Reviewerly/exHarmony huggingface dataset:
k-Medoids Clustering Based on Kernel Density Estimation and Jensen-Shannon Divergence

Several conventional clustering methods consider the squared $$L_2$$ -norm which is calculated from objects coordinates. To extract meaningful clusters from a set of massive objects, it is required to calculate the dissimilarity from both objects coordinates and other features such as objects distribution. In this paper, JS-divergence based k-medoids (JSKMdd) is proposed as a novel method for clustering network data. In the proposed method, the dissimilarity that is based on objects coordinates and an object distribution is considered. The effectiveness of the proposed method is verified through numerical experiments with artificial datasets which consist non-linear clusters. The influence of the parameter in the proposed method is also described.
Spatial Institutional Cryptoeconomics

We explore the connection between new decentralised data infrastructure and the spatial organisation of cities. Recent advances in digital technologies for data generation, storage and coordination (e.g. blockchain-based supply chains and proof-of-location services) enables more granulated, decentralised and tradeable data about city life. We propose that this new digital infrastructure for information in cities shifts the organisation and planning of city life downwards and opens new opportunities for entrepreneurial discovery. Compared to centralised governance of smart cities, crypto-cities are more emergent orderings. This paper introduces this research agenda on the boundaries of spatial economics, the economics of cities, information economics, institutional economics and technological change.
Joint Bayesian Spatial Inversion of Lithology/fluid Classes, Petrophysical Properties and Elastic Attributes

Summary We consider joint prediction of lithology/fluid classes, petrophysical properties and elastic attributes in a Bayesian spatial framework based on a set of geophysical observations. A probabilistic model accounting for both vertical and lateral spatial dependency is proposed based on a Markov random field prior model for the lithology/fluid classes. We discuss in specific the rock physics model for the elastic attributes, which is well-known to be multimodal and skewed due to the presence of different lithology/fluid classes and saturation effects of the subsurface. The posterior model is assessed by an efficient Markov chain Monte Carlo algorithm. The proposed workflow is demonstrated on a Norwegian Sea gas discovery, with realistic spatial continuity in the predictions.
A conversation around the design and experience of artifacts

column Share on A conversation around the design and experience of artifacts Authors: Nick Dulake Sheffield Hallam University Sheffield Hallam UniversityView Profile , Eva Hornecker Bauhaus-Universität Weimar Bauhaus-Universität WeimarView Profile , Daniela Petrelli Sheffield Hallam University Sheffield Hallam UniversityView Profile Authors Info & Claims InteractionsVolume 26Issue 5September-October 2019 pp 52–57https://doi.org/10.1145/3344941Published:22 August 2019Publication History 0citation652DownloadsMetricsTotal Citations0Total Downloads652Last 12 Months197Last 6 weeks39 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Investigating Mobile Banking in Mali: HCI Experience of ‘Man in the Street’

Many studies investigating the use of mobile banking in developing countries focus on specific user groups (i.e., illiterates, low- and semi-literates, the unbanked, and/or poor, rural and underserved communities). Therefore, existing literature fails to provide understandings about mobile banking use in the developing world from a general perspective. In this paper, we report on a study conducted in Mali to understand the use of a mobile banking service. In total, 77 people coming from different neighborhoods of Bamako and exercising a large spectrum of jobs participated in the study. The paper sheds light on the use of mobile phone and mobile banking in Mali; suggests additional features, particularly related to communication, for the mobile banking service; and discusses findings that are of relevance for Human-Computer Interaction for Development (HCI4D) in general.
Strategic Constructions of Diversity in Blame Games Surrounding the Overvaal Furore

This article critiques the appropriation of diversity in blame games surrounding the Hoërskool Overvaal (Overvaal High School) controversy that seized media attention in January 2018. Relying on discourse analysis, the study builds on previous research into the discursive practices that structure the imputation of blame for social problems emanating from politically controversial events. For sampling, the study draws from a corpus of nineteen journalistic opinion pieces published by online news sites in reaction to conflict at Overvaal. Its examination unravels a particular construction of diversity in blame games around Overvaal by focusing on an exemplar that narrows the value diversity to two dimensions: the non-racialism achieved through cross-racial contact, and linguistic diversity as conducive to long-term advantages in the labour market. To advance these goals, the study theorises blame as a social practice that involves argumentation. Authors make propositions about blame-worthy individuals or groups, prior to substantiating these claims with reasons. Claims and reasons are bridged by underlying modes of reasoning that may involve taken-for-granted assumptions about social values, such as diversity. As one way of addressing the risk that such values can be reduced to floating signifiers, the study critically assesses a prominent pattern in the way diversity is constructed.
Effectiveness of Power Point Media in 4 Seasons as the Sakura Culture Festival

