Reviewerly/exHarmony huggingface dataset:
Image Color Reduction Using Progressive Histogram Quantization and Kmeans Clustering

Color reduction is an important tool for different image processing and computer vision applications. In this paper, a progressive histogram-based color reduction (quantization) is used with the Kmeans clustering algorithm to speed up the quantization process of the Kmeans method. The progressive histogram quantization (PHQ) is a simple iterative algorithm where a single histogram bin is merged to one of its two nearest neighbors' bins at each iteration. The histogram bin is merged according to the differences in the value (pixel counts) and the location of the left and right bins. The PHQ algorithm is used as a pre-quantization for the Kmeans clustering to reduce the size of the data and speed up the clustering process. The experimental results show that the PHQ+Kmeans algorithm maintains good image quality and enhances the execution time compared to the Kmeans clustering algorithm alone when applied on remote sensing images.
File-level Deduplication by using text files – Hive integration

With the enormous increase in data size, the complexity of finding duplicate data is recognized as one of the significant challenges. Elimination of duplicate data is an essential step in data cleaning as redundant data can affect a system's performance in the data processing. In order to do this deduplication technique is used to eliminate the duplicated data at the file or content level which helps to only store one copy of the file in the database. In this paper a technique is proposed to solve the storage issues and deduplication where the Hadoop Distributed File System is used to solve the vast amount of data storage issues and to identify the duplicate data a cryptography algorithm SHA 256 is used. Finally, HBase a non-relational distributed database including Hive Integration is used for data retrieval. The dataset containing counts of tests and results for COVID-19 is taken from Data.gov for experimentation. The experimental results divulge an increase in deduplication ratio, less time consumed and a gain in the storage space used.
Meaning-Making Orientations for the Self-development of a Future Teacher in an Integrative Educational Environment

The identification of the natural essence of meaning and its definition is one of the challenges of the philosophy of education. The article considers the problem of classifying meanings and meaning-making orientations in the activities of a future teacher. The meaning-making orientations of the future teacher’s self-development are worldview concepts which have a great importance for the formation of his spiritual and moral personality. The purpose of the empirical study was to determine the interdependence of self-development and leadership as life orientations, which are necessary for a future teacher to make professional and pedagogical activities successfully.The leading approach to the study of the process of personal and professional self-development of a future teacher in the modern educational environment is an integrative-environmental methodological approach that allows to understand deeper the organization of self-development. The essence of the integrative-environmental approach is the holistic integration of previously separated disjoined components. The integrative-environmental approach is based on the understanding of integration of educational environments as their “unity of diversity”, and meanwhile, a new objectivity is being creating with the emerging qualities and potentials of elements, their connections and relationships.As a result of the research, the classification of meanings and meaning-making orientations in the future teacher’s activity is determined. Empirical research shows that all students-future teachers- are characterized by a high degree of self-development. Besides, the results of the study illustrate that there is a significant relationship between leadership and the ability to self-development: the higher is the ability to self-development, the more pronounced the leadership of the students is.The novelty of the research results in comparison with previously published materials lies in a qualitatively different approach to substantiating the self-development of a future teacher based on life-orientations. Such presentation will significantly improve the process of self-development of a future teacher as a person and as a professional in an integrative educational environment.
Applying An Adaptive Multi-Population Optimization Algorithm to Enhance Machine Learning Models for Computational Finance

Developing effective machine learning models to maximize the generalization capability of the learned data patterns while minimizing the risk of overfitting and also the ultimate computational costs of the trained models are very challenging yet significant tasks in many real-world applications. Due to the high complexity and huge amount of data involved in financial applications, the critical task of constructing appropriate machine learning models will surely become more challenging. Typically, data scientists or researchers may employ various optimizers to enhance the feature selection and/or tuning of the involved hyper-parameters in order to improve the overall performance of the obtained learning models. In this paper, a very flexible optimizer, namely the Adaptive Multi-Population optimization Algorithm (AMPOA), utilizing multiple populations with different search strategies is considered in which two of its variants are carefully evaluated with the other state-of-theart optimizers to enhance the feature selection process of the commonly used K-nearest-neighbor classifier approach on a set of 12 well-known benchmark problems. The first variant named the BAMPOA-R approach employs a rounding technique to determine on the binary decision of choosing an input feature or not for the underlying classifier while the other BAMPOA- T approach utilizes a specific transform function to decide on the feature selection. To demonstrate the feasibility of the proposed optimizer for financial applications, the BAMPOA- R approach with the best performance in the previous test is integrated with the Support Vector Regression (SVR) as the BAMPOA-R-SVR algorithm to compare against other regressors on 10 major financial market indexes. The evaluation results clearly demonstrate the remarkable performance of the proposed AMPOA approach to enhance the prediction performances of the underlying machine learning models through more vigorous feature selection for numerous real-world applications including those challenging problems in computational finance.
Present state and future scope of Assamese text processing

