Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryptocurrency platform ecosystem: a systematic literature review from information systems perspective

Cryptocurrency platform continues to attract public attention in recent times as an alternative payment platform. The platform forms a new ecosystem of different entities such as users, cryptocurrency exchange, wallet providers, miners and platform developers that are interacting together in a value. Information systems (IS) and other related fields’ scholars continue to explore the evolution of these emerging disruptive financial innovations. However, there is a lack of systematic overview that focus on the cryptocurrency platform ecosystem layer. Thus, the objectives of this work are: (1) to identify the number of published IS and other related fields researches that contributed to the ecosystem layer; (2) to determine the research methods and theories used in these published works; and (3) to suggest potential research opportunities in cryptocurrency. A systematic review following [1] and [2] guidelines was conducted to address these objectives. The review analyzes the existing literature published between the years of 2012 to 2017. This period was chosen because cryptocurrency phenomenon is a new field. The results of the review show that there is an inadequate utilization of IS theories and methods in reporting the previous findings. This paper presents and compares the contributions of IS and other IS related fields, scholars regarding the cryptocurrency ecosystem evolution. Finally, the paper concludes by discussing the implications for researchers and practitioners and outlining the potential open research opportunities.
Joint Modelling of Longitudinal and Survival Data with Applications in Heart Valve Data

markdownabstract__Abstract__ The heart is one of the most important organs in the entire human body. Specifically, it is a pump composed of muscle which pumps blood throughout the blood vessels to various parts of the body by repeated rhythmic contractions. The four heart valves determine the pathway of blood flow through the heart and they normally allow blood flow in only one direction through the heart. Moreover, they open or close incumbent upon differential blood pressure on each side. Specifically, the four valves are: the tricuspid valve, the pulmonary valve, the mitral valve and the aortic valve. Figure 1.1, represents graphically the heart anatomy. The blood flows from the right atrium to the right ventricle through the tricuspid valve. Thereafter, the blood flows through the pulmonary valve to the lungs, where oxygenation takes place. Next, the blood re-enters the heart into the left atrium, through the mitral valve into the left ventricle. Finally, it enters the aorta through the aortic valve. Another important part of the heart is the aortic root which connects the heart to the systemic circulation. Heart valve disease occurs when one or more valves are not functioning properly due to stenosis and/or regurgitation. Valve stenosis is the disease in which the opening of the valve is narrowed, while valve regurgitation or insufficiency is the leaking of the valve that causes blood to flow in the reverse direction during ventricular diastole. Echocardiography is an excellent tool to evaluate patients with suspected heart valve disease. All four valves can develop the diseases mentioned above, however, in this thesis we focus on the aortic valve which lies between the left ventricle and the aorta.
Erklärungsmodelle der Angst aus der Sicht der Biopsychologie und Pharmakopsychologie

: To understand the biological basis of anxiety, the following psychological aspects are discussed: The difference between "trait" and "state" anxiety, types of anxiety as related to knowledge about causes and consequences, anxiety as a chronological process involving coping strategies and different levels of responses. The lack of specificity is physiological indicators of anxiety is demonstrated by experiments based on electrodermal and cardiovascular responses. Among hormones, special emphasis is placed on the constellation between catecholamines and cortisol as being relevant for anxiety research. It is emphasized that configurations of hormone parameters may be more relevant predictors for anxiety than single response values, and the study of postoperative catecholamine and cortisol responses is used for demonstrating differences between patients in a high and low preoperative state of anxiety. Differences are observed only on the emotional and pain response levels, but not in physiological parameters. The neurophysiological model representing central nervous system substrates for anxiety is the behavioural inhibitory system described in the theory by Gray [17], and the most relevant transmitters noradrenaline, serotonin, and the GABA-system are discussed with regard to their relevance for anxiety in animal studies, in studies using provocation tests with pharmacological substances, and in clinical studies with anti-anxiety drugs. Experimental anxiety research in psychology is frequently characterised by significant interactions between many mediators of responses, in particular the type of stressor, the level of trait anxiety and other personality variables, and the type of substances used. It is concluded that stressors as well as drugs frequently do not specifically induce anxiety but may nonspecifically affect general arousal and may only be operating in certain groups and certain levels of stress intensity.
Inter-Relationship of PCOS with BMI, Obesity and Exercise.

