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International Conference on Systems, Control and Automation, ICSCA 2023

作者： Teja, Pulakala Verma, Vijay Department of Computer Engineering National Institute of Technology Haryana Kurukshetra India

ISBN: (纸本)9789819773831

The excess growth of digital information on the Internet and the excessive use by many users have created an issue of information over-load, where the data remains unfiltered and uncategorized. Many large corporations, like Deezer, JioSaavn, Spotify, and Wynk music streaming apps, have included recommendation algorithms to assess possible consumer preferences and propose suitable products to the user. However, it can be challenging to recommend an item to a new user with minimal or no interaction with the system. This problem is popularly known as the new user cold start problem, which refers to the issue of recommending music to users with little or no listening history. Deep learning-based approaches have recently shown great potential in addressing this challenge. This paper aims to extensively analyze the latest deep learning techniques to tackle the challenge of the new user cold start issue in the music recommendation field. Additionally, the paper explores the potential of using supplementary data such as user profiles and lyrics to enhance the performance of deep learning-based methods. Finally, we critically analyze the current state-of-the-art and identify open research directions for future work. This paper provides a valuable resource for researchers and practitioners in the music recommendation domain who seek to use deep learning-based approaches to tackle the new user cold start problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Matrix factorization

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Kavach - An Investigation tool for Cryptocurrency Forensics 4

Kavach - An Investigation tool for Cryptocurrency Forensics

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Shinde, Sandeep Chordia, Sankalp Nilesh Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350354218

The expansion of decentralized cryptocurrencies poses notable complexities for law enforcement in terms of detecting unlawful behaviors, as well as in the identification of individuals and the retrieval of transaction histories of perpetrators who take advantage of the pseudonymous nature inherent in the cryptocurrency system. This research paper puts forth a solution called Kavach. The designated user of Kavach will be an investigator. The tool leverages graph machine learning for the categorization of transactions as illicit or legitimate. It utilizes graph-based embeddings for the recognition of potentially suspicious addresses within the bitcoin network. The tool incorporates a predefined watch list for such suspicious addresses and will have the capability to trace the digital trail of these addresses using Open Source Intelligence (OSINT). © 2024 IEEE.

关键词： Graph embeddings

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Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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A Knowledge Discovery Framework for Maritime Intelligence on Dark Vessels 17

A Knowledge Discovery Framework for Maritime Intelligence on...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Jayaswal, Bharat Ghosh, Soumya K. Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India

ISBN: (纸本)9798331531195

Maritime Intelligence is essential for safeguarding maritime interests of coastal nations. Traditionally, vessel movements are tracked using self-reported positions via Automatic Identification System (AIS) transponders. However, vessels engaged in illicit activities often disable their AIS transponders to evade detection, thereby going dark. Satellite-based sensors, such as Synthetic Aperture Radar (SAR) and Visible Infrared Imaging Radiometer Suite (VIIRS) can be used to detect Dark Vessels. However, extraction of actionable insights for maritime intelligence on Dark Vessels is posed with several challenges. The spatial estimation of activities of vessels over various time periods is complicated due to spatial and temporal overlaps in satellite scans. This poster presents our ideas on knowledge discovery framework that integrates spatial analytics methods to gain actionable insights on Dark Vessels. Preliminary results are shown on Global Fishing Watch (GFW) Dataset of Dark Vessels. © 2025 IEEE.

关键词： Radar imaging

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Learning Non-cooperative Driving Practices and its Impact on Road Traffic Dynamics 17

Learning Non-cooperative Driving Practices and its Impact on...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Osho Chakraborty, Suchetana Indian Institute of Technology Department of Computer Science and Engineering Jodhpur India

