Reviewerly/exHarmony huggingface dataset:
Understanding IIIF image usage based on server log analysis

Abstract Numerous libraries and museums have adopted the International Image Interoperability Framework (IIIF) that promotes mutual use of images among different institutions. In a IIIF-compatible digital collection, images are retrieved via IIIF Image API (Application Programming Interface), wherein regions of images can be specified. Thus, it is possible to investigate image usage in detail by examining the image regions that have been requested. In this article, we propose a log analysis method to measure the image usage and to visualize the analysis outcomes. Specifically, we employ the number of accesses to each pixel and visualize the results using heat maps. Given that a pixel is the smallest image unit, we apply herein a fine-grained analysis. The analysis method can be used in different applications including research tools in which researchers examine images and heat maps that show which regions of the images have already been examined by collaborators.
Increasing security to public key cryptography for point-to-point communication

In the beginning of 2020, the new idea of public key cryptography was proposed. This method is from the combining between RSA and Chebyshev maps. It is very difficult to break this system because it is based on both of Integer Factorization Problem (IFP) and Chaotic maps Discrete Logarithm Problem (CMDL). However, Chebyshev polynomials taking many computation costs (many modular multiplications and modular subtraction operations) are the equation to find the result of Chebyshev maps. In this paper, the new improvement of public-key cryptography is proposed for point-to-point communication. The main key is to reduce time and increase the security level. In fact, time is reduced by replacing some Chebyshev maps with modular exponentiation equations using only modular multiplication processes. In addition, the security level can be increased, because it is based on three problems, IFP, CMDL and Discrete Logarithm Problem (DLP). Although, DLP is included in the proposed method, it does not affect the computation time in both of encryption and decryption sides, because DLP is selected to exchange the RSA's public key. The experimental results show that time can be reduced in both sides especially in decryption side. The reason is that the private key of the compared method must be assigned too large, it is larger than the traditional RSA's private key. On the other hand, the private key for the proposed method is similar to RSA's private key.
Privacy-Preserving Data Sharing for Medical Research

Electronic patient medical records contain vast amounts of information of potential value to researchers striving to increase understanding of diseases, treatments, and outcomes. Effective use of such data is limited by privacy and technical concerns. Privacy laws require the removal of Personally Identifiable Information (PII) from the released data. Technical concerns are that the data must be abstracted for consistency across different providers. To be most useful, data from different providers for the same patient must be linked together. This paper applies cryptographic techniques to the problem of privacy-preserving linking of medical records.
A Study into Accessibility and Usability of Automated Teller Machines for Inclusiveness

At first glance, interaction with an Automated Teller Machine (ATM) tends to look limiting and prescriptive. Both hardware and interface do not seem to provide adaptability layers for vulnerable groups of users, particularly those with disabilities. This study considers users who have different requirements because of temporary or permanent disabilities and needs. After an overview of ATMs’ functionality and principles of user interactions, we introduce the main topics of this study: accessibility and usability for inclusiveness. We then describe a heuristic evaluation exercise as well as the methods and criteria used in order to assess how ATM systems, even if sharing the same functionalities, differ substantially in providing a usable and accessible experience to users. Finally, we reflect on the emerging issues that affect the user experience with ATM and highlight how even for such a simple everyday use tool, we are still far from real inclusion. Therefore, with the support of the literature, we propose some recommendations for further studies.
PixelSieve: Towards Efficient Activity Analysis From Compressed Video Streams

Pixel-level data redundancy in video induces additional memory and computing overhead when neural networks are employed to mine spatiotemporal patterns, e.g. activity and event labels from video streams. This work proposes PixelSieve, to enable highly efficient CNN-based activity analysis directly from video data in compressed formats. Instead of recovering original RGB frames from compressed video, PixelSieve utilizes the built-in metadata in compressed video streams to distill only the critical pixels that render relevant spatiotemporal features, and then conducts efficient CNN inference with the condensed inputs. PixelSieve removes the overhead of video decoding and significantly improves the performance of CNN-based video analysis by 4.5x on average.
Machine Learning in High Energy Physics

Machine learning (ML) [1] refers to all algorithms and models that provide a system with the ability to learn and improve, based on the inference of statistical dependencies, without being explicitly programmed to perform a specific task.
P2P locality-aware Live IPTV over SDN based FiWi Network

