Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Top-k Packages via Preference Elicitation

There are several applications, such as play lists of songs or movies, and shopping carts, where users are interested in finding top-k packages, consisting of sets of items. In response to this need, there has been a recent flurry of activity around extending classical recommender systems (RS), which are effective at recommending individual items, to recommend packages, or sets of items. The few recent proposals for package RS suffer from one of the following drawbacks: they either rely on hard constraints which may be difficult to be specified exactly by the user or on returning Pareto-optimal packages which are too numerous for the user to sift through. To overcome these limitations, we propose an alternative approach for finding personalized top-k packages for users, by capturing users' preferences over packages using a linear utility function which the system learns. Instead of asking a user to specify this function explicitly, which is unrealistic, we explicitly model the uncertainty in the utility function and propose a preference elicitation-based framework for learning the utility function through feedback provided by the user. We propose several sampling-based methods which, given user feedback, can capture the updated utility function. We develop an efficient algorithm for generating top-k packages using the learned utility function, where the rank ordering respects any of a variety of ranking semantics proposed in the literature. Through extensive experiments on both real and synthetic datasets, we demonstrate the efficiency and effectiveness of the proposed system for finding top-k packages.
Pornography object detection using Viola-Jones algorithm and skin detection

Pornography can be an image that contains obscenity or sexual exploitation, so unwittingly can damage human morals, especially for children who are certainly not old enough. This is an important task for the community in dealing with, handling, or avoiding this negative character of pornography. One prevention in order to avoid pornography is to create application to detect pornography object. The method used in this application are Viola-Jones algorithm and skin detection. In the process, this application produced Region of Interest (ROI) from the process of detecting pornography object using the Viola-Jones pornography object detector, and the ROI is further processed into the skin detection stage. The test results show that this application has been able to detect pornography objects from an image with test accuracy value reaching 78.29% and the best parameters of pornography object detector training is False Alarm Rate parameter with value 0.05 and Number of Stages parameter with value 10.
Fostering Dialogue or Monologue? Estonian Party Websites During the 2009 European Parliament Elections

This paper presents data from the analyses of political party web pages during the 2009 European Parliament elections in Estonia. It examines the presence and absence of web 2.0 features on the sites and aims to find out whether interactivity-based applications are used by parties to increase participation and to foster deliberative politics. Estonia as a small ex-Soviet country has emerged after the Soviet Union collapse as one of the most advanced e-societies in the world. Therefore, Estonia is chosen as a case study to explore whether and how decision makers use web 2.0 elements for fostering Habermasian dialogue between the citizens and the power holders in the society where technical obstacles for deliberative politics do not exist any longer. The results show that the Estonian parties still focus on the one-sided or top-down model of communication, based on web 1.0 features, even though all conditions for deliberation from the technical and infrastructural side in Estonia are fulfilled. The paper concludes with a discussion on the possible reasons parties might not be interested in using web 2.0 elements in their web campaign and how it might be linked to the conditions where citizens’ participation and interest in politics is low. There is also emphasis on the need for further systematic comparative research in order to draw conclusions on the changes in the online campaigning and political communication process in the era of cyber-democracy.
Hardware-accelerated point-based rendering of surfaces and volumes

In this paper, we present a fast GPU-based algorithm for ray-tracing point-based models, which includes an efficient computation of secondary and shadow rays, contrary to previous work which supported ray-surface intersections for primary rays only. Volumetric effects are added to the models by means of scattered data interpolation in order to combine point-based surface and volume rendering in the same scene. This allows us to obtain effects such as refraction within volumetric objects. The flexibility of our method is demonstrated by combining shadows, textured objects, refraction and volumetric effects in the same scene comprised uniquely by point sets.
Metabolism and Tissue Distribution of Orally Administered Trichloroethylene in Male and Female Rats: Identification of Glutathione- and Cytochrome P-450-Derived Metabolites in Liver, Kidney, Blood, and Urine

