Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Physical-Cognitive Dual Task Training on Executive Function and Gait Performance in Older Adults: A Randomized Controlled Trial

Physical and cognitive training seem to counteract age-related decline in physical and mental function. Recently, the possibility of integrating cognitive demands into physical training has attracted attention. The purpose of this study was to evaluate the effects of twelve weeks of designed physical-cognitive training on executive cognitive function and gait performance in older adults. Thirty-six healthy, active individuals aged 72.30 ± 5.84 years were assigned to two types of physical training with major focus on physical single task (ST) training (n = 16) and physical-cognitive dual task (DT) training (n = 20), respectively. They were tested before and after the intervention for executive function (inhibition, working memory) through Random Number Generation and for gait (walking with/without negotiating hurdles) under both single and dual task (ST, DT) conditions. Gait performance improved in both groups, while inhibitory performance decreased after exercise training with ST focus but tended to increase after training with physical-cognitive DT focus. Changes in inhibition performance were correlated with changes in DT walking performance with group differences as a function of motor task complexity (with/without hurdling). The study supports the effectiveness of group exercise classes for older individuals to improve gait performance, with physical-cognitive DT training selectively counteracting the age-related decline in a core executive function essential for daily living.
Web-based processing of remote sensing data in a workflows environment

Since its inception, Earth observation from space has been hampered by the difficulty of managing and processing the enormous volumes of data that satellite sensors are capable of generating. Modern sensors are able to produce more channels of spectral data more frequently at greater spatial resolution than ever before, and the range of potential geophysical products is continually increasing. Generation of products, access to, analysis and visualisation of these large data sets is often perceived as highly technical and an often daunting set of procedures. This paper introduces a project aimed at providing to non-technical users access to a suite of tools via a web-based graphical user interface to a Workflows system (RS-YABI), linked to a high performance computing system and a national- scale remote sensing data archive.
Entry in PDAs with WtX

Size is a mixed blessing for portable devices. While they feature a wide range of applications and services that can be used anywhere and anytime, their user interface is poor, hampered by the screen size. Furthermore, portable devices are meant to be used everywhere, even in uncomfortable situations (while standing up or walking for instance). Consequently, some tasks get hard to be accomplished. One of them is text entry, which is still far from being as comfortable as on desktop PCs. Different solutions have been envisaged, including small hardware keyboards, software (also called virtual) keyboards, predictive input techniques and handwriting recognition systems. In this paper we give a thorough overview of our text entry tool Word Tree version X (WtX), especially focusing on recent improvements. The new version of WtX features a handwriting recognition system and a mechanism (which we called First-Third-Last rule or simply FTL rule) forcing users to insert the characters of a word so as to improve text prediction.
Effect of increasing voltage levels on power saving obtained by multiple voltages design

Researchers believe that the power reduction at the earliest stages of the system design process will have higher impacts on the final result. Multiple supply voltage design is broadly acknowledged as a compelling approach to reduce the power consumption of a CMOS circuit. A SAT-based approach which targets operation scheduling with varying voltages and produces a circuit that consumes less power is proposed in this paper. Experiments with HLS benchmarks shows that the proposed schemes achieve more reduction in power once the number of operating voltage levels are increased (here 5v, 3.3v and 2.4v).
A new method of modeling of inquiry diagnosis for coronary heart disease in traditional Chinese medicine

Coronary heart disease (CHD), as one of the most common cardiovascular diseases in the world, is invading younger patients and brings increasing mortality. In Traditional Chinese Medicine (TCM), the diagnosis and treatment of CHD have accumulated a wealth of experience enjoying a long history. Nevertheless, the diagnosis and treatment of CHD usually depend on individual experience of doctors and lack of the standard and objective inquiry information in TCM. In this paper, a new method based on association analysis and feature selection is proposed to establish a clinical data based practical diagnostic model for Chinese medicine syndrome identification in patients with CHD, by way of seeking a combination of symptoms, signs and laboratory criteria associated with the typical syndromes of the disease. A syndrome-topologic and laboratory investigation on a total of 100 features is conducted in 1058 CHD patients. The most typical syndromes revealed in the 1058 CHD patients are the blood stasis syndrome (707 patients, accounting for 66.82%) and the deficiency of heart qi syndrome (727 patients, 68.71%). The models of diagnosis and treatment for these two syndromes are established, respectively. Then, the two diagnostic models for identifying the two syndromes are proved to have the accurate diagnostic rates of 76.3% and 71.4%, respectively. A new method of modeling of diagnosing the two typical syndromes in CHD patients, the blood stasis syndrome and the deficiency of heart qi syndrome, is proposed, which is helpful for shifting the diagnosis of syndrome from traditional experience-based pattern to the data-model-based one, to make the syndrome diagnosis more standard and objective.
Empirical Research on Managerial Risk-Averse and Financing Behavior

