the targeted objects consist of test spheres, of different diameters (12, 16, and 20 μm), used in aqua solutions. A pump regulated the sphere's speed to 0.8 m/s. The objects were recorded by a 10 kframe/s capable neuromorphic camera, with a temporal resolution of 1 μs. The camera detects pixel's contrast changes (events), similar to biological systems [2]. The recorded events were exported into 1 kframes/sec videos through a synthetic frame generator software, resulting to 2988 images per particle [2]. Images were post-processed using only noise reduction by frame subtraction and image cropping so as to reduce data volume to 100 x 100 pixels. © 2023 IEEE.

关键词： Cameras

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Automated Boundary Identification for Machine Learning Classifiers

Automated Boundary Identification for Machine Learning Class...

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Search-Based and Fuzz Testing (SBFT), IEEE/ACM International Workshop on

作者： Felix Dobslaw Robert Feldt Dept. of Quality Mngmt Communication and Inf. Systems Mid Sweden University Östersund Sweden Dept. of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (数字)9798400705625

ISBN: (纸本)9798350376012

AI and Machine Learning (ML) models are increasingly used as (critical) components in software systems, even safety-critical ones. This puts new demands on the degree to which we need to test them and requires new and expanded testing methods. Recent boundary-value identification methods have been developed and shown to automatically find boundary candidates for traditional, non-ML software: pairs of nearby inputs that result in (highly) differing outputs. These can be shown to developers and testers, who can judge if the boundary is where it is supposed to ***, we explore how this method can identify decision boundaries of ML classification models. The resulting ML Boundary Spanning Algorithm (ML-BSA) is a search-based method extending previous work in two main ways. We empirically evaluate ML-BSA on seven ML datasets and show that it better spans and thus better identifies the entire classification boundary(ies). The diversity objective helps spread out the boundary pairs more broadly and evenly. This, we argue, can help testers and developers better judge where a classification boundary actually is, compare to expectations, and then focus further testing, validation, and even further training and model refinement on parts of the boundary where behaviour is not ideal.

关键词： Training Conferences Machine learning Fuzzing Software systems Classification algorithms Testing

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Unveiling Disparities: NLP Analysis of Software Industry and Vocational Education Gaps

Unveiling Disparities: NLP Analysis of Software Industry and...

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Natural Language-Based Software engineering (NLBSE), IEEE/ACM International Workshop on

作者： Emil Bäckstrand Rasmus Djupedal Lena-Maria Öberg Francisco Gomes De Oliveira Neto Dept. of Quality Management Communication and Inf. Systems Mid Sweden University Östersund Sweden Dept. of Computer Science and Engineering Chalmers|University of Gothenburg Gothenburg Sweden

ISBN: (数字)9798400705762

ISBN: (纸本)9798350352559

The rapid growth of software industry highlights the importance of the education system in producing competent professionals to meet industry demands. Previous research has identified a gap between industry needs and the content of educational programs. This study presents Vocational Education and Labour Market Analyser (VELMA), a tool designed to extract information from job ads and educational curricula (both from Sweden), utilising topic modelling to identify the diverse technologies and skills in demand within the industry and those covered by professional education. Particularly, we use Latent Dirichlet Allocation (LDA) to categorise keywords into cohesive themes for document frequency analysis. Our findings highlight industry demand for skills in cloud and embedded technologies, security engineering, and software architecture. In contrast, the Higher Vocational Education (HVE) curricula emphasise the education of web developers and general object-oriented programming languages. CCS CONCEPTS • Applied computing $\rightarrow$ Document management and text processing; Education; $\cdot$ Software and its engineering $\rightarrow$ Designing software.

关键词： Industries Analytical models Text analysis Object oriented modeling Education Software Natural language processing

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Thermal Satellite Imagery Analysis and Emissivity Characteristics for the Prediction of Oil Reservoirs Existence 7

Thermal Satellite Imagery Analysis and Emissivity Characteri...

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7th International Conference on Space Science and communication, IconSpace 2021

作者： Tarish, Ali Badri Sali, Aduwati Mohamed Shariff, Abdul Rashid Hanafi, Marsyita Ismail, Alyani Mohammed, Intehaa A. Upm Dept. Of Computer & Communication Systems Engineering Serdang Selangor Malaysia Upm WiPNET Research Centre Dept. Of Computer & Communication Systems Engineering Serdang Selangor Malaysia Upm Dept. Of Biological & Agricultural Engineering Serdang Selangor Malaysia Uob College Of Education For Pure Sciences Dept. Of Physics Babylon Iraq

ISBN: (纸本)9781665425230

Simultaneous transformation of natural land cover contributes significantly to changing the surface phenomena making accurate forecasting difficult. Ground surveys would permit Land Use Land Cover (LULC) classification, but they are burdensome, expensive, and time-consuming and lacks accuracy in the exploration for all target areas at the same time, which highlights satellite imagery an evident and preferred alternative. A new mathematical method has been used for calculating the highest and lowest Land Surface Temperature (LST) to improve model accuracy for a particular location and detect oil seep-induced alteration from Landsat Data Continuity Mission (LDCM). Two sites within different patterns were chosen to represent a diversity of thermal anomalies positions in the study area. The results show that there are no traces of oil in either zone 1 lies which in the Kanoya province and zone 2 located east of the coast of Kagoshima which is overlooking the Pacific Ocean. In the end, the night-time scenes of the Thermal Infrared Sensor (TIRS) achieve a high gain of the thermal image with radiance 3.2-12.65 (Watts/m2 sr μm). Moreover, the analysis of the (TIRS) image is an optimal explanation for geomorphology and subsurface geology in southern Japan via the potentiality of the simulators set. © 2021 IEEE.

关键词： Satellite imagery

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Neuromorphic computing by means of recurrent spectrum slicing for next generation high baud rate transmission systems

Neuromorphic computing by means of recurrent spectrum slicin...

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LEOS Summer Topical Meetings

作者： Adonis Bogris Kostas Sozos George Sarantoglou Stavros Deligiannidis Charis Mesaritakis Dept. Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Information and Communication Systems Engineering University of the Aegean Karlovassi Greece

In this paper we review our recent work in photonic neural networks based on recurrent optical spectrum slicing as potential accelerators for the mitigation of transmission impairments in short reach, high symbol rate...

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