Culture festival of the cherry country or what is called the "Matsuri" has many and varied, that is why in every place in Japan has its own cultural festival.The Japanese cultural festival has high values for its visitors or we can conclude that the Japanese cultural festival is an activity of exchange of values to uphold the customs of their existence.Japanese cultural festivals follow the 4 seasons in Japan, namely spring (haru), summer (natsu), autumn (aki) and winter (fuyu).These 4 seasons are a technology for Japanese people and are very influential in their cultural festivals.Many festivals occur and follow the 4 seasons in Japan, and the most interesting, with the emergence of the most popular festivals, and only occur every season, namely the spring festival hanami (haru), the summer festival tanabata (natsu), momiji festival in the autumn (aki) and Sapporo festival in winter (fuyu).In this research, researchers will discuss Japanese culture festivals that affect 4 seasons in Japan.Where the researchers will introduce it through existing power point slide media.In this research, the effectiveness of power point slide media in 4 seasons as Sakura's cultural festival, will use qualitative research methods, namely a contextual study that makes humans as instruments, and adapted to a reasonable situation in relation to data collection which is generally qualitative.This research took place at the Manado State Polytechnic Department of Business Administration.Sources of data are primary, namely data taken directly at the student.While secondary data is a literature study and Japanese language curriculum.Data collection techniques are observation and research questionnaire.The data analysis technique is an effort to systematically search and organize the results of observations and dissemination of questionnaires to improve researchers' understanding of the findings based on the problems studied.The results of this study are research instruments in the form of questionnaires with 9 questions, 3 options given 1 -3 and number of respondents 143 people.Each item gets the highest score, and the result = 3 × 9 × 143 = 3861.For the highest score that is = 3, with the number of items = 9 How to cite this paper:
Deep Speaker Embedding for Speaker-Targeted Automatic Speech Recognition

In this work, we investigate three types of deep speaker embedding as text-independent features for speaker-targeted speech recognition in cocktail party environments. The text-independent speaker embedding is extracted from the target speaker's existing speech segment (i-vector and x-vector) or face image (f-vector), which is concatenated with acoustic features of any new speech utterances as input features. Since the proposed model extracts the speaker embedding of the target speaker once and for all, it is computationally more efficient than many prior approaches which estimate the target speaker's characteristics on the fly. Empirical evaluation shows that using speaker embedding along with acoustic features improves Word Error Rate over the audio-only model, from 65.7% to 29.5%. Among the three types of speaker embedding, x-vector and f-vector show robustness against environment variations while i-vector tends to overfit to the specific speaker and environment condition.
The Augmented Laboratory – a mixed reality setup for physics education

Abstract We discuss an educational project, The Augmented Laboratory, aimed to bring innovation in educational physics laboratories in formal and informal contexts. It is based on the capability of obtaining 3D reconstructions of the physical world which can be visualized both live as the data is acquired and later on as interactive playbacks. The setup allows to obtain 3D tracking of multiple objects, to project data of interest directly on and around the objects used in a real experiment, and to introduce the new concept of “augmented experiments”. The setup was tested with a group of university students and as a scientific exhibit for hands-on activities.
Text Mining and Big Textual Data: Relevant Statistical Models

A general overview is provided through examples and case studies, retrieved from research experiences, to foster description and debate on effectiveness in Big Data environments. At issue are early stage case studies relating to: research publishing and research impact; literature, narrative and foundational emotional tracking; and social media, here Twitter, with a social science orientation. Central relevance and importance will be associated with the following aspects of analytical methodology: context, leading to availing of semantics; focus, motivating homology between fields of analytical orientation; resolution scale, which can incorporate a concept hierarchy and aggregation in general; and acknowledging all that is implied by this expression: correlation is not causation. Application areas are: quantitative and also qualitative assessment, narrative analysis and assessing impact, and baselining and contextualizing, statistically and in related aspects such as visualization.
Rating Assessment of Students' Knowledge vis-a-vis Rating Evaluation of University Teachers

