Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific Stimuli Induce Specific Adaptations: Sensorimotor Training vs. Reactive Balance Training

Typically, balance training has been used as an intervention paradigm either as static or as reactive balance training. Possible differences in functional outcomes between the two modalities have not been profoundly studied. The objective of the study was to investigate the specificity of neuromuscular adaptations in response to two balance intervention modalities within test and intervention paradigms containing characteristics of both profiles: classical sensorimotor training (SMT) referring to a static ledger pivoting around the ankle joint vs. reactive balance training (RBT) using externally applied perturbations to deteriorate body equilibrium. Thirty-eight subjects were assigned to either SMT or RBT. Before and after four weeks of intervention training, postural sway and electromyographic activities of shank and thigh muscles were recorded and co-contraction indices (CCI) were calculated. We argue that specificity of training interventions could be transferred into corresponding test settings containing properties of SMT and RBT, respectively. The results revealed that i) postural sway was reduced in both intervention groups in all test paradigms; magnitude of changes and effect sizes differed dependent on the paradigm: when training and paradigm coincided most, effects were augmented (P<0.05). ii) These specificities were accompanied by segmental modulations in the amount of CCI, with a greater reduction within the CCI of thigh muscles after RBT compared to the shank muscles after SMT (P<0.05). The results clearly indicate the relationship between test and intervention specificity in balance performance. Hence, specific training modalities of postural control cause multi-segmental and context-specific adaptations, depending upon the characteristics of the trained postural strategy. In relation to fall prevention, perturbation training could serve as an extension to SMT to include the proximal segment, and thus the control of structures near to the body’s centre of mass, into training.
Text categorization methods application for natural language call routing

Natural language call routing can be treated as an instance of topic categorization of documents after speech recognition of calls. This categorization consists of two important parts. The first one is text preprocessing for numerical data extraction and the second one is classification with machine learning methods. This paper focuses on different text preprocessing methods applied for call routing. Different machine learning algorithms with several text representations have been applied for this problem. A novel text preprocessing technique has been applied and investigated. Numerical experiments have shown computational and classification effectiveness of the proposed method in comparison with standard techniques. Also a novel features selection method was proposed. The novel features selection method has demonstrated some advantages in comparison with standard techniques.
Augmented Reality-Based Synchronous Human-Human Communication

The constant desire humans have to find new ways to communicate with one another has led to many technological innovations throughout history. The use of computer-based communication media is certainly a current and broadly used mean. In this context, this research intends to explore the potential of Augmented Reality (AR) solutions when incorporated to synchronous human-human communication support systems in different space scenarios – same space and distributed. For this work, two prototype systems (HANDY and Meetsu) were developed and evaluated qualitatively. The results gave an insightful understanding of the AR impact in the overall user experience as an engaging and ease of communication tool.
A Comparative Study of Daily 3-Gy Hypofractionated and 1.8-Gy Conventional Breast Irradiation in Early-Stage Breast Cancer

AbstractWe retrospectively compared accelerated hypofractionation (AHF) with conventional fractionation (CF) in the radiation therapy (RT) for early-stage breast cancer patients.Three hundred seventy-nine early-stage (pT1–2 and pN0–1a) breast cancer patients who received RT with AHF after breast-conserving surgery (BCS) were included. These patients were matched with 379 corresponding patients who received BCS and RT with CF at a different center with respect to the year BCS was performed, patient age (±3 years), and cancer stage. The AHF regimen consisted of 39 Gy in 13 fractions to the whole breast and a consecutive boost of 9 to 12 Gy in 3 to 4 fractions to the tumor bed. CF comprised whole-breast irradiation up to 50.4 Gy in 28 fractions and a boost of 9 to 14 Gy in 5 to 7 fractions to the tumor bed.The median follow-up period was 75 months (range, 3.8–110.8 months). There was no statistically significant difference between the AHF and CF groups in terms of age distribution, T and N stage, resection margin, and histologic grade. There were 5 ipsilateral breast tumor relapse (IBTR) cases in the AHF group compared with 7 cases in the CF group. Seven and eight locoregional relapse (LRR) cases were observed in the AHF and CF groups, respectively. The 7-year rates of IBTR-free survival, LRR-free survival, and disease-free survival were 98.9%, 98.4%, and 97.1% in the AHF group and 98.1%, 97.9%, and 96.0% in the CF group, respectively (P > 0.05). The incident rates of grade 3 edema, hyperpigmentation, or wet desquamation at the end of RT were higher in the CF group than in the AHF group (16.4% vs 0.2%, respectively; P < 0.01). AHF RT of 39 Gy to the whole breast plus a 9-Gy boost in 16 fractions showed excellent tumor control and tolerable skin toxicity, a finding that is comparable to CF RT in patients with early-stage breast cancer.
Competitive Pricing Analysis in Mature & Evolving Markets: A Time Series Approach

