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Asia-Pacific Conference on Software engineering

作者： Amirali Amiri Uwe Zdun André van Hoorn Faculty of Computer Science Research Group Software Architecture University of Vienna Vienna Austria Department of Informatics Software Engineering and Construction Methods University of Hamburg Hamburg Germany

Many dynamic routing architectural patterns are available, including distributed routing, e.g., using the sidecar pattern, or centralized routing, e.g., using event stores or service buses. Different Quality-of-Service (QoS) factors influence routing schemas and technology selection, such as performance, reliability, scalability, and control properties offered by the patterns. An analytical model can formalize the QoS factors and facilitate the architectural decision-making when changing the routing scheme, i.e., to more distributed or centralized routing. So far, the impact of these architectural patterns on performability, i.e., the overall performance of a system with impeded reliability, has not been extensively studied. This is important because deciding to increase performance, e.g., by parallel processing of requests, may lead to decreased reliability because of the added points of a crash. We propose an analytical performability model during component crashes. For the empirical validation of our proposed model, we ran an extensive experiment of 2412 hours of runtime on a private cloud infrastructure and Google Cloud Platform. The low prediction error of 1.75 % indicates the high accuracy of our performability model. These results provide important insights when making architectural decisions regarding service- and cloud-based dynamic routing.

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Design a CPW-Fed Circular Polarization Printed Antenna for 5G Sub-Band Applications

Design a CPW-Fed Circular Polarization Printed Antenna for 5...

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Contemporary Information Technology and Mathematics (ICCITM), International Conference on

作者： Haider Saad Mahmood Farhan Raed Abd-Alhameed Computer Techniques Engineering Middle Technique University Baghdad Iraq Faculty of Engineering and Informatics University of Bradford Bradford U.K

In this paper, a coplanar waveguide-fed (CPW) printed antenna with circular polarization is suggested for the sub-6 GHz 5th generation spectrum. The proposed antenna is characterized by its single metallic layer being printed on one side of an FR4 substrate dielectric material with epsilon value ($\varepsilon_{r}$) of 4.4 and tangent loss (tan$\delta$) of 0.02. The total size of the suggested antenna is 30$\times$ 23.2$\times $ 1 mm 3 . The results show a wide-impedance bandwidth starts at 3.9GHz and going up to more than 8GHz with an S 11 value smaller than -10dB (S 11 $\le$10 dB) and the axial ratio bandwidth (ARBW) varying from 4GHz to 7.38GHz with an axial ratio(AR) value smaller than -3dB. The gain varies from 2.8dB up to 4.18dB in the entire band. This antenna covers all the sub-6GHz frequency bands of the fifth generation (5 G) applications. The HFSS software is used to design and simulate the suggested antenna and the *** is used to validate the results.

关键词： Polarization Bandwidth Software Mathematics Coplanar waveguides Impedance Information technology

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Dataset Preprocessing Leveraging Vision Language Models: Storytelling for Accident Detection and Description

Dataset Preprocessing Leveraging Vision Language Models: Sto...

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Electrical engineering (ICEENG), International Conference on

作者： Mohamed Yossri Elwaly Amgad Abdo Aly Ahmed Sewelam Sarah Elshamy Asmaa Zayed Mohamed Elsayed Mohamed Abdou Mohamed Saleh Faculty of Computers and Data Science Alexandria University Alexandria Egypt Dept. of Electrical Engineering Phaors Uniersity in Alexndria Alexandria Egypt Faculty of Computer Science and Engineering Alamein International University (AIU) Alamein Egypt Informatics Research Institute City of Scientific Research and Technological Applications (SRTA-City) Alexandria Egypt

ISBN: (数字)9798331519018

ISBN: (纸本)9798331519025

In recent years, the Vision-Language Models (VLMs) have significantly advanced the field of storytelling applications. Visual storytelling involves the use of Generative AI models to transform a sequence of video frames into a semantics-preserving story-like text. A critical aspect of developing these models lies in the preparation of datasets, which directly impacts their efficacy and robustness. This paper explores a comprehensive methodology for dataset preparation tailored to the detection and description of car accidents in video surveillance footage. This research explains the necessity of data collection, annotation, and preprocessing to transform a sequence of frames in a video into a semantics-preserving story-like text. We describe the steps, tools and challenges of this task.

关键词： Electrical engineering Generative AI Visual analytics Scalability Semantics Transforms Video surveillance Robustness Automobiles Accidents

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Indonesian Traditional Shadow Puppet Classification using Convolutional Neural Network

Indonesian Traditional Shadow Puppet Classification using Co...