Objective: Polycystic ovarian syndrome (PCOS) has emerged as a global women health problem affecting female from younger age to women of various age groups. The present study was undertaken to compile the data and to study parameters and to identify inter-relationship of parameters like BMI, obesity and exercise as contributing factor to PCOS. Aim was also to create awareness about PCOS amongst women from age groups ranging from 12-52. Methods: Project was conducted in Mumbai city across various schools, colleges, hospitals, etc. Questionnaire was designed and data distributed in respondents was collated from 994 female respondents and was analyzed statistically. Results: The study revealed that 22.33% of the respondents were reported positive for PCOS of which 23.87% respondents were obese against 18.52% in PCOS negative respondents.In PCOS positive respondents, 69.81% have BMI in the range 18-25, whereas PCOS negative respondents with BMI in the range of 18-25 is 60.8%. 75% of the PCOS positive respondents from all age groups did not follow any exercise regime and had sedentary life style. Conclusion: The study revealed that level of PCOS awareness was found to be low amongst the PCOS negative respondents. It was concluded that PCOS and BMI are highly interdependent. In our study, an interrelationship was observed between frequency of exercise and PCOS affliction.
Exploring roads less traveled: eye tracking in art

Eye-tracking technology provides valuable help to interdisciplinary collaboration between various domains, such as human-computer interaction, digital art and creative media, so as artistic creativity can be expressed and developed. In this paper we present (a) an overview of eye-tracking technology in art and (b) the first results of a digital art research project, entitled DiBaB, which were based on paintings made by vegetal dyes for the creation -via eye tracking technologyof new artworks. The result was experimentations with artworks that have made visible the invisible, becoming a window to artist’s mind.
ARTIFICIAL INTELLIGENCE AS A LOW-COST SOLUTION FOR MUSEUM VISIT
DIGITAL CONTENT ENRICHMENT: THE CASE OF THE FOLKLORE MUSEUM OF
XANTHI

Abstract. The on-demand content enrichment of an exhibition center visit is an active applied research domain. This work focuses on the exploitation of mobile devices as an efficient medium to deliver information related to an exhibit or an area within the exhibition center by utilizing machine learning approaches. We present YPOPSEI, an integrated system that formulates the information retrieval task as an image recognition mechanism, enabling visitors to simply capture an entity of interest in order to acquire information similar to a tour-guidance experience via their personal mobile devices. This scheme not only minimizes the additional infrastructure requirements, but additionally enhances the versatility in cases of exhibits topology alterations while still providing high accuracy in terms of image content recognition. Two hybrid approaches are developed that set Convolutional Neural Networks (CNNs) and Bags of VisualWords (BOVWs) to operate in a synergistic and cooperative manner. They are evaluated under real-world conditions on a client-server Web architecture system that experimentally operates within the premises of the Folklore Museum of Xanthi, Greece.
Development of Voxel Models Adjusted to ICRP Reference Children and Their Whole-Body Averaged SARs for Whole-Body Exposure to Electromagnetic Fields From 10 MHz to 6 GHz

New child voxel models that are adjusted to the International Commission on Radiological Protection (ICRP)’s reference values (1-, 5- and 10-yr-old children) have been developed. The whole-body averaged specific absorption ratios (WBA-SARs) of these child voxel models were calculated for the whole-body exposure conditions with the E-polarization and H-polarization plane wave incidence from 10 MHz to 6 GHz. The WBA-SARs are 40% to 60% higher for the child voxel models than for adult voxel models adjusted to the ICRP’s reference values (NORMAN and NAOMI). The WBA-SARs of the child voxel models exceed the basic restriction by at most 20% or 0.08 W/kg for the general environment when the incident power density is set to the reference level at each frequency of the ICNIRP’s RF safety guidelines.
A Model for Smart Vehicle Tracking: A Review

The ability to track vehicles is useful in many applications including security of personal vehicles, public transportation systems, fleet management and others. Furthermore, the number of vehicles on the road globally is also expected to increase rapidly. Therefore, the development of vehicle tracking system using the Global Positioning System (GPS), Global System for Mobile Communications (GSM) modem, General Packet Radio Service (GPRS) and Google or Open street map respectively is undertaken with the aim of enabling users to locate their vehicles in real time with ease and in a convenient manner. The system will provide users with the capability to track vehicle remotely through the mobile network. This project presents the development of the vehicle tracking system's server and client software. Specifically, the system will utilize GPS to obtain a vehicle's coordinate and transmit it using GSM modem to the user's phone through the mobile network. The system is divided into two parts which are the tracking and monitoring part. The tracking part consist of GPS and an android/IOS mobile phone for navigation purpose. The GPS will provide information about the location of the vehicle. After receiving the location data from the web server, the data is monitored by a personal computer. After processing the data, the location of the vehicle can be viewed on the map.
Improving disease surveillance: Sentinel surveillance network design and novel uses of Wikipedia