Competitive behavior between players in a mature market can have a different structure than those in growing markets. Pricing component of the marketing mix is less relied upon to expand market share in growing markets, while there is a greater reliance upon product differentiation and building stronger brand equity. On the other hand, in mature markets, there is usually very little scope for product differentiation, so there is a greater reliance on pricing for competitive gains. Since market share expansion in a mature market comes directly from competitive sales declines, pricing strategy changes in one brand leads to a fairly instantaneous reaction from other brands in the category and retail prices in general reflect the equilibrium condition of consumption. This paper applies methods from Time Series Econometrics to identify nonstationary behavior and long-run equilibrium of retail prices of brands in mature and evolving markets. The results indicate that long-run equilibrium in prices may be an outcome of the maturity of markets, as the persistence of the shocks in the prices do not result in the persistence in shocks to sales. The cointegrating condition created by the intense price competition imposes a stationarity restriction on sales, hence eliminating the possibility of any long term pricing strategy and pricing becomes tactical.
EDUCATIONAL GAMES AND SIMULATIONS: A TECHNOLOGY IN SEARCH OF A (RESEARCH) PARADIGM

Games and simulations entered the broad educational scene in the late 1950s. Until the early 1970s, they were not part of the instructional design movement. Instead, these exercises were primarily developed by business and medical education faculty and sociologists who adapted instructional developments pioneered by the military services. Although popular in the public schools in the 1960s, games and simulations in United States classrooms declined with the advent of the basic-skills movement.
Using Blogs to Promote Literary Response during Professional Development

T he blogging has, I don’t want to say forced, but kind of made me read books that I haven’t necessarily read before, and I don’t think I would have. I’ve read lots of children’s books just through student teaching and everything, but it makes me look outside the box and maybe at other genres that I wouldn’t look at necessarily. (Sam, a preservice teacher, blogging in a children’s literature course) Providing preservice teachers such as Sam (all names are pseudonyms) with opportunities to expand their literary horizons and to explore children’s literature through response or discussion activities may encourage literature-rich instructional practices in language arts classrooms. That perspective guided Amy Hutchison, Sam’s instructor and an author of this article, during a required children’s literature course for preservice teachers. Amy believes that if teachers engage in responding to children’s literature, they are more likely to use reader response effectively with their own students. There is good reason to emphasize reader response activities in language arts classrooms. Theoretically grounded in Rosenblatt’s (1985) views of reading as a transaction between readers and texts from which personal meaning emerges, reader response promotes critical thinking and in-depth discussion centered in literature (Almasi, 1995; Eeds & Wells, 1989; Goatley, Brock, & Raphael, 1995; Langer, 1995, 2010; Rosenblatt, 2004). In this view, responses are best nurtured when readers share personal connections to literature in an open forum designed to foster critical reading and thoughtful reflection through discussions of a literary work (Galda & Beach, 2001). Amy developed a class project that utilized an online social network, specifically a Ning network, to facilitate responses to children’s and young adult literature. One option in this increasingly popular online genre for interactive communication, the Ning may be used to extend and enhance opportunities to integrate reader response into language arts instruction. Jamie (Colwell) and David (Reinking) then collaborated with Amy to consider how online social networks might be useful for instructors who provide professional development to language arts teachers. Here, we draw connections between Amy’s class and the larger field of teacher education that encompasses both preservice and practicing teachers. For the purposes of this article, we use the term teachers to refer to both preservice and inservice educators participating in professional development activities.
Automatic NIDS Rule Generating System for Detecting HTTP-like Malware Communication

HTTP is the main protocol of the Internet and many network applications rely on it. Malware also utilizes it as a covert channel through which to evade the firewall (FW) or network intrusion detection system (NIDS). We recognize a malware, which employs HTTP to communicate as the HTTP-like Botnet. Some parts of the network traffic of an HTTP-like Botnet are different from normal HTTP applications. Based on the differences between HTTP-like Botnet traffic and normal HTTP applications, we developed an Automatic NIDS Rule Generating System (ARGS). The ARGS is a proof of concept (POC), which generates the corresponding NIDS rules efficiently and precisely from the input malign traffic (MT). ARGS is an incremental method to generate and optimize the rules. It can generate rules quickly and precisely without first requiring the collection of many malware samples for clustering. For practical purposes, we adopt Snort as our IDS engine in ARGS. In our experiments, the time required by ARGS to process MTs and generate corresponding rules is significantly shorter than existing solution when the rule-optimization is not required. Besides, the generated rule set can detect more 30% malware traffic compared to SourceFire IDS full-set and thus can efficiently stop the spreading of malware in time.
Dual 2DLDA Based on Gabor Features for Face Recognition

