Miracle-dz/UniFAR-FTUs huggingface dataset:
Invariant Local Features for Face Detection

In the domain of object recognition, the SIFT feature [1] is known to be a very successful local invariant feature. The performance of the recognition task using SIFT features is very robust and also can be done in real-time. This project present an approach that adopt the SIFT feature for the task of face detection. A feature database is created for the detection of generic face features and a model fitting algorithm is used to resolve the scale, orientation and position of the faces in images. Because of the advantages brought by the SIFT features, the system can easily detect faces of any scale and rotation. A test is done using 16 images with 200 faces in total. The result shows a detection rate of 72.5% with 46 false detections.
Re-scheduling in railways: the rolling stock balancing problem

This paper addresses the Rolling Stock Balancing Problem (RSBP). This problem arises at a passenger railway operator when the rolling stock has to be re-scheduled due to changing circumstances. These problems arise both in the planning process and during operations. The RSBP has as input a timetable and a rolling stock schedule where the allocation of the rolling stock among the stations does notfit to the allocation before and after the planning period. The problem is then to correct these off-balances, leading to a modified schedule that can be implemented in practice. For practical usage of solution approaches for the RSBP, it is important to solve the problem quickly. Therefore, the focus is on heuristic approaches. In this paper, we describe two heuristics and compare them with
Harmonic Rayleigh-Ritz extraction for the multiparameter eigenvalue problem

We study harmonic and refined extraction methods for the multiparameter eigenvalue problem. These techniques are generalizations of their counterparts for the standard and generalized eigenvalue problem. The methods aim to approximate interior eigenpairs, generally more accurately than the standard extraction does. We study their properties and give Saad-type theorems. The processes can be combined with any subspace expansion approach, for instance a Jacobi-Davidson type technique, to form a subspace method for multiparameter eigenproblems of high dimension.
An Assessment of Task-Technology Fit, Subjective Norm and Internet Experience of Learning Management System in Views of Malaysian Higher Education Students

In recent years, the use of Learning Management System (LMS) in higher education has dramatically increased. However, many students use LMS for limited purposes such as downloading course materials. There are many factors that may affect LMS utilization by students. In the present study three factors, namely Internet experience, subjective norm, and task-technology fit were examined. The participants of the study were 216 undergraduate students of faculty of education in one of the local universities in Malaysia. The results revealed that the constructs of Internet experience and subjective norm obtained a high mean value. This result suggests students who used LMS have a sufficient internet experience which could easily help them in using it. University and lecturer support seems to be the most important sources that encourage them to use LMS. Students also responded their satisfaction with the functionality of LMS to assists them in the process of learning.
Literature-based discovery for Oceanographic climate science

This paper presents an overview of the field of literature-based discovery, as originally applied in biomedicine. Furthermore it identifies some of the challenges to employing the results of the field in a new domain, namely oceanographic climate science, and elaborates on some of the research that needs to be conducted to overcome these challenges.
Vitamin B12 in Obese Adolescents with Clinical Features of Insulin Resistance

Emerging evidence indicates an association between obesity, metformin use and reduced vitamin B12 status, which can have serious hematologic, neurologic and psychiatric consequences. This study aimed to examine B12 status in obese adolescents with pre-diabetes and/or clinical features of insulin resistance. Serum B12 was measured using chemiluminescence immunoassay in 103 (43 male, 60 female) obese (mean body mass index (BMI) z-score ± SD (2.36 ± 0.29)), adolescents aged 10 to 17 years, median (range) insulin sensitivity index of 1.27 (0.27 to 3.38) and 13.6% had pre-diabetes. Low B12 (<148 pmol/L) was identified in eight (7.8%) and borderline status (148 to 221 pmol/L) in an additional 25 (24.3%) adolescents. Adolescents with borderline B12 concentrations had higher BMI z-scores compared to those with normal concentrations (2.50 ± 0.22 vs. 2.32 ± 0.30, p = 0.008) or those with low B12 concentration (2.50 ± 0.22 vs. 2.27 ± 0.226, p = 0.041). In conclusion, nearly a third of obese adolescents with clinical insulin resistance had a low or borderline serum B12 status. Therefore, further investigations are warranted to explore the cause and the impact of low B12 status in obese pediatric populations.
Automatic extraction of subcategorization frames from corpora : an approach to Portuguese