With the onset of Covid-19 pandemic, unprecedented changes have been observed in the network infrastructure. The demand for peer to peer live video streaming has increased significantly. Therefore, Internet service providers must adapt to these changes. One such way is to localize the intra traffic which can reduce the overwhelming bandwidth demand and the data transfer period. Fixed wireless access (FiWi/FWA) with optical backhaul and wireless fronthaul is a prime candidate in supporting these demands. We propose to design P2P locality aware live IPTV traffic FiWi network based on SDN. The simulation evaluation has shown that our proposed LADBA has remarkably improved the overall QoS in terms system throughput and delay.
A Survey on Mechanisms of Reusable Code Component Retrieval from Component Repository

Modern software is more dominant of software components in the process of software development. Reuse is the primary benefit of a software component improving productivity and decreasing time, cost of implementation. The high demand of reusable software components leads to need of a mechanism to effectively store and retrieve components whenever similar functionality is required. Several researchers have proposed different mechanisms to build these storage spaces of components called as Repositories. This work intends to survey different effective retrieval methods and repositories built earlier. Also, this paper discusses various stochastic and statistical models for code reusability in software engineering. This survey will be a base to develop a user friendly and well-organized repository for retrieval of code components.
A Fuzzy Cognitive Mapping Approach for the Evaluation of Hospital’s Sustainability: An Integrated View

The relationship among sustainability criteria in the hospital cannot be assessed easily. As there exist a lot of criteria to evaluate if the hospital is sustainable based on green concept, the relationships between the qualifications by using fuzzy cognitive mapping (FCM) have been tried to be seen in a macro perspective. Furthermore, Fuzzy Cognitive mapping is a very useful tool to evaluate the relationship between the qualifications/concepts and see how the qualifications affect each other. It is clear that fuzzy cognitive mapping allows us to see which qualifications should be improved. Adjacent matrix of the mapping also shows the negative and positive effects in a quantitative way. In this study, it is aimed to investigate hospitals’ sustainability criteria by using fuzzy cognitive mapping approach. Based on the numerical analysis, indoor quality and policies and regulations are the most centered-ones while food quality and occupational health and safety are the least centered ones based on sustainability evaluation of hospitals. Also, it is tried to understand that policies and regulations are the most effecting concepts on the other concepts. Energy usage and water usage are relatively high effecting concepts of a hospital’s sustainability evaluation to be green hospital. There are many factors affecting a hospital’s view trying to be sustainable and high-qualified. As quality is a large concept including continuous improvement, in terms of sustainability, many factors should be taken into consideration by observing the relationship and correlation between factors.
How Content Drives Interaction With Public Displays

Existing research into user engagement with public displays tends to focus on aspects of visual and interaction design, with less thought given towards how the choice of content may influence user behavior. In this article, we survey the existing literature, particularly deployment studies of public displays, for lessons learned on the ramifications of content with different properties. We find that local and timely relevance of content, as well as user-driven content creation, have been independently shown to foster user engagement, but that few other solid conclusions can be drawn from the literature. On the whole, the aspect of content tends to be underspecified and not fully reflected in studies of public displays.
Dynamic Load Distribution in web-based AR

In a web-based Augmented Reality (AR) application, to achieve an immersive experience we require precise object detection, realistic model rendering, smooth occlusion, and accurate augmentation in real-time. To achieve these objectives on a device requires heavy computation capabilities unavailable on most mobile devices, this can be solved by using cloud computing but it introduces network latency issues. In this work, we propose a new network protocol named DLDAR (Dynamic Load Distribution in web-based AR) that facilitates and standardizes methods for dynamic division of compute between client and server for achieving real-time performance in a comprehensive AR web application. The protocol will manage computation and network latency by dynamically provisioning compute between client and server based on device and network condition to min-max latency and quality. We demonstrate our approach by developing a web application that enables users to celebrate the regional festival “Raksha Bandan” by sharing wristbands “rakhis” that can be augmented on your wrist. This protocol can be used to create complex web AR applications with more realistic rendering, animations, and interactive environments.
Tone and Image Processing in Graphic Design based on De-Mosaic Technology