Subspace learning techniques for face recognition have been attached growing attention. Two dimensional linear discriminate analysis (2DLDA) is a popular face recognition technique, which learns two interrelated subspace in an iterative manner. DialLDA is proposed as a complementary method to 2DLDA. Motivated by the success of 2DLDA and DialLDA for face recognition, in the paper we develop an innovative algorithm named Dual-2DLDAmethod, and it integrates the two complementary methods2DLDA and DialLDA to learn multiple subspaces by utilizing Gabor features extracted from the training data.The proposed method can fully extract the information in the training data effectively. We have experimentally compared our method to other popular feature extraction methods, such as 2DPCA, 2DLDA. Experimental results on ORL databases show that the proposed method is superior to the popular methods.
Column-based cluster and bar axis density in parallel coordinates

In this paper we organize multi-dimensional datasets with column-based approach instead of the traditional row-based method, each column referring to one dimension and we use bar axis in place of line axis to represent corresponding dimension. Then parallel coordinates with column-based cluster, bar axis density and other techniques is used to convey a large complex multi-dimensional dataset in a relative small screen through the following steps: (a) visualization of column-based clusters with user-defined granularity to simplify the corresponding dimension where we group all the data points into several discrete values; (b) several distinct colors to distinguish the lines contain different amount of data points; (c) opacity is introduced to visualization to tell the difference among the lines with the same color; (d) brand instead of polyline to reveal the centre and the extent of each cluster; (e) layer-based drawing technique to emphasize the heavy lines and to denote the trend of multi-dimensional datasets; (f) bar axis to provide special space to illustrate the density of the dataset on each axis. Anyway, our work has two primary goals: one is to convey large dataset with legible compact vivid visualization on a limited screen area. The other one is to simultaneously reveal as many information features as possible away from clutter.
A Kernel-Based Localization Approach in Wireless Sensor Networks

Our solution builds on a kernel-based method called the support vector machine (SVM) for determining the locations of the nodes. The basic SVM algorithm contains two steps: (1) one-region classification using the SVM; and (2) multi-region localization which is a repeated application of one-region classification for a number of different regions. In this paper, we first analyze the error effects of the choice of regions in the multi-region localization, which influences the accuracy of the localization results significantly. The realization of a choice of regions is posed as a beacon node coverage problem, i.e., the spatial distribution of the beacon nodes is determined from the coverage point of view. Second, we develop a method to arrange the regions, which we call expanded coverage region distribution, in order to avoid the problem of border effects in existing solutions. We show that expanded cover region distribution can reduce the localization errors. Our results show that, by optimally choosing and arranging the regions based on our analysis, we can significantly enhance the performance of SVM based localization. Furthermore, the optimal choice of regions to avoid the border effects can be similarly applied in other kernel-based learning methods for localization.
Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries

This paper analyzes productivity growth in seventeen OECD countries over the period 1979-88. A nonparametric programming method (activity analysis) is used to compute Malmquist productivity indexes. These are decomposed into two component measures, namely, technical change and efficiency change. The authors find that U.S. productivity growth is slightly higher than average, all of which is due to technical change. Japan's productivity growth is the highest in the sample with almost half due to efficiency change. Copyright 1994 by American Economic Association.
An increasing‐angle property of the conjugate gradient method and the implementation of large‐scale minimization algorithms with line searches

The search direction in unconstrained minimization algorithms for large‐scale problems is usually computed as an iterate of the preconditioned) conjugate gradient method applied to the minimization of a local quadratic model. In line‐search procedures this direction is required to satisfy an angle condition that says that the angle between the negative gradient at the current point and the direction is bounded away from π/2. In this paper, it is shown that the angle between conjugate gradient iterates and the negative gradient strictly increases as far as the conjugate gradient algorithm proceeds. Therefore, the interruption of the conjugate gradient sub‐algorithm when the angle condition does not hold is theoretically justified. Copyright © 2002 John Wiley & Sons, Ltd.
Anticollision Protocols for Single-Reader RFID Systems: Temporal Analysis and Optimization

One of the major challenges in the use of Radio Frequency-based Identification (RFID) on a large scale is the ability to read a large number of tags quickly. Central to solving this problem is resolving collisions that occur when multiple tags reply to the query of a reader. To this purpose, several MAC protocols for passive RFID systems have been proposed. These typically build on traditional MAC schemes, such as aloha and tree-based protocols. In this paper, we propose a new performance metric by which to judge these anticollision protocols: time system efficiency. This metric provides a direct measure of the time taken to read a group of tags. We then evaluate a set of well-known RFID MAC protocols in light of this metric. Based on the insights gained, we propose a new anticollision protocol, and show that it significantly outperforms previously proposed mechanisms.
An Adaptive Microphone Array for Hands-Free Communication

