Reviewerly/exHarmony huggingface dataset:
INDIAN SIGN LANGUAGE BASED STATIC HAND GESTURE RECOGNITION USING DEEP LEARNING

Hand gesture is the prominent medium of communication for speech and hearing-impaired community to express their feelings to normal people at public places and the normal community finds it difficult to interpret the communicated content. This problem can be resolved by developing a real time hand gesture recognition system that converts word level sign vocabulary to text. Convolution Neural network is used for the real time processing of hand sign gestures as feature extraction and classification is automatically handled by CNN. Feature map is obtained by convolving filter over the image. The ReLU activation function removes the nonlinearity from the image and gives the extracted feature map. The dimensionality of the feature map is reduced by max pooling layer and labelled. This labelling helps in classification of gesture. The 90 percent of self collected dataset is used for training and 10 percent is used for testing. During testing phase, the trained CNN directly classify the hand gesture and display the annotation corresponding to the hand gesture. The proposed system architecture achieves maximum validation accuracy of 99.78% and 100% by varying number of filters, and training accuracy of 99.56%, 99.46% and 99.42% by changing the optimizers.
The Problem of Platform Law

Abstract The internet would seem to be an ideal platform for fostering norm diversity. The very structure of the internet resists centralized governance, while the opportunities it provides for the “long tail” of expression means even voices with extremely small audiences can find a home. In reality, however, the governance of online speech looks much more monolithic. This is largely a result of private “lawmaking” activity by internet intermediaries. Increasingly, social media companies like Facebook and Twitter are developing what David Kaye, UN Special Rapporteur for the Promotion and Protection of the Right to Freedom of Opinion and Expression, has called “platform law.” Through a combination of community standards, contract, technological design, and case-specific practice, social media companies are developing “Facebook law” and “Twitter law,” displacing the laws of national jurisdictions. Using the example of content moderation, this chapter makes several contributions to the literature. First, it expands upon the idea of “platform law” to consider the broad array of mechanisms that companies use to control user behavior and mediate conflicts. Second, using human rights law as a foundation, the chapter makes the case for meaningful technological design choices that enable user autonomy. Users should be able to make explicit choices about who and what they want to hear online. It also frames user choice in terms of the right to hear, not the right to speak, as a way of navigating the tension presented by hate speech and human rights without resorting to platform law that sanitizes speech for everyone.
Supersingular isogeny graphs in cryptography

We describe recent applications of expander graphs in cryptography, particularly supersingular isogeny graphs. The security of these cryptographic constructions relies on the assumption that computing paths in these graphs is practically infeasible, even with a quantum computer. One of these cryptographic constructions is currently considered for standardization by NIST. We also recall a related construction based on Lubotzky-Philips-Sarnak's celebrated Ramanujan graphs. We describe an efficient path-finding algorithm for these graphs which was motivated by the cryptographic application, and we mention connections to the problem of optimal quantum circuit synthesis.
Social science for hydrologists: considerations when doing fieldwork with human participants

&amp;lt;p&amp;gt;Water is at the core of many current and future global challenges, which involve hydrological, technical and social processes. Therefore, successful interdisciplinary research on how water-related issues interact with human activities, actions and responses is increasingly important. Qualitative data and diverse perspectives provide much-needed information to improve our understanding and management of water-related issues. To collect this information, hydrologists are increasingly conducting fieldwork with human participants (e.g. individuals, policy-makers, community leaders, government representatives, etc.) themselves, and collaboratively with others. Although collaboration between hydrologists and social scientists in interdisciplinary projects is becoming more common, several barriers, including lack of understanding and experience, can result in hydrologists and social scientists remaining somewhat separate during research, leading to suboptimal research outcomes. Hydrologists who are planning and undertaking fieldwork involving human participants may be underprepared because they are unfamiliar with key social science approaches and concepts. Therefore, here, we help guide hydrologists to better understand some important issues to consider when working with human participants, to facilitate more collaborative research.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;As a group of social, natural, and interdisciplinary scientists, we discuss a number of important elements of fieldwork involving human participants that hydrologists might be unfamiliar with, or might have different approaches to than social scientists. These elements include good ethical practice, research question frameworks, power dynamics, communication of science (e.g. participatory mapping, photovoice, videography, and interactive graphs), and post-fieldwork reflections. There are also issues to consider when working collaboratively with social scientists, such as vocabulary differences and different methodologies and data collection approaches (e.g. interviews, focus groups, questionnaires, workshops, ethnography).&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We believe that by introducing hydrologists (and natural scientists in general) to some of the key considerations when working with human participants in the field, more holistic, ethical, and successful research outcomes can be achieved. We also want to stress that collaboration with social scientists stays important and research ethics, design, participant involvement, and results, may be compromised without the input and experience of social scientists themselves. Facilitating these collaborations between the natural and social sciences will improve interdisciplinary water research, resulting in a better understanding of the interactions between water and society.&amp;lt;/p&amp;gt;
Development of machine learning models for object identification of parasite eggs using microscopy

