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Real Time Skin Color Detection Based on Adaptive HSV Thresholding

Journal of Mobile Multimedia 2022年第6期18卷 1617-1632页

作者： Moumene, Mohammed Elamine Benkedadra, Khadidja Berras, Fatima Zohra Department of Mathematics and Computer Science Faculty of Exact Sciences and Informatics University Abdelhamid Ibn Badis Mostaganem Algeria

The detection of human skin color has been studied extensively during the past two decades. It is an essential task for various computer vision applications such as biometric authentication, face/hands tracking and gesture analysis. New machine learning methods are effective for skin color detection. However, they are not suitable for real time applications since they are computationally heavy. A lightweight approach for skin color detection consists of using segmentation rules extracted by an investigation on skin color distribution. The kin appearance varies with diversity of image types, acquisition parameters and scene illumination. There are no general segmentation rules that provide effective skin segmentation for different scene conditions. In this paper we present a real-Time skin color detector which adapts itself according to tracked human parts. First, initial thresholds are calculated using two popular skin datasets. Those thresholds can also be calculated quickly using small training sets. The proposed skin color detector showed comparable skin segmentation to DeepLabV3+ application and an improvement in term of F1 measure when compared to methods that relies on static rules. © 2022 River Publishers. All rights reserved.

关键词： histogram analysis. Human skin detection pixel classification skin color

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Long Short Term Memory (LSTM) Improvement Accuracy Using FastText and Glove for Language Translation Batak - Indonesian 2

Long Short Term Memory (LSTM) Improvement Accuracy Using Fas...

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2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Mandasari, Atikah Rahayu Nababan, Erna Budhiarti Mawengkang, Herman Informatics Program Universitas Sumatera Utara Medan Indonesia Universitas Sumatera Utara Faculty Of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Medan Indonesia

ISBN: (纸本)9798350351613

This research discusses the improvement of Long Short-Term Memory (LSTM) model accuracy in translating Batak to Indonesian by utilizing FastText and GloVe embeddings. Traditional LSTM models often struggle with the complexity and richness of underrepresented languages like Batak. By integrating FastText and GloVe, which provide word vectors with deeper semantic meanings, the translation quality can be significantly enhanced. Experimental results show that this approach offers a substantial performance improvement compared to conventional LSTM models, producing more accurate and contextual translations. These findings have the potential to be applied in broader multilingual translation systems and support the preservation and digital accessibility of minority languages. © 2024 IEEE.

关键词： Semantics

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Exploratory Study on User Experience (UX) of Public E-Procurement System in Malaysia: A Qualitative Approach 9

Exploratory Study on User Experience (UX) of Public E-Procur...

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9th International HCI and UX Conference in Indonesia, CHIuXiD 2023

作者： Mior Ibrahim, Emma Nuraihan Kusaini, Amiruddin Ismail, Juhaida Abu Hashim, Anis Hasliza Misron, Mudiana Mokhsin College of Computing Informatics and Mathematics Universiti Teknologi Mara Shah Alam Selangor Malaysia Mathematics and Computer Science University of Twente Hallenweg 15 Faculty of Electrical Engineering Netherlands

ISBN: (纸本)9798350304084

The public e-Procurement system in Malaysia is a crucial component of the e-Government services. Its primary function is to provide a platform for government agencies to efficiently procure goods and services from business users. The user experience (UX) of this e-Procurement system has emerged as a pivotal factor in the success of the broader e-Government digital transformation. Ensuring that the digitalization of the public e-Procurement system aligns with its objectives and delivers a top-tier Government Electronic Procurement System is imperative. This research aims to gain a comprehensive understanding of the UX issues and challenges faced by stakeholders when using the public e-Procurement system. The study employs a qualitative approach, delving into the perspectives and insights of e-Procurement system users. Data from interview sessions involving nine (9) participants have been meticulously interpreted, coded, and subjected to thematic analysis, revealing five distinct dimensions of issues and challenges: usability, performance, operational, quality, and user satisfaction. To address these identified concerns, we proposed several recommendations. Enhancements in system user interface (UI), navigational aspects, system features, performance, and operational aspects are essential to ensure sustained quality and user satisfaction within the e-Procurement system. The study also explores avenues for future work to further refine and augment these improvements. © 2023 IEEE.

关键词： User interfaces

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Separator Theorem and Algorithms for Planar Hyperbolic Graphs 40

Separator Theorem and Algorithms for Planar Hyperbolic Graph...

