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A Novel Music Recommendation System Using Filtering Techniques

Informatica (Slovenia) 2024年第4期48卷 595-610页

作者： Vashishtha, Srishti Varshney, Deepika Sarin, Eva Kaur, Simran Computer Science and Engineering Dept. Bharati Vidyapeeth’s College of Engineering GGSIPU New Delhi India Computer Science and Engineering Dept. Jaypee Institute of Information Technology Noida India

With the growth of the World Wide Web, a large amount of music data is available on the Internet. A large number of people listen to music online rather than downloading and listening offline. But only some sites provide personalized and accurately recommended songs while they listen to an auto-playing playlist. Hence the need for recommendation systems arises. Two approaches can be applied to the recommendation system: content based filtering and collaborative filtering. While in content-based filtering approach, analysis on the songs’ content which has been preferred by the user in history is done and the songs with relative similarity are recommended. While latter suggests songs that certain users of similar listening pattern have preferred. But collaborative filtering-based recommendation systems not only requires time to attain stability but also might recommend unsuitable music because it is not personalized to each user’s preference. Also, the latter requires the songs to be listened by a few users already to recommend it any other user. Hence for overall analysis, answers to few questions need to be implemented in recommendation systems: the very first one is how the properties should be analyzed, next one is how the analysis should be done and last is how the songs related to the user’s preference should be chosen. So, for suggesting the better system which solves these three questions as well as provides better and personalized recommendations, In this paper we build a collaborative filtering as well as content based filtering recommendation system, where various factors determine the essence of the songs, i.e. liveliness, keys used, loudness, pitch, valence, etc., are analyzed for comparison. From the experimental analysis in has been identified that content-based filtering technique performed best on KNN machine learning classifier with accuracy of 85%. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Collaborative filtering

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Optimizing relay node placement and routing in WBANs using free search krill herd and harmony search algorithm

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Multimedia Tools and Applications 2025年第10期84卷 7257-7295页

作者： Patra, Sushree Chinmayee Samal, Tusharkanta Kabat, Manas Ranjan Mishra, Manas Ranjan Barik, Ram Chandra Dept. of Computer Sc. & Engineering Veer Surendra Sai University of Technology Odisha Sambalpur India Dept. of Computer Sc. & Engineering DRIEMS University Odisha Cuttack India Dept. of Computer Sc. & Engineering C.V. Raman Global University Odisha Bhubaneswar India

Wireless Body Area Network (WBAN) plays an important role in healthcare applications like in medical, non-medical and psychological sector for remote monitoring of health conditions of patients. Since the biosensors in WBAN are energy constrained in nature, the architecture of energy efficient and cost sensitive WBAN has attracted the researchers during the last decade. In this paper, a mathematical model for optimization of relay node placement in WBAN using Free Search Krill Herd (FSKH) algorithm because of its diversified phases of searching has been proposed. Furthermore, a routing protocol for energy efficient and reliable for data transmission over WBAN by using Harmony Search (HS) algorithm has been designed. The proposed algorithm has less 11.02%, 6.8% energy consumption in standing position, 5.6% and 11.02% in siting position and 12.5% and 18.75% siting on chair than its counterparts EAWD and Modified EAWD. Throughput has increased significantly by approximately 4–5 times as compare to iM-SIMPLE and *** proposed methodology has also shown greater improvement as its first node is completely exhausted after 28,545 rounds of data transmission while its existing counterpart’s iM-SIMPLE and Co-LAEEBA first node dies at 5100 rounds and 6800 rounds of transmission respectively. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Wireless local area networks (WLAN)

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Fine-Tuning BERT for Aspect Extraction in Multi-domain ABSA

Informatica (Slovenia)

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Informatica (Slovenia) 2023年第9期47卷 123-131页

作者： Akram, Arwa Sabir, Aliea Faculty of Computer Science and Information Technology Computer Information System Dept. University of Basrah Basrah Iraq

Aspect extraction plays a crucial role in understanding the fine-grained nuances of text data, allowing businesses and researchers to gain deeper insights into customer opinions, sentiment distributions, and preferences. This study presents a BERT-based framework for aspect extraction in ABSA and evaluates its performance. Our research focuses on the comprehensive analysis of aspect extraction as we test our method using the SEMEVAL dataset of various consumer evaluations across diverse domains, including laptops, restaurants, and Twitter. By fine-tuning BERT on a large dataset, we aim to overcome the limitations of traditional approaches and improve the accuracy and efficiency of aspect extraction in ABSA. The experimental findings provide evidence of the efficacy of our methodology with a noteworthy aspect extraction accuracy of 0.98, highlighting its capacity to properly and consistently extract features. The article also explores the applicability of our approach to new domains and its possible applications in real-world scenarios. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Sentiment analysis

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Predicting Mental illness (Depression) with the help of NLP Transformers 2

Predicting Mental illness (Depression) with the help of NLP ...