Over one billion people in developing countries are afflicted by parasitic infections caused by soil-transmitted helminths. These infections are treatable with cheap and safe medicine that is widel ...
PENGARUH BAHASA DAERAH TERHADAP POLA KOMUNIKASI MAHASISWA FAKULTAS SASTRA UNIVERSITAS MUSLIM INDONESIA

The Influence of Regional Language on Communication Patterns of Students of the Faculty of Letters, Muslim University of Indonesia. This study aims to examine the description of regional language and its effect on student communication patterns. This type of research is quantitative research with regression techniques using a questionnaire instrument. The research data was sourced from students of the 2019 Indonesian Language and Literature Study Program. The number of samples was 59 people using descriptive statistical data analysis techniques and inferential statistics. The results showed that the local language had a significant influence on student communication patterns.
Utilization of Rapidminer using the K-Means Clustering Algorithm for Classification of Dengue Hemorrhagic Fever (DHF) Spread in Banda Aceh City

Dengue Hemorrhagic Fever (DHF) is still a serious problem in Banda Aceh City. The grouping of dengue disease distribution areas can use data mining techniques through the K-Means Clustering Algorithm by involving several factors that influence it such as population density, rainfall, air humidity and temperature. The purpose of this study is to try to create a distribution cluster group that is included in the high category (C1), medium (C2), and low (C3) in 9 sub-districts in the city of Banda Aceh. The data used in this study are secondary data during the period 2010 to 2017, which includes population density data obtained from the Banda Aceh City BPS office, rainfall, humidity, temperature were obtained from the BMKG Indrapuri Aceh Besar office and data on dengue cases were obtained from the Banda Aceh City Health Office. The results showed that up to 4 iterations of K-Means Clustering was good enough for the classification of dengue case data. The high cluster group (C1) is Baiturrahman, Kuta Alam and Syiah Kuala sub-districts, the medium cluster group (C2) is Jaya Baru, Banda Raya and Ulee Kareng sub-districts, then the low cluster group (C3) is Meuraxa and Kuta Raja.
The ADAM platform

&amp;lt;p&amp;gt;Operational Earth Observation (EO) satellite missions are entering their 5&amp;lt;sup&amp;gt;th&amp;lt;/sup&amp;gt; lifetime decade, and the need to access historical data has strongly increased, particularly for long-term science and environmental monitoring applications. This trend that drives users to request long time-series of data will increase even more in the future, in particular regarding the interest on global change assessment and monitoring to support policy makers decisions on atmosphere, ocean, cryosphere, carbon and other biogeochemical cycles safeguard.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The Copernicus initiative (https://www.copernicus.eu) is playing a unique and unprecedented role form the point of view of amount, relevance and quality of provided environmental data. In the frame of the European Commission funded activities, the Data and Information Access Service (DIAS) are operated by five different consortia to acquire, process, archive and distribute data from Copernicus and Third-Party Missions.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;With this enormous availability of past, present, and future geospatial environmental data, there is the need to make users able to identify the datasets that best fit with their needs and obtain these data in fastest and easiest-to-use possible way. The Advanced geospatial DAta Management - ADAM platform (https://adamplatform.eu/) provides discovery, access, processing and visualization services for data in the distributed cloud environment, significantly reducing the burden of data usability.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;ADAM allows the exploitation of the content of EO data archives extended from a few years to decades and therefore makes their continuously increasing scientific value fully accessible. The advances in satellite sensor characteristics (spatial resolution, temporal frequency, spectral sensors) as well as in all related technical aspects (data and metadata format, storage, infrastructures) underline the strong need to preserve the EO space data without time constraints and to keep them accessible and exploitable, as they constitute a humankind asset. This is a typical big data challenge that ADAM can face. &amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This paper describes the ADAM platform and various application domains supported with its data science analytics and visualization capabilities.&amp;lt;/p&amp;gt;
Open Science, open research data and the role of IOSSG

The paper illustrates the objectives and the on-going activities of the Italian Open Science Support Group (IOSSG) whose main goal is to promote the development and the dissemination of Open Science in Italy. It provides support and practical tools to researchers in the different steps of research process with reference to data collection, management, legal protection, access, archiving, preservation within the frame of the European Open Science Cloud (EOSC) initiative.
Institutional factors, entrepreneurship capital types, and economic growth in Asian countries

