Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced quaternion matrix-based sparse representation and its application to colour image processing

The traditional colour image sparse models ignore the relationship among the three separate colour channels. The authors propose a novel colour image sparse model by employing reduced quaternion matrix, which can treat independent colour channels as a whole. In addition, reduced quaternion matrix singular value decomposition is employed to design the corresponding dictionary learning algorithm. To make the proposed model robust and tractable, a reduced quaternion split Bregman iteration is developed to solve the minimisation problem. The proposed model cannot only preserve inherent colour structures but also avoid hue bias issue efficiently. Extensive experiments on colour image de-noising, in-painting, and super-resolution manifest that the proposed sparse representation model outperforms the state-of-the-art schemes.
ShieldStore: Shielded In-memory Key-value Storage with SGX

The shielded computation of hardware-based trusted execution environments such as Intel Software Guard Extensions (SGX) can provide secure cloud computing on remote systems under untrusted privileged system software. However, hardware overheads for securing protected memory restrict its capacity to a modest size of several tens of megabytes, and more demands for protected memory beyond the limit cause costly demand paging. Although one of the widely used applications benefiting from the enhanced security of SGX, is the in-memory key-value store, its memory requirements are far larger than the protected memory limit. Furthermore, the main data structures commonly use fine-grained data items such as pointers and keys, which do not match well with the coarse-grained paging of the SGX memory extension technique. To overcome the memory restriction, this paper proposes a new in-memory key-value store designed for SGX with application-specific data security management. The proposed key-value store, called ShieldStore, maintains the main data structures in unprotected memory with each key-value pair individually encrypted and integrity-protected by its secure component running inside an enclave. Based on the enclave protection by SGX, ShieldStore provides secure data operations much more efficiently than the baseline SGX key-value store, achieving 8--11 times higher throughput with 1 thread, and 24--30 times higher throughput with 4 threads.
Object Tracking by Unified Semantic Knowledge and Instance Features

Instance features based deep learning methods prompt the performances of high speed object tracking systems by directly comparing target with its template during training and tracking. However, from the perspective of human vision system, prior knowledge of target also plays key role during the process of tracking. To integrate both semantic knowledge and instance features, we propose a convolutional network based object tracking framework to simultaneously output bounding boxes based on different prior knowledge as well as confidences of corresponding Assumptions. Experimental results show that our proposed approach retains both higher accuracy and efficiency than other leading methods on tracking tasks covering most daily objects. key words: object tracking, convolutional neural networks, bounding box regression
Mobile or hostile? Using smartphones in learning English as a foreign language1

Abstract The purpose of this paper is to investigate the views of freshmen on using their smartphones in learning English as a foreign language. The study was designed based on a quantitative associational model. The data were collected from the 428 freshmen attending the English preparation programs run at İnönü and Fırat Universities, Turkey, using “Smartphone Use in Learning Foreign Language Scale”. The results showed that participants use their smartphones more frequently to engage in English listening and speaking activities than reading and writing activities. The participants also believe that smartphones scarcely have adverse effects on learning English. However, it was also found that the more time students spend online, the more they suffer from the adverse effects of smartphones in terms of language learning. Results about gender revealed that female students use their smartphones more frequently than their male peers to engage in formal language learning activities. Significant differences related to frequency of smartphone use for both formal and informal language learning purposes were detected, with the Business Administration and Molecular Biology and Genetics department students showing higher frequency. No statistically significant difference was found between students’ views about using smartphones for language learning according to the types of Internet connection (Wi-Fi, mobile data, or both).
A Two-Level Rolling Optimization Model for Real-time Adaptive Signal Control

Recently, dynamic traffic flow prediction models have increasingly been developed in a connected vehicle environment, which will be conducive to the development of more advanced traffic signal control systems. This paper proposes a rolling optimization model for real-time adaptive signal control based on a dynamic traffic flow model. The proposed method consists of two levels, i.e., barrier group and phase. The upper layer optimizes the length of the barrier group based on dynamic programming. The lower level optimizes the signal phase lengths with the objective of minimizing vehicle delay. Then, to capture the dynamic traffic flow, a rolling strategy was developed based on a real-time traffic flow prediction model. Finally, the proposed method was compared to the Controlled Optimization of Phases (COP) algorithm in a simulation experiment. The results showed that the average vehicle delay was significantly reduced, by as much as 17.95%, using the proposed method.
Conditional progressive network for clothing parsing