The field of visual communication includes a wide range of design. Besides logo design, it is also popular to use graphic flat design, packaging design, poster design, illustration design and so on. Based on the diversification of new media and the rapid development of the Internet, visual communication has gradually emerged some new characteristics of the times. This paper designs a joint image mosaic denoising method based on deep convolution network, and also utilizes the network to correct the learned mapping relationship. The experimental results show that this method can obtain color images with rich texture and good visual effect.
Application of Big Data in Analyzing the Impact of Explosive Cyclone on Ship Navigation Safety

The field of ship exists objectively for every ship, and the research on the field of ship is also a very important content in offshore engineering. Since Mr. Fujii, a Japanese scholar, first put forward the concept of the field of shipping, it has become a hot topic in the field of maritime experts and scholars. By studying different waters and different encounter states with different methods, various ship domain models have been obtained. In view of the above problems, this paper puts forward the flow reasoning mechanism and method for the navigation safety assessment of ships in the waters with fixed line system. The method in this paper is based on conditional information entropy rough set method to reduce the initial set, and further modified by expert model, so as to obtain the security evaluation elements for constructing the ontology.
Measurement and Analysis of Transient Information Characteristics of IOT Equipment Using Graphical Programming

Abstract The switching on and switching off operation of some IOT devices is a complex physical, chemical and mechanical nonlinear transient process, which contains a lot of information. The information has distinction, stability and clear physical meaning. Due to the short time of transient process and the rapid change of waveform and characteristic parameters from time to time, it is difficult for traditional test instruments to capture the characteristics of voltage, current and power consumption in the transient process. Therefore, this paper develops a set of transient characteristic test system of IOT equipment by using the graphical programming software LabVIEW, which realizes the accurate measurement, automatic analysis and display of transient process waveform and characteristic parameters. Taking the operating coil of an electronic product as the test object, the transient characteristics in the whole process of on-off, closing process and breaking process are tested and verified by using the test system, which improves the efficiency of detection and analysis of the performance of IOT equipment.
Contribution of the Emergence of Distance Learning in Times of the COVID-19 Pandemic: Perspectives of Pre-school and Primary School Teachers

The Portuguese educational system, like every other, all over the world was affected by the Covid-19 epidemiological outbreak. Classroom teaching has been replaced by distance learning, forcing teachers to change the methods of teaching and evaluating, with implications on personal and professional dynamics. In this article, we present the results of a study that had as main objective to know the perspectives of pre-school and primary school teachers, on the positive aspects and the constraints felt during distance learning. Data was collected near teachers at these levels of education (n = 245), through a questionnaire survey that contained items on teaching, learning, and assessment as well as an open question asking them to list the main constraints, as well as the main positive aspects of this experience. We use the webQDA® software to support the analysis of qualitative data, resulting from this issue. The results point out (a) the main constraints: the lack of teacher training, the feedback of the tasks, the lack of collaboration of some families, and the lack of technological means; (b) the most positive aspects: peer collaboration, new methods of teaching and learning, autonomy and involvement with some families.
Social Media Big Data Analytics: Security Vulnerabilities and Defenses

Recently, social networks have turned out to be core components of Internet lives, and their popularity is growing day-by-day. The social media platforms generate exceptionally high dimensional datasets that pose novel risks to their users due to the ability to access a large amount of personal information. The most challenging concern is to maximize the power of social media big data analytics while identifying and mitigating the security vulnerabilities, effectively. This paper identifies and evaluates the security vulnerabilities at different stages of social media analytics, i.e., data acquisition, preprocessing, data representation, analysis, and presentation. The identified security threats in the analytics process promote the exploration of innovative technologies and testing practices that pave the way for future research and practice. In line with this motivation, this paper suggests defense measures for social media big data analytics framework security vulnerabilities.
L’uso dell’Unità Didattica Digitale per lo sviluppo della competenza lessicale

This paper presents the main features of the UDD (Unità Didattica Digitale), a new operational model developed specifically for language teaching in e-learning. In particular, we will focus on how this model can be used to develop lexical competence, the features of which will be briefly defined, mainly by referring to the different phases envisaged in the teaching plan. The paper will then illustrate the possibilities that the UDD model offers for activating and supporting the development of lexical competence, the types of activities that can be carried out and in which ways the model can be used, highlighting the positive aspects and the critical issues still to be resolved.
Utility Evaluation of Software Product: An Industry Implementation