Traditional disease surveillance systems are instrumental in guiding policymakers’ decisions and understanding disease dynamics. The first study in this dissertation looks at sentinel surveillance network design. We consider three locationallocation models: two based on the maximal coverage model (MCM) and one based on the K-median model. The MCM selects sites that maximize the total number of people within a specified distance to the site. The K-median model minimizes the sum of the distances from each individual to the individual’s nearest site. Using a ground truth dataset consisting of two million de-identified Medicaid billing records representing eight complete influenza seasons and an evaluation function based on the Huff spatial interaction model, we empirically compare networks against the existing volunteer-based Iowa Department of Public Health influenza-like illness network by simulating the spread of influenza across the state of Iowa. We compare networks on two metrics: outbreak intensity (i.e., disease burden) and outbreak timing (i.e., the start, peak, and end of the epidemic). We show that it is possible to design a network that achieves outbreak intensity performance identical to the status quo network using two fewer sites. We also show that if outbreak timing detection is of primary interest, it is actually possible to create a network that matches the existing network’s performance using 42% fewer sites. Finally, in an effort to demonstrate the generic usefulness of these location-allocation models, we examine primary stroke center selection. We describe the ineffectiveness of the current self-initiated approach
The Internet Under Crisis Conditions: Learning from September 11

Although secondary to the human tragedy resulting from the September 11, 2001, attacks on the World Trade Center and the Pentagon, telecommunications issues were significant that day both in terms of damage (physical as well as functional) and of mounting response and recovery efforts. The Internet has come to be a major component of the nation’s (and the world’s) communications and information infrastructure. People rely on it for business, social, and personal activities of many kinds, and government depends on it for communications and transactions with the media and the public. Thus there is interest in how the Internet performed and was used on September 11. Unlike the situation with longer-standing telecommunications services (notably the public telephone network), there are few regulations, policies, or practices related to the Internet’s functioning in emergency situations. Nor are there many publicly available data to help policy makers or the industry itself assess the Internet’s performance — either on a continuing basis or in the aftermath of a crisis. No regular system exists for reporting failures and outages, nor is there agreement on metrics of performance. Some experiences are shared informally among network operators or in forums such as the North American Network Operators Group (NANOG), but that information is not readily accessible for national planning or research purpos es. The decentralized architecture of the Internet — although widely characterized as one of the Internet’s strengths — further confounds the difficulty of collecting comprehensive data about how the Internet is performing. It is therefore unsurprising that no definitive analyses exist on the impact of September 11 on the Internet, though a few conflicting anecdotal reports about its performance that day — such as several presentations at NANOG indicating relatively little effect and press accounts suggesting that the impact was severe — have appeared.
Nonlinear Equivariant Imaging: Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI

Current state-of-the-art reconstruction for quantitative tissue maps from fast, compressive, Magnetic Resonance Fingerprinting (MRF), use supervised deep learning, with the drawback of requiring high-fidelity ground truth tissue map training data which is limited. This paper proposes NonLinear Equivariant Imaging for MRF (NLEIMRF), a self-supervised learning approach to eliminate the need for ground truth for deep MRF image reconstruction. NLEI-MRF extends the recent Equivariant Imaging framework to the MRF nonlinear inverse problem. Only compressed-sampled MRF scans are used for training. NLEI-MRF learns tissue mapping using spatiotemporal priors: spatial priors are obtained from the invariance of MRF data to a group of geometric image transformations, while temporal priors are obtained from a nonlinear Bloch response model approximated by a pre-trained neural network. Tested retrospectively on two acquisition settings, we observe that NLEI-MRF closely approaches the performance of supervised learning.
Online Federated Learning via Non-Stationary Detection and Adaptation Amidst Concept Drift

Federated Learning (FL) is an emerging domain in the broader context of artificial intelligence research. Methodologies pertaining to FL assume distributed model training, consisting of a collection of clients and a server, with the main goal of achieving optimal global model with restrictions on data sharing due to privacy concerns. It is worth highlighting that the diverse existing literature in FL mostly assume stationary data generation processes; such an assumption is unrealistic in real-world conditions where concept drift occurs due to, for instance, seasonal or period observations, faults in sensor measurements. In this paper, we introduce a multiscale algorithmic framework which combines theoretical guarantees of FedAvg and FedOMD algorithms in near stationary settings with a non-stationary detection and adaptation technique to ameliorate FL generalization performance in the presence of concept drifts. We present a multi-scale algorithmic framework leading to <inline-formula> <tex-math notation="LaTeX">$\tilde {\mathcal {O}} (\min \{ \sqrt {LT}, \Delta ^{({1}/{3})}T^{({2}/{3})} + \sqrt {T} \})$ </tex-math></inline-formula> dynamic regret for <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> rounds with an underlying general convex loss function, where <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> is the number of times non-stationary drifts occurred and <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula> is the cumulative magnitude of drift experienced within <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> rounds.
Quality of Life of Patients with Diabetes Mellitus in a Nigerian Teaching Hospital

