Miracle-dz/UniFAR-FTUs huggingface dataset:
Password entry usability and shoulder surfing susceptibility on different smartphone platforms

Virtual keyboards of different smartphone platforms seem quite similar at first glance, but the transformation from a physical to a virtual keyboard on a small-scale display results in user experience variations that cause significant differences in usability as well as shoulder surfing susceptibility, i.e., the risk of a bystander observing what is being typed. In our work, we investigate the impact of both aspects on the security of text-based password entry on mobile devices. In a between subjects study with 80 participants, we analyzed usability and shoulder surfing susceptibility of password entry on different mobile platforms (iOS, Android, Windows Phone, Symbian, MeeGo). Our results show significant differences in the usability of password entry (required password entry time, typing accuracy) and susceptibility to shoulder surfing. Our results provide insights for security-aware design of on-screen keyboards and for password composition strategies tailored to entry on smartphones.
Infrared and Optical Observations of GRB 030115 and its Extremely Red Host Galaxy: Implications for Dark Bursts

We present near-infrared (NIR) and optical observations of the afterglow of GRB 030115. Discovered in an infrared search at Kitt Peak 5 hr after the burst trigger, this afterglow is the faintest ever observed in the R band at such an early epoch and exhibits very red colors, with R - K ≈ 6. The optical magnitude of the afterglow of GRB 030115 is fainter than many upper limits for other bursts, suggesting that without early NIR observations it would have been classified as a "dark" burst. Both the color and optical magnitude of the afterglow are likely due to dust extinction at moderate redshift z > 2 and indicate that at least some optical afterglows are very faint due to dust along the line of sight. Multicolor Hubble Space Telescope observations were also taken of the host galaxy and the surrounding field. Photometric redshifts imply that the host and a substantial number of faint galaxies in the field are at z ~ 2.5. The overdensity of galaxies is sufficiently great that GRB 030115 may have occurred in a rich high-redshift cluster. The host galaxy shows extremely red colors (R - K = 5) and is the first GRB host to be classified as an extremely red object (ERO). Some of the galaxies surrounding the host also show very red colors, while the majority of the cluster are much bluer, indicating ongoing unobscured star formation. As it is thought that much of high-redshift star formation occurs in highly obscured environments, it may well be that GRB 030115 represents a transition object, between the relatively unobscured afterglows seen to date and a population of objects that are very heavily extinguished, even in the NIR.
WS‐Naming: location migration, replication, and failure transparency support for Web Services

Naming transparencies, i.e. abstracting the name and binding of the entity being used from the endpoints that are actually doing the work, are used in distributed systems to simplify application development by hiding the complexity of the environment. In this paper, we demonstrate how to apply traditional distributed systems naming and binding techniques in the Web Services realm. Specifically, we show how the WS‐Naming profile on WS‐Addressing Endpoint References can be used for identity, transparent failover, replication, and migration. We begin with a discussion of the traditional distributed systems transparencies. We then present four detailed use cases. Next, we provide a brief background on both WS‐Addressing and WS‐Naming. Finally, we show how WS‐Naming can be used to provide transparent implementations of our use cases. Copyright © 2009 John Wiley & Sons, Ltd.
A robust algorithm for pupil center detection

The existing pupil center detection algorithms have fine performance for the ideal eye images. However, the captured eye images are often influenced by various conditions, such as eyelashes, hair, luminance, glasses and so on. In order to detect pupil center under disturbed conditions, this paper proposes a novel algorithm based on radial symmetry transform. Experimental results show that the method is effective and robust to various disturbances.
Data mining for detecting errors in dictation speech recognition

The efficiency promised by a dictation speech recognition (DSR) system is lessened by the need for correcting recognition errors. Error detection is the precursor of error correction. Developing effective techniques for error detection can thus lead to improved error correction. Current research on error detection has focused mainly on transcription and/or domain-specific speech. Error detection in DSR has been studied less. We propose data mining models for detecting errors in DSR. Instead of relying on internal parameters from DSR systems, we propose a loosely coupled approach to error detection based on features extracted from the DSR output. The features mainly came from two sources: confidence scores and linguistics parsing. Link grammar was innovatively applied to error detection. Three data mining techniques, including Na/spl inodot//spl uml/ve Bayes, neural networks, and Support Vector Machines (SVMs), were evaluated on 5M DSR corpora. The experimental results showed that significant performance was achieved in that F-measures for error detection ranged from 55.3% to 62.5%. This study provided insights into the merit of different data-mining techniques and different types of features in error detection.
Interleukin-18 and IL-18 Binding Protein

