Reviewerly/exHarmony huggingface dataset:
The impact of personality traits and cultural values on coordination effectiveness: A study of software development teams effectiveness

Authors:
raw_author_name: Mohammad Shameem
raw_affiliation_string: Department of Computer Science and Applications MIT World Peace University Kothrud Pune Maharashtra India
raw_author_name: Chiranjeev Kumar
raw_affiliation_string: Department of Computer Science and Engineering Dhanbad Jharkhand India
raw_author_name: Bibhas Chandra
raw_affiliation_string: Department of Management Studies IIT (ISM) Dhanbad Dhanbad Jharkhand India
raw_author_name: Arif Ali Khan
raw_affiliation_string: M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland
raw_author_name: Mohammad Nadeem
raw_affiliation_string: Department of Computer Science Aligarh Muslim University Aligarh India
raw_author_name: Muhammad Azeem Akbar
raw_affiliation_string: Department of Software Engineering LUT University Lappeenranta Finland

Abstract: Abstract Software development projects depend on collaborative teams. In the past 50 years of research, various studies have explored the effect of software engineer's personality traits and cultural values on team performance. These studies have led to better understand these relationships; however, how the personality traits and cultural values influence the team effectiveness is still far away in the literature. This research aims to investigate the relationships between social and psychological complexities (including personality traits and cultural values), team coordination, team motivation, and team success (which comprises team effectiveness and team climate) to explore the impact of social and psychological issues on software team success. An online survey targeting software development professionals and unstructured interviews were followed for data collection. We received 112 responses from software developers working in different countries. Findings indicate that personality traits and cultural values, that is, consciousness, openness, harmony, and autonomy, have positive relationship with team coordination effectiveness, while other factors such as neuroticism, embeddedness, hierarchy, and mastery were found to be related negatively with it. These negative relationships can be mitigated by motivating team members appropriately. Based on our research findings, we conclude that the negative impact caused by different personality and cultural traits could be reduced by improving team coordination effectiveness using effective motivation.
A performance analysis of Basin hopping compared to established metaheuristics for global optimization

Authors:
raw_author_name: Baioletti, Marco
raw_affiliation_string: Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy
raw_author_name: Santucci, Valentino
raw_affiliation_string: Department of Humanities and International Social Sciences, University for Foreigners of Perugia, Perugia, Italy
raw_author_name: Tomassini, Marco
raw_affiliation_string: Department of Information Systems, University of Lausanne, Lausanne, Switzerland

Abstract: During the last decades many metaheuristics for global numerical optimization have been proposed. Among them, Basin Hopping is very simple and straightforward to implement, although rarely used outside its original Physical Chemistry community. In this work, our aim is to compare Basin Hopping, and two population variants of it, with readily available implementations of the well known metaheuristics Differential Evolution, Particle Swarm Optimization, and Covariance Matrix Adaptation Evolution Strategy. We perform numerical experiments using the IOH profiler environment with the BBOB test function set and two difficult real-world problems. The experiments were carried out in two different but complementary ways: by measuring the performance under a fixed budget of function evaluations and by considering a fixed target value. The general conclusion is that Basin Hopping and its newly introduced population variant are almost as good as Covariance Matrix Adaptation on the synthetic benchmark functions and better than it on the two hard cluster energy minimization problems. Thus, the proposed analyses show that Basin Hopping can be considered a good candidate for global numerical optimization problems along with the more established metaheuristics, especially if one wants to obtain quick and reliable results on an unknown problem.
HABERTAN: Game Petualangan 3D Dengan Tema Pemilahan Sampah Sebagai Upaya Pendekatan Inovatif Untuk Pengenalan Lingkungan

Authors:
raw_author_name: Fony Revindasari
raw_affiliation_string: Politeknik Elektronika Negeri Surabaya

