Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmented Reality Tangible Interface for Distributed Design Review

Design review is a crucial step in the product creation process (PCP). In a design review, CAD software is often used to show the design result, however, CAD software's interface complexity frequently prevents diverse team members from directly interacting with the CAD models. This is further exacerbated when the design review is conducted in distributed fashion. The goal of this paper is to consider an alternative to 2D desktop based interfaces for design review, called augmented tangible interface (ATI). Moreover, as a continuation of our previous work, this paper describes the use and the implementation of the ATI for distributed design review
Evaluating the LEGO interface with experts

This work presents the results from a joint usability study concerning the LEGO programming environment, called "RoboLab". LEGO has already performed numerous evaluations concerning various usability aspects, aimed to enhance the overall usability and utility of the product. This study focuses on a more academic parameter, namely the combination of different evaluation methods on the same software piece, as well as on the combination of their results. So, two expert-based methods have been applied, a Cognitive Graphical Walktrough and a Heuristic Evaluation, at the Department of Informatics of the Aristotle University. The results of the study unveiled some deficiencies of the interface and some limitations of the employed methods as well.
The Influence of the Organizational Justice and Trust to the Leaders on Employee Engagement with Job Satisfaction as Intervening Variable

This study aimed to analyze the influence of organizational justice and trust to the leaders on employee engagement, with job satisfaction as an intervening variable. The research was conducted by taking samples of employees from Jabodetabek companies. Primary data were obtained by questionnaire filled by the respondents, then analyzed with simultaneous equations models and processed by AMOS program. The results showed that organizational justice has a significant effect on trust to the leaders. Organizational justice and trust to the leaders have a significant effect on employee job satisfaction. Employees' satisfaction influences significantly employee engagement, while organizational justice and trust to the leaders do not significantly influence employee engagement. It can be concluded that organizational justice and trust to the leaders do not directly influence employee engagement, but through job satisfaction as an intervening variable.
Fluid Simulation for High Speed Networks 1

We propose to use uid model based time-driven simulation to simulate high speed networks. For single class uid in feedforward networks, we prove that the error introduced by discretizing a uid model is within a deterministic bound proportional to the discretization interval length and is not related to the network size. We show that uid simulation ooers the exibility to trade accuracy for eeciency, and it is also easy to parallelize. These features enable us to speed up simulation by orders of magnitude compared to the event-driven simulation.
Frame Dispatcher: A Multi-frame Classification System for Social Movement by Using Microblogging Data

Framing is a phenomenon that is studied and debated widely in sociology and political science. It refers to the manner in which audiences interpret information and justify their claims or activities. The subconscious influence of framing might lead to opinion changes and social movements. However, multi-frame classification on microblogging data has not yet been investigated. In this study, we aim to classify a large number of posts into frames. We describe in detail the implementation of a new algorithm for multi-frame classification tasks called Frame Dispatcher, which aims to classify microblogging data into frames. In our experiments, we extracted over 15,000 posts from approximately 200 Facebook fan pages concerning an anti-curriculum student movement. The experimental results show that Frame Dispatcher can classify microblogging data into frames efficiently and effectively.
Iterative unsupervised object detection system

Current object detection systems provide good results, at the expense of requiring a large training database. This paper presents an unsupervised iterative object detection system using a selection of previously detected objects in order to perform new object detection. Our experiments show that this method enables face detection with a greatly reduced set of examples and outperforms the detection rates of our non iterative detection system based on normalized cross-correlation and affine deformation compensation.
Using Models of Score Distributions in Information Retrieval

Empirical modeling of a number of different text search engines shows that the score distributions on a per query basis may be fitted approximately using an exponential distribution for the set of nonrelevant documents and a normal distribution for the set of relevant documents. This model fits not only probabilistic search engines like INQUERY but also vector space search engines like SMART and also LSI search engines. The model also appears to be true of search engines operating on a number of different languages. This leads to the hypothesis that all ’good’ text search engines operating on any language have similar characteristics. The question then arises as to whether the shape of the score distributions reflects some underlying model of language or the search process itself. We discuss how they arise given certain assumptions about word distributions in documents. We then show that given a query for which relevance information is not available, a mixture model consisting of an exponential and a normal distribution can be fitted to the score distribution. These distributions can be used to map the scores of a search engine to probabilities. This model has many possible applications. For example, the outputs of different search engines can be combined by averaging the probabilities (optimal if the search engines are independent) or by using the probabilities to select the best engine for each query. Results show that the technique performs as well as the best current combination techniques. A number of different IR tasks may benefit from score modeling including filtering, multi-lingual retrieval and relevance feedback. We also discuss possible future improvements to the process of score modeling.
A review of hot executive functions in preschoolers

