Reviewerly/exHarmony huggingface dataset:
Proliferation of Internet-of-Things Devices in Consumer Technologies

Presents the introductory editorial for this issue of the publication.
Global Drumbeat

This article outlines the scope and significance of a special issue of The International Journal of Information, Diversity &amp; Inclusion dedicated to exploring the intersections of hip hop and the field of library and information sciences. The co-guest editors, Kafi Kumasi and André Brock, describe their respective research trajectories to help illuminate what constitutes a hip hop epistemology of LIS knowledge. This issue demonstrates that there are many robust conceptual access points for better understanding the LIS field through the lens of Hip Hop including areas like computational neuroscience, copyright and data science. The research articles are complimented by: two reports from the field; a creative section, which includes three poems; and a book review of two hip hop themed texts
A Content-based File Identification Dataset: collection, construction, and evaluation

File-Type Identification (FTI) is one of the essential functions that can be performed by examining the data blocks' magic numbers.However, this examination leads to a challenge when a file is corrupt, or these magic numbers are missing.Content-based analytics is the best way for file type identification when the magic numbers are not available.This paper prepares and presents a content-based dataset for eight common types of files based on twelve features.We designed our dataset to be used for supervised and unsupervised machine learning models.It provides the ability to classify and cluster these types into two levels, as a fine-grain level (by their file type exactly, JPG, PNG, HTML, TXT, MP4, M4A, MOV, and MP3) and as a coarse-grain level (by their broad type, image, text, audio, video).A dataset quality and features assessments are performed in this study.The obtained results show that our dataset is high-quality, nonbiased, complete, and with an acceptable duplication ratio.In addition, several multi-class classifiers are learned by our data, and classification accuracy of up to 81.8% is obtained.The main contributions of this work are summarized in constructing a new publicly available dataset based on statistical and information content-related features with detailed assessments and evaluation.
Annotation of User Data for Ubiquitous Systems - Welcome and Committees

The IEEE PerCom Workshop on Annotation of useR Data for UbiquitOUs Systems (ARDUOUS 2022) is an indisciplinary workshop with the purpose to build a scientific community around the topic of data annotation in the context of ubiqutous systems.With pervasive systems relying increasingly on large datasets for designing and testing models of users' activities, the process of data labelling and its quality are becoming a major concern for the community.Even more, with the increase of pervasive applications relying on annotated data, it becomes important to develop standards and normalisation methodologies for transferability of annotated data across different applications.This year's workshop focuses on experiences with existing tools, datasets and annotation approaches in real-world scenarios.The ARDUOUS 2022 committee evaluated the submitted full papers by both, quality and relevance to the topic of the workshop and carefully selected 7 high quality papers.For the workshop's program we planned three paper sessions: "Retrieval-based annotation of multi-channel time series data for HAR", "Annotation Frameworks", and "Applied Annotation".Additionally, one keynote session with the topic "Adventures in annotation" will be presented by Dr. Frank Krüger, University of Rostock, who will address the problem of creating high quality labels by manual annotation and their application in downstream classification tasks.We also included one session "Demonstration of annotation methods and tools" where some of the workshop participants will have the opportunity to show pipelines and tools they used during their research.In that way we hope to raise an interesting discussion and make the interactions during the workshop even more exciting.The last session of ARDUOUS 2022 will be a practical one entitled "Interactive design of an annotation tool with Miro".We would like to express our gratitude to the members of the program committee for providing detailed and high quality reviews, and thus making it possible to select interesting papers for the workshop's program.We would also like to thank the PerCom organizers and workshop co-chairs for assisting us with the organization of ARDUOUS.Finally, we would like to thank all the authors who submitted their papers to the workshop and all the participants and presenters.
Documentary Review about Computer Programming for the Development of Computer Thinking, Logical-Mathematical Skills, and Scientific Skills

Programming in school spaces has been essential because the main objectives are the training and development of skills of those who use it. This way, it contributes to the student’s activity from the professional field and in practical life. Therefore, in this article, a documentary review is carried out to inquire about the implementation of programming in school to contribute to the development of computational thinking, logical-mathematical, and scientific skills. The examination revealed essential research findings that consider programming an indispensable tool for the axes proposed in this work.&#x0D; &#x0D; Received: 21 January 2022 / Accepted: 2 April 2022 / Published: 5 May 2022
Structural Analysis of Information: Search for Methodology

