Miracle-dz/UniFAR-FTUs huggingface dataset:
A recognition of vehicle license plate using a genetic algorithm based segmentation

Extracting a license plate is an important stage in automatic vehicle identification. It is very difficult because vehicle images are usually degraded and processing the images is computationally intensive. We propose a new method to extract the plate region using a distributed genetic algorithm. The algorithm offers robustness in dealing with deformation of vehicle images and inherent parallelism to improve the processing time. A test with seventy images shows an extraction rate of 92.8%, working well within real world situations. This results suggest that the proposed method is pertinent to be put into practical use.
Music genre classification using self-taught learning via sparse coding

Availability of large amounts of raw unlabeled data has sparked the recent surge in semi-supervised learning research. In most works, however, it is assumed that labeled and unlabeled data come from the same distribution. This restriction is removed in the self-taught learning approach where unlabeled data can be different, but nevertheless have similar structure. First, a representation is learned from the unlabeled data via sparse coding and then it is applied to the labeled data used for classification. In this work, we implemented this method for the music genre classification task using two different databases: one as unlabeled data pool and the other for supervised classifier training. Music pieces come from 10 and 6 genres for each database respectively, while only one genre is common for both of them. Results from wide variety of experimental settings show that the self-taught learning method improves the classification rate when the amount of labeled data is small and, more interestingly, that consistent improvement can be achieved for a wide range of unlabeled data sizes.
White matter architecture of the language network

The relevance of anatomical connectivity for understanding of the neural basis of language was recognized in the 19th century, and yet this topic has only recently become the subject of wider research interest. In this paper, I review recent findings on white matter tracts implicated in language: the arcuate fasciculus, superior longitudinal fasciculus, extreme capsule, uncinate fasciculus, middle longitudinal fasciculus, inferior longitudinal fasciculus, and inferior fronto-occipital fasciculus. The reviewed findings on these tracts were reported in studies that used a variety of methods, from post-mortem dissection and diffusion imaging to intraoperative electrostimulation with awake surgery patients. The emerging picture suggests that there is currently no consensus with regard to the exact number and identity of the tracts supporting language, their origins, trajectories, and terminations, as well as their functional interpretation.
Compact UWB-MIMO antenna array with a novel decoupling structure

In this paper, a compact planar Ultra-Wideband (UWB) Multiple-input Multiple-output (MIMO) antenna array is proposed. This UWB-MIMO antenna array consists of two identical monopole antenna elements with a novel decoupling structure etched on the ground plane. The antenna performs very well over the UWB frequency range of 3.1-10.6 GHz. The decoupling structure improves the isolation between the antennas over the complete frequency band which can only be achieved otherwise by increasing the separation between the antenna elements. The analysis of antenna performance with and without stub is provided to demonstrate the significance of adding the decoupling stub to the design. The proposed compact and cost efficient antenna array system measures 27 × 47 mm2 only.
Efficient Browser Identification with JavaScript Engine Fingerprinting

For security and privacy on the Internet the webbrowser has become an important piece of software. Nowadays even mobil devices include a powerful browser, and in combination with cloud computing the webbrowser mimics more and more operating system functionality. For many use cases, legit server operators as well as attackers need to find out the exact version of a particular user’s webbrowser. While the user agent string (which is currently used for that purpose) can be easily manipulated, certain aspects of the underlying software cannot. In our approach we will use the deviance of Javascript engine implementations to identify the browser accurately. This approach is efficient and has low computational overhead, and might be used to identify the version of the webbrowser regardless of the possibly manipulated user agent string.
Assessment of prey overlap between a native (Polistes humilis) and an introduced (Vespula germanica) social wasp using morphology and phylogenetic analyses of 16S rDNA

In newly invaded communities, interspecific competition is thought to play an important role in determining the success of the invader and its impact on the native community. In southern Australia, the native Polistes humilis was the predominant social wasp prior to the arrival of the exotic Vespula germanica (Hymenoptera: Vespidae). Both species forage for similar resources (water, pulp, carbohydrate and protein prey), and concerns have arisen about potential competition between them. The aim of this study was to identify the protein foods that these wasps feed on. As many prey items are masticated by these wasps to the degree that they cannot be identified using conventional means, morphological identification was complemented by sequencing fragments of the mitochondrial 16S rRNA gene. GenBank searches using blast and phylogenetic analyses were used to identify prey items to at least order level. The results were used to construct complete prey inventories for the two species. These indicate that while P. humilis is restricted to feeding on lepidopteran larvae, V. germanica collects a variety of prey of invertebrate and vertebrate origin. Calculated values of prey overlap between the two species are used to discuss the implications of V. germanica impacting on P. humilis. Results obtained are compared to those gained by solely ‘conventional’ methods, and the advantages of using DNA‐based taxonomy in ecological studies are emphasized.
Ja n 20 00 Optimizing Traffic in Virtual and Real Space