Based on the study of irrational managers in behavioral corporate finance, this paper proposes a financing decision-making model by the construction of investors' rationality and analysis to managers' risk-aversion. Measuring managerial risk aversion under behavioral corporate finance paradigm according to risk aversion index, this paper analyzes the financing behavior of risk-averse managers by means of analyzing DJ-China 88 index from 2000 to 2004 through Logistic regression and mean analysis. The findings show that if other variables are well-controlled, then the risk-averse index has an obvious negative influence on debt financing decision. The higher is the level of risk-aversion, the less is the likelihood of application of debt financing, which means risk-averse managers prefer stock financing.
The Effect of Inclusive Leadership on Employees’ Procrastination

Based on self-determination theory, our study investigates the mechanism and boundary condition of procrastination behavior. We had a sample of 327 employees to test our hypothesis, and regression method and the structural equation model were used to analyze the data. The results show that: 1) inclusive leadership could negatively influence on procrastination behavior; 2) mediating effect of intrinsic motivation was found between inclusive leadership and procrastination; 3) moderating effects of perceived insider status were found upon the relationship between intrinsic motivation and procrastination behavior; 4) moreover, perceived insider status moderated the mediating effect of intrinsic motivation between inclusive leadership and procrastination behavior.
Confidence factor determination for performance evaluation of lighting pattern

In this paper the authors propose a new technique for determining a confidence factor applied to the performance prediction of individual luminaires within an overall pattern of luminaires. This work has relevance to any application where it is necessary to determine the performance of a lighting pattern e.g. street lighting, signal lighting etc. In this paper we apply our technique to a transportation application, namely, an airport landing lighting pattern. In the aviation industry it is imperative that the landing lighting pattern at individual airports performs according to standards. We have developed an automated technique which can be used to access the performance of luminaires within this pattern. We extend this work to also derive a confidence factor related to this prediction based on the quality of the data being utilised.
Scalable statistical learning: A modular bayesian/markov network approach

In this paper we propose a hybrid probabilistic graphical model for pseudo-likelihood estimation in high-dimensional domains. The model is based on Bayesian networks and Markov random fields. On the one hand, we prove that the proposed model is more expressive than Bayesian networks in terms of the representable distributions. On the other hand, we develop a computationally efficient structure learning algorithm, and we provide theoretical and experimental evidence showing how the modular nature of our model allows structure learning to scale up very well to high-dimensional datasets. The capability of the hybrid model to accurately learn complex networks of conditional independencies is illustrated by promising results in pattern recognition applications.
An Efficient Mobile Voting System Security Scheme Based on Elliptic Curve Cryptography

The wide-spread use of mobile devices has made it possible to develop mobile voting system as a complement to the existing electronic voting system. However, due to limited onboard resource, it is challenging to achieve both efficiency and security strength for mobile voting system. Conventional solution is to either use symmetric encryption algorithms or hybrid symmetric and asymmetric algorithms at the expense of weaker security strength. In our proposed mobile voting scheme, the users’ votes are secured by using the elliptic curve cryptography (ECC) algorithm. ECC is chosen as it has smaller key size than other public key cryptographies; and its homomorphic encryption property which is able to keep users’ anonymity. We evaluate the method of ECDH with AES and ECC in comparison with our proposed method. The experiment demonstrates that our proposed ECC based scheme can outperform the traditional hybrid symmetric and asymmetric cryptographic scheme in the context of mobile evoting environment.
ROAD: An RFID Offline Authentication, Privacy Preserving Protocol with Dos Resilience

As RFID applications become widespread, different authentication schemes have been proposed to address the security and privacy issues in RFID systems. Most recent protocols have employed a "central server" model. This kind of authentication is vulnerable to Dos attack. In this paper, we present an RFID offline authentication protocol with Dos resilience, ROAD, which provides a more flexible and privacy preserving authentication without the need of a central server. Moreover, we suggest another offline scheme, ROAD+ for a targeted tag authentication with high search efficiency. We also show that ROAD+ provides a technical support for an absolutely new application of RFID systems.
Human action recognition in surveillance video of a computer laboratory