Abstract: The increasing awareness of the importance of maintaining forest cleanliness as a primary ecosystem is becoming more urgent, especially in remote areas with limited deep socialization. This research aims to develop an innovative game titled "HABERTAN" focusing on waste sorting in forest areas to raise public awareness of the waste present in the forest. By utilizing a 3D model for visual assets with stages of 2D sketch, 3D modeling, UV Mapping, and Texture Baking. The development of this game is conducted using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) method. The ADDIE method is used to ensure a systematic game development process, starting from needs analysis to performance evaluation. The goal of this game is to provide players with an interactive experience that not only entertains but also provides a deep understanding of the impact of waste on forest sustainability. The game "HABERTAN (Let's Clean the Forest)" is designed to provide players with a fun and educational learning experience. The results of the development of this game show that "HABERTAN" provides a unique experience for players, with the ability to learn while playing. It is hoped that this game can be an effective tool in raising public awareness of the importance of maintaining forest cleanliness, especially in the context of waste sorting. Through this innovative approach, it is hoped to encourage active participation from the community in preserving forests as extremely valuable natural resources.
Focus Realization in Heritage Spanish

Authors:
raw_author_name: Maria del Mar Vanrell

Abstract: We shed light on the question of how narrow information (F) and contrastive focus (CF) are intonationally and syntactically realized by heritage speakers (HSs) of Peninsular Spanish (PS) who have German as their second L1, and compare their data to those of monolingual speakers (MSs) of PS. Results from a production experiment show clear differences between the groups with respect to preferred syntactic strategies and, consequently, the intonational realization of focal pitch accents. The preferred strategy of HSs is stress shift, followed by p-movement and simple clefts, for both focus types. Conversely, MSs mostly use different strategies for each focus type; that is, pseudo-clefts and p-movement for F, and simple clefts and focus fronting for CF. Interestingly, stress shift is not a relevant option. The attested differences support the view that the interface between discourse on one hand, and syntax and phonology on the other, is challenging for bilingual speakers (Sorace, 2011).
Exploring the Security Vulnerability in Frequency-Hiding Order-Preserving Encryption

Authors:
raw_author_name: JiHye Yang
raw_affiliation_string: Department of Computer Software, Daegu Catholic University, Daegu, Republic of Korea
raw_author_name: Kee Sung Kim
raw_affiliation_string: Department of Computer Software, Daegu Catholic University, Daegu, Republic of Korea

Abstract: Frequency-hiding order-preserving encryption (FH-OPE) has emerged as an important tool in data security, particularly in cloud computing, because of its unique ability to preserve the order of plaintexts in their corresponding ciphertexts and enable efficient range queries on encrypted data. Despite its strong security model, indistinguishability under frequency analyzing ordered chosen plaintext attack (IND-FA-OCPA), our research identifies a vulnerability in its design, particularly the impact of range queries. In our research, we quantify the frequency of data exposure resulting from these range queries and present potential inference attacks on the FH-OPE scheme. Our findings are substantiated through experiments on real-world datasets, with the goal of measuring the frequency of data exposure resulting from range queries on FH-OPE encrypted databases. These results quantify the level of risk in practical applications of FH-OPE and reveal the potential for additional inference attacks and the urgency of addressing these threats. Consequently, our research highlights the need for a more comprehensive security model that considers the potential risks associated with range queries and underscores the importance of developing new range-query methods that prevent exposing these vulnerabilities.
Prediksi Harga Minyak Dunia Dengan Fuzzy Time Series

Authors:
raw_author_name: Besse Helmi Mustawinar
raw_affiliation_string: UNCP
raw_author_name: Yuliani Yuliani
raw_affiliation_string: Universitas Cokroaminoto Palopo

Abstract: The government uses economic growth as a metric to measure prosperity and the effectiveness of economic development. However, oil price fluctuations can increase inflation through increasing fuel prices and have an impact on the world economy, including Indonesia. This research will apply a fuzzy time series using the Cheng method to predict world oil prices. The results of this research show that the MAPE value for forecasting world oil prices using the Fuzzy Time Series Cheng method is 2%, which means the forecasting model has very good value.
How are texts analyzed in blockchain research? A systematic literature review