In this paper we present a tool for the automatic extraction of subcategorization frames from Portuguese corpora. Subcategorization frames are important to many Natural Language Processing (NLP) tasks, such as the improvement of parsing results. The tool presented here, which is based on a system developed for French, comes to fill a gap in Portuguese, because the subcategorization frames of Portuguese verbs have not received much attention. We also present some results of the application of this tool to the task of automatic verb classification.
Technical Report: Control Using the Smooth Robustness of Temporal Logic

Cyber-Physical Systems must withstand a wide range of errors, from bugs in their software to attacks on their physical sensors. Given a formal specification of their desired behavior in Metric Temporal Logic (MTL), the robust semantics of the specification provides a notion of system robustness that can be calculated directly on the output behavior of the system, without explicit reference to the various sources or models of the errors. The robustness of the MTL specification has been used both to verify the system offline (via robustness minimization) and to control the system online (to maximize its robustness over some horizon). Unfortunately, the robustness objective function is difficult to work with: it is recursively defined, non-convex and non-differentiable. In this paper, we propose smooth approximations of the robustness. Such approximations are differentiable, thus enabling us to use powerful off-theshelf gradient descent algorithms for optimizing it. By using them we can also offer guarantees on the performance of the optimization in terms of convergence to minima. We show that the approximation error is bounded to any desired level, and that the approximation can be tuned to the specification. We demonstrate the use of the smooth robustness to control two quad-rotors in an autonomous air traffic control scenario, and for temperature control of a building for comfort.
Searching web databases by structuring keyword-based queries

On-line information services have become widespread in the Web nowadays. However, Web users are non-specialized and have a great variety of interests. Thus, interfaces for Web databases must be simple and uniform. In this paper we present an approach, based on Bayesian networks, for querying Web databases using keywords only. According to this approach, the user inputs a query through a simple search-box interface. From the input query, one or more plausible structured queries are derived and submitted to Web databases. The results are then retrieved and presented to the user as ranked answers. Our approach reduces the complexity of existing on-line interfaces and offers a solution to the problem of querying several distinct Web databases with a single interface. The applicability of the proposed approach was demonstrated by experimental results with 3 databases, obtained with a prototype search system that implements it. We have found that from 77% to 95% of the time, one of the top three resulting structured queries is the proper one. Further, when the user selects one of these three top queries for processing, the ranked answers present average precision figures from 60% to about 100%.
Proportional fair scheduling for multi-cell multi-user MIMO systems

In this paper, a multi-cell multi-user MIMO scheme with advanced user pairing and scheduling algorithm is proposed to effectively explore multi-user diversity and to combat both intra-cell and inter-cell interference in the downlink of wireless communication systems. The optimality of the proposed user paring and scheduling algorithm is shown under generalized proportional fair metrics. System-level simulations are conducted to verify the performance of the proposed scheme with the agreed LTE-Advanced (LTE-A) system parameters. The results suggest the proposed scheme is a promising candidate for improving both the cell-edge user throughput and average cell throughput, and furthermore for fulfilling the IMT-Advanced (IMT-A) requirements.
A Data Mining with Hybrid Approach Based Transaction Risk Score Generation Model (TRSGM) for Fraud Detection of Online Financial Transaction