Natural language processing has been a challenging area for researchers in recent times. A lot of research works are conducted to improve the performance of natural language processing that have helped many applications to be made available for our day to day life. Most of the developments have happened only for a few western languages. Researchers have also published some quality works related to Indian languages in recent times. However, the research works conducted for most of the other languages spoken in India, the country with the second largest population in the world, are at a very primitive stage. This paper aims to review the advances in this area for one of the Low Resource Indian languages -“Assamese”, the official language of Assam, the gateway to North East India. It is also spoken in many other states of North Eastern part of India. In this work, we present a highlight of research works related to various methods that are applied to Assamese Text processing. It is observed that certain language characteristics of Assamese are best applicable to certain popular methods used for Natural Language Processing. The reason behind this relook is to overview and report the present state and future possibilities of research in text processing in Assamese. This paper should serve as a good beginning for anyone interested to carry forward the computational works for Assamese. We conclude the paper with a brief discussion on the scope of Assamese Text processing in the future.
What do laboratory-forgetting paradigms tell us about use-inspired forgetting?

Directed forgetting is a laboratory task in which subjects are told to remember some information and forget other information. In directed forgetting tasks, participants are able to exert intentional control over which information they retain in memory and which information they forget. Forgetting in this task appears to be mediated by intentional control of memory states in which executive control mechanisms suppress unwanted information. Recognition-induced forgetting is another laboratory task in which subjects forget information. Recognizing a target memory induces the forgetting of related items stored in memory. Rather than occurring due to volitional control, recognition-induced forgetting is an incidental by-product of activating items in memory. Here we asked whether intentional directed forgetting or unintentional recognition-induced forgetting is a more robust forgetting effect. While there was a correlation between forgetting effects when the same subjects did both tasks, the magnitude of recognition-induced forgetting was larger than the magnitude of directed forgetting. These results point to practical differences in forgetting outcomes between two commonly used laboratory-forgetting paradigms.
Village library for sustainable community empowerment program case: Village library at Tirtomoyo Village Pakis, Malang District, East Java

Abstract National development is essentially the development of Indonesian people and all Indonesian people, both in cities and cities who live in villages. Libraries have a role as non-formal educational institutions, agents of change and development agents for the surrounding community. The public can take advantage of library collections for finding information, developing creative ideas and innovation, and looking for information about new things. This study aims to explore the active role of village library in society empowerment so that it can contribute in village development and community empowerment. The research method used was field observations to village library of Tirtomoyo at Malang District, East Java. The finding suggested there were three most important values and function of village library. For Values of Communication and Information, the library has a duty as an institution that manages information and resources information. For Educational Values and Social values, the library provides information sources that can support activities lifelong learning. It is suggested that Village Libraries should have been receiving direct support from the government, especially the local government. With this support is expected in the future, the community welfare is increase while the noble values of the culture are well preserved for future generations.
Ocean Data Sharing Based on Blockchain

In order to solve the problem of ocean data sharing difficulties and “isolated data island ”, a decentralized, tamperproof ocean data sharing system based on blockchain technology is designed. This paper takes ocean observation network data sharing as the background and fabric blockchain as the framework, and details the workflow and functional framework of the ocean data sharing system. Blockchain technology is used to ensure the security of ocean data, and privacy protection technology is used to achieve hierarchical and classified sharing of ocean data.
Research on Panoramic Stereo Live Streaming Based on the Virtual Reality