This chapter focuses on the problem of assessing the quality of higher education. It has been identified that the quality assessment of higher education consists of external and internal assessment of educational services quality. External assessment of educational services quality is carried out by all economic entities that are consumers. Internal assessment of educational services quality should be carried out by the university itself. For these purposes, the university develops a quality management system and organizes a department responsible for organizing and monitoring the quality of educational services. Internal assessment of educational services quality includes such parameters as the quality of student training and the quality of teaching at university. A rating assessment of students' knowledge is developed at university to control the quality of students' training. A rating assessment of the university academic staff is carried out to maintain the quality of teaching.
Reversible Data Hiding on the Basis of Dynamic Prediction Strategy

A dynamic programming predictor (DPP) has been used in reversible information hiding schemes to produce high capacity. That can embed of medical information into medical images by the dynamic programming scheme. The medical information includes medical case of illness, and personal information of illness. To use the dynamic programming predictor scheme to calculate the number of combinations of pixels arranged of predicting pixel value. To generate histogram and find two high and zero point pairs of difference values and use two high point pair to embed into information about medical treatment. When every time choice for the amount of the highest embedding information, and the total amount will be embedded in the largest amount of embedding information in the final levels. In our propose algorithm of dynamic programming methods does not spend many times in embedding medical information. In addition, that can avoid overflow or underflow problem in embedding medical information. The experimental results show that have the highest capacity in our algorithm and PSNR about 48dB of embedding medical information in the level one.
Analysis of Chinese Zither Modes Based on Finite Element Analysis

Abstract This paper makes a modal analysis of Chinese zither by using the finite element analysis method. By combining traditional Chinese national musical instruments with computer simulation technology, it studies the modal structure of Chinese zither according to the method of “data model - establishing FEM model - assigning material parameters - establishing constraints - solving the case”. Through modal analysis, it not only verifies the validity of computer simulation method, but also provides data support and theoretical support for the improvement of Chinese zither structure and the structural research of traditional Chinese plucked instruments.
Research on the Private Customized Information Retrieval based on Hadoop Cluster

Abstract With the development of science and technology, it is no longer a technical difficulty for users to find the answers they need from massive data of information retrieval. At present, with information retrieval methods, the most urgent need is how to find personalized search results that satisfy users and meet their needs. Therefore, private customized information retrieval technology has great research value. This paper builds a Hadoop distributed cluster search engine, improves the PageRank algorithm, adds classified attributes such as user tone, and further classifies and ranks the web pages. At the same time, the C4.5 algorithm is used to classify users, thus it provides private customized search service. Through comparative experimental analysis, it is proved that the improved method proposed in this paper is effective and has profound research value.
Predicting Sentiment in Yorùbá Written Texts: A Comparison of Machine Learning Models

Sentiment Analysis (SA) provides a rich set of tools and techniques for extracting, evaluating subjective information from large dataset. Users opinions concerning an event are what determines the user perspective of such event whether it is good or bad. This study compared three machine learning models (Logistic Regression, Naïve Bayes and Support Vector Machine) with a view to identifying the best model for predicting sentiment in Yorùbá written texts at sentence-level. Corpus of Yorùbá records was created from several online and offline sources such as dictionaries, experts, Bible, social media as well as awayoruba blog and processed using Tákàdá. The system was implemented using the Python programming language and evaluated using mean opinion score and receiver operating characteristics. The research concludes that Naïve Bayes (NB) outperforms other algorithm for analysis of sentiments for Yorùbá sentences.
SSUP-Growth: A Novel Mining High Utility Algorithm Itemset with Single-Scan of Database

Abstract High Utility Itemset Mining (HUIM) alludes to the identification of itemsets of high utility in the value-based database UP-Growth algorithm is a standout amongst the best algorithms for overcome the challenge of candidate generation and scan database reputedly of previous algorithms. However, it needs scan database twice to actualize the UP tree. Regarding of the updating existing data with new information, UP-growth needs for twofold scanning of new information and existing information. The fundamental motivation behind this work is to build up another algorithm, Single-Scan Utility Pattern Tree (SSUP-tree), for mining high utility itemsets from transaction database through only single-scan of database. In our algorithm, the details of high-utility itemsets is preserved in a particular data structure of the SSUP-Tree after a single-scan of database. Consequently, it can retrieve the identical UP-tree with a fixed minimum utility threshold. The proposed algorithm required to scan the new data only to update SSUP-tree. In this regard, in order to estimate the execution of the proposed algorithm, the SSUP-tree algorithm has been implemented on synthetic and real datasets. The results of this study revealed that SSUP-tree shows a significant enhancement in the execution in terms of runtime since it keeps the huge databases details in a compact format and it avoids repetition of database scanning.
PHENOMENON OF THE QUALITY OF EDUCATION: THE BAROQUE EPOCH