We show how optimization methods from economics known as portfolio strategies can be used for minimizing download times in the Internet and travel times in freeway traffic. While for Internet traffic, there is an optimal restart frequency for requesting data, freeway traffic can be optimized by a small percentage of vehicles coming from on-ramps. Interestingly, the portfolio strategies can decrease the average waiting or travel times, respectively, as well as their standard deviation (“risk”). In general, portfolio strategies are applicable to systems, in which the distribution of the quantity to be optimized is broad. Virtual Traffic in the World Wide Web Anyone who has browsed the World Wide Web has probably discovered the following strategy: whenever a web page takes too long to appear, it is useful to press the reload button. Very often, the web page then appears instantly. This motivates the implementation of a similar but automated strategy for the frequent “web crawls” that many Internet search engines depend on. In order to ensure up-to-date indexes, it is important to perform these crawls quickly. More generally, from an electronic commerce perspective, it is also very valuable to optimize the speed and the variance in the speed of transactions, automated or not, especially when the cost of performing those transactions is taken into account. Again, restart strategies may provide measurable benefits for the user. The histogram in Figure 1 shows the variance associated with the download times for the text on the main page of over 40,000 web sites. Based on such observations, an economics-based strategy has recently been proposed for quantitatively managing the time of executing electronic transactions [1]. It exploits an analogy with the modern theory of financial portfolio management by associating cost with the time it takes to complete the transaction and taking into account the “risk” given by the standard deviation of that time. Before, such a strategy has already been successfully applied to the numerical solution of hard computational problems [2]. In modern portfolio theory, risk averse investors may prefer to hold assets from which they expect a lower return if they are compensated for the lower return with a lower level of risk exposure. Furthermore, it is a non-trivial result of portfolio theory that simple diversification can yield portfolios of assets which have higher expected return as well as lower risk. In the case of latencies (waiting times) on the Internet, thinking of different restart strategies is analogous to asset 2 Dirk Helbing, Bernardo A. Huberman, and Sebastian M. Maurer
Analyzing the Presence and Consequences of Unobserved Heterogeneity in Recidivism Research

This study extends research on recidivism by examining the phenomenon via a survival mixture modeling approach, a method that is analogous to mixture modeling approaches used in trajectory analyses. Using this approach, the authors discover that multiple recidivism profiles are identifiable within a random sample of inmates released from Florida prisons between January 1998 and June 2001. Findings revealed that certain covariates predicted class membership and operated differently across the groups in predicting the hazard of recidivism, suggesting that a unilateral approach to reducing recidivism risk is an ineffective strategy. The Discussion section presents the findings in the context of theory, research, and policy.
AP-1-mediated invasion requires increased expression of the hyaluronan receptor CD44

Fibroblasts transformed by Fos oncogenes display increased expression of a number of genes implicated in tumor cell invasion and metastasis. In contrast to normal 208F rat fibroblasts, Fos-transformed 208F fibroblasts are growth factor independent for invasion. We demonstrate that invasion of v-Fos- or epidermal growth factor (EGF)-transformed cells requires AP-1 activity. v-Fos-transformed cell invasion is inhibited by c-jun antisense oligonucleotides and by expression of a c-jun dominant negative mutant, TAM-67. EGF-induced invasion is inhibited by both c-fos and c-jun antisense oligonucleotides. CD44s, the standard form of a transmembrane receptor for hyaluronan, is implicated in tumor cell invasion and metastasis. We demonstrate that increased expression of CD44 in Fos- and EGF-transformed cells is dependent upon AP-1. CD44 antisense oligonucleotides reduce expression of CD44 in v-Fos- or EGF-transformed cells and inhibit invasion but not migration. Expression of a fusion protein between human CD44s and Aequorea victoria green fluorescent protein (GFP) in 208F cells complements the inhibition of invasion by the rat-specific CD44 antisense oligonucleotide. We further show that both v-Fos and EGF transformations result in a concentration of endogenous CD44 or exogenous CD44-GFP at the ends of pseudopodial cell extensions. These results support the hypothesis that one role of AP-1 in transformation is to activate a multigenic invasion program.
Particle swarm for attribute selection in Bayesian classification: an application to protein function prediction

