Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-step image rectification

Image stereo-rectification is the process by which two images of the same solid scene undergo homographic transforms, so that their corresponding epipolar lines coincide and become parallel to the x-axis of image. A pair of stereo-rectified images is helpful for dense stereo matching algorithms. It restricts the search domain for each match to a line parallel to the x-axis. Due to the redundant degrees of freedom, the solution to stereorectification is not unique and actually can lead to undesirable distortions or be stuck in a local minimum of the distortion function. In this paper a robust geometric stereorectification method by a three-step camera rotation is proposed and mathematically explained. Unlike other methods which reduce the distortion by explicitly minimizing an empirical measure, the intuitive geometric camera rotation angle is minimized at each step. For un-calibrated cameras, this method uses an efficient minimization algorithm by optimizing only one natural parameter, the focal length. This is in contrast with all former methods which optimize between 3 and 6 parameters. Comparative experiments show that the algorithm has an accuracy comparable to the state-of-art, but finds the right minimum in cases where other methods fail, namely when the epipolar lines are far from horizontal.
Exchange Rates and Producer Prices: Evidence From Micro-Data

We use a unique data set that matches survey data on domestic and export prices to plant census information to address the following questions. Are desired markups constant or variable? How are markups adjusted in response to demand shocks? Does the probability that prices change respond to demand shocks? Our identi cation strategy is based on matched observations for the price charged for a given product by a given plant in two markets that are segmented by variable exchange rates. Changes in exchange rates shift perceived relative demand across the two markets while potentially also a¤ecting costs. We use xed e¤ects to control for changes in marginal cost and focus on markup responses to demand shocks. Our ndings suggest that desired markups are not constant. In particular, it appears that desired markups increase in response to increases in demand and fall in response to reductions in demand. Our ndings on the state-dependence of price setting are equivocal. We are unable to distinguish between the case of no state dependence and the case of state dependence combined with a unit elasticity of desired markups with respect to exchange rate-driven demand shocks. JEL Classi cation: F31, F41, L11, L16 This work contains statistical data from the Central Statistics O¢ ce, which is CSO copyright. The possibility for controlled access to the two con dential micro data sets on the premises of the CSO is provided for in the Statistics Act 1993. The use of statistical data in this work does not imply the endorsement of the CSO in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce statistical aggregates published by the CSO. We thank the sta¤ of the CSO for making this project possible. We are grateful to Manuel Amador, Nir Jaimovich, Pete Klenow and to seminar participants at the ESRI, Nottingham, CEAD-Budapest and Stanford for helpful comments and suggestions. All remaining errors and omissions are our responsibility. yDepartment of Economics, Stanford University, Stanford, CA 94305, d tzger at stanford.edu zEconomic and Social Research Institute, Sir John Rogersons Quay, Dublin 2, Ireland, stefanie.haller at esri.ie
Foreign Direct Investment Attraction in Central, Eastern and South-Eastern Europe: The Importance of Public Policy

The paper enhances the discussion about the determinants of foreign direct investment (FDI) in Central, Eastern and South-Eastern European countries and the ability of public policy to influence their FDI attractiveness. Based on data for 15 countries in 2013 and 2017, we build a composite index, which allows us to rank countries in terms of their overall FDI attractiveness, as well as its most important dimensions, such as institutional framework, infrastructure endowment, labour force quality and cost competitiveness. In addition to allowing comparison between economies across these dimensions, the results reveal areas in which some countries need improvement so that they can attract more FDI.
Player Modeling for Role-Playing Games

In many other popular role-playing games, the player modeling features and overall AI are considered poor and overlooked by the AAA video game industry, despite the fact that these are proven to enhance the player experience regarding its content and narrative. In this work, we present a Player Modeling architecture that uses a Machine Learning instance that analyses player actions and interactions with the virtual world, associates them with a player profile and creates a tailored experience that should provide better enjoyment and immersion for the player. We do believe that such solution adds more replay value, enjoyment and a better storytelling experience to any RPG by ultimately giving the player more power to influence its gaming experience.
ProntAPP: A mobile question answering application for medicines

We have been witnessing an increased amount of medical data that is available online. Such data is accessed not only by medical staﬀ but also by patients, and the public in general. However, with that much data, it has become increasingly diﬃcult to search for the correct answers we are looking for in a speciﬁc situation. ProntAPP is an Android and iPhone mobile application that aims at ful-ﬁlling this gap with a question-answering system in Portuguese for medicines. In this document, we describe the main features of ProntApp, we present the current state-of-the-art of the medical domain question-answering systems, web-based systems and mobile applications for medicines, its architecture and the implementation decisions. Finally, we describe the experimental evaluation that we conducted to validate ProntApp and the results obtained, and draw some ﬁnal conclusions.
Graphical Interfaces for User Behavior Transformation in the Energy Domain