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2021 International Seminar on Application for Technology of Information and Communication, iSemantic 2021

作者： Prabowo, Dwi Puji Nugraha, M. Kuncoro Aji Ulumuddin, Dimas Irawan Ihya' Pramunendar, Ricardus Anggi Santosa, Stefanus Universitas Dian Nuswantoro Faculty of Computer Science Department of Visual Communication Design Semarang50131 Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Department of Informatics Engineering Semarang50131 Indonesia Politeknik Negeri Semarang Department of Civil Engineering Semarang50275 Indonesia

ISBN: (纸本)9781665428040

The reduced interest and knowledge of the Indonesian people about traditional culture has threatened the wayang kulit culture with extinction. Young people have forgotten and do not know the wayang kulit culture. Therefore, computer vision technology is expected to help introduce wayang kulit to young congregations. The technology that utilizes the Convolutional Neural Network (CNN) method is widely used by researchers and allows it to provide high recognition performance. Therefore, this study applies the CNN method with the MobileNet architecture to help recognize shadow puppets, especially character name recognition. The results of the MobileNet architecture on CNN provide a higher recognition performance than using the VGG-16 architecture, which gives an increase of 1.67% become 86,67%.. © 2021 IEEE.

关键词： Convolutional neural networks

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Cypher by Example: A Visual Query Language for Graph Databases

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SSRN 2023年

作者： Rabuzin, Kornelije Šestak, Martina Faculty of Organization and Informatics University of Zagreb Pavlinska ulica 2 Varaždin42000 Croatia University of Maribor Faculty of Electrical Engineering and Computer Science Koroška cesta 46 Maribor2000 Slovenia

Considering the constantly increasing connectivity in terms of data exchanged between applications, devices etc., modern IT systems are in need of a data storage solution able to capture and handle data about connections and patterns formed between system participants (entities). As a potential solution for this challenge, graph database emerged in the previous decade. Since the standardization of a graph database query language is still an undergoing effort, any interested parties can interact with a graph database and explore graph data by using query languages such as Cypher or Gremlin, which are supported by modern Graph Database Management Systems (GDBMSs). Even though the syntax of these languages is well developed and documented, potential end-users with little knowledge of graph databases and the graph data model can still face a steep learning curve before being able to write queries on their own data stored in a form of a property graph. Consequently, this brings to a limited interest among the users to implement graph databases in their domains, as there is obviously a missing tool for maintaining the graph database in a visual manner. To address this gap, this paper introduces Cypher by Example, a visual graph query language consisting of a visual interface and a set of operations for interacting with the underlying graph database. The paper presents the basic elements of the proposed query language and demonstrates its effectiveness and completeness on a series of Cypher queries executed for a sample education domain. © 2023, The Authors. All rights reserved.

关键词： Query languages

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Advancements in cheating detection algorithms in FPS games

Advancements in cheating detection algorithms in FPS games

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2024 International Conference on computer Application and Information Security, ICCAIS 2024

作者： Xu, Ziwen Yu, Ruotong Liang, Yan Chen, Zihan Wan, Ye School of Computer Science and Technology Tongji University Shanghai201804 China Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College Guangdong Zhuhai519087 China Luddy School of Informatics Computing and Engineering Indiana University of Bloomington Indiana BloomingtonIN47405 United States Guangdong Guangya High School Guangdong Guangzhou510000 China School of Computer Science and Technology Northeastern University Hebei Qinhuangdao066000 China

ISBN: (纸本)9781510689312

Over the past two decades, the increasing variety of cheating techniques in FPS games has led to the development of cheating detection algorithms. This literature review provides a chronological review of advancements in cheating detection techniques. Early methods, such as avatar trajectory-based detection, focused on behavioral analysis and identified bots by analyzing movement patterns. A remote anomaly-based system called Fides was presented to detect client-side manipulations with client-server architectures. With the emergence of machine learning, a variety of supervised learning methods have been introduced into the field of game detection to achieve real-time detection. More recent studies have been more innovative. Traps like the "bait-target" technique were introduced to detect cheating mechanisms that mimic human behavior. Methods combining deep learning and computer vision were proposed to detect complex cheating based on visual images. Overall, this review shows the diversity of cheat detection algorithms that have evolved to maintain the fairness of competitive gaming environments. © The Authors.

关键词： Supervised learning

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review 3

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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3rd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Noprisson, Handrie Ermatita, Ermatita Abdiansah, Abdiansah Ayumi, Vina Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3-25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50. © 2021 IEEE.

关键词： Weaving

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Wrapper-Based Feature Selection to Improve The Accuracy of Intrusion Detection System (IDS)

Wrapper-Based Feature Selection to Improve The Accuracy of I...