Clothing parsing is significant to many clothing applications. Recently, a lot of clothing parsing methods have been presented, which explore the innovation of the parsing pipeline or try to find more specific prior information. Although these methods perform well in some benchmarks, a few challenging problems have not been solved yet, such as the complicated mutual interference among labels. In this study, the authors propose a Conditional Progressive Network to parse clothing in different scales and prevent the mutual interference among labels. The authors’ solution consists of three sub-networks, including Conditional Parsing Network (CPN), Pose Estimation Network (PEN) and Label Transform Network (LTN). Specifically, the CPN module generates the intermediate parsing result in the form of the multiple progressive stages, which combines with the previous outputs in each stage and the specific prior conditions. The PEN module provides a series of heat maps about the human pose information. The LTN module suppresses the redundant labels to avoid the mutual interference among labels. They demonstrate their solution in parsing the fashion clothing cases on the ATR and the Fashion dataset. In their experiments, their method obtains a better performance than the state-of-the-art methods.
Fiscal Decentralization Dilemma in Indonesia: Between Corruption Accountability and Probability at Local Levels

Decentralization in Indonesia is an unfinished reform and to date, its implementation has not been maximized especially fiscal decentralization. This study aims to investigate the dilemma of fiscal decentralization in Indonesia, between accountability and the probability of corruption at the local level. Data collection in this research is in the form of documentation study to collect secondary data. Secondary data, this study will rely on documentary analysis of official documents from government, NGOs and news items from the media. For data analysis, the study will run analysis processes such as coding, combining emerging codes into themes, verifying themes through theory and follow-up interviews, and drawing conclusions. Whereas the validity mechanism applies member checks, triangulation, multiple sources of data, and looking for counterexamples. This research empirically found that the implementation of fiscal decentralization in Indonesia not only had a positive impact on the financial accountability of local governments but also had a positive impact on the occurrence of corruption in local governments. This means, fiscal decentralization is like two sides of a coin, on the one hand, it is able to increase the financial accountability of local governments, but on the other hand the greater the balance of funds provided by the central government to the regions, the higher the probability of corruption in local governments. Therefore, the supervision of the implementation of fiscal decentralization in order to create good financial governance and minimize corruption in the local government body in Indonesia.
Fog-Computing-Based Heartbeat Detection and Arrhythmia Classification Using Machine Learning

Designing advanced health monitoring systems is still an active research topic. Wearable and remote monitoring devices enable monitoring of physiological and clinical parameters (heart rate, respiration rate, temperature, etc.) and analysis using cloud-centric machine-learning applications and decision-support systems to predict critical clinical states. This paper moves from a totally cloud-centric concept to a more distributed one, by transferring sensor data processing and analysis tasks to the edges of the network. The resulting solution enables the analysis and interpretation of sensor-data traces within the wearable device to provide actionable alerts without any dependence on cloud services. In this paper, we use a supervised-learning approach to detect heartbeats and classify arrhythmias. The system uses a window-based feature definition that is suitable for execution within an asymmetric multicore embedded processor that provides a dedicated core for hardware assisted pattern matching. We evaluate the performance of the system in comparison with various existing approaches, in terms of achieved accuracy in the detection of abnormal events. The results show that the proposed embedded system achieves a high detection rate that in some cases matches the accuracy of the state-of-the-art algorithms executed in standard processors.
Pushing the Limits of Increased Casino Advantage on Slots: An Examination of Performance Effects and Customer Reactions

This field study examined performance data from reel slot games located in two casinos. The paired design incorporated games that appeared identical to the players but featured substantially different, yet concealed, pars (i.e., prices). The results revealed significantly elevated revenues for the high-par games, despite egregious price hikes, while also failing to provide compelling evidence of rational play migration to the low-par games. The latter result suggested that frequently visiting players were not able to detect differences in the pars of games, even over lengthy sample periods. These outcomes were produced by the greatest par gaps of any paired-design study. These expanded gaps also generated the greatest revenue gains within this research stream. Increasing pars may represent a rare opportunity for operators to increase revenues, without concern for eventual brand damage or loss of market share. Limitations regarding the current uses of reel pars are also revealed.
Virtual full-duplex relaying in multi-hop DF cooperative networks using half-duplex relays with buffers