This paper demonstrates the need for the structural analysis of information as a distinctive methodological tool for two reasons.The first is that this form of inquiry is underrepresented and inadequate in the study of information.The second, a closely related reason, is that there are many misconceptions about the distinction between different forms of inquiry reduced to only two, characterized as qualitative and quantitative, with surprisingly little attention paid to the role of structural analysis, not only in the study of information, but in all scientific and intellectual domains.Since the first step towards this structural analysis is in defining concepts in structural terms, the established structural methodology may also contribute to choosing a satisfactory-for-all definition of information and to develop its uniform theory.
Industrial Image Enhancement Method Based on Cloud Edge Fusion

Aiming at the problems of high mean square error, low peak signal-to-noise ratio, and long enhancement time of traditional industrial image enhancement methods, an industrial image enhancement method based on cloud edge fusion was proposed. Firstly, the industrial image is preprocessed and denoised by median filtering algorithm to detect the edge of denoised image. Then, the image is enhanced by top hat transform. Finally, the cloud edge fusion method is used to complete the task of industrial image enhancement to improve the efficiency of industrial image enhancement. The experimental results show that the mean square error of this method is kept at a low level, the peak signal-to-noise ratio is always above 53 dB, and the average industrial image enhancement time is 0.96 s. This method has good performance and can obtain a good industrial image enhancement effect, which has certain application value.
FedRN

Robustness is becoming another important challenge of federated learning in that the data collection process in each client is naturally accompanied by noisy labels. However, it is far more complex and challenging owing to varying levels of data heterogeneity and noise over clients, which exacerbates the client-to-client performance discrepancy. In this work, we propose a robust federated learning method called FedRN, which exploits k-reliable neighbors with high data expertise or similarity. Our method helps mitigate the gap between low- and high-performance clients by training only with a selected set of clean examples, identified by a collaborative model that is built based on the reliability score over clients. We demonstrate the superiority of FedRN via extensive evaluations on three real-world or synthetic benchmark datasets. Compared with existing robust methods, the results show that FedRN significantly improves the test accuracy in the presence of noisy labels.
A Firefly Algorithm-Based Approach for Web Query Reformulation

A major difficulty in using a web-based information retrieval system is the choice of terms to be used for expressing and processing a query. The user has to examine a lot of data to find the necessary documents or information. The problem that often appears in this situation is that the query is incorrect and does not express those needs. Researchers have come up with various solutions to overcome this problem among them the use of query reformulation. This paper presents an approach called FA-QR based on this technique using the Firefly metaheuristic. This algorithm was applied to frequent itemsets generated by frequent- pattern growth (FP Growth). The algorithmic solution allowed the user to select the best path among all the possible solutions for the initial query. Experimentally, the results demonstrated that our proposed approaches achieved a significant improvement over other different methods on TREC and FIRE datasets.
The Benefits of Distance Education, During the Covid-19 Pandemic: Greek Teachers’ Opinions

In Greece, the COVID-19 pandemic resulted in the schools&amp;#39; closure during the 2019-2020 school year. The Ministry of Education tried to develop online platforms so that the students could have access to education. The use of distance learning came to the fore. The teachers used the online teaching tools available as a response to this challenging situation. Nevertheless, most of them had not received any relevant training and had at their disposal minimal resources, mainly of their own and not public ones. A nationwide survey was designed investigating teachers&amp;#39; views on distance learning benefits. 515 teachers working in Greek primary education sector - both at kindergartens and primary schools- participated in the research. Their answers show three main benefits from the distance learning implementation at school education: (a), it enabled some students to access school education. Those students could not otherwise attend school education (b) it contributed to the communication among students as well as between students and teachers, and (c) it increased the ICT use by teachers. Despite these benefits mentioned, teachers stated that distance learning is not a substitute for ordinary classes and face-to-face learning.
Data Security and Privacy in Cloud Computing Platforms: A Comprehensive Review

Cloud computing is the on-demand usage of computer resources through the internet, allowing us to relocate application software and databases. Its purpose is to deliver IT services that enable clients to benefit from the pay-per-use model's substantial cost advantages and the ability to flexibly scale up or down without having to make significant investments in new hardware. On the other hand, the provider manages the data and services under this cloud architecture. Consequently, cloud clients have less control over their outsourced data and depend on cloud service providers to safeguard their data and infrastructure from both external and internal threats. In this study, we look at information security in cloud computing. It is the consideration of information on the cloud, considering security concerns. This article will go through data protection strategies utilized all around the globe to provide optimum data security by lowering risks and threats. Information accessibility is beneficial for various cloud applications, but it poses risks by exposing data to apps that already have security escape clauses. In addition, the presentation will outline information security highlights for Data in Transit and Data at Rest.
Privatization of SOEs a Shift from Protectionism and a Factor of Economic Growth