This paper investigates the relationship between institutional factors, entrepreneurial types, and economic growth. The analysis is based on an unbalanced panel data of 18 Asian countries over 2006-2018 using a 3SLS estimation method. It extends the neoclassical growth model with entrepreneurship capital types as an endogenous variable to the economic growth function. Findings/Originality: The results show that new business density and productive entrepreneurship significantly affect GDP per capita. Additionally, a reverse impact of economic growth on entrepreneurship is revealed. Institutions constructs, namely corruption control and the rule of law, are crucial to entrepreneurship, which in turn stimulate economic growth. The results also confirm the significant role of human capital, accumulating domestic investment, economic openness, and controlling inflation in the economic growth model of the Asian countries.
DISTRIBUTED DENIAL OF SERVICE ATTACKSCONCEPTS, MATHEMATICAL AND CRYPTOGRAPHIC SOLUTIONS

Cryptography has been used to code and decodes the data in military practices. In the coming era,Cyber security is a major concern throughout society. Growth in electronic/digital data storage andcommunicated by electronic data processing systems, both the public and private sectors want to protect theirinformation from hackers and enemies. Presently, digitalization is popular in fund transfers, financialtransactions, international business and other communication devices with help of electronic medium andprivacy play an important role to keep our data safe and secure. Mathematical and cryptographic preliminariesalso play an important role to keep the data safe and secure. Mathematician and computer engineers are usingcryptography tool to encrypt and decrypt the data, which is coming from unwanted sources. Cryptography helpsto protect information transmitted from the public communication network, such as satellites, telephones, emailsand various fund transfer mediums. The present study will focus on concepts of cryptography (for exampleCaesar cipher technique using number theory approach, Symmetrical ciphers, Confidentially using symmetricdata encryption and data decryption) and how cryptographic methods are useful to prevent in Distributed Denialof services attacks.
PENERAPAN MULTIMEDIA DALAM PEMBELAJARAN YANG EFEKTIF

APPLICATION OF MULTIMEDIA IN EFFECTIVE LEARNING The purpose of this study is to analyze the use of multimedia in learning. The research method is meta-analysis. The research begins by formulating the problem, then proceed by collecting existing research data through Google Scholar search. From the research obtained in the form of 7 relevant scientific journals. Research results from researchers were analyzed by quantitative comparison methods. Based on the results of the analysis, the use of multimedia in learning can improve student learning outcomes from the lowest 0.1% to the highest 1.2%..
A Measure to Match Robot Plans to Human Intent: A Case Study in Multi-Objective Human-Robot Path-Planning

Measuring how well a potential solution to a problem matches the problem-holder's intent and detecting when a current solution no longer matches intent is important when designing resilient human-robot teams. This paper addresses intent-matching for a robot path-planning problem that includes multiple objectives and where human intent is represented as a vector in the multi-objective payoff space. The paper introduces a new metric called the intent threshold margin and shows that it can be used to rank paths by how close they match a specified intent. The rankings induced by the metric correlate with average human rankings (obtained in an MTurk study) of how closely different paths match a specified intent. The intuition of the intent threshold margin is that it represents how much the human's intent must be "relaxed" to match the payoffs for a specified path.
A TECHNICAL REVIEW ON 3D FACE RECOGNITION TECHNOLOGIES

Facial recognition is a process of identifying an individual using their face. Face recognition is widely used in security and surveillance system for identifying a person without its cooperation. The main preferment of face recognition over other human characterizing features is its uniqueness and affable acceptance, and the system used for this purpose is called a face recognition system. Face recognition systems mainly have two tasks, the first is verification, and the second is identification. In the verification process, a query image is verified against the face image already stored in the database and then for identification, compares the query face image against all face images to determine the identity of the query face. For this purpose, many algorithms have been elaborated. Mostly in the current scenario in FR, 2D, and 3D face representation is used. However, these systems are not substantial to variation to lighting, facial pose, and expression. Although 3D systems are less sensitive to these variations as compared to 2D systems. In 3D systems advanced feature extraction and classification techniques are used which enhance the recognition rate of these systems. And with the involvement of 3D scanner these system becomes more accurate. 3D systems can recognize the faces under pose variation, expression variation, and occlusion. But these systems can only support these variations up to a certain limit. In this paper, we discuss and explored feature extraction and recognition techniques.
Terapia Comunitária Integrativa para idosos em plataforma virtual durante a pandemia associada a COVID-19

This study aimed to share the experience lived among elderly people on a virtual platform. It is based on the practical strategy of Integrative Community Therapy (ICT) and the Theory of Praxis Intervention of Nursing in Collective Health (TIPESC). The collection was carried out by means of specific instruments; 14 ICT circles with a participation of 90 (100%) elderly people were carried out and a sample was taken for convenience. Among the main results, the circle stands out as a soft technology that intends to give voice to this age group considered a risk group and contribute to the implementation of new policies in Brazil, advancing to insert the elderly in the new world technology, fighting the existing challenges and aiming at preventing the socio-economic impacts after the pandemic associated to Covid-19.
WeChat Mobile Library Service in Chinese Academic Libraries