ISBN: (纸本)9798331531195

Cooperative driving that prioritizes global safety and efficiency over self-interest is crucial in ensuring smooth traffic flow and enhanced road safety. However, experiencing noncooperative driving is common under heterogeneous and chaotic on-road traffic conditions. While non-cooperativeness is often context-dependent and assessed during direct vehicle interactions, it can be inferred through longitudinal analysis of driving patterns from vehicular kinematics data. This behavior not only adversely affects the vehicle itself but also has a cascading impact on nearby vehicles, ultimately disrupting overall traffic flow. In this study, we quantify a vehicle's non-cooperativeness using kinematic data and further model its cascading effects on nearby cooperative vehicles. Experimental analysis was conducted using the SUMO traffic simulator and the TraCI interface to assess the impact of non-cooperativeness on overall traffic dynamics. This research is among the first to examine the cascading effects of a vehicle's non-cooperativeness on its cooperative nearby vehicles. © 2025 IEEE.

关键词： Motor transportation

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SlidEar: Exploring eSense in-Ear Wearable for Voice-Assisted Smart Slide Supervision 17

SlidEar: Exploring eSense in-Ear Wearable for Voice-Assisted...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Mondal, Susmita Zingre, Sameeran Ravishankar Chakraborty, Suchetana Indian Institute of Technology Department of Computer Science and Engineering Jodhpur India

ISBN: (纸本)9798331531195

In corporate settings, conferences, or classrooms, an orator relies on manual slide transitions, which can disrupt their presentation flow. Presentation devices can be inaccessible due to the physical limitations of individuals, reducing engagement with the audience. Traditionally used remote-controlled wireless presenters are hand-held devices that usually require a compatible connector slot for the presentation device and partially engage one hand of the orator. To ease the hand-free presentation of slides, we introduce SlidEar, a voice-assisted smart slide supervision successfully tested on eSense in-ear wearables. SlidEar leverages voice recognition fusion with wearable sensors to facilitate seamless slide operations. It allows real-time feedback on natural language commands during the presentation of slides. Compared with conventional methods, SlidEar enhances engagement and accessibility through hand-free in-ear placement and helps the orator focus on delivering their content without any disruption or distraction. The evaluation shows promising results that improve the presentation experience profusion. SlidEar significantly reduces errors and can be widely adopted in diverse presentation scenarios. © 2025 IEEE.

关键词： Speech recognition

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An Empirical Evaluation of Design Smells and Code Smells Over Multiple Versions of Software Evolution 5th

An Empirical Evaluation of Design Smells and Code Smells Ove...

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5th International Conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Sharma, Kapil Chhabra, Jitender Kumar Computer Engineering Department National Institute of Technology Kurukshetra India

ISBN: (纸本)9789819725496

Software code smells serve as indicators of potential flaws in code design. It signifies that the code has not been created while following the design principles. Code smells do not mean the software system is faulty, but their persistence may affect the code maintainability, readability, and modularity. In this study, code smell evolution has been identified on three publicly available open-source software systems, and it was observed how design smells and traditional code smells evolve in different versions of each software system. Detection of these anomalies is performed by publicly available source code analyzers PMD and DesigniteJava. DesigniteJava finds design smells based on violation of object-oriented principles like abstraction, encapsulation, modularization, and hierarchy. PMD finds the traditional code smells. Based on the analysis of code smells evolution over multiple versions of software in this study, the findings suggest that the abstraction design smells out of all design smells are abundant, out of which unutilized abstraction is the maximum, and God class code smells, which was most discussed in this domain, are also increasing in subsequent versions. Consequently, on the basis of this analysis, a decision will be made regarding whether code smells are increasing beyond a certain limit, which component of the system the designer ought to center their attention on and whether or not it ought to be taken into consideration for redesigning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Modular construction

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Hyperbilirubinemia or jaundice detection using CNN in machine learning 1st

Hyperbilirubinemia or jaundice detection using CNN in machin...

