Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Method for Edge Detection Based on the Criterion of Separability

This paper presents a new edge detection algorithm based on calculating the difference value of two clusters. An edge is defined as a boundary that separates two adjacent regions that are relatively homogenous. For each image pixel, a window is first defined by placing the pixel at the center, and this window is partitioned into two sub- regions respectively in four different directions. An appropriate function is then selected to estimate the difference between each pair of two adjacent regions and to calculate edge information in terms of edge stre ngth and direction by maximizing the difference value. Finally, the non-maxima suppression is adopted to derive the output edge map. Experiments on a variety of noise contaminated images show that the new algorithm is more robust under noisy conditions. In addition, the proposed algorithm can also be applied to color or multi-spectral images.
Ontology-based Competency Analyses in New Research Domains

Ontology-driven methods of competence management oriented on support of scientific research for new domains are proposed. Ontologies of research domain are matched with personal information about scientific researchers represented into Web (for example, at the social networks) and results of their work (publications, monographs, reports etc.) are processed by logical methods and ontological analysis. Web-services and multi-agent programming paradigm are used for their software realization.
What should I landmark? Entropy of normals in depth juts for place recognition in changing environments using RGB-D data

One open problem in the fields of place recognition and mapping is to be able to recognise a revisited place when its appearance and layout have changed between visits. In this paper, we investigate this problem in the context of RGB-D mapping in indoor environments. We propose to segment the scene in juts (neighbourhood of 3D points with normals that stick out from the surroundings) and look at low-level features, like textureness or entropy of the normals. These could differentiate those zones of the scene that change or move along time from those that are likely to remain static. We also present a method which improves the matching between images of the same place taken at different times by pruning details basing on these features. We evaluate on a number of communal areas and also on some scenes captured 6 months apart. Experiments with our approach, show an increase up to 70% in inlier matching ratio at the cost of pruning only less than 20% of correct matches, without the need of performing geometric verification.
Integrating a Verb Lexicon into a Syntactic Treebank Production

The creation of linguistically interpreted corpora is a ted ious task and the automation of the annotation process is indispensable. A fully a utomated annotation is hardly possible to achieve, since it requires very sophis ticated and large knowledge bases which are, themselves difficult to create. Howev er, a "machine-aided approach" to the annotating process, using as many as availa ble sources of linguistic information is justified and desirable. The creation of an HPSG-based syntactic treebank of Bulgari an [18] is a process of incremental augmentation of the real-world sentenc es with linguistic annotation as the result of linguistic analysis at different p rocessing levels. At this stage of the treebank production, there are the follo wing main sources of linguistic knowledge that can be integrated into a gramma r for automated chunk connection and assignment of grammatical relations:
HUMAN RESOURCE MANAGEMENT PRACTICES IN SHIPPING COMPANIES A STUDY

HE need of organizations for people and people for organizations will be more difficult to satisfy in the todays competitive business environment. Firms competitive advantage could be generated from human resources (HR) and firm performance is influenced by a set of effective HRM practices. In this study, we intend to assess the HR practices in shipping companies. Primary data based on 250 observations from 125 shipping companies was analyzed to bring out the human resource management practices practiced in shipping companies. Factor analysis brought about five factors, which were further analyzed. Two factors namely training and performance appraisal and hiring and compensation system emerged very strong HR practices followed by career development. Job analysis and HR planning was moderately practiced in shipping companies. Workforce diversity and flexi-work system also showed presence but did not emerge as strong practice.
Ranking in discrete choice experiments

A common problem in ethology is ranking of animal preferences for several discrete stimuli or options. We considered experiments where animals chose one of all possible simultaneously presented options. The animals might be observed at repeated occasions. In the ethological literature the analysis is often focused on testing the global hypotheses of no difference in preferences by non-parametric methods. This fails to address the estimation of a ranking. Often this approach cannot adequately reflect the the experimental setting and the repeated measurement structure. Therefore, we propose to model to the choice probabilities for the options with a multinomial logistic model. The correlation induced by repeated measurements is incorporated by animal specific random intercepts. The ranking of the options is taken as the order of the choice probabilities. Adopting a Bayesian approach samples from the posterior distribution of the choice probabilities provide directly samples from the posterior of the rankings. Based on this an estimate of the ranking and description of its variability can be derived. The computation was performed via Markov chain Monte Carlo sampling and was implemented using WinBUGS. We illustrate our approach with an experiment to determine the preference of pigs for three different rooting materials. The proposed method allowed to derive an overall ranking for different combinations of the materials and the spatial orientation
A Brief Survey of Detection and Mitigation Techniques for Clickjacking and Drive-by Download Attacks

the advent of the World Wide Web the whole world became closure to each other. Further it has provided a medium to socialise over long distances. This has further abated the growth of many social media platforms. The social media platforms have brought many, even the non tech-savvy user on the internet. So, social media platform users have become an easy targets of the attackers and hackers who exploit the vulnerabilities of users, including the web browsers. Clickjacking and drive-by downloads have become a popular tools through which the attackers try to exploit the users. This paper takes a look at the different systems that have been proposed to detect, mitigate and prevent clickjacking and drive-by download attacks.
Semiparametric inference in matched case-control studies with missing covariate data