The paper reviews recent approaches to the evaluation of education quality. The critical view of education quality in Ukraine today and its phenomenal success in the age of baroque is represented. Considerations for characteristic features of the education philosophy are founded on the analysis of Ukrainian and foreign authors’ works. The conclusions concerning the reasons of the complications with the correct approach to evaluation of education quality on one hand and disadvantages of highly specialized education and its consequences on the other, outline the main issues of the article. The phenomenon of education quality of baroque age was reviewed from the position of the European educative system of Septem Artes Liberales. The Kyiv Mohyla Academy in XVII–XVII centuries was chosen as the most specifically Ukrainian historical example. The article indicated the importance of the formation of kinship of ideological foundations in the environment of educated aristocracy and the problems of both assessment of education quality and the degree of conformity of education to different social requirements. The comparison of cooperation of nowadays and baroque epoch erectors (as the architect and the customer) confirms big gap in their worldviews. Baroque’s education, its phenomenon, or rather the phenomenon of its quality, and calling things in terms of the industrial age – efficiency and effectiveness, is the topic with enormous practical potential in terms not only and perhaps not so much of the historical point of view, when the purpose of the researcher is to study the past in search of «white spots», but also in terms of searching for the ways of preparing the successful «golden age» educators. The model suggested is suitable for realisation in modern Ukrainian education process.
Global Currencies and Domestic Regulation: Embedding through Enabling?

This article identifies cryptocurrencies and other virtual currencies as global currencies that could have a major impact on national jurisdictions. Regulation concerning cryptocurrencies can be described in the terms of the ‘double movement’ that Karl Polanyi identified for the expansion of the market society in the 19th and 20th centuries. Cryptocurrencies have been developed by anti-establishment individuals and groups, and other opponents of the global financial system that – in Polanyi’s terms – belong to a collectivist counter-movement. The effect they have produced, though, is rather to expand global markets and the market system. This has spurred a counter-movement to the counter-movement, or what could be called the ‘anti-countermovement.’ The response of the anti-countermovement to the expansion and influence of the global currencies is paradoxical if not schizophrenic. The anti-countermovement treats global currencies both as currencies and as a technology. This has led to various regulatory measures in different jurisdictions. When viewed as currency, cryptocurrencies are regulated both as money and commodities leading to an indifferent approach to their regulation or a command-and-control approach or various intermediate approaches. When viewed as a technology, different jurisdictions have taken an enabling approach to the regulation of cryptocurrencies by establishing ‘innovation hubs’ and ‘regulatory sandboxes’ for FinTech companies. This paper concludes by discussing the dangers of embedding cryptocurrencies through enabling them, namely the problem of more finance, and possibly an internal clash of domestic agencies. The way to mitigate the dangers of embedding through enabling is by regulating the new cryptocurrency intermediaries.
ZenCam: Context-Driven Control of Autonomous Body Cameras

In this paper, we present - ZenCam, which is an always-on body camera that exploits readily available information in the encoded video stream from the on-chip firmware to classify the dynamics of the scene. This scene-context is further combined with simple inertial measurement unit (IMU)-based activity level-context of the wearer to optimally control the camera configuration at run-time to keep the device under the desired energy budget. We describe the design and implementation of ZenCam and thoroughly evaluate its performance in real-world scenarios. Our evaluation shows a 29.8-35% reduction in energy consumption and 48.1-49.5% reduction in storage usage when compared to a standard baseline setting of 1920×1080 at 30fps while maintaining a competitive or better video quality at the minimal computational overhead.
Reimagining vision with infinity mirrors

This paper studies the possibility of interfacing motion control of an infinity mirror by using viewer eye tracking and the advantages and drawbacks of such an interface.
Visual Ontology Sketching for Preliminary Knowledge Base Design

Knowledge base is an important component of intelligent system and the main part of an expert system. Nowadays ontologies become a mainstream technology in knowledge base design. This technology helps to represent knowledge in the form of concepts, their properties, and axioms. Ontology is relevant not only for developers but also for managers, sponsors of the project, domain experts, and future users. Our analysis of successful ontology-based diagrams shows that visual sketching reveals the main concepts and the relations between them in informal way that helps to catch the main idea, the essence of the domain knowledge. The research analysis of the visual sketching method was performed using the semiotic approach. The paper contributes to the discussion on the influence of visual ontology diagrams on user’s perception and understanding. It highlights the features which allow making ontology conceivable and suitable for the better human interpretation and communication. It suggests considering aesthetic and ergonomic characteristics of ontology as supplements to countable ones.