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1st International Conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Gupta, Priyanka Upasna Rai, Vishal Department of Computer Science and Engineering ABES Institute of Technology Ghaziabad India

ISBN: (纸本)9781032874036

Jaundice, also called congenital hyperbilirubinemia, is a common condition caused by alterations in an infant’s red blood cell metabolism within the initial week of life. There are many symptoms associated with this multifactor disorder, and we have systems available both invasive and non-invasive. A practical and precise method for monitoring neonatal jaundice using the CNN algorithm has been described in this paper. The method’s accuracy and viability are predicated on the different detection systems examined. The methodologies and detection techniques discussed offer practical insights. To find a linear regression function, the SVR algorithm was used to find linear relationships within an elevated feature space. An approaching nonlinear function was used to map the input data to a scope. The color card is an additional method of detection that allows for the rapid identification of disease fatalities based on skin color and eyes. The old invasive methods of diagnosing jaundice have several drawbacks, including the inability to monitor simultaneously, the length of time required, the trauma to the patient, and the thousands of dollars involved. To reduce the discomfort associated with these techniques, a non-intrusive approach has been devised to identify jaundice in the early months of life, utilizing the image processing technologies and CNN algorithm. © 2025 the Author(s).

关键词： Neonatal monitoring

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Illicit Events Evaluation on the Dark Web Using NSGA-2 Algorithms Based on Energy Consumption

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Informatica (Slovenia) 2024年第18期48卷 77-96页

作者： Rawat, Romil Rajavat, Anand Department of Computer Science Engineering Shri Vaishnav Institute of Information Technology Shri Vaishnav Vidyapeeth Vishwavidyalaya Indore India

The proposed work objective is to adopt the non-dominated sorting genetic algorithm II (NSGA-II), a type of MOEA (multi-objective evolutionary algorithms), to reduce the dimensionality and identify the most relevant features. The objectives and hypotheses tested using NSGA-II and MOEA are to develop predictive models that best fit the problem of traffic analysis, analyse the set of features associated with the dataset, and apply NSGA techniques to reduce the data dimensionality. The work used the datasets and considered the Transnational Terrorist Hostage Event (TTHE) and Counter Trafficking Data Collaborative (CTDC) datasets, which relate to global human trafficking (HTr). The method used is focused on analysing the energy consumption (Econ) with the carbon footprint (CFP) of the proposed algorithm for different values of the main parameters on different hardware platforms, where the quality of each individual is computed based on ML algorithms. The result represents the "F-measure" metric obtained from support vector machines (SVM) and the number of features in order to determine the dimensionality, the execution time, the Econ, and the CFP during the feature engineering process. To estimate performance, the parameter values are computed using *** proposed work concludes that cybercrime employs and represents susceptible behaviour on the OSN Channels network. We identified the threat patterns by using NSGA-II and Econ analysis to establish connections between the variables in the dataset. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Support vector machines

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Simulating Application Driven Mobile D2D underlay Networks using Gym API 17

Simulating Application Driven Mobile D2D underlay Networks u...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Batabyal, Suvadip National Institute of Technology Department of Computer Science & Engineering Durgapur India

ISBN: (纸本)9798331531195

Device-to-device (D2D) communication underlay cellular network improves spectral efficiency by reusing cellular resources over short and low-power links between the devices. For this, the D2D paradigm is considered to be an integral part of all kinds of future networks and is an active area of research at different levels. This requires a simple, configurable, scalable, and realistic evaluation of the protocols proposed for the D2D networking paradigm. Although there exists a few platform to evaluate a D2D underlay network, they have one or more of the following drawbacks: (i) long development time and complex environment, (ii) limited support for mobility, (iii) no support for application specific development and evaluation. In this work, we developed a framework for simulating an application-driven mobile D2D underlay network using the Gym API, where D2D connections are made spontaneously based on the application requirements. The proposed framework includes modules for generating application-specific traffic, buffer for transmission and caching of application data, and mobility management. This complements several earlier works on application (or utility) driven resource allocation in D2D underlay network. The framework is used to evaluate a D2D network using different mobility models and performance of cache based video streaming in a D2D underlay network. Finally, the framework is compared with ns-3 and OMNET++ simulators and is observed to have lower CPU utilization and run-time under the same network settings. © 2025 IEEE.

关键词： Resource allocation

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