a unique and hybrid approach containing data mining techniques, artificial intelligence and statistics in a single platform for fraud detection of online financial transaction, which combines evidences from current as well as past behavior. The proposed transaction risk generation model (TRSGM) consists of five major components, namely, DBSCAN algorithm, Linear equation, Rules, Data Warehouse and Bayes theorem. DBSCAN algorithm is used to form the clusters of past transaction amounts of the customer, find out the deviation of new incoming transaction amount and finds cluster coverage. The patterns generated by Transaction Pattern Generation Tool (TPGT) are used in Linear equation along with its weightage to generate a risk score for new incoming transaction. The guidelines shown in various web sites, print and electronic media as indication of online fraudulent transaction for Credit Card Company is implemented as rules in TRSGM. In the first four components, we determine the suspicion level of each incoming transaction based on the extent of its deviation from good pattern. The transaction is classified as genuine, fraudulent or suspicious depending on this initial belief. Once a transaction is found to be suspicious, belief is further strengthened or weakened according to its similarity with fraudulent or normal transaction history using Bayes theorem.
Joint spectrum sharing and power allocation for secondary users in cognitive radio networks

Spectrum sharing and power allocation are interesting issues in cognitive radio networks. In our paper, we introduce a pricing scheme to demonstrate the spectrum sharing scenario between primary users and secondary users. We demonstrate the joint optimal allocation scheme of both spectrum and power for secondary users buying spectrum from multiple primary users. The joint optimal allocation scheme maximizes secondary users' utilities while primary users' utilities meet certain requirements. Moreover, we illustrate a distributed resource allocation scheme to jointly optimize usage of power and spectrum when each secondary user does not know others' buying strategies. Our simulation results show that under some utility requirements, the joint optimized resource allocation scheme has 3dB gain over that under even resource allocation.
Mining Privacy Goals from Privacy Policies Using Hybridized Task Recomposition

Privacy policies describe high-level goals for corporate data practices; regulators require industries to make available conspicuous, accurate privacy policies to their customers. Consequently, software requirements must conform to those privacy policies. To help stakeholders extract privacy goals from policies, we introduce a semiautomated framework that combines crowdworker annotations, natural language typed dependency parses, and a reusable lexicon to improve goal-extraction coverage, precision, and recall. The framework evaluation consists of a five-policy corpus governing web and mobile information systems, yielding an average precision of 0.73 and recall of 0.83. The results show that no single framework element alone is sufficient to extract goals; however, the overall framework compensates for elemental limitations. Human annotators are highly adaptive at discovering annotations in new texts, but those annotations can be inconsistent and incomplete; dependency parsers lack sophisticated, tacit knowledge, but they can perform exhaustive text search for prospective requirements indicators; and while the lexicon may never completely saturate, the lexicon terms can be reliably used to improve recall. Lexical reuse reduces false negatives by 41%, increasing the average recall to 0.85. Last, crowd workers were able to identify and remove false positives by around 80%, which improves average precision to 0.93.
A Geostatistically Based Preprocessing Algorithm for Hyperspectral Data Analysis

We present a preprocessing algorithm for hyperspectral remote sensing datasets. The algorithm is based on a geostatistical method and should be helpful when a spatial relationship is detected in a dataset. One significant advantage of hyperspectral remote sensing using spectral profiles is the ability to compare an unknown pixel's profile with endmembers that have already been identified by a variety of methods (e.g., laboratory experiments with high-precision spectrometers), with the final goal of determining the unknown pixel. The conditions under which the airborne or spaceborne hyperspectral data are collected, however, differ from those that prevail in the laboratory or field. Therefore, a dataset should be preprocessed so as to eliminate or considerably reduce these differences; the algorithm presented here could be used for that purpose. The result will not only improve the smoothness of spectral profiles, but it may also offer advantages for geological investigations to study mineral anomalies using hyperspectral data. Concentrations of minerals in rock bodies often have certain patterns and follow trends that can be modeled by computing a semivariogram. The advantages of using such a trend have induced mining engineers to develop innovations in geostatistics. These trends should be taken into account when handling hyperspectral datasets. In all methods presented for boosting spectral profiles, the spatial relationships among pixels' DNs are neglected, but, in the method presented here, this relationship is calculated by geostatistics, and an algorithm is applied to improve spectral profiles. The nugget effect is calculated separately for each channel, and its square root is subtracted from the reflectance of all pixels in that channel. Finally, we examine the effectiveness and validation of the method examined using the AVIRIS dataset from Cuprite, Nevada. The results are satisfactory, as the algorithm yields a better mineral detection process.
Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual Energy X-Ray Absorptiometry in Obese Women