Evaluating the utility of a software product is necessary because it allows organizational processes to function properly and for end users to be satisfied. At this way, we decided to automate the management process in the planning, register and monitoring of activities in the development and quality areas of a technology development company. We figured out that this process has limitations due to the use of multiple tools such as software and applications that work in isolation, which complicates the orderly and systematized work and activities of the team. In this study we evaluated the utility of quality in use over a software implementation called "ITE CHECK ONE" that automated that process. In the evaluation we used five utility metrics based on the ISO/IEC 25010 and ISO/IEC 25022 standards; the artifacts used in the evaluation are available in a public link on Zenodo. The results show that the utility of the software reached 90.28% by users. We conclude that the evaluation process answers the research question and reveals characteristics of possible improvements in the evaluated software.
Simplified Evaluation Framework for Query Extraction Techniques

The growing number of database management systems and applications that use them directly or through some form of proxy has led to the problems when trying to understand the queries sent from the application to the database. There are multiple ways to extract queries from the application, network or database management systems and the way to extract largely depends on the format of the application, technology used and the security concerns. Given these non-functional requirements, we generalize the possible functional features that can be used for evaluation: query extraction and subsequent query modification. The results are then presented using three dimensions: technique (approach), requirement (non-functional criterion), and feature (functional criterion) where applicable. Each combination is analyzed and given the possible use case. Developers can then use this to make an informed decision for their applications.
Trust Computation in Robust Writer Identification for Indic Language(TCRWIL)

Finding Trust on Writer Identification assumes a significant part in misrepresentation discovery while thinking about the instance of unapproved access in banking and other privacy checks. Indic Forensic archive investigation is additionally done by trusted author identification (TWI). We have tested penmanship acknowledgment utilizing a convolution neural organization utilizing Tensor-Flow and contrast with discovering Trust. We have prepared and tried neural organization for transcribed archives of Different understudies. After effectively perceiving and characterizing the transcribed records we at that point prepared and tried the information of certain understudies for improving the exactness of the organization. It's extremely mind-boggling to effectively remove the words and characters from a transcribed report to getting the Trust written in Hindi (Devanagari). At that point, we utilized our organization ofother Indic Language like Kannada. The convolution neural organization is productive for perceiving or characterizing information of various dialects in light of its element extraction and preparing at various pooling and convolution stages. So It is powerful and trusted because it's chipping away at an alternate data set like Devanagari, Kannada, and Arabic data set with their confided in an incentive at various stages. Dealing with the security framework is certainly not an easy breezy. Contingent on the correspondence organization, the degree of security may differ. Those requiring a huge information sharing organization for the most part utilize a high-upkeep security framework alongside a serious programming/equipment framework that works in relationship with the security framework to successfully distinguish and keep assaults from the few malevolent offices. So wecheckthetrustindifferentwriteridentificationtechniques.
Proficiency Assessment of Experts in Online Social network Q/A Communities

Detecting experts and their quality continuous participation in online networks of Question/Answer based communities has always been an important area of research in the field of Online Social networks. Various algorithms and measures based on identifying network structure, user behavior, link analysis have been used. Most of these expert finding methods focus on count of answer, gamification score but fail to give due credit to the usefulness and quality of posts. The kind of questions posed by a user and the quality of answers provided throw a significant light on the expertise of a user. This paper measures the proficiency of an expert on these two pertinent factors. The work proposes a novel metric ‘Proficiency Score’ which measures the expertise of a user in Online Question/Answer networks. The presented approach considers various factors such as the number of people benefitted from an expert's posts; the frequency of information(answer/question) provided; (popularity) of an expert for a particular tag and usability of a post (question/answer). It was experimentally established that “Proficiency Score” is indicative of a more active participation of the expert as compared to the existing metrics.
Image Inpainting Method based on Multi-scale Feature Fusion

To solve the problems of texture blurring and structure inconsistency in large area image inpainting. This paper proposes an image inpainting method based on multi-scale feature fusion. We design a multi-scale feature fusion module to expand the receptive field. Besides, we devise attention module to capture information from distant areas in the feature map. In this paper, partial convolution and recursive structure are adopted to repair the boundary of the missing area progressively. This method can continuously strengthen the constraint on the center of the missing region and make the repair results more refined. Experimental results show that, compared with the existing image inpainting methods, this structure improves the performance of image inpainting, and the image quality generated by it is the best.