Intelligent Energy Management Systems (EMSs), both for homes and buildings, have been designed with the goal of presenting information regarding energy spending and cost, aiming at fostering reductions in consumption. However,EMSs user interfaces are primarily designed to present energy consumption data to be interpreted by facilities and energy managers; the design of EMS user interfaces in a way that eﬀectively triggers changes in user behavior still remains an open issue [1, 2, 3]. This work discusses diﬀerent aspects of user behavior transformation and analyses the most relevant work in the area, identifying a set of design principles that are applied in the development of a graphical user interface of a domestic Energy Management software. This interface is augmented with elements that motivate users to take action towards energy saving. Results indicate that, when coupled appropriate interface elements, energy reporting becomes more eﬀective at inducing adequate user actions and raising awareness.
Respiratuar Distres Sendromlu Bronkopulmoner Displazi Gelişen Hastalarımızda Klinik ve Demografik Bulgularımız ve Literatürün Gözden Geçirilmesi

Amac : Bu calismanin amaci unitemizde RDS tanisi ile takip ve tedavi ettigimiz preterm bebeklerdeki BPD gorulme orani, bu bebeklerin klinik ve demografik verileri ve risk faktorleri paylasilarak gelisen yenidogan yogun bakim tekniklerine ragmen hastaligin surecten nasil etkilendiginin belirlemesidir. Gerec ve Yontemler: Meram Tip Fakultesi Yenidogan Yogun Bakim Unitesi'nde 2017 Ocak ile 2018 Mart aylari arasinda, prematurelik nedeniyle yatirilarak RDS tanisi ile surfaktan verilen ve izlemlerinde BPD tanisi alarak, tedavi verdigimiz 10 olgunun dosyalarindan verileri kaydedildi. Bulgular: Ocak 2017- Mart 2018 arasinda 10 (%13,3) hasta BPD tanisi aldi. Ortalama dogum haftasi 26,5 ±1,64 (25-29), ortalama dogum kilosu 821,8 ± 236,9 gr (1378-490) idi. Olgularin 7 (%70) tanesi 28 haftanin altinda ve 9 (%90) tanesi 1000 gr’in altinda idi. Olgularin 8 (%80) tanesi erkek, 2 (%20) tanesi kizdi. Olgular ortalama 19,35 ± 19,52 (1,5-41) gun invaziv, 25,6± 11,76 (4-43) gun non-invaziv mekanik ventilasyon ile solunum destegi aldi. Serbest oksijen ihtiyaclari eve oksijen ile taburcu olan agir BPD’li 1 hasta haric ortalama 39,5 ±17,19 (69-14) gun surdu. Sonuc: Sonuc olarak yenidogan bakim uygulamalarindaki tum gelismelere ragmen BPD ciddi bir sorun olmaya devam etmektedir. Calismamizda da prematurite, dusuk dogum agirligi, invaziv mekanik ventilasyon uygulama suresi, yogun ve uzun sureli oksijen destegi BPD’nin zemin hazirlayan risk faktorleri olarak one cikmaktadir.
Evaluation of the Chinese version of the swallowing screen in stroke patients with dysphagia

Objective: The purpose of this study was to validate a Chinese version of the modified Standardized Swallowing Assessment (SSA) instrument used by nurses in stroke patients with dysphagia and explore the feasibility of the simplified instrument. Materials and Methods: This study involved a cross-sectional design. Nurses independently applied the modified SSA to 127 patients with stroke before a complete dysphagia evaluation conducted by a speech–language pathologist. Factor analysis of eight dysphagia variables in the modified SSA was performed to evaluate construct validity. The accuracy of the screening instrument was assessed through receiver operating characteristic (ROC) analysis. Results: The comprehensive swallowing assessment revealed that 49.6% of the stroke patients had dysphagia. The modified SSA had an acceptable internal consistency coefficient. The inter-rater agreement between nurses using the modified SSA showed a Kappa coefficient of 0.509. All items had a communality loading of >0.5, and two factors accounted for 73.89% of the response variance. The area under the ROC curve was 0.79 (95% confidence interval: 0.71–0.87). The sensitivity and specificity derived for dysphagia detection were satisfactory according to the results obtained from the original 8-item and simplified 6-item scales (sensitivities = 82.50% and 81.00% and specificities = 59.40% and 64.10%, respectively; accuracy = 70.87% and 72.44%, respectively). Conclusion: This preliminary study suggests that the modified SSA is a potentially reliable and valid nurse-administered screening instrument for dysphagia detection in patients with stroke.
The Impact of Honor and Shame on Public Goods Dilemmas