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40th International Symposium on Computational Geometry, SoCG 2024

作者： Kisfaludi-Bak, Sándor Masaříková, Jana van Leeuwen, Erik Jan Walczak, Bartosz Węgrzycki, Karol Department of Computer Science Aalto University Espoo Finland Institute of Informatics University of Warsaw Poland Department of Information and Computing Sciences Utrecht University Netherlands Department of Theoretical Computer Science Faculty of Mathematics and Computer Science Jagiellonian University Kraków Poland Saarland University Saarbrücken Germany Max Planck Institute for Informatics Saarbrücken Germany

ISBN: (纸本)9783959773164

The hyperbolicity of a graph, informally, measures how close a graph is (metrically) to a tree. Hence, it is intuitively similar to treewidth, but the measures are formally incomparable. Motivated by the broad study of algorithms and separators on planar graphs and their relation to treewidth, we initiate the study of planar graphs of bounded hyperbolicity. Our main technical contribution is a novel balanced separator theorem for planar δ-hyperbolic graphs that is substantially stronger than the classic planar separator theorem. For any fixed δ ≽ 0, we can find a small balanced separator that induces either a single geodesic (shortest) path or a single geodesic cycle in the graph. An important advantage of our separator is that the union of our separator (vertex set Z) with any subset of the connected components of G− Z induces again a planar δ-hyperbolic graph, which would not be guaranteed with an arbitrary separator. Our construction runs in near-linear time and guarantees that the size of the separator is poly(δ) · log n. As an application of our separator theorem and its strong properties, we obtain two novel approximation schemes on planar δ-hyperbolic graphs. We prove that both Maximum Independent Set and the Traveling Salesperson problem have a near-linear time FPTAS for any constant δ, running in npolylog(n) · 2O(δ2) · Ε−O(δ) time. We also show that our approximation scheme for Maximum Independent Set has essentially the best possible running time under the Exponential Time Hypothesis (ETH). This immediately follows from our third contribution: we prove that Maximum Independent Set has no no(δ)-time algorithm on planar δ-hyperbolic graphs, unless ETH fails. © Sándor Kisfaludi-Bak, Jana Masaříková, Erik Jan van Leeuwen, Bartosz Walczak, and Karol Węgrzycki.

关键词： Approximation algorithms

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Radial level planarity with fixed embedding

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Journal of Graph Algorithms and Applications 2021年第1期25卷 353-366页

作者： Rutter, Ignaz Brückner, Guido Faculty of Computer Science and Mathematics University of Passau Germany Faculty of Informatics Karlsruhe Institute of Technology Germany

We study level planarity testing of graphs with a fixed combinatorial embedding for three different notions of combinatorial embeddings, namely the level embedding, the upward embedding and the planar embedding. These notions allow for increasing degrees of freedom in their corresponding drawings. For the fixed level embedding there are known and easy to test level planarity criteria. We use these criteria to prove an "untangling" lemma that plays a key role in a simple level planarity test for the case where only the upward embedding is fixed. This test is then adapted to the case where only the planar embedding is fixed. Further, we characterize radial upward planar embeddings, which lets us extend our results to radial level planarity. No algorithms were previously known for these problems. © 2021, Brown University. All rights reserved.

关键词： Embeddings

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Multi-Tier Topology Design of Wireless Sensor Networks using Multi-Objective Particle Swarm Optimization 7

Multi-Tier Topology Design of Wireless Sensor Networks using...

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7th International Conference on Sustainable Information Engineering and Technology, SIET 2022

作者： Amron, Kasyful Kusumawinahyu, Wuryansari Muharini Anam, Syaiful Mahmudy, Wayan Firdaus Informatics Department Faculty of Computer Science Universitas Brawijaya Indonesia Mathematics Department Faculty of Natural Science Universitas Brawijaya Indonesia

ISBN: (纸本)9781450397117

In WSN, node placement is the most fundamental and growing topic since the location and function of the nodes define network performance. Recently, the placement methods are formulated as an optimization problem and solved by multi-objective optimization (MOO) approaches. This research aims to examine the implementation of MOO for relay placement. The goals of the MOO are to develop a WSN with minimum cost and fault tolerance ability. The MOO method in this research was constructed over a swarm intelligence algorithm. The area with targets and sensors is mapped into triangular cells and relays are placed at the triangular points. This mapping allows each sensor to connect to at least two different relays and construct multi-paths to the sink with the minimum number of relays. With random sensors that cover the entire area, this method uses around 58% to 67% of all relays on average. © 2022 ACM.

关键词： Multiobjective optimization

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An analysis of privacy preservation in electric vehicle charging

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Energy informatics 2022年第1期5卷 1-27页

作者： Unterweger, Andreas Knirsch, Fabian Engel, Dominik Musikhina, Daria Alyousef, Ammar de Meer, Hermann Center for Secure Energy Informatics Salzburg University of Applied Sciences Puch bei Hallein Austria Faculty of Computer Science and Mathematics University of Passau Passau Germany

Electric vehicles (EVs) are gaining widespread adoption, which requires expanding the charging infrastructure. This infrastructure is part of a complex ecosystem that consists of multiple entities interacting with each other and exchanging (often personal) user data. Such a heterogeneous system with multiple participants exchanging personal data poses severe privacy risks to users. State-of-the-art literature insufficiently covers privacy aspects of charging ecosystem use cases. In this paper, a profound analysis of this ecosystem with respect to privacy is provided: First, the EV charging ecosystem and its entities are defined. Second, high-level use cases for EV charging identified in literature are analyzed and used for defining data flows within the charging ecosystem. Third, the identified use cases are compared in terms of privacy guarantees and adherence to standards. Fourth, representative implementations of these use cases are evaluated, i.e., all actors and (unintended) data flows are described and potential privacy threats are identified and visualized. It is found that privacy is not sufficiently covered by standards and implementations of EV charging use cases from literature. Furthermore, recommendations and future directions for protecting user privacy in the EV charging ecosystem are derived. In summary, stricter adherence to standards and privacy by design are suggested. © 2022, The Author(s).