We consider the problem of matched studies with a binary outcome that are analysed using conditional logistic regression, and for which data on some covariates are missing for some study participants. Methods for this problem involve either modelling the distribution of missing covariates or modelling the probability of data being missing. For this second approach, the previously proposed method did not make use of data for those persons with missing covariate data except in the model for the missingness. We propose a new class of estimators that use outcome and available covariate data for all study participants, and show that a particular member of this class always has better efficiency than the previously proposed estimator. We illustrate the efficiency gains that are possible with our approach using simulated data. Copyright Biometrika Trust 2002, Oxford University Press.
Wear and its effects on dental topography measures in howling monkeys (Alouatta palliata).

OBJECTIVES Three dental topography measurements: Dirichlet Normal Energy (DNE), Relief Index (RFI), and Orientation Patch Count Rotated (OPCR) are examined for their interaction with measures of wear, within and between upper and lower molars in Alouatta palliata. Potential inferences of the "dental sculpting" phenomenon are explored. MATERIALS AND METHODS Fifteen occluding pairs of howling monkey first molars (15 upper, 15 lower) opportunistically collected from La Pacifica, Costa Rica, were selected to sample wear stages ranging from unworn to heavily worn as measured by the Dentine Exposure Ratio (DER). DNE, RFI, and OPCR were measured from three-dimensional surface reconstructions (PLY files) derived from high-resolution CT scans. Relationships among the variables were tested with regression analyses. RESULTS Upper molars have more cutting edges, exhibiting significantly higher DNE, but have significantly lower RFI values. However, the relationships among the measures are concordant across both sets of molars. DER and EDJL are curvilinearly related. DER is positively correlated with DNE, negatively correlated with RFI, and uncorrelated with OPCR. EDJL is not correlated with DNE, or RFI, but is positively correlated with OPCR among lower molars only. DISCUSSION The relationships among these metrics suggest that howling monkey teeth adaptively engage macrowear. DNE increases with wear in this sample presumably improving food breakdown. RFI is initially high but declines with wear, suggesting that the initially high RFI safeguards against dental senescence. OPCR values in howling monkey teeth do not show a clear relationship with wear changes.
Open(ed) Classroom – Who cares?

Social Media werden zunehmend auch im Rahmen formaler Lernsettings eingesetzt. Teilweise werden hierbei bereits die Moglichkeiten von Social Media zur Offnung von Lernsettings uber die ursprunglichen Adressaten hinaus genutzt. Durch diese Offnung von Lernraumen entstehen neue Anreize zum sozialen Austausch. Doch was geschieht, wenn immer mehr Individuen am Austausch teilhaben (konnen)? Werden die neuen potentiellen Austauschpartner wahrgenommen? Und bedeuten «mehr Austauschpartner» gleichzeitig auch grosseren Lernerfolg? Um Antworten auf diese Fragen zu finden, wurde eine theoretisch hergeleitete Wahrnehmungstaxonomie entwickelt, welche in einem ersten Setting uberpruft wurde. Die Ergebnisse der Untersuchung geben Hinweise darauf, dass Lernende in geoffneten Lernsettings die neuen potentiellen Austauschpartner wahrnehmen. Die weiteren Dimensionen der Taxonomie, Perspektive und Group Awareness, tragen ebenfalls signifikant zum Ergebnis bei. Dieser Artikel skizziert die theoretische Herleitung der Wahrnehmungstaxonomie, fasst die zentralen Untersuchungsergebnisse zusammen und gibt Impulse fur Folgestudien.
Algebraic quantum gravity (AQG): I. Conceptual setup

We introduce a new top down approach to canonical quantum gravity, called algebraic quantum gravity (AQG). The quantum kinematics of AQG is determined by an abstract *-algebra generated by a countable set of elementary operators labelled by an algebraic graph. The quantum dynamics of AQG is governed by a single master constraint operator. While AQG is inspired by loop quantum gravity (LQG), it differs drastically from it because in AQG there is fundamentally no topology or differential structure. A natural Hilbert space representation acquires the structure of an infinite tensor product (ITP) whose separable strong equivalence class Hilbert subspaces (sectors) are left invariant by the quantum dynamics. The missing information about the topology and differential structure of the spacetime manifold as well as about the background metric to be approximated is supplied by coherent states. Given such data, the corresponding coherent state defines a sector in the ITP which can be identified with a usual QFT on the given manifold and background. Thus, AQG contains QFT on all curved spacetimes at once, possibly has something to say about topology change and provides the contact with the familiar low energy physics. In particular, in two companion papers we develop semiclassical perturbation theory for AQG and LQG and thereby show that the theory admits a semiclassical limit whose infinitesimal gauge symmetry agrees with that of general relativity. In AQG everything is computable with sufficient precision and no UV divergences arise due to the background independence of the fundamental combinatorial structure. Hence, in contrast to lattice gauge theory on a background metric, no continuum limit has to be taken. There simply is no lattice regulator that must be sent to zero.
Wheat Canopy Structure and Surface Roughness Effects on Multiangle Observations at L-Band