Male and female Fischer 344 rats were administered trichloroethylene (TRI) (2, 5, or 15 mmol/kg body weight) in corn oil by oral gavage, and TRI and its metabolites were measured at times up to 48 h in liver, kidneys, blood, and urine. Studies tested the hypothesis that gender-dependent differences in distribution and metabolism of TRI could help explain differences in toxicity. Higher levels of TRI were generally observed in tissues of males at lower doses. Complex patterns of TRI concentration, sometimes with multiple peaks, were observed in liver, kidneys, and blood of both males and females, consistent with enterohepatic recirculation. Higher concentrations of cytochrome P-450 (P450)-derived metabolites were observed in livers of males than in females, whereas the opposite pattern was observed in kidneys. Trichloroacetate was the primary P450-derived metabolite in blood and urine, although it generally appeared at later times than chloral hydrate. Trichloroethanol was also a significant metabolite in urine. S-(1,2-Dichlorovinyl)glutathione (DCVG) was recovered in liver and kidneys of female rats only and in blood of both males and females, with generally higher amounts found in females. S-(1,2-Dichlorovinyl)-l-cysteine (DCVC), the penultimate nephrotoxic metabolite, was recovered in male and female liver, female kidneys, male blood, and in urine of both males and females. The relationship between gender-dependent differences in distribution and metabolism of TRI and susceptibility to TRI-induced toxicity is discussed.
Interpolation Based Tracking for Fast Object Detection in Videos

Detecting objects in images and videos is very challenging due to i) large intra-class variety and ii) pose/scale variations. It is hard to build strong recognition engines for generic object categories, while applying them to large video collections is computationally infeasible (due to the explosion of frames to test). In this paper, we present a detection-by-interpolation framework, where object-tracking is achieved by interpolating between candidate object detections in a subset of the video frames. Given the location of an object in two frames of a video-shot, our algorithm tries to identify the locations of the object in the intermediate frames. We evaluate two tracking solutions based on greedy and dynamic programming approaches, and observe that a hybrid method gives significant performance boost as well as speedup in detection. On 6 hours of HD quality video, we were able to cut-down the detection time from 10000 hours to 1500 hours, while simultaneously improving the detection accuracy from 54% to 68%. As a result of this work, we build a dataset of 100,000 car images, spanning a wide range of viewpoints, scale and make, about 100 times larger than existing collections [2], [3].
Identifying pathways of teachers’ PCK development

Abstract This paper describes a method of analysing teacher growth in the context of science education. It focuses on the identification of pathways in the development of secondary school teachers’ pedagogical content knowledge (PCK) by the use of the interconnected model of teachers’ professional growth (IMTPG). The teachers (n = 12) participated in a one-year action research project focused on their individual concerns related to teaching science. The use of the IMTPG revealed that teachers use different pathways of learning to develop different aspects of their PCK. For each PCK component, three distinct pathways could be identified, two of which clearly were associated with professional growth. When examining these two pathways in detail, it was found that (1) teachers learned about new instructional strategies and assessment methods mostly through literature reviews and discussions with peers and (2) teachers who analyzed and reflected on student learning as it happened in their classrooms developed understandings that helped them to select and apply instructional strategies to further promote student learning. Both the analytical method as well as the identification of the different developmental pathways help to better understand teacher development in the context of classroom practices.
Protein Attributes Microtuning System (PAMS): an effective tool to increase protein structure prediction by data purification

Given the expense of more direct determinations, using machine-learning schemes to predict a protein secondary structure from the sequence alone remains an important methodology. To achieve significant improvements in prediction accuracy, the authors have developed an automated tool to prepare very large biological datasets, to be used by the learning network. By focusing on improvements in data quality and validation, our experiments yielded a highest prediction accuracy of protein secondary structure of 90.97%. An important additional aspect of this achievement is that the predictions are based on a template-free statistical modeling mechanism. The performance of each different classifier is also evaluated and discussed. In this paper a protein set of 232 protein chains are proposed to be used in the prediction. Our goal is to make the tools discussed available as services in part of a digital ecosystem that supports knowledge sharing amongst the protein structure prediction community.
New paradigm for segmentation and recognition of handwritten numeral string

String recognition is rather paradoxical problem because it requires the segmentation of the string into understandable units, but proper segmentation needs a-priori knowledge of the units and this implies a recognition capability. To solve this dilemma therefore, both a-priori knowledge of meaningful units and a segmentation method have to be used together, and they should dynamically interact with each other. In other words, the results of segmentation are used as fundamental information to suppose what is most likely to be, and then its a-priori knowledge is used to help the segmentation. This model makes explicit segmentation unnecessary because it does not speculate on possible break positions. It is also possible to recognize a digit even if it contains strokes that do not belong to to it. Using this paradigm for 100 handwritten numeral strings belonging to the NIST database has resulted in 95% recognition.
Sirius: An Open End-to-End Voice and Vision Personal Assistant and Its Implications for Future Warehouse Scale Computers