The discrete particle swarm optimization (DPSO) algorithm is an optimization technique which belongs to the fertile paradigm of Swarm Intelligence. Designed for the task of attribute selection, the DPSO deals with discrete variables in a straightforward manner. This work empowers the DPSO algorithm by extending it in two ways. First, it enables the DPSO to select attributes for a Bayesian network algorithm, which is more sophisticated than the Naive Bayes classifier previously used by the original DPSO algorithm. Second, it applies the DPSO to a set of challenging protein functional classification data, involving a large number of classes to be predicted. The work then compares the performance of the DPSO algorithm against the performance of a standard Binary PSO algorithm on the task of selecting attributes on those data sets. The criteria used for this comparison are (1) maximizing predictive accuracy and (2) finding the smallest subset of attributes.
Tadzebao and WebOnto: discussing, browsing, and editing ontologies on the Web

In this paper I describe two systems which, in different ways, address the shortcomings of current approaches to enabling ontology construction and use via the World-Wide Web. The first system Tadzebao, enables knowledge engineers to hold synchronous and asynchronous discussions about ontologies. Tadzebao addresses the fact that an integral part of communal design, dialogue, has largely been ignored by the community. The second system WebOnto uses a Java based client to alleviate the acknowledged problems of creating interfaces in `vanilla HTML'.
A time domain spherical near-field measurement facility for UWB antennas employing a hardware gating technique

A spherical near-field antenna measurement facility employing a time domain hardware gating technique is presented. On-off keyed sinusoidal impulses are used as stimuli requiring wideband antennas with a bandwidth in excess of 400 MHz. The received signal is evaluated in the time interval after reaching the steady state and before multipath components arising in the non-ideal anechoic chamber distort the signal. An application specific pulse generator synthesizing sinusoidal impulses with a sub-nanosecond settling time and a low-cost equivalent time (ET) sampling receiver developed and optimized for this particular purpose are described. Measurement results of typical ultra-wideband (UWB) antennas show a significant improvement of the measured antenna pattern compared to conventional techniques.
When is scene recognition just texture recognition

Subjects were asked to discriminate scenes after very brief exposures (37-69 ms). Their performance was always above chance and increased with exposure duration, confirming that subjects can get the gist of a scene with one fixation. We propose that a simple texture analysis of the image can provide a useful cue towards rapid scene identification. Our model learns texture features across scene categories and then uses this knowledge to categorize new scenes. The texture analysis leads to similar categorizations and confusions as subjects with limited processing time. We conclude that a simple texture discrimination model mostly explains early scene identification.
Practical Path Guiding for Efficient Light‐Transport Simulation

We present a robust, unbiased technique for intelligent light‐path construction in path‐tracing algorithms. Inspired by existing path‐guiding algorithms, our method learns an approximate representation of the scene's spatio‐directional radiance field in an unbiased and iterative manner. To that end, we propose an adaptive spatio‐directional hybrid data structure, referred to as SD‐tree, for storing and sampling incident radiance. The SD‐tree consists of an upper part—a binary tree that partitions the 3D spatial domain of the light field—and a lower part—a quadtree that partitions the 2D directional domain. We further present a principled way to automatically budget training and rendering computations to minimize the variance of the final image. Our method does not require tuning hyperparameters, although we allow limiting the memory footprint of the SD‐tree. The aforementioned properties, its ease of implementation, and its stable performance make our method compatible with production environments. We demonstrate the merits of our method on scenes with difficult visibility, detailed geometry, and complex specular‐glossy light transport, achieving better performance than previous state‐of‐the‐art algorithms.
ADAPTIVE COLOR FILTER ARRAY INTERPOLATION ALGORITHM BASED ON HUE TRANSITION AND EDGE

Most of the digital cameras used now has single sen sor with an array of color filters to capture the d igital images. Color Filter Array (CFA) uses alternating c olor filters to sample only one color of a pixel lo cation to reduce the price. In the entire image, only one third of sampled pixels have genuine values from th e sensors. Remaining pixels are interpolated from the se genuine values. In this work, a new adaptive CF A interpolation model is proposed. Pixels are divided into edge pixels and non-edge pixels. If the pixel s not in an edge, then smooth hue transition interpolatio n is used. For the pixels in the edge, Edge sensing interpolation algorithm is used. A mathematical mod el is proposed for interpolation based on the direc tion of the edges. Two sample images are taken and recon structed by methods such as hue transition interpolation, edge sensing interpolation and combi ned approach. PSNR is used to compare the results o f proposed technique.
Representing Threats in BPMN 2.0