The multiangle observation capability of the Soil Moisture and Ocean Salinity mission is expected to significantly improve the inversion of soil microwave emissions for soil moisture, by enabling the simultaneous retrieval of the vegetation optical depth and other surface parameters. Consequently, this paper investigates the relationship between soil moisture and brightness temperature at multiple incidence angles using airborne L-band data from the National Airborne Field Experiment in Australia in 2005. A forward radio brightness model was used to predict the passive microwave response at a range of incidence angles, given the following inputs: 1) ground-measured soil and vegetation properties and 2) default model parameters for vegetation and roughness characterization. Simulations were made across various dates and locations with wheat cover and evaluated against the available airborne observations. The comparison showed a significant underestimation of the measured brightness temperatures by the model. This discrepancy subsequently led to soil moisture retrieval errors of up to 0.3 m3/m3. Further analysis found the following: 1) The roughness value HR was too low, which was then adjusted as a function of the soil moisture, and 2) the vegetation structure parameters tth and ttv required optimization, yielding new values of tth = 0.2 and ttv = 1.4 from calibration to a single flight. Testing the optimized parameterization for different moisture conditions and locations found that the root-mean-square simulation error between the forward model predictions and the airborne observations was improved from 31.3 K (26.5 K) to 2.3 K (5.3 K) for wet (dry) soil moisture condition.
The Effects of a Single Bout of Exercise on Mood and Self-Esteem in Clinically Diagnosed Mental Health Patients

Objectives: Research has highlighted the importance of regular exercise within the general population and mental health groups in regard to mood and self-esteem, as well as single bout exercise within the general population. However, research into single bout exercise in mental health population is lacking. This study investigated the impact of a single bout of exercise, on mood and self-esteem, in patients with a wider clinical mental health diagnosis. Design: A quantitative questionnaire was completed immediately pre and post a single, 45 minute bout of moderate intensity exercise, consisting of the Brunel Universal Mood States (BRUMS) questionnaire and the Rosenberg Self Esteem Scale (RSE). Methods: Participants attending a mental health hospital with a clinical mental health diagnosis (N = 54) completed the questionnaire. Information regarding physical activity levels, mental health diagnosis and length of hospital stay were collated. Results: A significant improvement was identified on the RSE as well as the BRUMS (depression, anger, confusion, anxious tension and vigour) over time. Conclusion: The significant findings highlight the importance of exercise promotion within this population group, and the potentially beneficial role that a single bout of exercise can have on mood and self-esteem in patients experiencing mental health problems.
Metacognitive Training at Home: Does It Improve Older Adults’ Learning?

Background: Previous research has described the success of an intervention aimed at improving older adults’ ability to regulate their learning. This metacognitive approach involves teaching older adults to allocate their study time more efficiently by testing themselves and restudying items that are less well learned. Objective: Although this type of memory intervention has shown promise, training older adults to test themselves in the laboratory can be very time-intensive. Thus, the purpose of the present study is to transport the self-testing training method from the laboratory to home use. Methods: A standard intervention design was used that included a pretraining session, multiple training sessions, and a posttraining session. Participants were randomly assigned to either the training group (n = 29) or the waiting list control group (n = 27). Moreover, we screened participants for whether they used the self-testing strategy during their pretraining test session. Results: Compared to the performance of the control group, the training group displayed significant gains, which demonstrates that older adults can benefit from training themselves to use these skills at home. Moreover, the results of the present study indicate that this metacognitive approach can effectively improve older adults’ learning, even in those who spontaneously self-test prior to training. Conclusions: Training metacognitive skills, such as self-testing and efficient study allocation, can improve the ability to learn new information in healthy older adults. More importantly, older adult clients can be supplied with an at-home training manual, which will ease the burden on practitioners.
Customer requirements based ERP customization using AHP technique