From the beginning of time cooperation between individuals exists and is necessary for the maintenance of populations, but explaining its emergence and maintenance, overcoming the rational egoism that is still foreseen by classical economics, remains an open question. In this work we use the Public Goods Games paradigm, used to study the evolutionary dynamics of cooperators and defectors in a population in which groups of people interact. However human behavior is more complex than just two decisions, and so we model actions as a continuous interval in which an individual can cooperate at different levels. To obtain results computational simulations of multi-agent populations are used, where each agent acts and learns using processes proposed by Evolutionary Game Theory and we study the evolution in different types of social structures represented here through complex networks. Well-mixed structures (all agents interact with equal probability) and heterogeneous interaction networks (scale-free). With this study we propose a model for the emergence of cooperation: honor and shame. We conclude that the structure of the network and the knowledge that an individual has about the degree of others in the network affect learning and that in a general way honor and shame have a positive impact on altruistic behavior, which is more intense when combined.
On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property

The benefit of exploiting label dependence in multi-label classification is known to be closely dependent on the type of loss to be minimized. In this paper, we show that the subsets of labels that appear as irreducible factors in the factorization of the conditional distribution of the label set given the input features play a pivotal role for multi-label classification in the context of 0/1 loss minimization, as they divide the learning task into simpler independent multi-class problems. We establish theoretical results to characterize and identify these irreducible label factors for any given probability distribution satisfying the Composition property. The analysis lays the foundation for generic multi-label classification and optimal feature subset selection procedures under this subclass of distributions. Our conclusions are supported by carefully designed experiments on synthetic and benchmark data.
Multi-criteria assessment of university readiness for digital transformation

This article proposes a methodology for assessing the readiness of a university for digital transformation in four aspects: the architecture of organization, process management, human resources and financing tools. Since each of these areas has its own characteristics, the assessment is carried out using different methods and approaches: TOGAF, CMMI, BPMM, PCF APQC and others. To enable analysis, evaluation and monitoring of changes in the degree of readiness for digital transformation, as well as to facilitate the analysis of available information for each research area or the university as whole, it was proposed to use the dashboard method.
GeoFriends: Recommendation System in Location-Based Social Networks

Location-based Social Networks are getting increasingly more popular due to the fact that nowadays it is extremely easy for someone to record and share his location. This type of geographical data can be used to link the physical and digital worlds and as such, location-based services can enhance the real world experience of their users. In this thesis we move towards this direction and aim at finding similar users from their location traces, while also letting them interact with each others via geographical annotations. A system called GeoFriends is presented which main objective is to retrieve information from location data, and use it to recommend both users and nearby content. In addition to the traditional approach of comparing locations’ coordinates, GeoFriends takes into account factors such as the sequence and the travel times between regions. GeoFriends tackles some scalability issues such as how to deal with the possible constant location updates from its users. We evaluated such scenarios and found that GeoFriends scales much better than a straight forward approach. Moreover, using a publicly available dataset, we found that GeoFriends was able to retrieve approximately 55% of any user’s friends using only location data.
CHANGES OF INSPIRATORY PARAMETERS AND SWIMMING PERFORMANCE BY INFLUENCE OF POWERBREATHE PLUS LEVEL 3

The aim of the study was to detect changes of inspiratory parameters and performance in underwater swimming by the use of the device POWERbreathePlus Level 3 (POWER®breathe, Southam, UK). The research specimens were comprised of probands (n = 5, height = 177.8±7.6 cm, weight = 66.0±6.6 kg)aged 17.5to23. 1years. POWERbreathePlus Level 3 (POWER®breathe, Southam, UK) was integrated into the training process for 10 weeks. The experimental factor was given twice a day for 30 inspirations in the morning and evening. The impact of the experimental factor was monitored by an assay on the POWERbreathe K 5 (POWER®breathe, Southam, UK) breathing equipment. The assay was focused on finding out the intensity index (S – index), maximum speed of inhalation(flow) andvolume of inhaled air. The other test included underwater swimming on single breath. In parameter S – index was average levelin input testing 111.0±42.7 cmH2Oand the average level in output testing was 133.6±46.2 cmH2O which means significant improvement (T = 0, n = 5, p < 0.05, ES = 0.90 – large effect). The improvement of the ensemble ́s level was also detected in third inspiratory parameterwhere the volume was following: (T = 0, n = 5, p < 0.05, ES = 0.92 – large effect). The input level was 3.02±0.48and output level was 3.52±0.52 l. Significant increase of the average level of the ensemble (T = 0, n = 5, p < 0.05, ES = 0.91 – large effect) was detected also when the distance was increased which was swum under the water when the value of the ensemble during input testing was 38±6 m and during output testing was 43±6 m.
Movement pattern training compared with standard strengthening and flexibility among patients with hip-related groin pain: results of a pilot multicentre randomised clinical trial