In the framework of economic development, we argue that privatization of State Owned Enterprises (SOEs) is unarguably one of the gateways to succeeding in economic growth. It provides the basis for perfect market competition, promoting employment, reducing government expenditure burden on its budget, promoting employment growth and provides efficient services, boost innovation and the technological revolution of especially developing countries which is an undisputable evidence for economic growth seen for example in Asia and China to be specific. China and a good number of countries with perfect market structures, early economic successes can be largely accredited to privatization of their underperforming SOEs model of promoting economic growth. In this article, we will attempt to draw the attention of readers on the conjectural background of privatization of SOEs, its effects in promoting economic growth and strategies of its implementation drawing from the experiences of other countries. We used descriptive analysis approach to describe the facts and effects about the significance of privatization of SOEs in economies that are opening up or still moving up the economic development ladder. The paper also draws lessons from developed economies like the US where privatization is a symbol of a capitalist and free market society, although focusing on developing countries with specific reference to Sierra Leone, bench marking the case of China. We discovered that privatization helps government save more and improve efficiency largely through competition that motivates development as well as innovation.
Low-cost client-side encryption and secure Internet of things (IoT) provisioning

Conclusion Security and ease of provisioning of IoT devices onto cloud infrastructure is instrumental to the deployment of IoT devices. With not much information available on the ease of secure provisioning of IoT devices couple with inherent challenge of these devices in encrypting data before transmission to the cloud due to their constrained nature, this work implements a low-cost client-side encryption algorithm based on the AES to carry out data encryption at the IoT device’s communication end using a SAMG55 microprocessor, following which the device is securely provisioned to a cloud platform as shown in Fig. 3. Related work and direction for future work is further detailed in Online Resources 1 and Online Resources 2.
Data Augmentation using Counterfactuals: Proximity vs Diversity

Counterfactual explanations are gaining in popularity as a way of explaining machine learning models. Counterfactual examples are generally created to help interpret the decision of a model. In that case, if a model makes a certain decision for an instance, the counterfactual examples of that instance reverse the decision of the model. Counterfactual examples can be created by craftily changing particular feature values of the instance. Though counterfactual examples are generated to explain the decision of machine learning models, we have already explored that counterfactual examples can be used for effective data augmentation. In this work, we want to explore what kind of counterfactual examples work best for data augmentation. In particular, we want to generate counterfactual examples from two perspectives: proximity and diversity. We want to observewhich perspective works best in this regard. We demonstrate the efficacy of these approaches on the widely used “Adult-Income” dataset. We consider several scenarios where we do not have enough data and use each of these approaches to augment the dataset. We compare these two approaches and discuss the implications of the results.
The Whole Community Development in Supporting Children's Literacy in Rural Areas: Community and Parents’ Participation to Foster Children’s Literacy in Rural Areas

&#x0D; &#x0D; &#x0D; Indonesia was ranked 72nd out of 77 countries in reading assessment based on Programme for International Students Assessment (PISA). Through the National Literacy Movement, the Indonesian government attempt to increase children's reading proficiency, which is also an indicator of SDG 4.1.1. This study explores the important roles of the parents and community in improving children's literacy competencies. This study used a qualitative approach and collected both primary and secondary data. The findings highlighted that parents supporting children's literacy could improve children's reading interest and early-phase of reading competencies through the availability of reading corners and home-based literacy activities. There were 300 parents supporting children's literacy activities and 73 community facilitators facilitating 20 village reading clubs. The village government also supported the sustainability of the reading club by providing incentives for the facilitators and developing the infrastructure through village fund allocation.&#x0D; &#x0D; &#x0D;
Visualization of the Virtual Tour by Stitching 360 Panoramic Images

During the COVID pandemic and the series of closures it has introduced, 360 Images virtual travel allows individuals to remotely experience cultural places and artifacts from the safety of their homes. A popular form of virtual tourism is 360-Images virtual tours: digital experiences that render a 360-Images visual representation of the real-world environment on the users’ personal device. Despite the increasing popularity of 360 virtual tours, there is no common conceptual framework for creating them. In our work, we analyzed multiple existing virtual tours and constructed a 360 Images framework for virtual tour design. We give you a platform to attach your 360 Images in a Virtual tour manner and add detail about it by using our 360 images virtual tool, then you are ready to use a Virtual tour by adding links on social media or websites.
EXAMINING MEDIA RESPONSE TO GENDER-BASED VIOLENCE IN THE GAMBIA – THE CHALLENGES AND THE WAY FORWARD

