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6th International Conference on Advancements in Computing, ICAC 2024

作者： Harindi, Dewmini Perera, Nirmal Liyanage, Chamath Dematagoda, Hirushini Fernando, Harinda Rathnayake, Samadhi Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper presents machine learning-based strategies for mitigating the problem of misinformation in social media, with a special focus on political misinformation detection and clickbait detection. The following research work attempts to address the pressing issue of the rapid spread of false or misleading information by making use of deep recurrent neural networks (RNN s) combined with semi-supervised learning methodologies. For political misinformation detection, a hybrid model integrating Long Short-Term Memory (LSTM) networks with fully connected layers was developed, achieving 94.22 % accuracy on the CIC Truth Seeker dataset. Clickbait detection was made using a sequential architecture that combines LSTM and Gated Recurrent Units (GRU) layers with Simple RNN layers to achieve an accuracy of 96% on test data. This study underlines the effectiveness of different machine learning techniques in battling misinformation that would contribute to online dignity in political discourse and ensure better public communication in a digital world. © 2024 IEEE.

关键词： Self-supervised learning

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AI-Based Child Care Parental Control system 4

AI-Based Child Care Parental Control System

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Jayasekara, Udara Maniyangama, Hansindu Vithana, Kalhan Weerasinghe, Tharana Wijekoon, Janaka Panchendrarajan, Rrubaa Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Due to the prevalence of the COVID-19 epidemic around the globe, children were compelled to engage in remote learning through online platforms, hence mobile phone has become one of their predominant devices. Mobile device with Internet access offers a major outlet for education, entertainment, and social connection, but this combination can lead to several significant bad sequences such as online exploitation, harmful addictions, and other negative impacts of online social networking. To address harmful effects, parental controls are becoming more crucial, yet Sri Lankan parents are less aware of this. Consequently, this study proposes a parental control system to monitor their child's activities. Android, Microsoft Azure, Java, Python, OpenCV, MySQL, and FastAPI are among the most prominent technologies utilized in the proposed application's development. The suggested approach focuses primarily on the Sri Lankan context and aims to enhance parental digital literacy while safeguarding children from cyber threats. Yielded results showed the proposed mobile application for the identification of toxic words, drugs & alcohol content, game character images, and Instagram Sinhala comments severity as 94%, 95%, 97%, and 55% respectively in controlled experiments. © 2022 IEEE.

关键词： Control systems

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Sagittarius: Floating Self Navigating Robot for Monitor the Water Quality of Rural Reservoirs 6

Sagittarius: Floating Self Navigating Robot for Monitor the ...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Pedige, Nishan Ilandara Abeywarna, Thaveesha Amarasinge, Randheera Bandara, Menuka Nawarathna Javakody, Anuradha Gamage, Narmada Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper proposes an optimal solution for monitoring water quality in Sri Lanka, where reservoirs are essential for daily life and agriculture, especially in rural areas. Despite its importance, 3.6 million communities are affected by severe water quality problems, contributing to a high incidence of chronic kidney diseases. While water purification plants are the only solution, high salinity and hardness often make these sources unsuitable. Many rural reservoirs remain unpurified but could potentially provide safe water if properly monitored and maintained. Yet water sources are frequently contaminated by chemical waste and activities associated with agricultural business but effective solutions for continuous water quality monitoring are lacking. This study introduces an autonomous robot equipped with advanced sensors to monitor critical water quality parameters in real-time. By integrating machine learning for data analysis and prediction, Sagittarius enables continuous assessment of reservoir water quality, providing timely insights for public health protection. Field tests demonstrate a prediction accuracy exceeding 98.5%, supporting proactive water management and monitoring. This system has shown potential to aid in early detection of contamination, informing authorities promptly for preventive actions, and enabling sustainable water usage. This solution can significantly contribute to public health protection and informed water resource management decisions. © 2024 IEEE.

关键词： Reservoirs (water)

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Matched design method for concatenated trellis-coded modulation

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND computer SCIENCES 1996年第11期E79A卷 1911-1917页

作者： Wadayama, T Wakasugi, K Kasahara, M Faculty of Computer Science and System Engineering Okayama Prefectural University Soja-shi 719-11 Japan Department of Electronics and Information Science Kyoto Institute of Technology Kyotoshi 606 Japan

A new design method, which is referred to as the matched design method, for concatenated trellis-coded modulation (TCM) is presented. Most of the conventional concatenated TCM employs TCM designed to maximize the minimum squared Euclidean free distance, d(free)(2). With the matched design method, we maximize d(1)(2)(t) instead of d(free)(2), where d(1)(2)(t) is the effective minimum squared Euclidean distance (MSED) when the outer code has a t-error correcting capability. The effective MSED is derived from the Euclidean/Hamming (E/H) joint weight distribution of terminated TCM. We here assume the concatenated TCM whose transmitted symbol corresponds to a symbol of outer code. The new classes of 2-dimensional(2D) and 4-dimensional(4D) codes are found by a computer search. Under the performance measures of the effective MSED or the effective multiplicity, these codes are superior to the conventional codes such as the Ungerboeck's 2D-codes when those are used as an inner code. We disclose an interesting fact that the new class of codes using rate-1/2 encoder is superior to the class of codes using rate-2/3 encoder. This fact implies that the codes using rate-1/2 encoder have two advantages: 1) better overall decoding performance and 2) less decoding complexity.