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International Conference on Wireless and Telematics (ICWT)

作者： Jupriyadi Arief Budiman Eki Ahmad Zaki Hamidi Syaiful Ahdan Ridha Muldina Negara School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Department Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798350377057

ISBN: (纸本)9798350377064

An Intrusion Detection System (IDS) is a system that can detect attacks on a network. IDS systems can be built using machine learning approaches. However, significant network traffic and many features cause machine learning algorithms to work slowly. Not all available features are essential for use as a reference in an intrusion detection system. Feature selection is important because it can reduce the dataset and speed up computing time in building models and detection systems. In this paper, feature selection using the wrapper method is proposed. Its performance is compared with filter-based feature selection, such as chi-square, information gain, gain ratio, and correlation-based feature selection (CFS). Based on the exploration, the results showed that the feature selection algorithm using the wrapper method was superior to other algorithms. The number of critical features discovered and the detection system's precision serve as proof of the wrapper approach. With only three features as a reference, the detection system produces an accuracy of 96.22%. It increases 5.84% from 90.38% to 96.22%. Computation time also increases because the number of features used is tiny compared to other algorithms and uses all features.

关键词： Wireless communication Accuracy Machine learning algorithms Computational modeling Buildings Intrusion detection Telecommunication traffic

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Deep Learning Algorithm for Room Temperature Detection Using Bioelectric Potential of Plant Data

SSRN

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SSRN 2024年

作者： Tahyudin, Imam Rozaq, Hasri Akbar Awal Nambo, Hidetaka Department of Information System Faculty of Computer Science Amikom Purwokerto University Jl. Letjendpol Soemarto Banyumas Purwanegara 53127 Indonesia Graduate School of Informatics Faculty of Computer Science Gazi Üniversitesi Ankara Yenimahalle Turkey Graduate School of NST Division of Electrical Engineering and Computer Science Kanazawa University Kakumamachi Ishikawa Kanazawa920-1192 Japan

Plants are living things that have many secrets in them. One that is very interesting is how plants can communicate with the surrounding environment through the activities of the plants themselves. Then, from this communication activity, plants produce electricity, which we can use to study further the behavior of these plants, commonly known as bioelectric potential. This study has aim to analyze the ability of bioelectric potential of plant to response a room temperature in different condition. This research is analyzed using a deep learning algorithm, namely Long-Short Term Memory (LSTM). The data was recording using a modified amplifier and the output is signal data. The signal obtained is an analog signal which is then converted into a digital signal. The data that has been obtained is then transformed first before being analyzed using the Wavelet Transform method. The algorithm will be evaluated between the baseline and hyperparameter tuning models. The result showed that hyperparameter tuning has the smallest RMSE. Therefore, it is better than baseline model. © 2024, The Authors. All rights reserved.

关键词： Wavelet transforms

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Machine Speech Chain with Emotion Recognition

Machine Speech Chain with Emotion Recognition

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International Conference of Advanced informatics: Concept, Theory and Application (ICAICTA)

作者： Akeyla Pradia Naufal Dessi Puji Lestari Ayu Purwarianti Kurniawati Azizah Dipta Tanaya Sakriani Sakti School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Faculty of Computer Science University of Indonesia Depok Indonesia Graduate School of Information Science Nara Institute of Science and Technology Nara Japan

ISBN: (数字)9798331520311

ISBN: (纸本)9798331520328

Developing natural speech recognition and speech synthesis systems requires speech data that authentically represents real emotions. However, this type of data is often challenging to obtain. Machine speech chain offers a solution to this challenge by using unpaired data to continue training models initially trained with paired data. Given the relative abundance of unpaired data compared to paired data, machine speech chain can be instrumental in recognizing emotions in speech where training data is limited. This study investigates the application of machine speech chain in speech emotion recognition and speech recognition of emotional speech. Our findings indicate that a model trained with 50% paired neutral emotion speech data and 22% paired non-neutral emotional speech data shows a reduction in Character Error Rate (CER) from 37.55% to 34.52% when further trained with unpaired neutral emotion speech data. The CER further decreases to 33.75% when additionally trained with combined unpaired speech data. The accuracy of recognizing non-neutral emotions ranged from 2.18% to 53.51 %, though the F1 score fluctuated, increasing by up to 20.6% and decreasing by up to 23.4%. These results suggest that the model demonstrates a bias towards the majority class, as reflected by the values of the two metrics.

关键词： Training Emotion recognition Accuracy Error analysis Natural languages Training data Speech recognition Speech enhancement Data models Speech synthesis

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