Executive functions (EF), a term used to refer to a large number of abilities involved in self-regulation, has become an important focus of research in early development. A distinction between cool and hot EF is often made based on whether a problem involves abstract versus motivational aspects. While research on cool EF in preschoolers is abundant, relatively little work has been done on hot EF abilities. The current paper focuses primarily on research utilizing two hot EF tasks: the delay of gratification task (Mischel et al. 1989) and preschool variants of the Iowa Gambling task (Bechara et al. 1994). The pattern of findings clearly indicate age improvements in hot EF during the preschool period. Finally, processes involved in hot EF tasks are placed into the broader context of early EF and self-regulation and areas warranting future research are discussed.
Elliptic differential equations with measurable coefficients

We prove the unique solvability of second order elliptic equations in non-divergence form in Sobolev spaces. The coefficients of the second order terms are measurable in one variable and VMO in other variables. From this result, we obtain the weak uniqueness of the martingale problem associated with the elliptic equations.
Complementary and Alternative Medicine: A Survey of Its Use in Pediatric Oncology

Background. The use of complementary and alternative medicine (CAM) is high among children and youths with chronic illnesses, including cancer. The objective of this study was to assess prevalence and patterns of CAM use among pediatric oncology outpatients in two academic clinics in Canada. Procedure. A survey was developed to ask patients (or their parents/guardians) presenting to oncology clinics at the Stollery Children's Hospital in Edmonton and the Children's Hospital of Eastern Ontario (CHEO) in Ottawa about current or previous use of CAM products and practices. Results. Of the 137 families approached, 129 completed the survey. Overall CAM use was 60.5% and was not significantly different between the two hospitals. The most commonly reported reason for not using CAM was lack of knowledge about it. The most common CAM products ever used were multivitamins (86.5%), vitamin C (43.2%), cold remedies (28.4%), teething remedies (27.5%), and calcium (23.0%). The most common CAM practices ever used were faith healing (51.0%), massage (46.8%), chiropractic (27.7%), and relaxation (25.5%). Many patients (40.8%) used CAM products at the same time as prescription drugs. Conclusion. CAM use was high among patients at two academic pediatric oncology clinics. Although most respondents felt that their CAM use was helpful, many were not discussing it with their physicians.
Recovery of function in osteoarthritic chondrocytes induced by p16INK4a-specific siRNA in vitro.

OBJECTIVE To demonstrate the roles of p16(INK4a) in the senescence of human chondrocytes and the progression of osteoarthritis (OA). METHODS Immunohistochemistry and reverse transcriptase polymerase chain reaction (RT-PCR) were performed to examine p16(INK4a) expression in fetal, normal age-matched and OA cartilage, and Western blot was used in primary cultured chondrocytes from different origins. To explore a functional p16(INK4a) knockdown in OA chondrocytes, the primary cultured cells were treated with p16(INK4a)-specific small interfering ribonucleic acids (siRNAs). Expression of p16(INK4a), p14(ARF) and p53 was observed by Western blot and RT-PCR. The phosphorylation status of pRb, senescence-associated beta-galactosidase (SA-beta-gal), cell G1/S transition and cell proliferation were studied by Western blot, histological staining, 3H-thymidine incorporation and cell counts respectively. Expression of the collagen I, collagen II and aggrecan genes was measured by semiquantitative RT-PCR. To establish the response of chondrocytes to cytokines, cells were treated with transforming growth factor-beta1 (TGF-beta1) or interleukin-1alpha (IL-1alpha) and examined for incorporation of 3H-thymidine, 3H-proline and 35S-sulphate respectively. RESULTS A significant increase of p16(INK4a) was detected in OA chondrocytes compared with normal age-matched and fetal chondrocytes (P<0.01) in vivo and in vitro. Treated with p16(INK4a)-specific siRNAs, OA chondrocytes displayed a significant decrease in p16(INK4a) expression with an increase of phosphorylated pRb, but no alteration of p14(ARF) and p53 expression, followed by decreases of senescent features and increases in the expression of some chondrocyte-specific genes and overall repair capacity. CONCLUSIONS p16(INK4a) is instrumental in the senescence of human articular chondrocytes or OA. The reduction of p16(INK4a) by RNA interference (RNAi) contributed to the recovery of osteoarthritic chondrocytes, suggesting that p16(INK4a) may be a viable future therapeutic candidate.
Preliminary results for a force feedback bimanual rehabilitation system