Interleukin-18 (IL-18) is a member of the IL-1 family of cytokines. Similar to IL-1β, IL-18 is synthesized as an inactive precursor requiring processing by caspase-1 into an active cytokine but unlike IL-1β, the IL-18 precursor is constitutively present in nearly all cells in healthy humans and animals. The activity of IL-18 is balanced by the presence of a high affinity, naturally occurring IL-18 binding protein (IL-18BP). In humans, increased disease severity can be associated with an imbalance of IL-18 to IL-18BP such that the levels of free IL-18 are elevated in the circulation. Increasing number of studies have expanded the role of IL-18 in mediating inflammation in animal models of disease using the IL-18BP, IL-18-deficient mice, neutralization of IL-18, or deficiency in the IL-18 receptor alpha chain. A role for IL-18 has been implicated in several autoimmune diseases, myocardial function, emphysema, metabolic syndromes, psoriasis, inflammatory bowel disease, hemophagocytic syndromes, macrophage activation syndrome, sepsis, and acute kidney injury, although in some models of disease, IL-18 is protective. IL-18 plays a major role in the production of interferon-γ from T-cells and natural killer cells. The IL-18BP has been used safely in humans and clinical trials of IL-18BP as well as neutralizing anti-IL-18 antibodies are in clinical trials. This review updates the biology of IL-18 as well as its role in human disease.
SCALABLE NETWORK BASED E 2 E ADMISSION CONTROL USING FUZZY ARTMAP

The traditional approach to admission control assumes that traffic descriptor is provided by the user or application for each flow prior to establishment for the real time multimedia communication. How ever this approach suffers from several problems. So, we propose a network-based endpoint admission Control system for scalable QoS guaranteed real-time communication services. This system is based on a sink tree-based resource management strategy, and is particularly well suited for DiffServ based architectures which keeps minimum signaling overhead by performing the admission decisions at the end points. In addition, the proposed system integrates routing and resource reservation along the routes, and therefore displays higher admission probability and better link resource utilization. This approach achieves low overall admission control overhead because much of the delay computation is done during system configuration, and so resources can effectively be pre-allocated before run time. We investigate a number of resources sharing approaches that allow resources to be efficiently re-allocated at run time with minimized additional overhead. We provide simulation experiments that illustrate the benefits of using DS tree-based resource management for resource preallocation and for routing, both with and without resource sharing.
Irritable Bowel Syndrome Is Associated with an Increased Risk of Dementia: A Nationwide Population-Based Study

Purpose Abnormal interaction in the brain–gut axis has emerged as one of the relevant pathophysiological mechanisms for the development of irritable bowel syndrome (IBS). Moreover, the brain–gut axis has recently been demonstrated to be crucial for the maintenance of cognitive performance. Therefore, we assessed the risk of dementia following diagnosis of IBS. Methods Using the Taiwan National Health Insurance Research Database (NHIRD) to obtain medical claims data from 2000 to 2011, we employed a random sampling method to enroll32 298 adult patients with IBS and frequency-matched them according to sex, age, and baseline year with 129 192 patients without IBS. Results The patients with IBS exhibited an increased risk of dementia [adjusted hazard ratio (aHR) = 1.26, 95% confidence interval (CI) = 1.17–1.35]after adjustment for age, sex, diabetes, hypertension, stroke, coronary artery disease (CAD), head injury, depression, and epilepsy, and the overall incidence of dementia for the cohorts with and without IBS was 4.86 and 3.41 per 1000 person-years, respectively. IBS was associated with an increased risk of dementia in patients older than 50 years in both male and female, and in those with comorbidity or without comorbidity. After adjustment for age, sex, and comorbidity, patients with IBS were also more likely to develop either non- Alzheimer’s disease (AD) dementia (aHR = 1.24, 95% CI = 1.15–1.33) or AD (aHR = 1.76, 95% CI = 1.28–2.43). Conclusions IBS is associated with an increased risk of dementia, and this effect is obvious only in patients who are ≥50 years old.
Stylized Rendering of Yunnan Heavy Color Painting

A research on stylized rendering of Yunnan heavy color painting is attempted in this paper. First, plentiful Yunnan heavy color paintings are collected. Texture patches are extracted from these paintings and a texture library is constructed. The technique of edge detection in image space is used to extract the outline from photographic image and produce an outline drawing. The photographic image is divided into several regions on which we synthesize with texture patches chosen from texture library. Last, the synthesized image and outline drawing are fused to obtain a stylized painting with Yunnan heavy color painting style.
Effect of confounding factors on blood pressure estimation using pulse arrival time

