Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Reference Architecture for the Portuguese Health Sector

The need to improve the information activities has been proved to be fundamental for the competitivity of all organizations. One of the identified ways to reach that goal is the creation of Information Reference Architecture (IRA) that enable the guidance and restriction of the instantiations of a set of individual architectures and solutions. In this work, we suggest a method of develop reference IA able to ensure an easy maintenance and the semantic interoperability. Such method follows a bottom-up approach and involves both the mapping of the main information systems in a certain sector of activity, and the use of reverse engineering, models enhancements and integration models techniques. The main contribution of the method resides in the model integration step, where a process enabling the identification of correspondent informational entities in different models, created following a set of similarity rules, is stressed. This methodology is instanced in the specific Portuguese Public Health Sector, culminating in the development of a reference IA for the sector. We used the Design Science Research Methodology to conduct our research. The method suggested in this work and the corresponding instantiation to the Portuguese Public Health Sector are assessed with the help of metric systems of IA and models.
Faster Approximate Lossy Generalized Flow via Interior Point Algorithms

We present faster approximation algorithms for generalized network flow problems. A generalized flow is one in which the flow out of an edge differs from the flow into the edge by a constant factor. We limit ourselves to the lossy case, when these factors are at most 1. Our algorithm uses a standard interior-point algorithm to solve a linear program formulation of the network flow problem. The system of linear equations that arises at each step of the interior-point algorithm takes the form of a symmetric M-matrix. We present an algorithm for solving such systems in nearly linear time. The algorithm relies on the Spielman-Teng nearly linear time algorithm for solving linear systems in diagonally-dominant matrices. For a graph with m edges, our algorithm obtains an additive epsilon approximation of the maximum generalized flow and minimum cost generalized flow in time tildeO(m^(3/2) * log(1/epsilon)). In many parameter ranges, this improves over previous algorithms by a factor of approximately m^(1/2). We also obtain a similar improvement for exactly solving the standard min-cost flow problem.
Quantifying Parallel Evolution

7 Parallel evolution is consistently observed across the tree of life. How8 ever, the degree of parallelism between replicate populations in evolution 9 experiments is rarely quantified at the gene level. Here we examine par10 allel evolution as the degree of covariance between replicate populations, 11 providing a justification for the use of dimensionality reduction. We ex12 amine the extent that signals of gene-level covariance can be inferred in 13 microbial evolve-and-resequence evolution experiments, finding that devi14 ations from parallelism are difficult to quantify at a given point in time. 15 However, this low statistical signal means that covariance between repli16 cate populations is unlikely to interfere with the ability to detect diver17 gent evolutionary trajectories for populations in different environments. 18 Finally, we find evidence suggesting that temporal patterns of parallelism 19 are comparatively easier to detect and that these patterns may reflect the 20 evolutionary dynamics of microbial populations. 21 Keywords— Experimental evolution, Microbial evolution, Parallel evolution 22
Static Detection of Event-based Races in Android

Event-based races are the predominant source of concurrency errors in Android apps. So far all the approaches for detecting event-based races have been dynamic. Due to their dynamic nature, these approaches suffer from coverage and false negative issues, and despite being dynamic they still have a high rate of false positives. We introduce a static approach and tool, named SIERRA, for detecting Android event-based races centered around a new concept of “concurrency action” (that reifies threads, events/messages, system and user actions) and statically-derived order (happensbefore relation) between actions. Establishing action order is complicated in Android, and event-based systems in general, because of externally-orchestrated control flow, use of callbacks, asynchronous tasks, and ad-hoc synchronization. Our approach introduces several key enablers for inferring order relations statically: models which impose order among lifecycle and GUI events; static analysis refinements, e.g., pathsensitive pointer analysis; and finally, on-demand path sensitivity via backward symbolic execution to further rule out false positives. We evaluate SIERRA on 194 Android apps. Of these, we chose 20 apps for manual analysis and comparison with a dynamic race detector. Experimental results show that our approach is effective and efficient, typically taking 1,230 seconds to analyze an app and revealing 33 potential races. Moreover, SIERRA can refute false positive races reported by the dynamic detector. Our approach opens the way for precise analysis and static event race detection in other event-driven systems beyond mobile platforms.
Hierarchical Implicit Surface Joint Limits for Human Body Tracking