Objective: To assess the quality of life of patients with diabetes mellitus and to determine the clinical and sociodemographic factors that affect the quality of life of these patients. Patients and Methods: This was a cross-sectional study of 251 patients with diabetes mellitus attending the University of Ilorin Teaching Hospital, Nigeria. The World Health Organization quality of life instrument, short version and a sociodemographic questionnaire was administered to assess quality of life. Results: Most of the respondents performed fairly well on the World Health Organization quality of life instrument, short version. Poor quality of life was associated with some of the physical complications of diabetes mellitus, lower income, lower educational status, and type 2 diabetes mellitus. Conclusions: Lower income, lower education, low-rated employment, and physical complications adversely affect the quality of life of patients with diabetes mellitus. Such factors need to be addressed by caregivers and physicians managing these patients.
Creating Collaborative Learning Environments: A Curriculum Proposal for Instructors

An abstract of the thesis of Carol Rae Chislett for the Master of Science in Education: Educational Policy, Foundations, and Administrative Studies presented November 7, 1996. Title: Creating Collaborative Learning Environments: A Curriculum Proposal for Instructors. Groups of students or employees working together to solve problems, gain conceptual understanding, or create new approaches are expected to yield results significantly better than when working individually. Classroom collaboration leads to increased learning and retention, improved interpersonal skills, and enhanced appreciation for and commitment to the educational process. With the increased discussion of its benefits, there is more emphasis on including collaboration in the classroom. The challenge for today's faculty and students is to learn what their roles and expectations are in the successful collaborative environment. The purpose of this study was to design a curriculum for instructors in techniques for creating collaborative environments. In 2 addition to reviewing the current literature to learn about collaborative environments in the college classroom, instructors were interviewed to learn about their experiences and successes with collaborative learning. Information from the literature review and the faculty interviews were used to propose the curriculum. Principles of collaborative learning evident through the literature and the interviews are that it requires trust, development of relationships, conversation, incorporating differences, the teacher as learner, and students be responsible for their own learning. The instructor must be able to create that environment by teaching social and collaborative skills, being willing to self-disclose, assessing where students are and by taking care of technical tasks such as preplanning, assigning students to groups, designing collaborative activities and evaluating results of the collaborative process, the group's product and the individual's contribution. Caffarella's (1994) interactive model for program development provided the structure for the development of the curriculum. Through the application of the model, curriculum ideas were explored and narrowed into the development of the program objectives. Transfer of learning activities incorporated into the curriculum are reliant upon intense practice of collaborative skills throughout the course. The learning is experiential. The curriculum includes objectives, instructional plans, evaluation plan and questionnaire, and proposed assignments. Proposed as a traditional ten-week course, it is intended as a generic example of the course format. Depending upon the context in which the course occurs and its audience, it may be formatted to fit a weekend workshop or other teacher oriented format. 3
Testing the Distinctiveness of Intonational Tunes: Evidence from Imitative Productions in American English

Understanding the structure of intonational variation is a longstanding issue in prosodic research. A given utterance can be realized with countless intonational contours, and while variation in prosodic meaning is also large, listeners nevertheless converge on relatively consistent form-function mappings. While this suggests the existence of abstract intonational representations, it has been unclear how exactly these are defined. The present study examines the validity of a well-defined set of phonological representations for the generation of intonation in the nuclear region of an intonational phrase in American English: namely, the combination of binary pitch accents (H*/L*), phrase accents (H-/L-), and boundary tones (H%/L%) proposed in Pierrehumbert (1980). In an exploratory study, we examined whether speakers maintained the eight-way distinction among intonational contours posited to exist in this representational system. We created eight synthesized contours according to Pierrehumbert (1980) and examined whether listeners generalized these contours to novel productions. Speakers largely distinguished rising from nonrising contours in production, but few other distinctions were maintained. While this does not rule out the existence of additional contours in production, these findings do suggest that the representation of rising and non-rising contours may be privileged and more readily accessible in the intonational grammar.