As user demand scales for intelligent personal assistants (IPAs) such as Apple's Siri, Google's Google Now, and Microsoft's Cortana, we are approaching the computational limits of current datacenter architectures. It is an open question how future server architectures should evolve to enable this emerging class of applications, and the lack of an open-source IPA workload is an obstacle in addressing this question. In this paper, we present the design of Sirius, an open end-to-end IPA web-service application that accepts queries in the form of voice and images, and responds with natural language. We then use this workload to investigate the implications of four points in the design space of future accelerator-based server architectures spanning traditional CPUs, GPUs, manycore throughput co-processors, and FPGAs. To investigate future server designs for Sirius, we decompose Sirius into a suite of 7 benchmarks (Sirius Suite) comprising the computationally intensive bottlenecks of Sirius. We port Sirius Suite to a spectrum of accelerator platforms and use the performance and power trade-offs across these platforms to perform a total cost of ownership (TCO) analysis of various server design points. In our study, we find that accelerators are critical for the future scalability of IPA services. Our results show that GPU- and FPGA-accelerated servers improve the query latency on average by 10x and 16x. For a given throughput, GPU- and FPGA-accelerated servers can reduce the TCO of datacenters by 2.6x and 1.4x, respectively.
Universal HIV Screening at Postnatal Points of Care: Which Public Health Approach for Early Infant Diagnosis in Côte d'Ivoire?

Background Universal HIV pediatric screening offered at postnatal points of care (PPOC) is an entry point for early infant diagnosis (EID). We assessed the parents' acceptability of this approach in Abidjan, Côte d'Ivoire. Methods In this cross-sectional study, trained counselors offered systematic HIV screening to all children aged 6–26 weeks attending PPOC in three community health centers with existing access to HAART during 2008, as well as their parents/caregivers. HIV-testing acceptability was measured for parents and children; rapid HIV tests were used for parents. Both parents' consent was required according to the Ivorian Ethical Committee to perform a HIV test on HIV-exposed children. Free HIV care was offered to those who were diagnosed HIV-infected. Findings We provided 3,013 HIV tests for infants and their 2,986 mothers. While 1,731 mothers (58%) accepted the principle of EID, only 447 infants had formal parental consent 15%; 95% confidence interval (CI): [14%–16%]. Overall, 1,817 mothers (61%) accepted to test for HIV, of whom 81 were HIV-infected (4.5%; 95% CI: [3.5%–5.4%]). Among the 81 HIV-exposed children, 42 (52%) had provided parental consent and were tested: five were HIV-infected (11.9%; 95% CI: [2.1%–21.7%]). Only 46 fathers (2%) came to diagnose their child. Parental acceptance of EID was strongly correlated with prenatal self-reported HIV status: HIV-infected mothers were six times more likely to provide EID parental acceptance than mothers reporting unknown or negative prenatal HIV status (aOR: 5.9; 95% CI: [3.3–10.6], p = 0.0001). Conclusions Although the principle of EID was moderately accepted by mothers, fathers' acceptance rate remained very low. Routine HIV screening of all infants was inefficient for EID at a community level in Abidjan in 2008. Our results suggest the need of focusing on increasing the PMTCT coverage, involving fathers and tracing children issued from PMTCT programs in low HIV prevalence countries.
Automation of Model-based Regression Testing Mr

Model-Based Testing is the automatic generation of efficient test procedures using models of system requirements and specified functionality. Model-based regression testing is an important activity that ensures the reliability of evolving software [1]. One of the major issues in this type of testing is the optimal selection of test-cases to test the affected portion of the software. Model-based selective regression testing promises reduction in cost and labour by selecting a subset of the test suite corresponding to the modifications after system evolution. Identification of such changes in modification and selection of test cases is very difficult task. In this paper, MBRT (Model Based Regression Testing) tool has been developed, which is a java base testing tool used for generation, reduction of test cases and also classify the test cases into obsolete, reusable and re-testable test cases which results in reduction in time and cost. In this paper use of class diagram and state machine diagram has been made for presenting the idea of regression testing and also use of flow graph to generate the test cases.
Detecting weak targets in a speckled distributed scene by SAR reconfiguration

In this paper a discussion on the difference between point-like targets and distributed scene in SAR images is presented starting from basic radar equations. The target detection requirements are formulated considering also the speckle characteristics of the distributed scattering of the background. An equation is presented for the estimation of the minimum radar cross section of a target to become detectable within a scene with speckled distributed background and detection criteria are discussed for the multi-look case. Experimental evaluations are based on airborne SAR data of a calibration test site.
Development of Chloroplast and Nuclear DNA Markers for Chinese Oaks (Quercus Subgenus Quercus) and Assessment of Their Utility as DNA Barcodes