关键词： Ecosystems

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Blockchain-based Internet of Musical Things

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Blockchain(Research and Applications) 2022年第3期3卷 60-69页

作者： Luca Turchet Chan Nam Ngo Department of Information Engineering and Computer Science University of TrentoTrento38122Italy Faculty of Mathematics Informaticsand Mechanics of the University of WarsawWarsaw00-927Poland

Blockchain technology is impacting several industries,including the creative industries and those operating in the Internet of Things(IoT).Lately,researchers'attention has been devoted to the application of blockchain in the recorded music ***,thus far,no research has investigated the use of such technology in the Internet of Musical Things(IoMusT).The IoMusT is a new area emerging in industry and academy as an extension of the IoT to the musical *** IoMusT itself,as the IoT,is a distributed network of musical things,which are objects augmented with information and communication technologies serving a musical *** IoMusT vision requires,above all,IoT features such as decentralization,seamless authentication,transparency,data integrity and privacy,and self-maintenance,as well as the musical domain features such as efficient handling of copyrights and speed of royalties *** features can be brought by *** this paper,we investigate the integration of blockchain technology with the IoMusT,and we name such synthesis“Blockchain-based IoMusT”.We present a vision for this new paradigm in terms of the novel opportunities that are enabled,and we propose a set of application scenarios enabled by technological ***,we outline the open research directions in this promising area.

关键词： Internet of Musical Things Blockchain Music industry Privacy Security Internet of Things

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Enhanced Speech Emotion and Gender Recognition Using Hybrid CNN-LSTM Models 4

Enhanced Speech Emotion and Gender Recognition Using Hybrid ...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Priyadharshini, S. Sundar, G. Naveen Narmadha, D. Thangavel, Senthil Kumar Ajibesin, Adeyemi Abel Kolandapalayam Shanmugam, Selvanayaki Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Amrita School of Computing Department of Computer Science and Engineering Coimbatore India Cape Peninsula University of Technology Faculty of Informatics and Design Department of Information Technology South Africa Ashland University Department of Mathematics and Computer Science United States

ISBN: (纸本)9798331523923

The current paper proposes a new approach for peripheral speech emotion analysis and gender estimation incorporating the best machine learning architectures such as CNNs and LSTMs. Its correct depiction of emotions and the variation of the gendered speech to indicate manifold signal-to-noise ratio make the approach accommodate the difficulty inherent in recognizing emotions from the recording of voices as well as predicting the gender of a speaker. It is then able to ally with preprocessing and collection of a vast range of different speech samples, feature extraction of pitch, tone and spectral data. These features serve as input to the CNNs and LSTMs: LSTMs work well at temporal regular features and the CNNs work well in feature extraction by location (spatio feature). The approach is tested on the RAVDESS and IEMOCAP datasets and establishes a near perfect match to prior approaches with reference to recognition accuracy of emotion analysis and gender prediction. Thus, applying the identified dual method approach, which could be described by such characteristics as highly accurate data pre-preprocessing, clear indication of the features of interest, a different CNN-LSTM model joint training, it offers a reasonably good platform to gain certain insights into such characteristics of the speech as our experiment demonstrates. This work offers satisfactory configurations on concerns such as human computer relation, customer relation and mental health surveillance to suggest that other applications could be achieved in future. © 2025 IEEE.

关键词： Convolutional neural networks

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Developing an Artificial Intelligence Tool for Image Generation Using a Unique Dataset with Image-to-Image Functionality 24

Developing an Artificial Intelligence Tool for Image Generat...

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25th International Conference on computer Systems and Technologies, CompSysTech 2024

作者： Toktosunova, Akbiike Ergeshov, Alymbek Esenalieva, Gulzada Ermakov, Andrei Isaev, Ruslan Department of Applied Mathematics and Informatics Ala-Too International University Kyrgyzstan Department of Compute Science Ala-Too International University Kyrgyzstan Faculty of Engineering and Computer Science Ala-Too International University Kyrgyzstan

ISBN: (纸本)9798400716843

This article describes the application of a unique artificial intelligence model, trained on the basis of a special dataset, for drawing images. Artificial intelligence is very important in the modern world because it is a key driver of progress, offering innovative solutions to improve processes in various fields. A feature of this work is the use of the Stable Diffusion model and the creation of the LoRa model to create a specific object. The use of a special dataset, which is a classified set of images, to train models based on a stable propagation mechanism. The application of the image-to-image method, which consists in completely generating an image by having the model reproduce all the objects in the image, trying to preserve the maximum amount of detail in the image. As a result, a tool has been developed that can generate images of characters of a certain style. © 2024 ACM.

关键词： Adversarial machine learning

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