To increase the reliability of existing human motion tracking algorithms, we propose a method for imposing limits on the underlying hierarchical joint structures in a way that is true to life. Unlike most existing approaches, we explicitly represent dependencies between the various degrees of freedom and derive these limits from actual experimental data. To this end, we use quaternions to represent individual 3 DOF joint rotations and Euler angles for 2 DOF rotations, which we have experimentally sampled using an optical motion capture system. Each set of valid positions is bounded by an implicit surface and we handle hierarchical dependencies by representing the space of valid configurations for a child joint as a function of the position of its parent joint. This representation provides us with a metric in the space of rotations that readily lets us determine whether a posture is valid or not. As a result, it becomes easy to incorporate these sophisticated constraints into a motion tracking algorithm, using standard constrained optimization techniques. We demonstrate this by showing that doing so dramatically improves performance of an existing system when attempting to track complex and ambiguous upper body motions from low quality stereo data.
The Influence of Oceanic Stochastic Forcing on the Atmospheric Response to Midlatitude North Pacific SST Anomalies

The stochastic sea surface temperature (SST) anomalies are always present because of the internal oceanic variability due to small‐scale SST variability and based on a set of ensemble experiments forced by Pacific Decadal Oscillation‐related midlatitude North Pacific SST anomalies with and without oceanic stochastic forcing, their influences on atmospheric variability in coarse‐resolution models are investigated in this study. Comparisons of experiment results show that oceanic stochastic forcing can improve the simulated atmospheric response by generating more organized atmospheric transient eddies through the increases of both thermal activity and atmospheric baroclinicity, similar to the high‐resolution observations and simulations. Dynamic diagnostics further reveal the dominant contributions of corresponding transient eddy vorticity forcing to the significantly enhanced westerly wind with equivalent barotropic structure. It suggests that the oceanic stochastic forcing is important and nonnegligible for the understanding and theory of oceanic feedback to the atmosphere in the midlatitudes.
Performance Prediction Technology for Agent-based Resource Management in Grid Environments

Resource management constitutes an important infrastructural component of a computational grid environment. The aim of grid resource management is to efficiently schedule applications over the available resources provided by the supporting grid architecture. Such goals within the high performance community rely, in part, on accurate performance prediction capabilities. This paper introduces a resource management infrastructure for grid computing environments. The technique couples application performance prediction with a hierarchical multi-agent system. An initial system implementation utilises the performance prediction capabilities of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on local grid resources. The validation results show that a high level of accuracy can be obtained, that cross-platform comparisons can be easily undertaken, and that the estimates can be evaluated rapidly. A hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the grid system architecture. An agent is a representative of a local grid resource and is considered to be both a service provider and a service requestor. Agents are organised into a hierarchy and cooperate to provide service advertisement and discovery. A performance monitor and advisor has been developed to optimise the performance of the agent system. A case study with corresponding experimental results are included to demonstrate the efficiency of the resource management and scheduling system. The main features of the system include: hard quality of service support using PACE performance prediction capabilities; agent-based dynamic resource advertisement and discovery capabilities; simulationbased quantitative grid performance analysis and useroriented scheduling of local grid resources.
Pragmatic evaluation of computer-aided self-help for anxiety and depression

Background Most anxiety/depression is not effectively treated. Aims Open evaluation of a free clinic giving immediate computer-aided cognitive – behavioural therapy (CBT) self-help plus brief advice from a therapist. Method Test of outcome of self-referrals who used one of four computer-aided CBT systems for depression, phobia/panic, general anxiety or obsessive-compulsive disorder. Results The equivalent of one full-time clinician managed 355 referrals over a year. Of the 266 who had a screening interview 79% were suitable. Completers and non-completers of computer-aided CBT had similar pre-treatment features, with very chronic, moderately severe problems. Completers of the computer-aided self-help had a mean total of an hour's live therapist support over 12 weeks. They improved significantly and clinically meaningfully with three of the four systems and felt ‘fairly satisfied’. Improvement resembled that in controlled and other trials of computer-aided CBT. Conclusions Computer-aided self-help is a‘clinician extender’ that greatly cuts per-patient therapist time without impairing improvement. It could reduce the per-patient cost of CBT.
Structure-from-motion in Spherical Video using the von Mises-Fisher Distribution.