Stroke, a cardiovascular disease, is causing an increasingly heavy financial and medical load in modern societies. Yet the current therapeutic alternatives leave many individuals with stroke with limited ability to sustain an independent lifestyle. In turn, stroke survivors' quality of life is significantly diminished. Physical therapy is considered the main course of treatment for individuals with chronic stroke. Predominantly, research in rehabilitation investigates methods aiming to maximize the treatment benefits to patients. A novel Bimanual Wearable Robotic Device (BWRD) and protocol are proposed for the rehabilitation of stroke patients. The BWRD is composed of Master and Slave devices for the non-paretic and paretic upper limbs respectively. While the non-paretic arm controls the paretic arm in position, force feedback from the paretic arm, providing an indication of impairment, is sent back to the non-paretic arm. In this preliminary study, three participants with chronic unilateral stroke were recruited to participate in a total of three sessions per participant. To evaluate the effects of the BWRD, participants underwent pre and post training functional assessments. In addition we explored the neurobiological effects of this therapy using indices of brain excitability (Transcranial Magnetic Stimulation (TMS)), brain activity (Electroencephalography (EEG)) and muscle activation (Electromyography (EMG)). This work presents preliminary results. Following bimanual training, we measured an increase in excitability of both hemispheres as well as reduced inhibition as measured by Transcallosal Inhibition Laterality Index (TCI LI). The presented data supports and validates the approach implemented with the BWRD.
Mixing time of surface active agent solutions

One of the basic properties of the surfactant solutions is their ability to reduce the interfacial tension and form the micelle associates. The phenomenon depends on the surfactant concentration in a solution and surfactant structure as well as on the kind and the concentration of salt present. The paper deals with the experimental studies directed to mixing time in drag reducing micellar solutions. It has been shown that in TTAB/NaSal aqueous solutions agitated the dumping of turbulent vortex in microscale exists. The effects of the decrease of mass transport in the tank volume and increase of the mixing time, have been observed too.
Combining Powers of Two Predictors in Optimizing Real-Time Bidding Strategy under Constrained Budget

We address the bidding strategy design problem faced by a Demand-Side Platform (DSP) in Real-Time Bidding (RTB) advertising. A RTB campaign consists of various parameters and usually a predefined budget. Under the budget constraint of a campaign, designing an optimal strategy for bidding on each impression to acquire as many clicks as possible is a main job of a DSP. State-of-the-art bidding algorithms rely on a single predictor, namely the clickthrough rate (CTR) predictor, to calculate the bidding value for each impression. This provides reasonable performance if the predictor has appropriate accuracy in predicting the probability of user clicking. However when the predictor gives only moderate accuracy, classical algorithms fail to capture optimal results. We improve the situation by accomplishing an additional winning price predictor in the bidding process. In this paper, a method combining powers of two prediction models is proposed, and experiments with real world RTB datasets from benchmarking the new algorithm with a classic CTR-only method are presented. The proposed algorithm performs better with regard to both number of clicks achieved and effective cost per click in many different settings of budget constraints.
A new Kernelized Fuzzy Possibilistic C-Means for high dimensional data clustering based on kernel-induced distance measure

Data clustering is most commonly used in several clustering applications. Due to the fast development of the internet and its applications, several high dimensional data clustering algorithms has come into existence. It is very complicated to handle high dimensional data clustering by using the traditional clustering algorithms. Hence, in order to overcome this difficulty, a Kernelized Fuzzy Possibilistic C-Means (KFPCM) algorithm has been proposed for effective clustering results. The proposed KFPCM uses a distance measure which is based on the Kernel-Induced Distance Measure. FPCM combines the advantages of both FCM and PCM, moreover the Kernel-Induced Distance measure helps in obtaining better clustering results in case of high dimensional data. The proposed KFPCM is evaluated using the UCI Machine Learning Repository (Iris and Wine dataset) in terms of clustering accuracy and execution time. The results prove the effectiveness of the proposed KFPCM.
10 4 v 2 5 N ov 2 00 3 Properties of Kaluza-Klein black holes

We detail numerical methods to compute the geometry of static vacuum black holes in 6 dimensional gravity compactified on a circle. We calculate properties of these Kaluza-Klein black holes for varying mass, while keeping the asymptotic compactification radius fixed. For increasing mass the horizon deforms to a prolate ellipsoid, and the geometry near the horizon and axis decompactifies. We are able to find solutions with horizon radii approximately equal to the asymptotic compactification radius. Having chosen 6-dimensions, we may compare these solutions to the non-uniform strings compactified on the same radius of circle found in previous numerical work. We find the black holes achieve larger masses and horizon volumes than the most non-uniform strings. This sheds doubt on whether these solution branches can merge via a topology changing solution. Further work is required to resolve whether there is a maximum mass for the black holes, or whether the mass can become arbitrarily large. hep-th/0310104 DAMTP-2003-103 KUNS-1872 e-mail: kudoh@yukawa.kyoto-u.ac. jp e-mail: twiseman@fas.harvard. edu
THE NATURAL FLOW REGIME. A PARADIGM FOR RIVER CONSERVATION AND RESTORATION