Two confounding factors were selected and analyzed in blood pressure estimation using pulse arrival time (PAT) for each individual. The heart rate was used as the confounding factor for the cardiac cycle, and the duration from the maximum derivative point to the dicrotic peak (TDB) in the photoplethysmogram was used as another confounding factor representing arterial stiffness. By considering these factors with PAT in multiple regression analysis, the performance of blood pressure estimation is enhanced significantly in the diastolic phase as well as in the systolic phase. The reproducibility of this method was also validated with formerly obtained regression equations from the training set. The correlation between estimated and measured blood pressure decreased a little, but the validity was still maintained (r ≅ 0.8). This shows the value of the method in non-intrusive blood pressure estimation for individual patients and may be useful for various applications.
Answer ranking based on named entity types for question answering

Question answering (QA) using triples has been widely studied. One important aspect is answer ranking, that is, which answer candidates should be used to find correct answers. We are proposing a new method using type-matching information for ranking QA triples. We recommend using a new ranking method that includes type-matching scores from semantic answer types, and named entity types of answer candidates. Our experiments provided new ranking results with ranking average values that were lower by 24.80. We conclude that our proposed method has great potential for answer ranking.
Information-Theoretic Learning Using Renyi's Quadratic Entropy

Learning from examples has been traditionally based on correlation or on the mean square error (MSE) criterion, in spite of the fact that learning is intrinsically related with the extraction of information from examples. The problem is that Shannon’s Information Entropy, which has a sound theoretical foundation, is not easy to implement in a learning from examples scenario. In this paper, Renyi’s Entropy definition is used and integrated with a nonparametric estimator of the probability density function (Parzen Window). We develop a physical analogy for the estimation method which we call the information potential field. The “information potential” method is rather general and will have many applications.
New IDEAs and more ICE by learning and using unconditional permutation factorizations

Solving permutation optimization problems is an important and open research question. Using continuous iterated density estimation evolutionary algorithms (IDEAs) in combination with crossover from genetic algorithms (GAs) has recently [5] been shown to give promising results. In IDEAs, the probability distribution of the solutions is estimated based upon a selection of solutions. So far, only continuous probability theory has been applied to a continuous encoding of permutations. In this paper, we show how we can estimate and use unconditional factorization distributions in the space of permutations directly. We show that the resulting IDEAs process the permutation linkage information more effectively than previously used continuous IDEAs. As a result, deceptive permutation optimization problems of a bounded order can be solved more efficiently.
Simple and Effective OCV Prediction Mechanism for VRLA Battery Systems

This paper presents an effective technique to monitor and predict the open circuit voltage (OCV) for lead-acid battery cells. The underlying principal of the technique described in this paper employs one simple equation to predict the equilibrated cell voltage after a small rest period. The technique was tested and analyzed using results obtained from experiments conducted at the Yuasa Battery laboratories. Lead-acid battery system analysis was carried out with reference to the standard battery system models available in the literature. The results indicate that by using this technique appreciable benefits can be accrued and it is possible to maintain high standard products in safe operating conditions.
Molecular Hydrogen Formation in the Interstellar Medium

We have developed a model for molecular hydrogen formation under astrophysically relevant conditions. This model takes fully into account the presence of both physisorbed and chemisorbed sites on the surface, allows quantum mechanical diffusion as well as thermal hopping for absorbed H atoms, and has been benchmarked versus recent laboratory experiments on H2 formation on silicate surfaces. The results show that H2 formation on grain surfaces is efficient in the interstellar medium up to some 300 K. At low temperatures (≤100 K), H2 formation is governed by the reaction of a physisorbed H with a chemisorbed H. At higher temperatures, H2 formation proceeds through a reaction between two chemisorbed H atoms. We present simple analytical expressions for H2 formation that can be adopted to a wide variety of surfaces once their surface characteristics have been determined experimentally.
Influences d'un contexte informationnel, d'une préférence et d'une norme conventionnelle sur l'évaluation du confort thermique

L’objectif de la recherche presente est de montrer l’impact de normes dichotomisantes dans les activites de jugement. Ces normes sont etudiees sur la base de leurs relations avec un contexte informationnel immediat. Pour cela, nous avons choisi une tâche d’evaluation du confort associe a des releves de temperature ambiante, et manipule le champ de reference : selon les conditions, les sujets devaient prendre appui sur leurs propres preferences ou sur celles supposees d’autrui. Il ressort de cette etude que deux normes peuvent produire une structuration dichotomique de l’activite et en consequence rester stables, un optimum personnel et une norme conventionnelle. Les effets contextuels obtenus sont compatibles avec l’hypothese selon laquelle, avec une telle dichotomisation des jugements, le compromis etendue-frequence opere separement de chaque cote de l’optimum, comme si le sujet etablissait un contexte pour les temperatures les plus chaudes et un autre contexte pour les plus froides.
Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots

We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.
An SNR-Based CAC Algorithm for Optimizing Resource Assignment in the Downlink of M-WiMAX