One of the driving forces of behavior recognition in video is the analysis of surveillance video. In this video, humans are monitored and their actions are classified as being normal or a deviation from the norm. Local spatio-temporal features have gained attention to be an effective descriptor for action recognition in video. The problem of using texture as local descriptor is relatively unexplored. In this paper, a work on human action recognition in video is presented by proposing a fusion of appearance, motion and texture as local descriptor for the bag-of-feature model. Rigorous experiments was conducted on the recorded UTP dataset using the proposed descriptor. The average accuracy obtained was 85.92% for the fused descriptor as compared to 75.06% for the combination of shape and motion descriptor. The result shows an improved performance for the proposed descriptor over the combination of appearance and motion as local descriptor of an interest point.
Comparison of two azithromycin distribution strategies for controlling trachoma in Nepal.

OBJECTIVE The study compares the effectiveness of two strategies for distributing azithromycin in an area with mild-to-moderate active trachoma in Nepal. METHODS The two strategies investigated were the use of azithromycin for 1) mass treatment of all children, or 2) targeted treatment of only those children who were found to be clinically active, as well as all members of their household. FINDINGS Mass treatment of children was slightly more effective in terms of decreasing the prevalence of clinically active trachoma (estimated by clinical examination) and of chlamydial infection (estimated by DNA amplification tests), although neither result was statistically significant. CONCLUSION Both strategies appeared to be effective in reducing the prevalence of clinically active trachoma and infection six months after the treatment. Antibiotic treatment reduced the prevalence of chlamydial infection more than it did the level of clinically active trachoma.
Experiences in Specifications: Learning to Live With Ambiguity

paper describes our practical experiences in setting and working with requirements for a piece of security software. Principally, it discusses the conicts that occurred between the ease of putting the initial requirements on paper and the diculty in applying them. The requirements were not formally specied, but the process of turning them into code followed our standard software development process. How- ever, the informality of the requirements was not the pri- mary source of our conicts; we believe that ambiguity al- ways exists, ambiguity leads to assumptions, and assump- tions are what lead to aws { some of which may cause security vulnerabilities. By explaining our journey through the software development process, we show how seemingly obvious and easily stated requirements lead to ambiguity, choices, and the need for re- visiting specications throughout the process. We conclude with some recommendations from our experiences that we hope will be useful to other practitioners.
Ranking-Based Multi-source Rating Aggregation with Social Contexts

Rating aggregation is critical to the quality control of recommendation systems and its effectiveness is a deep concern of all users. However, there are some problems in existing recommendation systems. For example, some of the raters from certain source are much more stringent than others, leading the phenomena that some entities with better quality are rejected. In this paper, we propose a novel raNking-based multI-source ratiNg Aggregation (NINA) approach. In this approach, based on the collected social context of recommenders and recommendees, the credibility of rankings of ratings from multiple sources can be estimated, and it can be used to deal with the disagreement during ranking-based rating aggregation from multiple sources. Hence, the proposed approach can effectively estimate the 'true' rating during aggregation based on the ratings from multiple sources, even though no prior knowledge exists about the distribution of stringent raters and lenient raters in different sources. We have studied the properties of NINA empirically. In particular, the experiments illustrate that compared with existing approaches, our proposed NINA can significantly reduce the influence of ratings from stringent raters and lenient raters, leading to trust enhanced rating aggregation, no matter what kind of the distributions of stringent raters and lenient raters are.
Portable inter-workgroup barrier synchronisation for GPUs

Despite the growing popularity of GPGPU programming, there is not yet a portable and formally-specified barrier that one can use to synchronise across workgroups. Moreover, the occupancy-bound execution model of GPUs breaks assumptions inherent in traditional software execution barriers, exposing them to deadlock. We present an occupancy discovery protocol that dynamically discovers a safe estimate of the occupancy for a given GPU and kernel, allowing for a starvation-free (and hence, deadlock-free) inter-workgroup barrier by restricting the number of workgroups according to this estimate. We implement this idea by adapting an existing, previously non-portable, GPU inter-workgroup barrier to use OpenCL 2.0 atomic operations, and prove that the barrier meets its natural specification in terms of synchronisation. We assess the portability of our approach over eight GPUs spanning four vendors, comparing the performance of our method against alternative methods. Our key findings include: (1) the recall of our discovery protocol is nearly 100%; (2) runtime comparisons vary substantially across GPUs and applications; and (3) our method provides portable and safe inter-workgroup synchronisation across the applications we study.
Fork-Coupled Resonators for High-Frequency Characterization of Dielectric Substrate Materials

