Reviewerly/exHarmony huggingface dataset:
Radial basis function networks with lightweight multiscale fusion strategy‐based underwater image enhancement

Abstract A novel underwater picture enhancement approach under non‐uniform lighting is presented to solve the issues of underwater photographs with unevenness due to additional lighting in deep‐sea and night‐time environments. Water suspended particles can cause image noise, low contrast, and colour deviation. The heterogeneous feature fusion module aims to combine multiple levels and levels of features with improving the network's ability to perceive semantic and specific information. The capability of autonomous underwater and remotely driven cars to explore and comprehend their environments is contingent on improving underwater images, a crucial low‐level computer vision challenge. Recent applications of deep learning models include enhancing aquatic image quality and resolving several computer vision problems. Although several deep learning‐based techniques exist for enhancing underwater images, their implementation is challenging due to the high memory and model parameter requirements. We propose a solution based on radial basis function networks (RBFN) for lightweight multiscale data fusion (LMFS). The LMFS incorporates diverse branches with varying kernel sizes to generate multiscale feature maps. The proposed RBFN‐LMFS The convolution layer with jump connection and the attention module produces the output from the feature extraction module, which aims to extract various features at the network's beginning. The outcomes of our experiments on diverse data sets demonstrate that our proposed RBFN‐LMFS technique performs well in processing both synthetic and authentic underwater images and successfully recovers image colour and texture characteristics. The visual output is superior to existing underwater image enhancement algorithms and is consistent with aspects of human vision.
Study on the Copyright Law of Short Video "Handling" Phenomenon

As the speed of mobile transmission continues to escalate, in the era of information explosion, the use of short videos as a carrier to record daily life entertainment has gradually become mainstream. However, under the evolution of capital marketization, the economic attributes of short videos have gradually become obvious, and the success of Li Ziqi's video commercial operation has further promoted the rapid development of the short video industry. In this paper, we first analyse whether the disputed short videos meet the criteria of work composition from the perspective of the basis of copyright rights. As China's copyright has not yet made specific provisions for short videos in relation to the classification of works, it is necessary to explore what criteria short videos need to meet in order to constitute "audiovisual" works. Secondly, this article focuses on the main elements of infringement in short-form video infringement disputes, and thus in determining whether a short-form video constitutes a work, more emphasis should be placed on the three characteristics of audience appreciation and response, original expression and specificity of plot. The possible infringement situations of short video works are divided, and the boundaries between the obligations of short video platforms and the fair use of other users are explored from the perspective of the common infringing subjects in infringement disputes. On this basis, we analyse the types and modes of existing regulatory instruments of short-form video copyright law, and provide a theoretical basis for later proposing the standards and obligations of different subjects in determining short-form video infringement. Finally, on the basis of the existing means of regulation, new suggestions for regulation are explored, i.e. the scope of indirect and direct infringement liability of short video platforms should be expanded, and short video infringement should be regulated from the process of production, review, dissemination and reproduction, requiring higher platform liability. As far as other users are concerned, the whole-process fair use standard should be adopted to determine whether infringement of another's work is constituted, with emphasis on the impact caused by the user to the original creator in the actual use.
Models for the digitization of the learning process in higher schools / on the example of University of National and World Economy/

The report presents models for the digitization of the learning process in higher schools on the example of the University of National and World Economy. The experience and good practices of the university in the field of digitization of university education are presented.
Online Team-based Learning for Productivity Management Module

This paper describes our experience in delivering a productivity management module using Team-based Learning (TBL) to a group of final-year Information and Communication Technology students during the height of the COVID-19 infection outbreak in Singapore. As these students were also doing their internships in different companies, to mitigate transmission of COVID-19 among students and further on to staff in these companies, this module was delivered online over Zoom. Every week, students attempted the individual readiness assessment test (iRAT) and group readiness assessment test (gRAT) over Zoom and worked on their team projects solving an industry problem using Lean Methodology and A3 report in Zoom breakout rooms. We explain how we conducted TBL over Zoom and present our findings and feedback from students.
Analysis Of Multi-Service Networks For The Provision Of Multimedia Services Based On IMS

Nowadays, information technology and communication systems are evolving, and there is a growing demand for multiservice network analysis processes to provide multimedia services through IMS. IP Multimedia Subsystem (IMS) is a next-generation standard-based network architecture designed for telecommunications operators who want to deliver cutting-edge services over mobile and fixed networks. IMS is a service-oriented architectural framework that aims to provide current and future Internet services to fixed and mobile end users on an all-IP multi-access platform. The 3rd Generation Partnership Project (3GPP) and 3GPP2 developed IMS to provide service delivery platforms for a converged communication model [1].
Anonymising Video Data Collection at the Edge Using DeepDish