Chloroplast DNA (cpDNA) is frequently used for species demography, evolution, and species discrimination of plants. However, the lack of efficient and universal markers often brings particular challenges for genetic studies across different plant groups. In this study, chloroplast genomes from two closely related species (Quercus rubra and Castanea mollissima) in Fagaceae were compared to explore universal cpDNA markers for the Chinese oak species in Quercus subgenus Quercus, a diverse species group without sufficient molecular differentiation. With the comparison, nine and 14 plastid markers were selected as barcoding and phylogeographic candidates for the Chinese oaks. Five (psbA-trnH, matK-trnK, ycf3-trnS, matK, and ycf1) of the nine plastid candidate barcodes, with the addition of newly designed ITS and a single-copy nuclear gene (SAP), were then tested on 35 Chinese oak species employing four different barcoding approaches (genetic distance-, BLAST-, character-, and tree-based methods). The four methods showed different species identification powers with character-based method performing the best. Of the seven barcodes tested, a barcoding gap was absent in all of them across the Chinese oaks, while ITS and psbA-trnH provided the highest species resolution (30.30%) with the character- and BLAST-based methods, respectively. The six-marker combination (psbA-trnH + matK-trnK + matK + ycf1 + ITS + SAP) showed the best species resolution (84.85%) using the character-based method for barcoding the Chinese oaks. The barcoding results provided additional implications for taxonomy of the Chinese oaks in subg. Quercus, basically identifying three major infrageneric clades of the Chinese oaks (corresponding to Groups Quercus, Cerris, and Ilex) referenced to previous phylogenetic classification of Quercus. While the morphology-based allocations proposed for the Chinese oaks in subg. Quercus were challenged. A low variation rate of the chloroplast genome, and complex speciation patterns involving incomplete lineage sorting, interspecific hybridization and introgression, possibly have negative impacts on the species assignment and phylogeny of oak species.
A Study on Teacher Questioning in English Major Classroom from the View of Scaffolding

Teacher questioning receives little attention from scholars of applied linguistics in China,even though it is known that teacher questioning lies in a significant role in foreign language classroom.The study attempts to probe the role of scaffolding of different questioning types and questioning strategies by observing and recording the two English major classrooms with different language competence.The author finds that teacher question which is put forward in the zone of the proximal development(ZPD) of students can enhance the language communicative ability and critical thinking to a large extent.Plus,there are some limitations on the study,which is in a position to provide a new angle and expects further researches on the teacher questioning.
Mitigating Multipath Bias Using a Dual-Polarization Antenna: Theoretical Performance, Algorithm Design, and Simulation

It is well known that multipath effect remains a dominant error source that affects the positioning accuracy of Global Navigation Satellite System (GNSS) receivers. Significant efforts have been made by researchers and receiver manufacturers to mitigate multipath error in the past decades. Recently, a multipath mitigation technique using dual-polarization antennas has become a research hotspot for it provides another degree of freedom to distinguish the line-of-sight (LOS) signal from the LOS and multipath composite signal without extensively increasing the complexity of the receiver. Numbers of multipath mitigation techniques using dual-polarization antennas have been proposed and all of them report performance improvement over the single-polarization methods. However, due to the unpredictability of multipath, multipath mitigation techniques based on dual-polarization are not always effective while few studies discuss the condition under which the multipath mitigation using a dual-polarization antenna can outperform that using a single-polarization antenna, which is a fundamental question for dual-polarization multipath mitigation (DPMM) and the design of multipath mitigation algorithms. In this paper we analyze the characteristics of the signal received by a dual-polarization antenna and use the maximum likelihood estimation (MLE) to assess the theoretical performance of DPMM in different received signal cases. Based on the assessment we answer this fundamental question and find the dual-polarization antenna’s capability in mitigating short delay multipath—the most challenging one among all types of multipath for the majority of the multipath mitigation techniques. Considering these effective conditions, we propose a dual-polarization sequential iterative maximum likelihood estimation (DP-SIMLE) algorithm for DPMM. The simulation results verify our theory and show superior performance of the proposed DP-SIMLE algorithm over the traditional one using only an RHCP antenna.
Design of Safety Education System for Children Based on Virtual Reality Technology

In this paper, a novel scheme on experienced safety education system for child is proposed based on virtual reality technology. The author constructed safety education system in application senses and discussed advantages over traditional technologies employing virtual reality technology and components of system, as well as functions of system. In this system, children can enrich all kinds of safety knowledge and learn skills protecting themselves with immersive feeling.