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2nd International Conference on Data Science and Information System, ICDSIS 2024

作者： Kokane, Vedant Abhyankar, Ajit Shrirao, Nikhil Khadkikar, Prajakta Pune Institute Of Computer Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350381665

In today's rapidly developing world, mental health is very important because it directly impacts the human thought process, productivity, relationships, etc. Being one of the most important aspects of a human's life, it is often neglected. Poor mental health can lead to anxiety, hopelessness, struggling to manage emotions, a lack of concentration, and loneliness. A mentally ill person can also have suicidal thoughts. In today's world, almost every person uses social media to share their lives and thoughts. With social media serving as a ubiquitous platform for self-expression and interaction, leveraging artificial intelligence (AI) and natural language processing (NLP) techniques becomes feasible for detecting mental health statuses based on users' social media posts. In this research paper, we proposed a methodology using NLP Transformers to study human behaviour as well as symptoms of depression. We analysed the status of mental health by examining the text of posts posted by different people on Twitter and Reddit. In our proposed methodology, we applied 4 different NLP Transformers (BERT, XLNet, RoBERTa, and DistilBERT) Transformers on two different datasets. Our proposed model concluded that DistilBert was the most accurate Transformer among the four with accuracy with 91% accuracy on twitter dataset and 84% accuracy on reddit dataset. Our proposed methodology will be effective in detecting mental illness in a person. © 2024 IEEE.

关键词： Diseases

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CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR CANCELLABLE FACE TEMPLATE

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer Science 2024年第1期86卷 155-166页

作者： Alwan, Hiba Basim Ku-Mahamud, Ku Ruhana Dept. of Computer Science University of Technology Iraq School of Computing Universiti Utara Malaysia Malaysia

Biometrics systems utilizing hand geometry, fingerprint, iris, face, palm print, voice, gesture, and palm print have been utilised for authentication purposes. Through these templates, the face template is suggested as the strongest. However, problems still exist in face-matching implementation which affects biometric security. Thus, in this paper, a new cancellable face image algorithm using the Convolution Neural Network (CNN) feature extraction technique and Winner-Takes-All hashing method is proposed. The algorithm is to overcome the problem of matching which will enhance its security. ORL and Yale datasets were utilized in the evaluation of the proposed algorithm. Several common algorithms were utilised in the comparison based on Equal Error Ratio (ERR) measurement. The outcomes displayed the verification performance of the unimportant differences with EER = 0.95% and 3.25% for the extended version of the face dataset for the Yale and ORL face datasets, respectively. The acceptable implementation of the proposed algorithm demonstrates that it can be used for the security purpose of biometric trait tasks. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Convolution

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IoTeach: Prototyping and Evaluation of Learning Support System for IoT Programming by Integrating Real Devices and Sequential Contents

Computer Software

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computer Software 2023年第3期40卷 97-112页

作者： Kawatani, Tomohiro Tsukada, Koji Kurihara, Kazutaka Dept. of Media Architecture Future University Hakodate Japan Dept. of Computer Science College of Liberal Arts Tsuda University Japan

In recent years, as the IoT has become popular, there are more requirements for sharing operation/mechanisms of IoT devices, such as Arduino and M5Stack. In addition, because of the corona disaster, many educational institutions adopted online lectures, such as on-demand tutorial videos and live lectures using video conference systems. For IoT programming education, these methods have problems such as lack of linkage with real-world devices and source codes. In this study, we propose a system called "IoTeach", which supports learning of IoT programming by attaching a script language on sequential contents such as videos and slides shared on the Web. Thus, the IoTeach can link videos and slides with real-world IoT devices and source code. In this paper, we describe the concept and implementation of the system. We also perform a basic evaluation and discuss challenges and prospects. © 2023 Japan Society for Software Science and technology. All rights reserved.

关键词： Online systems

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Skin Melanoma diagnosis using machine learning and ABCD rule 4

Skin Melanoma diagnosis using machine learning and ABCD rule

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4th International Conference of Science and Information technology in Smart Administration, ICSINTESA 2024

作者： Kadeem, Zahra B. Mosa, Qusay O. College of Computer Science and Information Technology Dept. Computer Science Diwaniyah Iraq