Authors:
raw_author_name: Felix Irresberger
raw_affiliation_string: Durham University Business School, Durham University, Mill Hill Lane, DH1 3LB, Durham, Germany

Abstract: Abstract This paper provides a systematic literature review of text analysis methodologies used in blockchain-related research to comprehend and synthesize existing studies across disciplines and define future research directions. We summarize the research scope, text data, and methodologies of 124 papers and identify the two most common combinations of these dimensions: (1) papers that focus on specific cryptocurrencies tend to apply sentiment analysis to instant user-generated content or news articles to discover the correlations between public opinion and market behavior, and (2) studies that examine the broad concept of blockchain with text data from documents published by companies tend to apply topic modeling techniques to explore classifications and trends in blockchain development. We discover five major research topics in the academic literature: relationship discovery, cryptocurrency performance prediction, classification and trend, crime and regulation, and perception of blockchain. Based on these findings, we highlight three potential research directions for researchers to select topics and implement suitable methodologies for text analysis.
Exploring Bitcoin dynamics against the backdrop of COVID-19: an investigation of major global events

Authors:
raw_author_name: Xiaochun Guo
raw_affiliation_string: School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China

Abstract: Abstract COVID-19 has significantly influenced global financial markets, including Bitcoin. Recent studies have focused on investigating the first wave of the COVID-19 outbreak and accounting for market changes, which were mostly due to the pandemic. This research not only analyzes the contagion effects of COVID-19 but also considers aftermath events beyond the first pandemic wave to examine spillovers of Bitcoin. The study employs Diebold and Yilmaz’s method to explore the static and dynamic spillovers of the selected variables and identifies several major global events, including crypto-specific affairs, macroeconomic policies, and geopolitical conflicts, to explain the new market dynamics of Bitcoin using network analysis. The findings identify a few high-contagion periods related to Bitcoin. The paper also found that Bitcoin is more likely to produce extreme returns and is more connected to other markets. Contagion effects “from” and “to” other markets are asymmetrical in terms of arrival time and market response. Bitcoin is more likely to be affected by other markets in extreme situations and receives spillovers from them sooner than it transmits spillovers to others. In the context of various global events, impacts arising from developed countries are stronger. China still has some impact on cryptocurrency markets, but they are waning. Bitcoin is thus not a safe haven from the shocks of global events, but can sometimes work as a hedge or diversifier. The results offer alternative explanations for Bitcoin’s different market dynamics and enrich our understanding of Bitcoin’s safe haven, hedge, and diversifier properties within a diversified portfolio.
The Implementation of Technique Used by Teacher to Develop Students’ Speaking Skill: A Case Study at Muhammadiyah University of Surakarta in 2023/2024

Authors:
raw_author_name: Endang Fauziati
raw_affiliation_string: Universitas Muhammadiyah Surakarta

Abstract: Techniques are a way to assist students to explore and increase their ability. This study aimed to describe (1) the classroom techniques used by teacher and their purposes, (2) the teacher’s role in implementing the techniques, and (3) the elements of speaking improved in implementing the techniques. This research used a case study qualitative method. The subjects are English teachers instructing third-semester speaking classes in the English Education Department at Muhammadiyah University of Surakarta in 2023/2024. The researcher used observation, interview, and documentation to collect the data. The result of the research showed that teachers used some techniques in teaching speaking, such as conversation drill, debate, role play, and presentation. Debate and conversation drill is mostly used by the English teachers in teaching and learning speaking. Teachers’ role in implementing technique in teaching speaking are as controller and tutor. Elements that need to be improved in implementing techniques in teaching speaking, namely fluency and accuracy, then grammar, vocabulary, and pronunciation. The implementation of conversation drill and debate technique as a teaching technique developed the students’ speaking performance in terms of accuracy dealing with acceptable pronunciation, correct grammar, and appropriate word choice as well as making possible chance to students to work cooperatively, brainstorm ideas, develop vocabulary, and read to support an opinion. The researcher suggests that teachers use various techniques as it encourages students in speaking
Advanced systems and technologies for the enhancement of user experience in cultural spaces: an overview