H umans have long been fascinated by the dynamism of free-flowing waters. Yet we have expended great effort to tame rivers for transportation, water supply, flood control, agriculture, and power generation. It is now recognized that harnessing of streams and rivers comes at great cost: Many rivers no longer support socially valued native species or sustain healthy ecosystems that provide important goods and services (Naiman et al. 1995, NRC 1992).
Modeling First-Order Bayesian Networks (FOBN)

Bayesian networks provide an elegant formalism to perform inferences under uncertainty. Their shortcoming of being propositional in nature, however, restricts their expressive power and restrains their use in domains where number of instances may vary from situation to situation. First-order Logic (FOL), on the other hand, enjoys that power of expressiveness but is deterministic in nature. Integration of Bayesian networks and first-order logic provides powerful mechanism to capture and process domains that are truly dynamic and non-deterministic. The paper explores and compares three different probabilistic languages, namely Bayesian Logic Program (BLP), Bayesian Logic (BLOG) and Multi-Entity Bayesian Network (MEBN) that provide support to develop First Order Bayesian Networks (FOBN). The study identifies key characteristics that are prevalent in all three languages and compares their relative strengths and weaknesses.
A new signal for scalar top bound state production

We study the production and decay of a scalar \stst\ bound state \sigst\ at hadron supercolliders, where \st\ is the lighter stop eigenstate. If \st\ has no tree--level 2--body decays, the dominant decay modes of \sigst\ are $gg$ or, if $m_h<\mst \ll \mstt$, a pair of light scalar Higgs bosons $h$. Nevertheless the branching ratio into two photons is often large enough to yield a detectable signal.
Robust Data Mining: An Integrated Approach

The continuous improvement and application of information system technologies have become widely recognized by the industry as critical for maintaining a competitive advantage in the marketplace (Shin et al., 2006). It is also recognized that improvement and application activities are the most efficient and cost-effective when implemented during an early process/product design stage. Data mining (DM) has emerged as one of the key features of many applications in computer science. Often used as a means for predicting the future directions and extracting hidden limitations and specifications of a product/process, DM involves the use of data analysis (DA) tools to discover previously unknown and valid patterns and relationships from a large database. Most DM methods for factor selection reported in literature may yield a number of factors associated with interesting response factors without providing detailed information, such as relationships between the input factor and response, statistical inferences, and analyses (Yang et al., 2007; Witten & Frank, 2005). Based on this, Gardner and Bieker (Gardner & Bieker, 2000) suggested an alternative DA approach toward resolving semiconductor manufacturing problems in order to determine the significant factors. Furthermore, Su et al. (Su et al., 2005) developed an integrated procedure combining a DM method and Taguchi methods. DA is a term coined to describe the process of sifting through large databases for discovering interesting patterns and relationships. This field spans several disciplines such as databases, machine learning, intelligent information systems, statistics, and expert systems. Two approaches that enable the application of standard machine learning algorithms to large databases are factor selection and sampling. Factor selection is known to be an effective method for reducing dimensionality, removing irrelevant and redundant data, increasing mining accuracy, and improving result comprehensibility (Yu & Liu, 2003). Consequently, factor selection has been a fertile field for research and development since the 1970s and proven to be efficient in removing irrelevant and redundant features, increasing efficiency in mining tasks, improving mining performance like predictive accuracy, and enhancing comprehensibility of the learned results. The factor selection algorithm performs a search through the space of feature subsets (Allen, 1974). In general, two categories of the algorithm have been proposed to resolve the factor selection problem. The first category is based on a filter approach that is independent of the learning algorithms and serves as a filter to sieve out the irrelevant factors. The second category is based on a wrapper approach, which uses an induction algorithm itself as part of the function evaluating the factor subset (Langley, 1994). Since most of the filter methods are based on a heuristic O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
LLCPS: A new secure model for Internet of Things services based on the NFC P2P model

This paper presents a new secure model for NFC (Near Field Communication) services based on the P2P (Peer to Peer) mode. NFC is a proximity communication technology more and more supported by smartphones or consumer devices that seems a promising technology for the Internet of Things (IoT). It is used in applications such as payment, access control, transport and more generally for the exchange of small pieces of information. NFC P2P sessions are managed by the Logical Link Control Protocol (LLCP). We introduce LLCPS, a TLS security layer working over LLCP. This framework enforces data privacy and integrity; it also provides identity to smart objects, bound to certificates providing strong mutual authentications. Two experimental platforms are described built with NFC devices and smartphones.
Are iris crypts useful in identity recognition?

We conducted an experiment in which participants were asked to annotate the crypts they see in iris images. The results were used to assess the utility of crypts in identity recognition for forensic applications. Although the inter-participant annotation consistency may be limited by crypts' noticeability and the range of genuine similarity scores obtained by the adopted matcher is correlated to the number of crypt pixels in the given image, the intra-iris crypt perception is sufficiently consistent for nearly 95% of query images to be correctly identified. The performance is expected to be better for the professional examiners with comprehensive training.