Virtual Reality (VR) technology has been successfully applied in many fields, such as education, tourism, games, etc. Some researchers hope to combine VR to watch panoramic stereo video and bring a brand new living experience in the field of live broadcasting. However, in practical applications, there are many problems such as panoramic video real-time stitching and high-resolution video compression coding, so it is still difficult to construct a panoramic stereo living video system. In this paper, we design and implement a panoramic stereo video living system. The system based on the eight-eye panoramic annular lens, the 360-Degree binocular video is stitched. Compared with the traditional coding algorithm, H.265 coding algorithm is used to compress the video, which improves the compression rate by more than fifty percent. Then the video stream is pushed to the cloud for forwarding. The receiving end combines VR helmet to watch panoramic stereo video live, bringing viewers a brand new viewing experience.
"That's dastardly ingenious"

Scholars have previously described how online communities engage in particular discourses and forms of argumentation. In parallel, HCI and STS researchers have described discourses surrounding ethics and values and their role in shaping design processes and outcomes. However, little work has addressed the intersection of ethical concern and the discourses of non-expert users. In this paper, we describe the argumentation strategies used by Redditors on the subreddit 'r/assholedesign' as they discuss ethically problematic design artifacts. We used content and sequence analysis methods to identify the building blocks of ethical argumentation in this online community, including ethical positioning when raising issues of concern, identification of potential remedies to the original design artifact or issues of concern, and means of extending or negating these elements. Through this analysis, we reveal the breadth of ethical argumentation strategies used "in-the-wild" by non-experts, resulting in an increased awareness of the capacity of community members to engage in "everyday ethics" regardless of specific ethics training. We describe future opportunities to connect these ethical argumentation strategies with design practices, education, and methods.
Conversations with GUIs

Annotated datasets of application GUIs contain a wealth of information that can be used for various purposes, from providing inspiration to designers and implementation details to developers to assisting end-users during daily use. However, users often struggle to formulate their needs in a way that computers can understand reliably. To address this, we study how people may interact with such GUI datasets using natural language. We elicit user needs in a survey (N = 120) with three target groups (designers, developers, end-users), providing insights into which capabilities would be useful and how users formulate queries. We contribute a labelled dataset of 1317 user queries, and demonstrate an application of a conversational assistant that interprets these queries and retrieves information from a large-scale GUI dataset. It can (1) suggest GUI screenshots for design ideation, (2) highlight details about particular GUI features for development, and (3) reveal further insights about applications. Our findings can inform design and implementation of intelligent systems to interact with GUI datasets intuitively.
Comparative Study on Different Encryption and Decryption Algorithm

With the advancement in digitalization, the security of data/file has become a major point of concern. With this digitalization the Encoding and decoding of information have recently been widely developed and investigated, because there is a demand for an inviolable encoding and decoding algorithm which is hard to crack. To fulfill all the demands Cryptography plays major roles. Nowadays, many researchers have proposed many encryption and decryption algorithms such as HMAC, DES, RSA, TWOFISH, BLOWFISH, AES, IDEA and others. But most of the proposed algo's/systems have encountered some problems such as lack of noun muscular and a large amount of time applied to the packet delay to preserve the protection between the terminals on the communication channel. The comparison has been made and the final analysis results are briefed in the result.
On resilience of security-oriented error detecting architectures against power attacks

It has been previously shown that hardware implementation of fault attack countermeasures based on error-detecting codes (EDCs) can make the circuit more vulnerable to power analysis attacks. We revisit this finding and show that the hypothesis space can grow significantly when a state-of-the-art security-oriented robust EDC is properly crafted. We use the Roth-Karp decomposition as an analytical tool to prove that by a simple re-ordering of the EDC's bits, the number of extra bits needed to formulate the hypotheses becomes so large that power analysis (that tries to exploit additional information from the redundant bits) is rendered infeasible.
Lee Distance of (4<i>z</i> – 1)-Constacyclic Codes of Length 2<sup> <i>s</i> </sup> Over the Galois Ring <i>GR</i>(2<sup> <i>a</i> </sup>,<i>m</i>)