关键词： trellis-coded modulation concatenated code weight distribution

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A self learning VLSI lab along with web-based platform to design schematics and layouts

A self learning VLSI lab along with web-based platform to de...

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International Conference on technology for Education

作者： Sharma, Shashank Azeemuddin, Syed Anwar, Mohd Computer Science Engineering Department International Institute of Information Technology Hyderabad India Center for VLSI and Embedded System Technology International Institute of Information Technology Hyderabad India

ISBN: (纸本)9780769545349

We present a web-based environment along with an interactive interface for VLSI schematic design, simulation, and layout design. It consist of 10 experiments starting from transistor level design of inverter, then some basic gates such as NAND, NOR, XOR etc, finally design of D latch and flip flop. In each experiment student will learn how to design VLSI circuits both schematic and layout. It also consists of experiment components such as objective, introduction, quiz, and theory etc. which gives step by step explanation of each experiment. It is a powerful self learning supplement for the VLSI design course offered in undergraduate engineering program. Along with teaching schematics and layouts of circuits, this virtual lab also consists of some experiment explaining about SPICE coding, VHDL and Verilog coding. An interactive panel is given in which student will write programming codes, simulate and see real time waveforms. The web based schematic and layout editor is designed to maintain the commonality with EDA tools such as Cadence Virtuoso, HSpice Cosmos, Tanner tools etc. © 2011 IEEE.

关键词： E-learning

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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling

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Environment International 2025年 199卷 109496页

作者： Ahmed, Maqsood Zhang, Xiang Shen, Yonglin Ahmed, Tanveer Ali, Shahid Ali, Ayaz Gulakhmadov, Aminjon Nam, Won-Ho Chen, Nengcheng National Engineering Research Center of Geographic Information System School of Geography and Information Engineering China University of Geosciences Wuhan430074 China Department of Computer Science School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Software College Northeastern University Shenyang110169 China Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Research Center of Ecology and Environment in Central Asia Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi830011 China Institute of Water Problems Hydropower and Ecology of the National Academy of Sciences of Tajikistan Dushanbe734042 Tajikistan School of Social Safety and Systems Engineering Institute of Agricultural Environmental Science National Agricultural Water Research Center Hankyong National University Anseong Korea Republic of

Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on single static image analysis, which does not account for the dynamic and temporal nature of air pollution. Meanwhile, research on video-based air quality estimation remains limited, particularly in achieving accurate multi-pollutant outputs. This study proposes Air Quality Prediction-Mamba (AQP-Mamba), a video-based deep learning model that integrates a structured Selective State Space Model (SSM) with a selective scan mechanism and a hybrid predictor (HP) to estimate air quality. The spatiotemporal forward and backward SSM dynamically adjusts parameters based on input, ensures linear complexity, and effectively captures long-range dependencies by bidirectional processing of spatiotemporal features through four scanning techniques (row-wise, column-wise, and their vertical reversals), which allows the model to accurately track pollutant concentrations and air quality variations over time. Thus, the model efficiently extracts spatiotemporal features from video and simultaneously performs regression (PM2.5, PM10, and AQI), and classification (AQI) tasks, respectively. A high-quality outdoor hourly air quality dataset (LMSAQV) with 13,176 videos collected from six monitoring stations in Lahore, Pakistan, was utilized as the case study. The experimental results demonstrate that the AQP-Mamba significantly outperforms several state-of-the-art models, including VideoSwin-T, VideoMAE, I3D, VTHCL, and TimeSformer. The proposed model achieves strong regression performance (PM2.5: R2 = 0.91, PM10: R2 = 0.90, AQI: R2 = 0.92) and excellent classification metrics: accuracy (94.57 %), precision (93.86 %), recall (94.20 %), and F1-score (93.44 %), respectively. The proposed model delivers consistent, real-time performance with a latency

关键词： Air quality

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Cluster-Based Saliency-Guided Content-Aware Image Retargeting

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Journal of Electronic Science and technology 2017年第2期15卷 141-146页