Increase in popularity of various deep learning methodologies has led to a huge increase in demand for training data. These training data often contain video featuring people but these videos often cannot be used due to privacy concerns as people are identifiable. We present an extension to the DeepDish object tracking system running on a Raspberry Pi. DeepDish performs object detection in the Raspberry Pi itself, avoiding the need to ship raw video data off the device. Our extension adds online face detection and blurring to preserve privacy. We implement and evaluate four different face detection algorithms, achieving 83% accuracy using YuNet, while increasing the latency by 75%. We then implement and evaluate three different object tracking algorithms to reduce the latency increase by running the simpler object tracking algorithm, reducing the number of calls to the expensive face detection algorithm. The result is a significant decrease in latency at the cost of a small decrease in accuracy. We also implemented and compared three different face obfuscation algorithms, one of which achieves differential privacy.
Statistical Characterization of Snapshot OSNMA Spoofing Detection

Spoofing detection in Global Navigation Satellite Systems (GNSS) is gradually becoming need of the hour due to significant increase in sophisticated spoofing attacks that compromise the signal integrity and security. To withstand against these attacks, Galileo is providing the Open Service Navigation Message Authentication (OSNMA) in its E1-B signal component, comprises of a cryptographic protocol that conveys unpredictable data symbols to the user to verify the content of the I/NAV message. In this context, the following paper proposes a reliable spoofer detector by employing the snapshots of received unpredictable symbols and compares them with the authentic ones. The problem is formulated as a Binary Symmetric Channel (BSC), where the feasibility is determined by the probabilities of error at the spoofer’s and the user’s sides. However, due to the presence of signal impairments, the spoofing detector faces the hypothesis inversion problem (i.e. chooses the wrong hypothesis under certain conditions). The primary focus of this article is to avoid the hypothesis inversion problem by optimizing the statistical characterization of snapshot OSNMA detector and enhance the detection performance by designing appropriate test statistics conditions. Simulation results reveal that utilizing multiple test conditions solves the problem and strengthens the detection performance to a great extent.
A Pilot Study Investigating Student Interaction Preferences in Immersive Virtual Reality Environments

Since the outbreak of the COVID-19 pandemic, University of Nottingham Ningbo China (UNNC), the first Sino-foreign university in China, has been committed to digital transformation and increasing its technological capabilities and online provisions. At the forefront is Virtual Reality (VR), which is becoming more affordable and accessible. Immersive VR (iVR) is often referred to as the ultimate version of VR, and can be enhanced through sensory interfaces, such as audio and haptic. The present paper describes an iVR pilot study based on the virtual experiences of Design History, developed by V-ROOM, a special division within UNNC that focuses on digital pedagogy, and UNNC’s BEng Product Design and Manufacture (PDM) program. The study explores student preferences and efficacy regarding interaction interfaces and presentation types for learning content within iVR environments. The analysis is based on post-experience questionnaires, (pre/post) comprehension tests, students’ statements, and researchers’ observations. Results show that interaction interface types play a pivotal role in immersion and engagement within these environments, and that learning content utilising microlearning and/or gamification elements are preferred.
A New Proposed Technique For Object Identification Using Permanent Magnet Pieces

A new technique for identifying objects and creating a unique identity for objects has been created by implanting distributed permanent magnets into objects. Implanting permanent magnets and distributing them inside objects works to change objects' magnetic maps or magnetic identities. The new identity can be identified and revealed using a magnetic testing platform that contains four magnetic field sensors and a transceiver for sensor signal transmission to the computer. The signals generated by the sensors in the examination platform, which are proportional to the intensity of the magnetic flux resulting from the spinning of the permanent magnets at different angles up to 5 degrees, create a new magnetic map that expresses the identity of the magnetic object. The proposed system consists of the following parts: testing platform, testing object, and identification software programs. For the identification and classification process, there are four basic steps (sensor signals collection, sensor signal pre-processing, feature extraction, and identification process). The identification algorithms used mainly are K-Nearest Neighbor and Support Vector Machin. K-nearest neighbor gains an accuracy of about 96% and Support Vector Machin gains an accuracy of about 87%.
Analyze Wireless Sensor Network Structures for Intellectual Monitoring System

As one of the modern trends in the development of data transmission networks, wireless sensor networks are of great importance for solving problems related to the creation of tools for remote intelligent monitoring of devices. Wireless sensor networks are used in environmental monitoring, smart home, smart energy, smart transportation systems, smart agriculture, smart medicine and many other fields. Therefore, it is appropriate to model and research the hybrid energy supply sources of telecommunication systems as information transmission technologies in the IoT-based intelligent monitoring system, not based on a general approach to researching the characteristics of wireless sensor networks, but based on the parameters and specific characteristics of the system in which it is used.
Path Planning of Mobile Medical Robot Based on Genetic Algorithm