This paper introduces the WeChat mobile library service programme at Shanghai University Library and identifies problems and resolutions by reviewing the development process and experience and user feedback. A case study was conducted, and user feedback from a web survey was analysed to identify the programme's problems. Accordingly, recommendations and resolutions were developed. The author discovers that a WeChat account is crucial as an interaction platform between libraries and patrons, particularly on mobile devices. Patrons prefer to receive library services via WeChat rather than other channels. Their favourite features include online public access catalogue (OPAC), my library, and study facility availability. Libraries should conduct regular assessments to understand patrons' feedback or requests and make timely adjustments accordingly. The web survey and its data are novel in this area and provide a credible example to optimize WeChat library services.
IMPLEMENTASI ALGORITMA K-MEANS UNTUK MENGUKUR PERFORMA AKADEMIK MAHASISWA TIAP SEMESTER PADA PROGRAM STUDI TEKNIK INFORMATIKA STMIK NURDIN HAMZAH JAMBI:

The STMIK Informatics Engineering Study Program Nurdin Hamzah Jambi uses Student's Values from Attendance, Tasks, UTS, and UAS values to classify student Academic performance. During this time the technique used to classify the academic performance of students using statistical algorithms but the algorithm does not provide any effective results. Therefore, a combination of Mining Data K-Means Clustering is used to provide more effective results. The purpose of this study is to develop the implementation of the K-Means algorithm to measure the academic performance of students each semester in the STMIK Informatics Engineering Study Program Nurdin Hamzah Jambi. The Data Mining method used is k-means clustering using the Rapidminer application. In this study, the implementation of the k-means clustering algorithm was used to classify student academic performance into 3 clusters. Each cluster has an initial centroid that is randomly determined, the centroid changes if each clustering process transfers data to each cluster and changes the centroid to stop if there is no change in the data. Based on 3 attempts to classify 89 student data from semester 1 to 7 there were 89 students from each semester. The data inputted in the form of Absenteeism, Tasks, UTS and UAS Students of the 2015 Informatics Engineering Study Program. The resulting output is in the form of grouping students categorized as groups that are less satisfying, satisfying and very satisfying.after the rapidminer clustering process with k-means, 22.47% of students obtained an increase in academic performance from semester 1 to semester 7.3.37% students experienced a decline in academic performance and 74.15% the rest Fluctuated.
A Generic Blockchain-based Exchange Place

Considering the ongoing digital transformation in Orange ecosystem, different marketplaces may co-exist together for different use cases: Energy, Telecom connectivity resources, IoT (Internet of Things) and more. To allow such exchanging platform to be independent from specificities behind any use case, we present in this paper the Orange exchange place: a Blockchain-based generic exchange platform of goods and services. This exchange place exposes generic/common transactions as an On-chain digitally executed smart contracts. To emphasize the generic aspect of the exchange place, we separate the specific aspect of the use cases and encapsulate it as Off-chain modules (out of Blockchain). To enable the simple adaptation of the exchange place to different contexts, we propose a configurable exchange place data model. Therefore, the paper demonstrates how Blockchain technology, the On-chain/Off-chain approach and the configurable data model come together to design a generic distributed exchange place.
Facilitating the Decentralised Exchange of Cryptocurrencies in an Order-Driven Market

This article discusses a protocol to facilitate decentralised exchanges on an order-driven market through a consortium of market services operators.We discuss whether this hybrid protocol combining a centralised initiation phase with a decentralised execution phase outperforms fully centralised exchanges with regards to efficiency and security.Here, a fully efficient and fully secure protocol is defined as one where traders incur no trading costs or opportunity costs and counterparty risk is absent.We devise a protocol addressing the main downsides in the decentralised exchange process that uses a facilitating distributed ledger, maintains an order book and monitors the order status in real-time to provide accurate exchange rate information and performance scoring of participants.We show how performance ratings can lower opportunity costs and how a rolling benchmark rate of verifiable trades can be used to establish a trustworthy exchange rate between cryptocurrencies.The formal validation of the proposed technical mechanisms is the subject of future work.
Solving differential equations with reconfigurable Mach–Zehnder interferometer photonic networks

In this work we present and discuss the case of a reconfigurable, Mach-Zehnder interferometer-based photonic network, specially designed for implementing any arbitrary matrix operator. After a brief discussion on the available architectures we describe the main elements of the proposed architecture. Finally, using simulations we demonstrate a practical example where an 11 x MZI network is implement for the solution of differential equation.