In this study, the authors propose a novel virtual full-duplex relaying scheme, which is referred to as centre-partition max-link relaying by using buffer-aided half-duplex relays for multi-hop decode-and-forward cooperative networks. In the proposed scheme, they aim to select two independent available links for data packet transmission in the same time slot, which, in turn, improves the overall performance of the system. By modelling the evolution of buffer state transition as a Markov chain, the performance of the system is analysed in terms of outage probability and end-to-end average packet delay. The state transition matrix of the Markov chain is constructed and its steady-state distribution is obtained to derive the outage probability. Numerical results demonstrate that the proposed scheme has a potential to provide significant outage performance with reduced average packet delay as compared to that of buffer-aided multi-hop decode-and-forward relaying networks using the conventional max-link scheme.
Hypertext Navigation — An Intrinsic Component of the Corporate Intranet

As organizations continue to transform traditional text into digital documentation for corporate intranets, the need to explore relationships among salient variables that facilitate human processing in these environments is essential. The current study was designed to inspect the relationships among a set of variables that focus on domain knowledge, learners' interest in topics, text comprehension, and the ability to navigate through the hypertext environment. The literature and our experiences facilitated the choice of these variables as critical to assisting user navigation. Sophisticated data analyses were performed to test relationships between the variables identified. Results demonstrated that higher amounts of domain knowledge, as opposed to interest in the computerized medium, lead to increased flexibility in navigating through the medium. Additionally, domain knowledge positively affected the comprehension of the text. Implications for hypertext comprehension and navigation are discussed in this paper.
Inter-Organizational Knowledge Management: A Comparison of Law Firms in Norway and Australia

Law firms represent an industry that seems very well suited to knowledge management investigation. Law firms are knowledge intensive, and the use of advanced technology may well transform these organizations in the future. This paper reports results from a survey of Norwegian law firms on the use of information technology to support inter-organizational knowledge management. Two predictors of IT support were significant: firm cooperation and knowledge cooperation. Inter-organizational trust was not a significant predictor. An identical survey was conducted in Australia where knowledge cooperation turned out to be the only significant predictor of IT support. Both in Norway and Australia, mainly software and systems such as word processing, electronic mail and legal databases were used. Australian law firms seem to use IT to a larger extent than Norwegian law firms, especially electronic mail, presentations, other law firms' web pages on the Internet, library system, law firm's own Intranet, document systems, and other law firms' web pages on extranets.
The Changing Profile of Information Systems Research: 1995–2000

There has been considerable debate in the literature about the status of Information Systems (IS) as an academic discipline, its progress and its survival. Often these critiques focus on two major themes: (a) the need to develop theoretical foundations for IS and (b) the rigor and relevance of IS research. This paper presents the results of investigating four popular IS journals from 1995–2000 to determine the research methodologies used in published articles. Comparing the results to earlier studies shows that IS research is reducing its focus on subjective/argumentative studies and increasing its focus on experiments, case studies, and field tests. Some IS professionals contend that this changing publication focus provides evidence that the information systems discipline is becoming more rigorous and mature. This study also provides insights relating to the ongoing discussion concerning rigor and relevance of IS research.
Facilitating Innovation through Knowledge Sharing: A Look at the Us Naval Surface Warfare Center-Carderock Division

One of the key reasons for engaging in knowledge management is to stimulate innovation in organizations. This would hopefully lead to new products and services in the e-business age. Through knowledge management, a knowledge sharing culture will emerge to foster better collaboration and communication through communities of practice. This paper looks at knowledge sharing techniques and metrics for facilitating innovation and then discusses an organization, the US Naval Surface Warfare Center, pondering the use of these techniques. An approach for knowledge sharing selection is then discussed in context with this organization
An Observational Study on Clinico-Pathological Analysis of Fistula- In Ano in a Tertiary Care Hospital