ISBN: (纸本)9798350376111

Skin cancer, being the most predominant type of malignant growth, represents more than half of all cancer instances. While melanoma is less common than other skin cancers, it poses the highest risk due to its tendency to metastasize and potentially result in mortality. Nonetheless, early detection significantly increases the chances of curing melanoma. The detection of melanoma poses a considerable challenge, primarily attributed to the minimal interclass variance observed between images of melanoma and non-melanoma, alongside the heightened interclass variance within melanoma images. Hence, it is imperative to formulate a computer-aided Diagnosis (CAD) to identify such lesions and facilitate early disease diagnosis to enhance the probability of patient survival. The proposed methodology consists of a sequence of four distinct phases. The initial stage involves preprocessing, which incorporates the application of filtering and contrast enhancement algorithms such as the Median filter, Dull razor, and Histogram Equalization. The segmentation process proceeds by utilizing Otsu methods in order to detect any anomalies. Subsequently, the following phase involves the extraction of features through GLCM for textural attributes and ABCD base parameters, encompassing asymmetry, border irregularity, color, and diameter. Following this, a model based on artificial neural networks (ANN) is developed by leveraging these extracted traits to discern instances of skin cancer within the provided dataset. This methodology achieves a commendable overall accuracy rate of 99%. Dermatologists may derive significant assistance in their clinical decision-making procedures from this promising breakthrough. © 2024 IEEE.

关键词： Lung cancer

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A Review of Food Supply Chain Tracking Using Blockchain technology: Enabled Factors and Barriers 1

A Review of Food Supply Chain Tracking Using Blockchain Tech...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Hashem, Buthaina Algaphary, Ghaleb Almutawkil, Adnan Dept. Information Technology Faculty of Computer and IT University of Sana’a Sana’a Yemen Dept. Computer Science Faculty of Computer and IT University of Sana’a Sana’a Yemen

ISBN: (纸本)9798331533557

The food supply chain (FSC) deals with issues like reliability, security, and traceability due to information contradiction. While blockchain technology (BCT) shows promise in improving FSC operations, its adoption in this sector remains early. This study systematically reviews BCT's applications in FSC tracking, focusing on its layers, types, platforms, and features. Through a methodical literature review spanning 2019 to 2023, 50 relevant articles were examined to identify barriers to BCT adoption, such as scalability and costs, and enabling factors like data integrity and decentralization. The review aims to identify gaps in the present research, setting the basis for offering a structured classification for blockchain-based FSC tracking and developing a conceptual framework for future BCT adoption in FSC. This framework aims to present strategic guidance for applying blockchain technology in FSC tracking applications, enhancing operational efficiency and transparency in the food supply chain sector. The finding of this study could help the government sector focus on building mechanisms to encourage the agriculture sector to invest in supply chain tracking. © 2024 IEEE.

关键词： Barriers Blockchain technology Enabling Factors Food Supply Chains Tracking

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Flatness Improvement technology of Febry-Perrot Interferometer via Simultaneous Modulation of 3-Channel PZT Actuators and Interface Electronics Implementation

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Transactions of the Korean Institute of Electrical Engineers 2024年第5期73卷 827-833页

作者： Park, Jung-Woong Jeong, Sang-Won Lee, Hyun-Ho Jang, Min-Jun Lee, Keekeun Dept. of Electrical and Computer Engineering Ajou University Korea Republic of Dept. of Electrical and Computer Engineering Ajou University Korea Republic of J&C Technology Co. Gimcheon-si Korea Republic of

This study presents the development of a lead zirconate titanate (PZT)-based Febry-Perrot Interferometer (FPI) tailored for the selective transmission of specific wavelengths. Our FPI integrates two mirrors, 3-channel PZT actuators, and interfacing electronics, enabling dynamic adjustments in PZT actuator lengths through voltage application. The interface electronics facilitate precise voltage control over the multi-channel PZT actuators, regulating the air gap between mirrors. Experimental results demonstrate the effectiveness of the developed interfacing electronics in modulating the transmission peak of light, resulting in a narrowed full width at half maximum (FWHM) and a heightened transmittance rate at targeted wavelengths. Additionally, the interface adept.y manages multi-channel PZT voltages, mitigating potential mirror alignment discrepancies during FPI assembly. By optimizing the air gap between the mirrors, significant enhancements in the center wavelength of the transmitted beam are achieved. Copyright © The Korean Institute of Electrical Engineers.

关键词： Actuators

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Frequency Response Deterioration due to Surface Ridge Abrasion of Tactile Sensors 13

Frequency Response Deterioration due to Surface Ridge Abrasi...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Yanwari, Muhammad Irwan Okamoto, Shogo Polines Dept. Computer Engineering Technology Japan Tokyo Metropolitan University Dept. Computer Science Tokyo Japan

ISBN: (纸本)9798350355079

Epidermal ridges are crucial for tactile sensing in both human fingers and synthetic sensors. These ridges are made of compliant materials and susceptible to abrasion damage after iterative use. This study focuses on examining the impact of sensor ridge damage on the acquired signal, which encompasses a broad range of frequency components. We compared the frequency responses of a tactile sensor scanning sandpaper with both intact and damaged sensors. The degradation of signal levels was evident across the 0-1,000 Hz range, with particularly prominent suppression of the peak frequency component. This study demonstrates the frequency-dependent influence of ridge abrasion. © 2024 IEEE.

关键词： Friction

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