Whenever a major public health event occurs, considering the huge demand for materials, heavy disinfection tasks, shortage of medical staff, and the risk of cross-infection, the paper uses genetic algorithm for global path planning to assist medical robots complete path planning and optimization in a static environment. Genetic algorithms can automatically acquire and accumulate knowledge about the search space during the search process, and adaptively control the search process to obtain the best solution. The paper takes the makeshift hospital map as the background, uses the grid method to establish the environment model, and uses the genetic algorithm to plan the path of the mobile medical robot. The experimental results show that an optimal path for a mobile medical robot with a short average path length and a smooth path can be finally obtained.
Intelligent design for quadruped robot on a dynamic flexible surface with an active spine

This paper proposes an approach to design a quadruped robot with a dynamic spine using Reservoir Computing. Four bending sensors are integrated into the continuous dynamics spine to adjust spine force for balancing and enable closed-loop control of the Center of Mass (CoMs) mapping onto the dynamic surface. Passively modeling the system enabled a quadrupedal robot with a flexible spine to navigate rough terrain with improved efficiency, agility, and minimized impact on explosive power. Additionally, paper introduce to develop a novel, intelligent control mechanism for the quadrupedal robot to operate effectively on dynamic, flexible surfaces. Our approach focuses on a hierarchical distributed control mechanism developed for leg to cooperatively change centralized frames for a better functional reflection.
Visualizing Linked Geospatial Data

chapter Share on Visualizing Linked Geospatial Data Author: George Stamoulis View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 127–150https://doi.org/10.1145/3581906.3581915Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Question Answering Engines for Geospatial Knowledge Graphs

chapter Share on Question Answering Engines for Geospatial Knowledge Graphs Authors: Dharmen Punjani View Profile , Eleni Tsalapati View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 257–282https://doi.org/10.1145/3581906.3581922Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Geospatial RDF Stores

chapter Share on Geospatial RDF Stores Author: Theofilos Ioannidis View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 221–240https://doi.org/10.1145/3581906.3581920Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Geospatial Ontologies

chapter Share on Geospatial Ontologies Author: Charalampos Nikolaou View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 67–84https://doi.org/10.1145/3581906.3581912Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Linked Geospatial Data

chapter Share on Linked Geospatial Data Author: Despina-Athanasia Pantazi View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 85–98https://doi.org/10.1145/3581906.3581913Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Introduction

chapter Share on Introduction Author: Manolis Koubarakis View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 1–8https://doi.org/10.1145/3581906.3581908Published:14 June 2023Publication History 0citation1DownloadsMetricsTotal Citations0Total Downloads1Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Breast mass segmentation using mammographic data: a systematic review

Breast cancer continues to be the most prevalent cancer infecting humans worldwide. Timely detection can assist in the reduction of both mortality rates and treatment costs. Segmentation plays a crucial role in the timely detection of breast cancer. This study describes the methodology and findings of a systematic review (SR) that aimed to evaluate cutting-edge segmentation approaches in computer-aided diagnosis (CAD). The primary objective is to provide a general overview and analysis of each of these methods, as well as to address the limitations and difficulties associated with them. Based on the observed shortcomings, directions for future investigation have also been offered. In addition, this SR also provides an overview of numerous publicly available benchmark datasets used in the reviewed literature. Unsupervised algorithms have been found to be more commonly used than supervised and DL counterparts. DL techniques require powerful computers and enormous volumes of training data. In most of the existing segmentation approaches, digitised images from DDSM and mini-MIAS datasets have been employed for experimentation. Both medical professionals and researchers who are aiming to address research gaps and make significant contributions to breast cancer diagnoses may find this systematic review to be valuable.
Interlinking Geospatial Data Sources

chapter Share on Interlinking Geospatial Data Sources Author: George Papadakis View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 161–184https://doi.org/10.1145/3581906.3581917Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Putting It All Together: A Data Science Pipeline for Linked Earth Observation Data

chapter Share on Putting It All Together: A Data Science Pipeline for Linked Earth Observation Data Author: Manolis Koubarakis View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 283–288https://doi.org/10.1145/3581906.3581923Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Querying Geospatial Data Expressed in RDF

chapter Share on Querying Geospatial Data Expressed in RDF Authors: Despina-Athanasia Pantazi View Profile , Dimitris Bilidas View Profile Authors Info & Claims Geospatial Data Science: A Hands-on Approach for Building Geospatial Applications Using Linked Data TechnologiesJune 2023Pages 99–126https://doi.org/10.1145/3581906.3581914Published:14 June 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
A statistical approach to improve CNN classification accuracy

Convolutional neural networks (CNNs) have achieved state-of-the-art performance in image classification tasks. However, they may underperform for specific classes, resulting in misclassifications. To address this issue, the proposed method involves two steps that use the Mann-Whitney U test on generated image distributions. The method is evaluated on the publicly available dataset CIFAR100, utilizing ResNet-50 as the baseline network. The results show that the proposed method is effective in significantly improving the classification accuracy of low-accuracy image classes while preserving the high-accuracy classes.