In this paper we present a complete pipeline for computing structure-from-motion from sequences of spherical images. We revisit problems from multiview geometry in the context of spherical images. In particular, we propose methods suited to spherical camera geometry for the spherical-n-point problem (estimating camera pose for a spherical image) and calibrated spherical reconstruction (estimating the position of a 3D point from multiple spherical images). We introduce a new probabilistic interpretation of spherical structure-from-motion which uses the von Mises-Fisher distribution to model noise in spherical feature point positions. This model provides an alternate objective function that we use in bundle adjustment. We evaluate our methods quantitatively and qualitatively on both synthetic and real world data and show that our methods developed for spherical images outperform straightforward adaptations of methods developed for perspective images. As an application of our method, we use the structure-from-motion output to stabilise the viewing direction in fully spherical video.
AUC Knowledge Fountain AUC Knowledge Fountain

Generative Adversarial Networks [1] have been used for the task of image generation and has achieved impressive results [2][3]. There is always a challenge to train networks that generate large scale images since they tend to be huge and training needs a lot of data. In this work, we tackle this problem by dividing it into two smaller parts. We ﬁrst generate small scale images using GANs then use a super resolution network to enlarge the generated images resulting in large scale images. Using a super resolution network helps in adding more details to the image which results in a better quality image. This technique has been tested with a small amount of data and obtained better inception scores over the baseline GAN.
E-Government Implementation Challenges at Local Level: A Citizens' Centric Perspective

Majority of the studies reported in e-government literature identify the challenges involved in any e-government implementation from technical or project implementation perspective. In contrast, in this study, we take the citizen centric perspective to identify the factors and issues that influence the success of e-government implementation at local level. In this paper, we report the findings of a case study of e-government implementation undertaken recently at a local government authority in the UK. We conducted the study in two phases. During the first phase, we interviewed operational and managerial staff members at a local government authority in the UK who were involved with the e-government implementation. In the second phase, we interviewed 88 citizens to understand the issues and perceptions about egovernment services available to them. We use the design-reality gap analysis framework based on seven 'ITPOSMO' dimensions proposed by Heeks to compare and contrast the issues from citizens‟ perspective and those from government perspective. Our findings indicate that the success of e-government at local level requires a strong partnership between local government and citizens. The study results point to lack of clear strategy at local authorities‟ level for changing the way the government interacts with citizens. This paper contributes to our understanding of issues involved in implementing egovernment at local level both from citizens‟ perspective and government perspective.
A Toolkit to Support Rapid Construction of Ubicomp Environments

We describe the design and initial implementation of a toolkit for ubiquitous computing that reduces the cost – especially in time and effort – of developing applications and environments, and increases the potential involvement of designers and users in this process. The toolkit supports distributed applications running over multiple hosts by the creation, configuration and inter-connection of software components (both toolkit-aware and existing components) and components which represent physical devices and sensors. Users are supported by tools which provide various representations of the running environment, plus facilities for scripting and learning by example.
Briquettes from Tobacco Stems as the New Alternative Energy

Tobacco briquettes is the new alternative energy developed in PT Perkebunan Nusantara X (PTPN X). The tobacco briquettes research is important for PTPN X because of three reasons: high availability of the raw material, it can be used as substitution for coal briquettes, and expected for industrial scale. Currently, many researches have been conducted for biomass-briquettes but only few who used tobacco. PTPN X have been cultivated tobacco only for its leaves which latter used for cigar and the rests were thrown as waste. By conducting the tobacco briquettes research, many forms of utilization are expected. For short term, the aim of this research is generating a diversification of added value - produc from tobacco. For middle term, PTPN X is expected to be the role model for the tobacco growers. For long term, PTPN Xl’s goal is to decrease coal briquettes usage and break the negative stigma of tobacco. Briquetting process was conducted in Physical Laboratory of Tobacco Research of Jember and the observation located in Tobacco Processing Barn of Ajong Gayasan PTPN X. Analysis of proximate test showed that the moisture content of tobacco briquettes with cassava starch as adhesive was 8.00 to 8.97%, the volatile matter was 49.60 to 41.13%, the ash content was 9.93 to 7.89%, the fixed carbon was 32.47% to 42.01%, the sulphur content was 1.02 to 0.49%, the bulk density was from 0.35% to 0.41%, the calorific value was from 4,285 to 4,586 cal/gr, and flammable duration was from 592 to 697 minutes. The briquetting process did not affect the taste of leaves as cigar material.
An Empirical Study on Media Characteristics and Knowledge Sharing in Web 2.0 Environment