Improved understanding of how depot‐specific adipose tissue mass predisposes to obesity‐related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three‐dimensional (3D) contiguous “fat‐water” MR imaging (FWMRI) covering the majority of a whole‐body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type, and distribution of adipose and lean soft tissue would show great promise in body composition methodology.
Skin Detection using HSV color space

This work describes an implementation for skin detection which relies on the H channel to characterize the skin colors range. The openCv library is used for image processing. The program initially converts RGB images to HSV one. The H channel is used to characterize the colors range for skin detection. To illustrate the approach we compare this with others.
An educational environment for program behavior analysis and cache memory design

The authors present an educational software package (Csim) used as a teaching tool to analyze the structure and behavior of a cache memory and to help the student in the design of cache memories for embedded systems. By means of an integrated software development environment, the user can create a program and explore its behavior (locality analysis). The student can observe the cache actions needed for a memory operation and evaluate the cache performance as a function of the configuration parameters. Finally, the parametric-evaluation graphical tools help in the actual design of an embedded system, in order to find the cache and memory configuration which provides the best balance between cost and performance.
Evaluación y caracterización de clones regionales de cacao en la subregión del Urabá antioqueño: fase I

En esta investigacion se identificaron y evaluaron arboles elite de cacao, con caracteristicas de produccion, adaptabilidad y calidad sobresaliente; aprovechando la alta variabilidad genetica existente en la subregion de Uraba. En un sistema de siembra en triangulo (3.5 x 3.5 m) se seleccionaron 29 individuos (clones) con cinco arboles por cada clon. En cada individuo, se registraron longitud, diametro, peso de mazorca, de la cascara y humedad del grano. Los clones fueron identificados con las siglas FMA (Fedecacao La Marina Apartado). Mediante un diagrama de dispersion se determino el comportamiento de los clones con mayor o menor produccion obtenida, estos datos fueron estandarizados y normalizados. Por medio del analisis por conglomerados se seleccionaron cuatro grupos (A, B, C y D) formados a una distancia euclideana de alrededor de 0.7 unidades, que fue el numero de grupos con mejor asociacion en las caracteristicas fenotipicas de los clones. Finalmente, el grupo A, representado por los seis clones FMA 12, 13, 14, 18, 20 y 28 presentaron una produccion constante durante diez meses, asi como alto rendimiento durante el periodo de estudio; permitiendo establecer programas de propagacion y establecimiento en parcelas demostrativas de la subregion; los demas grupos (B, C y D) obtuvieron bajo nivel productivo, calidad y desarrollo fenologico. Por lo tanto, se recomienda evaluar la relacion compatible de los clones respecto a los demas materiales ya propagados y establecidos en la zona para implementarlos en arreglos de siembras comerciales.
Effect of nebulized budesonide on respiratory mechanics and oxygenation in acute lung injury/acute respiratory distress syndrome: Randomized controlled study