Purpose: Communication support for any development idea utilizing all levels of communication (interpersonal, group and mass) is very vital. The mass media industry has an important role to play in eliminating undesirable practices from society. Gender-based violence (GBV) is one of such practices. This study set out to examine the role of the media in tackling the menace of GBV in The Gambia, the challenges faced and how the challenges could be addressed.&#x0D; Methodology : research methods of focus group and key informant interviews were adopted to determine the level to which the media had been proactive, the challenges they face and strategies for surmounting the challenges.&#x0D; Findings : Findings show that the years of authoritarian rule have instilled the attitude of complacency and into many media practitioners in The Gambia and they have not been able to develop their investigative skills. Even though the current regime is largely liberal, the media needs to cultivate a new culture of undaunted dynamism. Apart from giving coverage to the programmes of development agencies on GBV, the media does not give adequate attention to sensitising and educating the public on gender-based violence and is also wanting in the area of following up cases of GBV while cases of online GBV are not given the required attention&#x0D; Unique contribution to theory, practice and policy(recommendation): It was recommended that all available strategies be employed for the sensitisation and education of the public on GBV and media practitioners be empowered to adequately tackle GBV. Furthermore, media organizations must be encouraged to monitor online content so that they can respond to instances of GBV directed at people in The Gambia.
Chinese Studies on the Logic of Natural Language

This paper makes a historic review on the development of the Logic of Natural Language (LNL) in China, which can be roughly divided into three periods: the first period which spanned from the late 1950s to the late 1980s was the initial period of LNL in China; the second period, a transitional period from the preliminarily integrated mode of LNL to the deeply integrated mode of LNL, lasted for the whole decade of the 1990s; the third period was from 2000 on, and during this period the deeply integrated mode became the mainstream of LNL. In today’s China, LNL is not only an important research field of logic, but has also exerted a great impact on linguistic studies and the studies in the field of natural language processing (NLP).
Impact of Human Capital and Social Capabilities on Economic Growth of Pakistan: A Time Series Analysis

Theoretically, human capital has a significant relationship with economic growth. In this regard, the present study was conducted to determine the conditions that have a significant and positive relationship with economic growth. The main objective of the study was to explore the impact of human capital and social capabilities or skills on the economic growth of Pakistan. The study estimates the impact of human capital and social capabilities on economic growth of Pakistan by using time series data from the period of 1980-2018 taken from World Bank. Autoregressive distributed lag framework is used for the valuation of variables relationship and direction of connection of variables. Human capital influenced by education expenditure, social capabilities, gross fixed capital formation (GFCF) and children mortality. This study indicates the role of human capital in growth and development of Pakistan. Results showed that health and education are the two main sectors which need significant attention of government. In addition, more investment on human capital can increase the social capabilities. Final consumption expenditure depends on current economic conditions of a nation. Results showed progressive human capital influence economic growth due to social capabilities. These objectives can be attained through sharing the suitable amount of GDP to these sectors.
ICTs for the Cognitive and Metacognitive abilities of the students with Specific Learning Disorder in Mathematics

This article is a literature review that analyses the cognitive and metacognitive abilities of the students with Specific Learning Disorder in Mathematics (SLDM). It aims to present the cognitive and metacognitive deficits of these students along with the ways and methods that can improve the corresponding cognitive and metacognitive abilities and analyze the role of the metacognitve knowledge in mathematics education. It also aims to present ICT tools that are used worldwide in order to asses and improve these abilities. These tools are designed for the assessment or the training of either the cognitive or the metacognitive abilities of the students with SLDM and include mobile and computer based applications, applications that use artificial intelligence and educational robotics.
How Does Financial Development Affect Economic Growth Volatility? Evidence from a Penalized Panel Quantile Regression

This paper aims to examine the effect of financial development on economic growth volatility for a sample of 63 countries during the period 1996-2016. Previous studies have reported mixed and inconclusive results regarding such an effect. I ascribe these controversial findings to the limitations of the ordinary least squares (OLS) regression and adopt the method of quantile regression with panel data as developed in Canay (2011). This methodological contribution allows us to test whether the effect of financial development varies across the full distribution, especially at the extreme quantiles of economic growth volatility. Unlike OLS regression, quantile regression captures the whole picture of the relationship between financial development and economic growth volatility by estimating the effect at each quantile of the distribution. Overall, our empirical results show that the effect of financial development on economic growth volatility is negative. However, this effect appears to not be uniform across the quantiles of the economic volatility distribution. This paper sheds more light on the association between financial development and economic growth volatility.