The success of the Enterprise 2.0 KMS (knowledge management systems) depends on the user’s continuous participation in the process of knowledge sharing. This study attempts to identify the determinants of the user’s intention to continuous knowledge sharing based on Expectation Confirmation Theory and Channel Expansion Theory. We also consider communication process modes (i.e., blog and wiki) as a moderator for perceived channel richness. The results of our analysis show the positive effects of all the predictors. With regard to the moderating effects of communication process modes, the effect of experiences shared with group members is greater in the channel to support conveyance, and the effects of experiences about the channel and the group task are greater in the channel to support convergence.
Understanding the Performance of Statistical MT Systems : A Linear Regression Framework F rancisco

We present a framework for the analysis of Machine Translation performance. We use multivariate linear models to determine the impact of a wide range of features on translation performance. Our assumption is that variables that most contribute to predict translation performance are the key to understand the differences between good and bad translations. During training, we learn the regression parameters that better predict translation quality using a wide range of input features based on the translation model and the first-best translation hypotheses. We use a linear regression with regularization. Our results indicate that with regularized linear regression, we can achieve higher levels of correlation between our predicted values and the actual values of the quality metrics. Our analysis shows that the performance for in-domain data is largely dependent on the characteristics of the translation model. On the other hand, out-of domain data can benefit from better reordering strategies. TITLE AND ABSTRACT IN ANOTHER LANGUAGE Modelos Lineales para el Análisis del Desempeño de la Traducción Automática En este documento presentamos una metodología para el análisis del desempeño de los sistemas de traducción automática. Utilizamos modelos lineales multivariados para determinar el impacto que diversas variables tienen en la calidad de las traducciones. En este estudio se asume que las variables que más contribuyen a predecir la calidad de las traducciones, son determinantes para entender las diferencias entre buenas y malas traducciones. Nuestros resultados demuestran que usando regresión lineal penalizada, se pueden obtener altos índices de predicción de calidad de traducción. Un análisis detallado revela que el desempeño de los sistemas de traducción frente a datos in-domain dependen en gran medida de las características de nuestros modelos de traducción. En contraste, la traducción de documentos out-of-domain está fuertemente ligada a las estrategias de reodenamiento que se utilicen.
AIS Electronic Library (AISeL)

Open data is a flagship initiative in open government program to increase transparency, social and commercial value, and participatory governance. Open data is a relatively new field and the factors affecting its adoption by citizen has not been widely studied. A better understanding of these factors can help government to formulate policies and strategies that can improve the acceptance and use of open data website. The research model is based on the Theory of Planned Behavior and integrated with the technology quality and trust factors. Data collection was conducted using questionnaire. Structural Equation Modeling (SEM) was used to test the research model. The results show that attitude, subjective norm, perceived behavioral control and trust directly affect intention to use open data website. Systems quality affects perceived usefulness, while information quality positively affects perceived usefulness, perceived ease of use, and trust. Both perceived usefulness and perceived ease of use affect user’s attitude. The analysis of this study suggests that each influencing factor provide implications for government to stimulate the use of open data website.
Classification of Posture and Movement Using a 3-axis Accelerometer

The real-time monitoring about the activity of the human provides useful information about the activity quantity and ability. The present study implemented a small-size and low-power acceleration monitoring system for convenient monitoring of activity volume and recognition of emergent situations such as falling during daily life. For the wireless transmission of acceleration sensor signal, we developed a wireless transmission system based on a sensor network. In addition, we developed a program for storing and monitoring wirelessly transmitted signals on PC in real-time. The performance of the implemented system was evaluated by assessing the output characteristic of the system according to the change of posture, and parameters and a context recognition algorithm were developed in order to monitor activity volume during daily life and to recognize emergent situations such as falling. In particular, recognition error in the sudden change of acceleration was minimized by the application of a falling correction algorithm.