In this paper we present an adaptive microphone array to suppress coherent as well as incoherent noise in disturbed speech signals. We use a generalized sidelobe cancelling (GSC) structure implemented in the frequency domain, because it allows a separate handling of determining the adaptive look direction response to suppress incoherent noise and adjusting the adaptive filters for cancellation of coherent noise. The transfer function in the look direction is an adaptive Wiener–Filter which is estimated using the short time Fourier–Transform and the Nuttall/Carter method for spectrum estimation.
Complete Genome Sequences of T4-Like Bacteriophages RB3, RB5, RB6, RB7, RB9, RB10, RB27, RB33, RB55, RB59, and RB68

ABSTRACT T4-like bacteriophages have been explored for phage therapy and are model organisms for phage genomics and evolution. Here, we describe the sequencing of 11 T4-like phages. We found a high nucleotide similarity among the T4, RB55, and RB59; RB32 and RB33; and RB3, RB5, RB6, RB7, RB9, and RB10 phages.
The ten-page introduction to Trusted Computing

Networked computer systems underlie a great deal of business, social, and government activity today. Everyone is expected to place a great deal of trust in their correct operation, but experience shows that this trust is often misplaced. Such systems have always been subject to failures due to oversights and mistakes by those who designed them; increasingly such failures are exploited by those with malicious intent. The concept of Trusted Computing has been present in the computer security literature for quite some time, and has influenced the design of some high-assurance solutions. These ideas are now becoming incorporated in mainstream products — PCs, mobile phones, disc drives, servers — and are the subject of much discussion and sometimes misinformation. Trusted computing implies a re-design of systems architecture in such a way as to support its factorization into relatively discrete components with well-defined characteristics. This permits, in particular, rational decisions based upon reasonable expectations of behaviour. Any such systems thinking must be motivated by an analysis of risks — so that effort is expended where it may give the best return — and an awareness of the limitations of such risk assessment (because frequently the raw data and parameters are simply not available, and because security properties are typically not compositional). The approach described here is largely the result of the work of an industry consortium (the Trusted Computing Group, TCG), itself informed by a history of research, largely in the area of high-assurance systems, from government and academe. TCG’s approach is distinctive in that previous trusted systems were usually bespoke and highly expensive: the current work aims to touch every computing device. This tutorial surveys the relevant notions of ‘trust’, exploring what this means for ‘trusted computing’. We describe briefly the interventions needed in hardware and software required to give a stable platform upon which such systems can be constructed. In essence, this gives us two new systems characteristics: (a) a high degree of confidence in the state (configuration, running software, etc.) of a local computing system—and hence a measure of its relative freedom from unwanted intervention; (b) a relatively high degree of confidence in the state of a remote system (a property called ‘remote attestation’). The first of those characteristics has perhaps always informed the way that users interact with desktop personal computers: many malware attacks exploit misplaced trust in the local system. The second characteristic is genuinely novel, and may be seen as an enabler of many new kinds of pattern of interaction in distributed systems. Knowing that a platform is in a particular state is neither a necessary nor sufficient condition for trustworthiness (or, indeed, security) — but helps to inform decisions about that. We explore how these capabilities are constructed, and some uses to which they might be put. We also briefly describe the state of deployment of these technologies, and some current areas of research.
An Eﬃcient Model for Dynamic and Constrained Resource Allocation Problems

Dynamic constraint satisfaction is a useful tool for representing and solving sequential decision problems with complete knowledge in dynamic world and particularly constrained resource allocation problems. However, when resources are unreliable, this framework becomes limited due to the stochastic outcomes of the assignments chosen. On the contrary, Markov Decision Processes (MDPs) handle stochastic outcomes of unreliable actions, but their complexity explodes when using state-deﬁned constraints. We thus propose an extension of the MDP framework so as to represent constrained and stochastic actions in sequential decision making. The basis of this extension consists in modeling the evolution of a dynamic constraint network by a MDP. We ﬁrst study the complexity of the problem of ﬁnding an optimal policy for this model and then we propose an algorithm for solving it. Comparison to standard MDP shows that this framework noticeably improves policy computation.
Energy Efficient Information Dissemination in Ad Hoc Networks Utilizing Bi-orthogonal Signaling

In this paper, we leverage bi-orthogonal signaling by using a time slot dependent identification scheme that enables energy efficient information dissemination, independent of the network topology. The approach, although motivated by cooperative modulation schemes that require information to be dispersed to other nodes within a wireless ad hoc network, can be applied directly to wired networks. As a measure of energy efficiency in information dissemination, we consider the number of transmissions required for broadcast. For the grid topology, we give a tighter bound than [1] without using our proposed time slot dependent identification scheme, and then focus on optimizing an information dissemination scheme for the grid topology.