Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating intercultural communicative competence components into the English for tourism curricula in Southern Thailand universities

Successful intercultural communication needs both language and cultural knowledge but in Thailand, English proficiency of Thais and Thai students are very low and the present English curricula including teaching practices do not integrate Intercultural Communicative Competence (ICC) which is important for intercultural interactions. The study of Incorporating ICC Components into the English for Tourism Curriculum in Southern Thailand Universities investigated the key components of ICC which are needed for undergraduate students who have high potentiality to work in tourism domain after graduation. Mixed method approaches were employed to find out (1) the appearance of ICC components in the present English for Tourism curriculum in five universities in Southern Thailand, (2) the importance of ICC from the students’, lecturers’, ICC academics’, tour guides’, and employers’ perspectives, (3) the most required ICC skills and dispositions for the undergraduate students, (4) the most relevant ICC skills for undergraduate students from the ICC academics’ perspectives, (5) the teaching practices of English for tourism courses. There were 857 participants consisted of 191 students, 5 lecturers, 3 ICC academics, 312 employers, and 346 tour guides and all of them were purposive samplings. The findings from the study revealed that most of the English for Tourism curricula did not include ICC curriculum elements especially the geo-political context and developmental factors. The majority of the participants agreed that ICC is very important and attitudinal dimension of ICC is the most important. Considering about required skills and dispositions, it was clear that the majority of students, employers, and tour guides agreed that tolerance of ambiguity was very important while the lecturer thought that empathy was the most important disposition and the ICC academics revealed that flexibility was as important as ability to adapt to new situations. Furthermore, the ICC academics agreed that skills of discovery and interaction was very important and the activities in class which help to promote them should be problem base, the materials used in classes should be authentic, and the activities should let the students explore about cultural differences. In fact, the tasks and activities which were employed in present English for Tourism courses in five universities put the weight on attitudinal dimension. Finally, it can be conclude that the ICC curricula in five universities in Southern Thailand need to focus more on skills dimension and knowledge dimension. The result of this study can minimize the scope of ICC in pedagogy relates to tourism domain and can be adapted in other ICC researches.
A Numerical Investigation of the Representation of Room Transfer Functions for Arti(cid:12)cial Reverberation.

In this paper we try to establish the system order for the correct representation of a set of room transfer functions (RTF), in order to partition memory between the common recursive part and the non-recursive part specialized for each RTF. To this end, we apply a few system theory concepts on a set of simulated rectangular rooms, whose impulse responses were generated using the image method [1]. A further validation of our results is provided by an analysis of the frequency density of a comb-(cid:12)lter modeling of the recursive part
AN EXTENSIBLE AND MULTIPERSPECTIVE APPROACH FOR MUSIC SIMILARITY

This paper describes a generic framework for content-based music similarity classification that combines supervised and unsupervised models in a extensible and scalable way. The output of different models are combined via rankaggregation which allows one to extend the functional range of the framework by simply plug-in additional features or classifiers. Both models make use of widely known and applied low level features. Additionally a set of mid level features has been implemented that combine a priori knowledge in the music domain and digital signal processing techniques. This paper is part of the submission to the MIREX’07 (Music Information Retrieval eXchange) audio similarity task. 1 MULTIPLE PERSPECTIVES Different models provide the framework with multiple perspectives of the music similarity problem. Two perspectives are combined in the submitted approach: 1.1 Holistic Perspective A whole song is considered as single entity, whereas the distance between single gaussians of individual songs (i.e. their features) can be seen as an valid implementation of this bag-of-frames concept. Thus the following underlying assumption becomes apparent: Similar feature distributions sound similar. 1.2 Aspect Perspective A song can be considered as a linear-combination of preferably orthogonal aspects. For example it can be subdivided into its constitutional properties as they are: intrumentation (mainly guitar, piano, etc.), vocals (available: male,female), rhythmic-pattern (four-to-the-floor, samba, etc.), style/genre (rock, electronic, jazz, etc.), etc. For each opposing aspect characteristics (e.g. aspect: instrumentation with opposing aspect characteristics: guitar vs. c © 2007 Austrian Computer Society (OCG). F i r s t L D A c o m p o n e n t Scond LDA coponent Th ird L DA c omp onen t Rock
Diffusion-Weighted Spectroscopy of Water and Cerebral Metabolites at Very Large b Values: What Multiple Components Tell Us