Purpose– Customization is a difficult task for many organizations implementing enterprise resource planning (ERP) systems. The purpose of this paper is to develop a new framework based on customers’ requirements to examine the ERP customization choices for the enterprise. The analytical hierarchy process (AHP) technique has been applied complementarily with this framework to prioritize ERP customization choices. Design/methodology/approach– Based on empirical literature, the paper proposed an ERP customization framework anchored on the customer's requirements. A case study research method was used to evaluate the applicability of the framework in a real-life setting. In a case study with 15 practitioners working on the vendor's and the client's sides in an ERP implementation, the paper applied the framework jointly with the AHP technique to prioritize the feasible customization choices for ERP implementation. Findings– The paper demonstrates the applicability of the framework in identifying the various feasible choices for the client organization to consider when they decide to customize their selected ERP product. Research limitations/implications– Further case studies need to be carried out in various contexts to acquire knowledge about the generalizability of the observations. This will also contribute to refining the proposed ERP customization framework. Practical implications– Very few literature sources suggest methods for exploring and evaluating customization options in ERP projects from requirements engineering perspective. The proposed framework helps practitioners and consultants anchor the customization decisions on the customer's requirements and use a well-established prioritization technique, AHP, to identify the feasible customization choices for the implementing enterprise. Originality/value– No previously published research studies provide an approach to prioritize customization choices for ERP anchored on the customer's requirements.
A Semantic Kernel for Semi-structured DocumentS

Natural Language Processing has emerged as an active field of research in the machine learning community. Several methods based on statistical information have been proposed. However, with the linguistic complexity of the texts, semantic-based approaches have been investigated. In this paper, we propose a Semantic Kernel for semi- structured biomedical documents. The semantic meanings of words are extracted using the UMLS framework. The kernel, with a SVM classifier, has been applied to a text categorization task on a medical corpus of free text documents. The results have shown that the Semantic Kernel outperforms the Linear Kernel and the Naive Bayes classifier. Moreover, this kernel was ranked in the top ten of the best algorithms among 44 classification methods at the 2007 CMC Medical NLP International Challenge.
A Microstrip Bandpass Filter With Ultra-Wide Stopband

This paper develops a novel microstrip bandpass filter with ultra-wide stopband. With the assistance of open stubs and interdigital capacitors, a very wide stopband with a sufficient rejection level can be achieved easily. Detailed design and synthesis procedures are provided. Moreover, the electromagnetic simulator IE3D is used, and the prototype of the bandpass filter is fabricated and measured. Good agreement between measured and theoretically predicted results demonstrates feasibility of the proposed filter.
Feasibility of low-dose coronary CT angiography: first experience with prospective ECG-gating.

AIMS To determine the feasibility of prospective electrocardiogram (ECG)-gating to achieve low-dose computed tomography coronary angiography (CTCA). METHODS AND RESULTS Forty-one consecutive patients with suspected (n = 35) or known coronary artery disease (n = 6) underwent 64-slice CTCA using prospective ECG-gating. Individual radiation dose exposure was estimated from the dose-length product. Two independent readers semi-quantitatively assessed the overall image quality on a five-point scale and measured vessel attenuation in each coronary segment. One patient was excluded for atrial fibrillation. Mean effective radiation dose was 2.1 +/- 0.6 mSv (range, 1.1-3.0 mSv). Image quality was inversely related to heart rate (HR) (57.3 +/- 6.2, range 39-66 b.p.m.; r = 0.58, P < 0.001), vessel attenuation (346 +/- 104, range 110-780 HU; r = 0.56, P < 0.001), and body mass index (26.1 +/- 4.0, range 19.1-36.3 kg/m(2); r = 0.45, P < 0.001), but not to HR variability (1.5 +/- 1.0, range 0.2-5.1 b.p.m.; r = 0.28, P = 0.069). Non-diagnostic CTCA image quality was found in 5.0% of coronary segments. However, below a HR of 63 b.p.m. (n = 28), as determined by receiver operator characteristic curve, only 1.1% of coronary segments were non-diagnostic compared with 14.8% with HR of >63 b.p.m. (P < 0.001). CONCLUSION This first experience documents the feasibility of prospective ECG-gating for CTCA with diagnostic image quality at a low radiation dose (1.1-3.0 mSv), favouring HR <63 b.p.m.
Rate-Distortion Optimized Frame Dropping Based on Dynamic Frame Concealment

In most existing rate-distortion optimized frame dropping schemes, the concealment dependencies among frames are presumed, which artificially prioritizes frames with a fixed pattern. However, a fixed frame concealment pattern cannot always meet the actual priorities among frames. In this paper, we propose a novel rate-distortion optimized video frame dropping scheme, where the frame concealment pattern is dynamically determined according to the side information sent along with video data. The output of the proposed frame dropping scheme contains not only an optimal frame dropping pattern, but also a frame concealment pattern. Simulation results show that the quality of the reconstructed video in the receiver is greatly improved by the frame concealment pattern for the dropped frames, at the cost of a little overhead in side information.