Study design Pilot, multicentre randomised clinical trial (RCT). Objectives Assess viability of performing a definitive RCT and compare preliminary effects of movement pattern training (MoveTrain) and strengthening/flexibility (Standard) to improve function in people with chronic hip-related groin pain (HRGP). Background To determine the best physical therapist-led intervention for patients with HRGP, we must understand treatment effects of different treatment modes. Methods Forty-six patients (17M:29F; 29±5.3 years; body mass index 25.6±6.3 kg/m2) with HRGP were randomised. MoveTrain included task-specific training to optimise biomechanics during daily tasks. Standard included strengthening/flexibility. Treatment included 10 visits/12 weeks and home exercise programme (HEP). Primary outcomes for feasibility were recruitment, retention, treatment adherence and treatment fidelity. Secondary outcomes were patient-reported function (Hip disability and Osteoarthritis Outcome Score (HOOS)), lower extremity kinematics and hip muscle strength. Results We achieved target recruitment, and retention was excellent (91%). Patient session attendance was high (93%); however, reported HEP adherence (62%) was lower than expected. Physical therapists’ adherence to treatment protocols was high (90%). Patients demonstrated high treatment receipt; 91% of exercises performed were rated independent. Both groups demonstrated clinically important improvements in function (HOOS) and muscle strength; however, there were no between-group differences (HOOS subscales, p≥0.13, strength, p≥0.34). Compared with Standard, MoveTrain demonstrated greater reductions in hip adduction (p=0.016) and pelvic drop (p=0.026) during a single leg squat. No adverse events were noted. Conclusion Our experience in completing this RCT confirmed that a larger, multicentre RCT is feasible and highlighted modifications we will implement to optimise the future RCT. Trial registration number NCT02913222.
Photo-consistent surface reconstruction from noisy point clouds

Existing algorithms for surface reconstruction from point sets are defeated by moderate amounts of noise and outliers, which makes them unapplicable to point clouds originating from multi-view image data. In this paper, we present a novel method which incorporates the input images in the surface reconstruction process for a better accuracy and robustness. Our approach is based on the medial axis transform of the scene, which our algorithm estimates through a global photo-consistency optimization by simulated annealing. A faithful polyhedral representation of the scene is then obtained by inversion of the medial axis transform.
Kinect Gestural Interaction for a Collaboration Game

Competition between players seems to be integrated in most video games in the video game industry. Yet, collaboration features can carry new game experiences that can interest some players. This thesis discusses some distinct Kinect and Wii Remote interactions, and relates them to if they can enhance collaboration though a casual collaboration game called Geometry Friends . Natural gestures, collaboration sense, gesture recognition, gesture exhaustion and space issues are some of the aspects compared between all interaction tested.
Treatment and Rehabilitation of Substance Use Disorder: Significance of Islamic Input in Malaysia

Drug addiction is a chronic relapsing disease which can be treated. Treatment, however is dependent on many variables; the drug of choice, severity of drug use, individual and personality characteristics such as religiosity; community and environmental factors, familial and social support, employment and many more. Many countries used the supply and demand reduction strategies, nonetheless some are successful, and some are not. The advent of HIV-Aids among IDUs forces treatment specialist to look at other alternatives. Harm reduction offer pragmatic approaches though sometimes controversial avenues to provide solutions to the HIV and substance users. Drug Substitution Therapies for people using opioids have proven to be more effective with other non-medical approaches such as contingency management, behavioral interventions and spiritual/religious enhancement. This paper reports the experience of Malaysia in its approach to SUD treatment and providing Islamic religious input to treatment and rehabilitation programs in government and non-government facilitiesInternational Journal of Human and Health Sciences Vol. 02 No. 04 October’18. Page : 209-216
Melanoma Detection using deep learning methods

Melanoma stands out as the deadliest skin cancer due to its propensity to metastasize. Early detection is crucial to deliver successful treatment. Computer-Aided Diagnosis (CAD) systems have been developed to provide an automated melanoma detection. This paper proposes a new CAD system to distinguish between melanoma and benign skin lesions. The novelty lies in the use and comparison of three different Convolutional Neural Networks (CNN) at a time, namely AlexNet, VGG and ResNet. These CNN were trained using transfer learning and data augmentation. The image dataset was extracted from the ISIC 2017 Challenge. The original dataset contains 2000 training images (1626 benign lesions and 374 melanomas), 150 validation images (120 benign lesions and 30 melanomas) and 600 test images (483 benign lesions and 117 melanomas). The training set was then augmented and contained 1626 benign examples and 1870 malign examples. For a test set of 600 images, ResNet reached a sensitivity of 79%, a specificiy of 60%, a balanced accuracy of 69% and an area under the receiver operating characteristic curve of 77%. Hence, the proposed system demonstrates the potential of CNN in CAD systems for automated melanoma detection