Fistula-in ano is an abnormal communication between the anal canal or rectum and perianal skin, which causes a chronic inflammatory response. The most common cause is nearly always by a previous ano-rectal abscess. This study was intended for a clinico-pathological analysis of fistula-in ano and their diagnostic and treatment modalities based on various demographic features and associated conditions. 150 patients were selected who were diagnosed as fistula-in ano admitted and underwent surgical interventions during December 2017 to June 2019. Data related to objectives of the study were collected and analysed. Patients belonging to the age group 31-50 constituted the majority (60%). There was male predominance with ratio of 2.4:1. Half (49.3%) of the cases had DM and 65.3% had perianal abscess before. Most fistula were low anal (80%). MRI Fistulogram was the most sensitive investigation. Fistulectomy was done in three-fourth (n-113, 75.3%). There was no complication in majority and most common complication observed was wound infection (15.3%). In majority (81.3%) of the cases the surgical wound healed by 4 weeks. There was statistically significant difference (p-0.001) in time taken to heal between diabetic and non-diabetic groups. Non-specific inflammation was the histopathology report in 146(97.3%) cases but Tuberculosis was seen in 2 cases.
Evaluating the Development of E-Government in Indonesia

This paper presents an analysis of the challenges for the development of electronic government (e-government) in Indonesia. The study mainly focuses on the implementation of e-government in the transaction stage. The type of e-government is discussed, the stage of e-government development is evaluated, and the progress of e-Indonesia initiative is assessed. There are various obstacles to the development of e-government in Indonesia including poor ICT infrastructure, inadequate human resources, lack of readiness among citizens to use e-government services, and unsupportive environment. Due to these challenges, it is recommended for the Indonesian Government to develop comprehensive programs and progress assessments which include technology, organization, citizen and environment dimensions to support the development of e-government.
“He didn’t know what he was doin’”: Student perspectives of a White teacher’s Hip-Hop class

In this article, I share findings from a research study about a high school Hip-Hop course in the United States and offer considerations toward informing culturally responsive teaching and decentering Whiteness in music education. I explored the experiences and perceptions of majority students of color in a Hip-Hop course taught by a White music educator who was largely inexperienced with Hip-Hop. I was curious to understand how the students saw their teacher, what they experienced as strengths and weaknesses of the course, and what they felt they took away from the experience. I designed the qualitative study employing elements of Hip-Hop musical practices (sampling and remixing), analyzed data informed by Hip-Hop vocal techniques (doubling and ad-libbing), and structured findings based on Hip-Hop aesthetic principles (flow and rupture). Overall, students appreciated the teacher’s acknowledgment of his lack of Hip-Hop experience and his ability to prioritize their perspectives and voices. They reported gaining valuable musical experiences in the course as well as developing cross-cultural competence to better understand their fellow students.
The struggle is real: Theorising community justice restructuring agonistically

This article is a novel use of the ‘agonistic framework’ – a theory of penal change developed in the US, which emphasises the role of hidden conflict – to analyse recent organisational reforms to probation in Scotland. It begins by drawing on recent empirical data to analyse the role of conflict between centralising and localist interests in driving these reforms. This is contrasted with a Scottish policy consensus over decarceration through diversion to community penalties, which despite broad support has been unsuccessful. To explain this contradictory situation, the article builds on recent agonistic literature on the exclusion of some conflicts from penal fields, adding new insights about the circumscription of smaller penal fields. It argues that together these factors serve to ‘crowd out’ debates necessary for substantive change. This new development of the agonistic framework helps explain Scotland’s lack of progress towards decarceration, with policy relevance for other smaller jurisdictions.
Context as co-creator in spiritual life stories: the contextual nature of South African adolescents’ spiritual identity development

ABSTRACT This study explored spiritual identity development in a sample of South African adolescents, by considering how the participants perceived and experienced their spirituality, as well as how these meaning-making experiences contributed to their identity development. Twelve adolescent participants were purposively sampled and participated in semi-structured interviews and reflective writing exercises. The themes that emerged from the analysis alluded to the importance of relationships and context. The roles of parents, peers, the educational environment, and geographical location were emphasised. Participants explored and committed to their spiritual identities through processes of personal reflection, discussion, and modelling. Spiritual development is thus a reciprocal and bidirectional process between the unique individual and context. Spiritual identity development is a fluid process that evolves and grows in connections and relationships with others. Personal, cultural, and contextual factors are thus important in the co-creation of individuals’ spiritual life stories.