Authors:
raw_author_name: Sonia Capece
raw_affiliation_string: Department of Engineering, University of Campania "Luigi Vanvitelli", Aversa, CE, Italy
raw_author_name: Giovanna Giugliano
raw_affiliation_string: Department of Engineering, University of Campania "Luigi Vanvitelli", Aversa, CE, Italy
raw_author_name: Mario Buono
raw_affiliation_string: Department of Engineering, University of Campania "Luigi Vanvitelli", Aversa, CE, Italy

Abstract: Abstract Human–computer interaction, Artificial Intelligence, and the multilingualism of digital culture open up unexpected scenarios in the contemporary design of cultural spaces with the creation of artifacts in which the analogic and digital dimensions come together to enhance the experience. Sensors and devices track user movement in the real world and translate the inputs into commands through hand gestures, speech recognition, head movements, tangible interfaces, or a combination of these elements. Through theorical models, concepts and tools, the paper reports the evolution of “User Experience” applied to personalized enjoyment and use of cultural places. The functional-performance survey of tools and technologies for perception, narrative and augmented interaction revealed models that highlight the diversity and richness of tangible and intangible cultural heritage through new forms of interaction and knowledge transfer. In this direction, new technological tools make it possible to detect, track and evaluate the personalized user experience by processing or producing large amounts of data. Therefore, on one hand the paper explores the limitations dictated by data management and user privacy in using such systems and, on the other, it prefigures new scenarios for amplifying and personalizing the user experience.
Quantifying coherence via the generalized Wigner–Yanase–Dyson skew information

Authors:
raw_author_name: Y. J. Fan
raw_affiliation_string: School of Mathematics and Information Science, North Minzu University, Yinchuan 750021, P. R. China
raw_author_name: Z. H. Guo
raw_affiliation_string: School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, P. R. China

Abstract: Quantum coherence is an important feature that distinguishes quantum mechanics from classical physics. In this paper, we study the coherence of a quantum state with respect to a quantum channel, and introduce a coherence measure in terms of the generalized Wigner–Yanase–Dyson skew information. The basic properties and operational significance of the measure are expounded in detail, which shows that it is indeed a veritable quantity and satisfies many desirable conditions intuitively required for the coherence measures. We illustrate the significance of characterizing channels from the coherence perspective through some examples. Finally, we consider the average coherence of a state based on the generalized Wigner–Yanase–Dyson skew information with respect to any complete mutually unbiased bases in prime power dimensional systems, as well as with respect to all orthonormal bases, and show that these two averages are equivalent since they both can be seen as the coherence of the quantum state with respect to the depolarizing quantum channel.
The mediating effect of entrepreneurship on financial support and economic growth in African emerging economies

Authors:
raw_author_name: Sagheer Muhammad

Abstract: Purpose The aim of the research is to examine in depth the relationship between financial support, entrepreneurship and economic growth in emerging African economies. Design/methodology/approach The study adopts the system-generalized methods of moments (sys-GMM) technique for data analysis and hypothesis testing on a sample of 34 African emerging economies (340 observations) from 2010 to 2019. Findings The results show that there is significant positive correlation between financial support, entrepreneurship, and economic growth. Moreover, entrepreneurship served as a partial mediator between financial support and economic growth in African emerging economies. Practical implications This research suggests that African governments should focus on entrepreneurial systems, which are essentially networks driven by the pursuit of individual opportunities and the promotion of new business creation; and introduce other forms of financial assistance, such as loans, loan guarantees, interest subsidies, technical assistance, insurance, etc. Originality/value The main novelty of the paper is that the authors empirically investigate the mediating role of entrepreneurship in the association between financial support and economic growth in 34 African emerging economies.
Partial Reasons