Efficient coupling of energy in and out of a resonator can significantly enhance its performance, particularly when used for dielectric characterization of materials. In this paper, a new microstrip resonator is introduced, which uses fork-shaped feed elements for improving the coupling efficiency. The proposed resonator is studied both experimentally and theoretically with field simulation software. An important advantage of the fork microstrip resonator is attributed to its single-layer geometry and easier manufacturing processes. This resonator is used to characterize three different dielectric materials. Comparison of measurement results from the fork resonator with those obtained with a stripline resonator suggests that the proposed resonator offers a superior performance
Structural basis of tRNA modification with CO2 fixation and methylation by wybutosine synthesizing enzyme TYW4†

Wybutosine (yW), one of the most complicated modified nucleosides, is found in the anticodon loop of eukaryotic phenylalanine tRNA. This hypermodified nucleoside ensures correct codon recognition by stabilizing codon-anticodon pairings during the decoding process in the ribosome. TYW4 is an S-adenosylmethionine (SAM)-dependent enzyme that catalyzes the final step of yW biosynthesis, methylation and methoxycarbonylation. However, the structural basis for the catalytic mechanism by TYW4, and especially that for the methoxycarbonylation, have remained elusive. Here we report the apo and cofactor-bound crystal structures of yeast TYW4. The structures revealed that the C-terminal domain folds into a β-propeller structure, forming part of the binding pocket for the target nucleoside. A comparison of the apo, SAM-bound, and S-adenosylhomocysteine-bound structures of TYW4 revealed a drastic structural change upon cofactor binding, which may sequester solvent from the catalytic site during the reaction and facilitate product release after the reaction. In conjunction with the functional analysis, our results suggest that TYW4 catalyzes both methylation and methoxycarbonylation at a single catalytic site, and in the latter reaction, the methoxycarbonyl group is formed through the fixation of carbon dioxide.
Implementing QoS-adaptation in coordination artifacts by enhancing Cougaar multi-agent middleware

Coordination artifacts are first-class software entities that encapsulate an abstract communication pattern either among agents or between an agent and its environment. By separating these coordination artifacts from agent implementations, both are simplified and acquire a nearly parallel structure. Coordination artifacts provide an ideal means for dealing with systemic issues, including survivability, allowing the remaining agent code to focus solely on its domain/business logic. Coordination artifacts can be implemented as a small set of extensions to the existing Cougaar agent middleware. In this paper, we present a design for coordination artifacts and their implementation in Cougaar.
Content-based Modeling of Reciprocal Relationships using Hawkes and Gaussian Processes

There has been growing interest in inferring implicit social structures using interaction data. This approach is motivated by the fact that entities organize themselves into groups having frequent interactions between each other. Unlike previous approaches that focused on subjectively declared relationships, the idea is to exploit the actual evidence at hand to reach conclusions about group formations, resulting in more objective data-driven inferences. To this end, [5] have employed Hawkes processes, and proposed a Hawkes IRM model to infer social structures from interaction data. A major factor that encourages the use of Hawkes processes is the capability to model reciprocity in the interaction between social entities. However, reciprocation is dynamically conditioned upon two key factors: the significance of each message sent by the sender, and the receptivity to each message received by the receiver. In the model proposed by [5], reciprocity is not affected by either of these factors, since the content of each message is not taken into account. In this paper, we extend the work of [5] by introducing Gaussian processes (GPs) into the Hawkes IRM model: based on the content of each message, GPs are used to model the message significance as well as receptivity. This allows us to more accurately capture the interactions among entities. The application of GPs also allows us to flexibly model the rates of reciprocal activities between two entities, allowing asymmetry in reciprocity to be captured more accurately. This leads to better cluster detection capability. Our model outperforms previous Hawkes and Poisson process-based models at predicting verbal, email, and citation activities.
Call admission control and traffic modeling for integrated macrocell/femtocell networks

Dense femtocells and the integration of these femtocells with the macrocell are the ultimate goal of the femtocellular network deployment. Integrated macrocell/femtocell networks surely able to provide high data rate for the indoor users as well as able to offload huge traffic from the macrocellular networks to femtocellular networks. Efficient handling of handover calls is the key for the successful macrocell/femtocell integration. An appropriate traffic model for the integrated macrocell/femtocell networks is also needed for the performance analysis measurement. In this paper we presented a call admission control process and a traffic model for the integrated macrocell/femtocell networks. The numerical and simulation results show the important of the integrated macrocell/femtocell network and the performance improvement of the proposed schemes.