The Business Process Modeling Notation (BPMN) has become a broadly accepted standard for process modeling, but is mostly being used to express the normal execution flow of business processes. In some situations there is also a need to express threats and unwanted incidents on that same abstraction level, for example to show how deviations from normal process flow should be handled. Enriching BPMN with threat information enables a process-centric threat modeling approach that complements risk assessment and attack scenarios. Though there has been a substantial amount of work enhancing BPMN 1.x with security related information, the opportunities provided by version 2.0 have not received a lot of attention in the security community. This paper shows several options and the benefit of representing threats in BPMN 2.0 for design-time specification and runtime execution of composite services with dynamic behavior. Our goal is to avoid downtime and preserve the overall security and trustworthiness of the composite service in an ever-changing Internet of Services. We have included examples showing the use of error events, escalation events and text annotations for process, collaboration, choreography and conversion diagrams.
Reflections on Dobermanns, poodles, and social rehabilitation for difficult-to-serve individuals with traumatic brain injury

In workshops dealing with social rehabilitation of adolescents and young adults with brain injury, we often show a cartoon of a once proud Dobermann pinscher, now with a look of panic and despair in his eyes as he throws himself out of a second-story window. The caption reads, `The Dobermann threw himself out the second-storey window soon after he realized the family had indeed named him ``Binky’’. ’ Veterans of brain injury rehabilitation recognize immediately that the Dobermann represents that clinically challenging population of risk-taking adolescents and young adults who sometimes ®nd themselves after a severe brain injury in a situation that they interpret as binki®cationÐthe typically counterproductive process of attempting to transform tough Dobermanns into passive and `socially appropriate’ poodles. We follow this with a cartoon showing two dogs seated on a delicate pink Victorian settee. One of the dogs is a dainty poodle with freshly coiåed white hair. The other is a tough looking Dobermann-type dog with a frightening studded collar around his bull neck. The poodle is barking into the ear of Spike the Stud Dog, who has his eyes shut as tight as possible, resisting the dreaded words, `Spike, that behaviour is simply inappropriate! ’ Our comment : `This, folks, is binki®cation ; furthermore (pointing to Spike), this is the predictable result of illconceived binkifying attempts. ’ Although anybody at any age can have an accident that results in traumatic brain injury (TBI), the population is disproportionately dominated by adolescent and young adult males, many of whom led risky and sometimes checkered lives prior to their injury. The subpopulation to which we direct our attention in this article includes adolescents and young adults with TBI whose high degree of oppositionality and resistance to professional eåorts to shape their goals and behaviour create signi®cant challenges for rehabilitation specialists. Many, though not all, of these individuals demonstrated oppositional behaviour prior to their injury. We currently work with young adults with an additional pre-injury history of serious substance abuse and con ̄ict with the law, although this degree of antisocial behaviour is not part of our operational de®nition of `Dobermann’. In capitalizing on the metaphorical meaning oåered by the terms Dobermann
Congruence of student teachers' pedagogical images and actual classroom practices

An understanding of student teachers' pedagogical images plays an important role in helping teacher educators plan learning experiences. The purposes of this study were to obtain a profile of pedagogical images of a group of student teachers, and to assess whether there is congruence between their pedagogical images and classroom practices. Applying the conception of teaching model proposed by Pratt, Chan developed a questionnaire to evaluate teachers' views about teaching, which was modified here and administered to 59 first-year student teachers before and after their teaching practicum in physical education for secondary schools. Results indicated that the student teachers possess a Nurturing image, whereas in actual classroom practices, their approach was a mix between the Apprenticeship and the Transmission approaches. In other words, whereas student teachers conceive themselves as having a more child-centred approach to teaching, in reality, their practices constituted more a teacher-centred approach. The investigators considered that this type of information would be helpful for teacher educators when planning learning experiences.
The Effect of E-Commerce Websites' Colors on Customer Trust

Establishing customer trust in an online vendor requires the provision of an environment in which customers can overcome their fear and reluctance about shopping transactions by forming trust and positive perceptions about the online vendor. This paper studies the impact of the colors of e-commerce websites, as an atmospheric variable of the interface, on customer trust. The effect of the colors of e-commerce websites on customer trust has only been indirectly examined in terms of website characteristics, such as website quality and usability, where color is viewed as a key interface attribute. Thus, the relationship between color itself and trust remains largely under investigated. To address this gap, this paper presents an exploratory qualitative study on how customers develop trust in an online vendor, as a result of the colors of the e-commerce website. The empirical findings provide theoretical and practical implications regarding the effect of web stores color on trust.