Background: We tested the hypothesis that nebulized budesonide would improve lung mechanics and oxygenation in patients with early acute lung injury (ALI) and/or acute respiratory distress syndrome (ARDS) during protective mechanical ventilation strategy without adversely affecting systemic hemodynamics. Methods: Patients with ALI/ARDS were included and assigned into two groups; budesonide group (30 cases) in whom 1 mg–2 ml budesonide suspension was nebulized through the endotracheal tube and control group (30 cases) in whom 2 ml saline (placebo) were nebulized instead of budesonide. This regimen was repeated every 12 h for three successive days alongside with constant ventilator settings in both groups. Hemodynamics, airway pressures, and PaO2/FiO2were measured throughout the study period (72 h) with either nebulized budesonide or saline. Furthermore, tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6) were analyzed serologically as markers of inflammation at pre- and post-nebulization sessions. Results: We found a significant difference between the two groups regarding PaO2/FiO2 (P = 0.023), peak (P = 0.021), and plateau (P = 0.032) airway pressures. Furthermore, TNF-α, IL-1β, and IL-6 were significantly reduced after budesonide nebulizations. No significant difference was found between the two groups regarding hemodynamic variables. Conclusion: Nebulized budesonide improved oxygenation, peak, and plateau airway pressures and significantly reduced inflammatory markers (TNF-α, IL-1β and IL-6) without affecting hemodynamics. Trial Registry: Australian New Zealand Clinical Trial Registry (ANZCTR) at the number: ACTRN12615000373572.
Inhibition of UCH-L1 in oligodendroglial cells results in microtubule stabilization and prevents α-synuclein aggregate formation by activating the autophagic pathway: implications for multiple system atrophy

α-Synuclein (α-syn) positive glial cytoplasmic inclusions (GCI) originating in oligodendrocytes (ODC) are a characteristic hallmark in multiple system atrophy (MSA). Their occurrence may be linked to a failure of the ubiquitin proteasome system (UPS) or the autophagic pathway. For proteasomal degradation, proteins need to be covalently modified by ubiquitin, and deubiquitinated by deubiquitinating enzymes (DUBs) before proteolytic degradation is performed. The DUB ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1) is a component of the UPS, it is abundantly expressed in neuronal brain cells and has been connected to Parkinson’s disease (PD). It interacts with α-syn and tubulin. The present study was undertaken to investigate whether UCH-L1 is a constituent of ODC, the myelin forming cells of the CNS, and is associated with GCIs in MSA. Furthermore, LDN-57444 (LDN), a specific UCH-L1 inhibitor, was used to analyze its effects on cell morphology, microtubule (MT) organization and the proteolytic degradation system. Towards this an oligodendroglial cell line (OLN cells), stably transfected with α-syn or with α-syn and GFP-LC3, to monitor the autophagic flux, was used. The data show that UCH-L1 is expressed in ODC derived from the brains of newborn rats and colocalizes with α-syn in GCIs of MSA brain sections. LDN treatment had a direct impact on the MT network by affecting tubulin posttranslational modifications, i.e., acetylation and tyrosination. An increase in α-tubulin detyrosination was observed and detyrosinated MT were abundantly recruited to the cellular extensions. Furthermore, small α-syn aggregates, which are constitutively expressed in OLN cells overexpressing α-syn, were abolished, and LDN caused the upregulation of the autophagic pathway. Our data add to the knowledge that the UPS and the autophagy-lysosomal pathway are tightly balanced, and that UCH-L1 and its regulation may play a role in neurodegenerative diseases with oligodendroglia pathology.
Association between floral traits and rewards in Erysimum mediohispanicum (Brassicaceae).

BACKGROUND AND AIMS Floral rewards may be associated with certain morphological floral traits and thus act as underlying factors promoting selection on these traits. This study investigates whether some traits that are under pollinator-mediated selection (flower number, stalk height, corolla diameter, corolla tube length and corolla tube width) in the Mediterranean herb E. mediohispanicum (Brassicaceae) are associated with rewards (pollen and nectar). METHODS During 2005 the phenotypic traits and the visitation rate of the main pollinator functional groups were quantified in 720 plants belonging to eight populations in south-east Spain, and during 2006 the same phenotypic traits and the reward production were quantified in 400 additional plants from the same populations. KEY RESULTS A significant correlation was found between nectar production rate and corolla tube length, and between pollen production and corolla diameter. Visitation rates of large bees and butterflies were significantly higher in plants exhibiting larger flowers with longer corolla tubes. CONCLUSIONS The association between reward production and floral traits may be a factor underlying the pattern of visitation rate displayed by some pollinators.