Authors:
raw_author_name: Federico L. G. Faroldi
raw_affiliation_string: Center for Logic and Philosophy of Science Ghent University and Research Foundation, Flanders (FWO) Blandijnberg 2 9000 Ghent Belgium; Department of Law University of Pavia Corso Strada Nuova 65 27100 Pavia Italy; Institute of Computer Science University of Bern  Neubrückstrasse 10 3012 Bern Switzerland

Abstract: Abstract Partial reasons are considerations in favor of something that, taken individually, are not sufficient to establish an obligation. I consider the extent to which partial reasons are reasons, and why they cannot be reduced to or identified with pro tanto reasons. I lay out two approaches to the content of reasons, the flat theory and the structured theory. I argue that parts of reasons are not partial reasons, by showing that natural ways to represent parts of reasons in the flat theory and the structured theory lead to overgeneration problems with regard to partial reasons. I then formulate two notions of partial reasons: one based on a notion of partial support, which is in turn captured by the notions of full support and partial content, and one based on the notion of in exact verification. I show under which conditions the two notions of partial reasons (based on partial content, and based on inexact verification) coincide.
Hate speech detection: A comprehensive review of recent works

Authors:
raw_author_name: Ankita Gandhi
raw_affiliation_string: School of Cyber Security and Digital Forensic National Forensic Sciences University Ganhinagar Gujarat India
raw_author_name: Kinjal Adhvaryu
raw_affiliation_string: Computer Engineering Shankarsinh Vaghela Bapu Institute of Technology Ganhinagar Gujarat India
raw_author_name: Pooja Shah
raw_affiliation_string: School of Technology Pandit Dindayal Energy University Ganhinagar Gujarat India
raw_author_name: Erik Cambria
raw_affiliation_string: School of Computer Science and Engineering Nanyang Technological University Singapore Singapore
raw_author_name: Soujanya Poria
raw_affiliation_string: Singapore University of Technology and Design, Singapore University of Technology and Design Singapore Singapore
raw_author_name: Amir Hussain
raw_affiliation_string: Edinburgh Napier University Edinburgh Scotland

Abstract: Abstract There has been surge in the usage of Internet as well as social media platforms which has led to rise in online hate speech targeted on individual or group. In the recent years, hate speech has resulted in one of the challenging problems that can unfurl at a fast pace on digital platforms leading to various issues such as prejudice, violence and even genocide. Considering the acceptance of Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques in varied application domains, it would be intriguing to consider these techniques for automated hate speech detection. In literature, there have been efforts to recognize and categorize hate speech using varied Machine Learning (ML) and Deep Learning (DL) techniques. Hence, considering the need and provocations for hate speech detection we aim to present a comprehensive review that discusses fundamental taxonomy as well as recent advances in the field of online hate speech identification. There is a significant amount of literature related to the initial phases of hate speech detection. The background section provides a detailed explanation of the previous research. The subsequent section that follows is dedicated to examining the recent literature published from the year 2020 onwards. The paper presents some of the hate speech datasets considered for hate speech detection. Furthermore, the paper discusses different data modalities, namely, textual hate speech detection, multi‐modal hate speech detection and multilingual hate speech detection. Apart from systematic review on hate speech detection, the paper also implement several multi‐label models to compare the performance of hate speech detection by employing classic ML technique namely, Logistic Regression and DL technique namely, Long Short‐Term Memory (LSTM) and a multiclass multi‐label architecture. In the implemented architecture, we have derived two new elements to quantify the hatefulness and intensity of hatred to improve the results for hate speech detection using Indonesian tweet dataset. Empirical Analysis of the model reveals that the implemented approach outperforms and is able to achieve improved results for the underlying dataset.