作者： Li-Wei Kang Ching-Yu Tseng Chao-Long Jheng Ming-Fang Weng Chao-Yung Hsu Graduate School of Engineering Science and Technology and the Department of Computer Science and Information Engineering MPI Corporation Hsinchu Changing Information Technology Inc.Hsinchu 308 Institute for Information Industry Taipei 106 automation and Instrumentation System Development Sec. China Steel CorporationKaohsiung 81233

Straightforward image resizing operators without considering image contents （e.g., uniform scaling） cannot usually produce satisfactory results, while content-aware image retargeting aims to arbitrarily change image size while preserving visually prominent features. In this paper, a cluster-based saliency-guided seam carving algorithm for content- aware image retargeting is proposed. To cope with the main drawback of the original seam carving algorithm relying on only gradient-based image importance map, we integrate a gradient-based map and a cluster-based saliency map to generate a more reliable importance map, resulting in better single image retargeting results. Experimental results have demonstrated the efficacy of the proposed algorithm.

关键词： Index Terms--Content-aware image retargeting image resizing multimedia adaptation saliency detection seam carving.

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Brain Tumor Detection Using Image Processing 5

Brain Tumor Detection Using Image Processing

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Wijerathna, Udari Dissanayake, Nimavi Nimasha, Dinithi Senarathne, Udara Weerasinghe, Lokeesha Kahandawaarachchi, Chathurangika Sri Lanka Institute of Information Technology Faculty of Computing Dept of Computer System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Dept of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Dept of Computer System Network Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Abnormal formation of cells in a layer. The brain is known as the brain cancer complex, and a brain cancer detection system is needed to detect cancer in its early stages Phase. As a result, the primary goal of this initiative is to assist existing doctors in their training for the early identification o f brain cancer by utilizing magnetic resonance imaging (MRI), which is the most effective approach to identifying brain cancer. This system is done through four components, and it has made it easier to detect brain tumors. These techniques with different image processing techniques include noise removal, segmentation, classification, a nd u se o fa nalysis segments f or detection. Pre-processing techniques prepare the image for further processing by removing image noise. During segmentation, the brain tumor system determines the size of the brain tumor and estimates its size. Specialists should examine them and classify brain tumors as meningiomas, gliomas, and pituitary tumors. In analysis, this component is expected to be designed so that users or medical experts can know the future through a dashboard. We explored the methodology of using generative adversarial networks (GANs) implemented in TensorFlow to denominate brain tumor images. Analyses the outcomes of various types of established deep learning models on the brain tumor MR image datasets, such as classification methods ResNet-50, VGG 16, CNN, and Inception V3. The validation precision, AUC, recall, and validation loss for CNN are 95.3%, 99.43%, 92.1 %, and 0.360 adjustments respectively. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Load balance controlling algorithm on unstructured P2P network

Load balance controlling algorithm on unstructured P2P netwo...

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2010 International Conference on Educational and Network technology, ICENT 2010

作者： Xu, Lijun Li, Xueyong Gao, Guohong Institute of Computer and Information Engineering Xinxiang University Henan Xinxiang 453003 China Henan Institute of Science and Technology School of Information Engineer Xinxiang 453003 China

ISBN: (纸本)9781424476619

To find hubs correctly on unstructured P2P network, considering different ability for different nodes, this paper imported load degree for nodes and takes nodes possessing high load degree as heavy ones, then proposed a balance control algorithm, in which loads from heavy nodes transfer to light ones. From simulation, this algorithm can equal efficiently loads from different nodes, especially for nodes from activity peer-to-peer network. © 2010 IEEE.

关键词： Peer to peer networks

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Cluster key scheme based on bilinear pairing for wireless sensor networks 4th

Cluster key scheme based on bilinear pairing for wireless se...

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4th International Conference on computer engineering and Networks, CENet2014

作者： Liu, Xiaoming Zhao, Qisheng Information Center Huaihai Institute of Technology LianyungangJiangsu222005 China Computer Engineer College Huaihai Institute of Technology LianyungangJiangsu222005 China

ISBN: (纸本)9783319111032

The past security policy about public key management strongly relied on the key matrix which was preset by the base station or generated by the algorithm embedded in the nodes, then to exchange the public key with others to finish the security communications, but a lot of public keys were stored in the nodes, which consumed much energy and might be captured and gained by the attacked nodes. In this chapter, we adopt the bilinear pairing theory to the public key generation and management which does not require the public key in the nodes and applies the node’s information to the public keys, which may reduce the cost of managing the public keys and enhances the security of key management;then we propose a cluster key distributed scheme on the basis of clustering by using the bilinear pairing key management in the wireless sensor network and demonstrate its feasibility and security theoretically. © Springer International Publishing Switzerland 2015.

关键词： Sensor nodes

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