In order to overcome the inherently challenging conditions of the mobile environment, the physical layer of 802.16e has utilized an Adaptive Modulation and Coding (AMC) scheme, capable of compensating for any SNR (Signal-to-Noise Ratio) fluctuations. As a result, the actual bandwidth demands of each data flow are not solely defined by its datarate requirements, but they are also highly dependent on the terminal's channel conditions. In this respect, the present paper introduces an efficient CAC (Connection Admission Control) algorithm, capable of optimizing the network revenue while guaranteeing the required QoS, under the bandwidth-limited and time-varying conditions of the IEEE 802.16e architecture. The proposed algorithm makes virtue of the terminals' SNR patterns so as to maximize the accuracy of the resource reservation predictions.
University Students' Travel Motivation, Memorable Tourism Experience and Destination Loyalty for Spring Break Vacation

ii Acknowledgement . iii List of Tables . vi List of Figures . vii Chapter 1 Introduction . 1 Overview . 1 Statement of the Problem . 3 Research Question . 4 Significance of the Study . 4 Summary . 5 Chapter 2 Literature Review . 6 Introduction . 6 Spring Break . 6 Travel Motivation . 7 Memorable Tourism Experience . 9 Destination Loyalty . 12 Atrribute Satisfaction . 14 Proposed Model . 18 Chapter 3 Method . 20 Introduction . 20 Sampling and Data Collection . 20
Leishmania pifanoi amastigote antigens protect mice against cutaneous leishmaniasis

In the search for a leishmaniasis vaccine, extensive studies have been carried out with promastigote (insect stage) molecules. Information in this regard on amastigote (mammalian host stage) molecules is limited. To investigate host immune responses to Leishmania amastigote antigens, we purified three stage-specific antigens (A2, P4, and P8) from in vitro-cultivated amastigotes of Leishmania pifanoi by using immunoaffinity chromatography. We found that with Corynebacterium parvum as an adjuvant, three intraperitoneal injections of 5 micrograms of P4 or P8 antigen provided partial to complete protection of BALB/c mice challenged with 10(5) to 10(7) L. pifanoi promastigotes. These immunized mice developed significantly smaller or no lesions and exhibited a 39- to 1.6 x 10(5)-fold reduction of lesion parasite burden after 15 to 20 weeks of infection. In addition, P8 immunization resulted in complete protection against L. amazonensis infection of CBA/J mice and partial protection of BALB/c mice, suggesting that this antigen provided cross-species protection of mice with different H-2 haplotypes. At different stages during infection, vaccinated mice exhibited profound proliferative responses to parasite antigens and increased levels of gamma interferon production, suggesting that a Th1 cell-mediated immune response is associated with the resistance in these mice. Taken together, the data in this report indicate the vaccine potential of amastigote-derived antigens.
Active noise control with fast array recursive least squares filters using a parallel implementation for numerical stability

Significant noise reduction in feedforward active noise control systems with a rapidly changing primary path requires rapid convergence and fast tracking performance. This can be accomplished with a fast-array Kalman method which uses an efficient rotation matrix technique to calculate the filter parameters. However, finite precision effects lead to unstable behavior. In this paper results of a recent algorithm [1] are presented, which exhibits the fast convergence, tracking properties and the linear calculation complexity of the fast array Kalman method, but which does not suffer from the numerical problems. This is achieved by using a convex combination of two parallel finite length growing memory recursive least squares filters. A periodic reset of the filter parameters with proper initialization is enforced, preventing the numerical instability. The performance of the algorithm is demonstrated in numerical simulations and in real-time experiments. Convergence rate and tracking performance are similar to that of a fast-array sliding window recursive least squares algorithm, while eliminating the numerical issues. It is shown that the new algorithm provides significantly improved convergence and tracking as compared to more traditional algorithms, such as based on the filtered reference least mean squares algorithm. [1] S. van Ophem and A. P. Berkhoff, A numerically stable, finite memory, fast array recursive least squares filter for broadband active noise control, International Journal of Adaptive Control and Signal Processing, 2014, submitted.
Notice of RetractionResearch of intra-organizational knowledge transfer based on dynamic game simulation

In the research of intra-organizational knowledge transfer, how to avoid member's opportunistic behavior under individual limited rationality constraint, especially to solve the “Prisoner's Dilemma” is worth concerning. In this article, we examined the intra-organizational knowledge transfer behavior strategy profile from individual level, established the player's behavioral models basis on the dynamic game theory, and then by using agent-based simulation tool “Swarm” to demonstrate equilibrium outcome. The result shows reduction of player's quantity by implementing the team work, regulation of player's payoff function by setting incentive mechanism to punish uncooperative members and reward the cooperative members, could significantly moderate non-cooperative strategy profile and enhance outcome of intra-organizational knowledge transfer. By introducing game theory and CAS (Complex Adaptive Systems) method, this article provides a meaningful approach for future research on intra-organizational knowledge transfer.