Let a and m be positive integers. The definition of Lee weights over ℤ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2a </sub> is generalized to its m-degree Galois extension GR(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup> , m) using a nonzero element ξ in GR(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup> , m) of order 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> - 1. For z ∈ GR(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup> , m), the minimum Lee weights of (4z-1)-constacyclic codes over GR(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup> , m) of length 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sup> are determined and shown to be independent of the choice of ξ. Using this, we construct some optimal binary codes of length 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sup> as Gray images of certain (4z - 1)-constacyclic codes over GR(4, m) and obtain some maximum distance separable (MDS) codes with respect to the Lee distance of length 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sup> over GR(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup> , m).
User involvement in digital systems design: Case studies of mobile money innovation in Kenya

Abstract This research explores the design of mobile money value‐added services in Kenya that engage marginalized users during the design process. Building on past research that sets out principles for user centered design (UCD), and drawing upon evidence from three case studies, the research finds that system designers follow UCD principles, but decisions to involve users are largely born out of pragmatism, to increase the probability of acceptance of the system, whereas the users main concern were the associated costs, and there was (at least in the early stages) resistance to involvement. This resistance was borne out of a tension between the motivation of the system designers (which was largely non‐altruistic) and the motivation of the users who became involved in the projects through self‐interest or some coercion. The research concludes that system designers require greater appreciation of diversity in interests, asymmetric power and cross‐cultural differences when applying UCD methods. The research extends current knowledge with regard to design interventions in the development of mobile money applications in sub‐Saharan Africa and the recommendations formulated from this research provide practitioners with actionable knowledge to reflect on their current tools and techniques to ensure better localized design processes.
Digital Monetization and Google Analytics

People nowadays spend more time on technology than before. This has paved the path and created new opportunities for monetization by managing Ads on different pages, SDKs and content distribution. Hence Google started providing advertisers with different types of platforms to promote and monetize their products. Different types of ads like organic, paid, social media displays ads etc. were introduced later on. This paper mainly talks about the process of building, implementing and maintaining an Advanced Reporting Platform for complete stack of Google monetization products that allow monetizing CPM & CPC with Display, Video & in APP products.
EXPERIENCE: Algorithms and Case Study for Explaining Repairs with Uniform Profiles over IoT Data

IoT data with timestamps are often found with outliers, such as GPS trajectories or sensor readings. While existing systems mostly focus on detecting temporal outliers without explanations and repairs, a decision maker may be more interested in the cause of the outlier appearance such that subsequent actions would be taken, e.g., cleaning unreliable readings or repairing broken devices or adopting a strategy for data repairs. Such outlier detection, explanation, and repairs are expected to be performed in either offline (batch) or online modes (over streaming IoT data with timestamps). In this work, we present TsClean, a new prototype system for detecting and repairing outliers with explanations over IoT data. The framework defines uniform profiles to explain the outliers detected by various algorithms, including the outliers with variant time intervals, and take approaches to repair outliers. Both batch and streaming processing are supported in a uniform framework. In particular, by varying the block size, it provides a tradeoff between computing the accurate results and approximating with efficient incremental computation. In this article, we present several case studies of applying TsClean in industry, e.g., how this framework works in detecting and repairing outliers over excavator water temperature data, and how to get reasonable explanations and repairs for the detected outliers in tracking excavators.
Deletable Blockchain based Secure EHR Storage Scheme in Multi-Cloud Environment

The large-scale deployment of the cloud-based electronic healthcare record (EHR) storage models has brought an enormous effect on modern society. However, the cloud-based EHR storage model poses severe security and privacy-related concerns. Further, the patients also no longer have direct control of their sensitive medical records. Fortunately, the advent of blockchain technology brings a new strategy to resolve these security concerns. In the cloud, blockchain technology characteristics such as decentralization, immutability, and verifiability satisfy the security requirements for the secure storage of EHR. Moreover, there is also a requirement to design a multi-cloud storage model to enhance the durability and availability of the outsourced EHRs. Therefore, in this paper, we introduce a blockchain-based immutable EHR storage in a multi-cloud environment. We also arrange the transactions as per the scheduled-appointment-time for the patient's treatment to ensure efficient block deletion. The extensive experimental and security analysis describes the feasibility of the proposed model.