OVERVIEW MR Spectroscopy at large diffusion weighting can specifically look at intracellular components of tissue that are characterized by restricted diffusion and a small apparent diffusion coefficient. Beyond water, H MRS of metabolites at large diffusion weighting proved to be very useful to separate extraand intracellular contributions of metabolites in the brain. Further application of diffusion-weighted MRS with other nuclei than H, e.g., P, F, Li, C, can be utilized to answer specific questions tied to various animal models of disease like ischemia, excitotoxicity, tumor or hydrocephalus (1). Such diffusion-weighted spectroscopy is a powerful tool, using information tied to different compartments, different metabolites, and different tracers.
Real-time generation and presentation of view-dependent binocular stereo images using a sequence of omnidirectional images

This paper presents a new method to generate and present arbitrarily directional binocular stereo images from a sequence of omnidirectional images. A sequence of omnidirectional images is taken by moving an omnidirectional image sensor in a static real environment. The motion of the omnidirectional image sensor is constrained to a plane. The sensor's route and speed are known. In the proposed method, a fixed length of the sequence is buffered in a computer to generate arbitrarily directional binocular stereo images by combining captured rays. Using the method a user can look around a scene in the distance with rich 3D sensation without significant time delay. This paper describes the principle of real-time generation of binocular stereo images. In addition, we introduce a prototype telepresence system of view-dependent stereo image generation and presentation.
Hierarchical Variable Ordering for Multiagent Agreement Problems

The Multiagent Agreement Problem (MAP) is a special form of Distributed Constraint Optimization (DCOP) that requires agents to choose values for variables to satisfy not only their own constraints, but also equality constraints with other agents. For solving MAPs, we introduce the AdoptMVA algorithm which is an extension of the existing Adopt algorithm designed to take advantage of the partial centralization that exists in MAP domains where agents control multiple variables. Second, while existing solution approaches to DCOP require variables to be prioritized in some fashion in order to guarantee optimality, it is unclear how to order variables effectively when agents own multiple variables. We investigate a hierarchical approach which leverages known ordering techniques from the sequential constraint satisfaction literature by combining ordering at the agent level with orderings at the variable level to obtain efficient global orderings. Finally, we identify a promising technique for converting known effective variable orderings into effective agent orderings and identify an intra-agent variable ordering heuristic for MAP that is the most efficient of the ones tested. While the contributions presented in this paper are applicable to general DCOPs, we focus our discussion on MAPs because we feel it is a significant problem class worthy of specific attention.
Perceptual organization based on temporal dynamics

This paper presents a computational model for perceptual organization. A figure-ground segregation network is proposed based on a novel boundary pair representation. The system solves the figure-ground segregation problem through temporal evolution. Gestalt-like grouping rules are incorporated by modulating connections, which determines the temporal behavior and thus the perception of the system. The results are then fed to a surface completion module based on local diffusion. Different perceptual phenomena, such as modal and a modal completion, virtual contours, grouping and shape decomposition are explained by the model with a fixed set of parameters. Computationally, the system eliminates combinatorial optimization, which is common to many existing computational approaches. It also accounts for more examples that are consistent with psychological experiments. In addition, the boundary-pair representation is consistent with well-known on- and off-center cell responses and thus biologically more plausible.
Generating Guitar Scores from a MIDI Source

Most music-related software packages were de- signed for students to learn music theories or for the music professionals to compose music. How- ever, amateur music instrument players often need another form - acquiring an instrument- specific score from a music source. In this paper, we describe a software package capable of automatically generating guitar chords and fin- gering styles from music sources in MIDI format. The software program extracts melody from a MIDI file, uses weighted rules based on harmon- ics to select appropriate chords, and then uses principles of guitar composition to generate a six-line score. This program, developed under MS Windows environments, also allow users to interactively edit chords and fingering styles in order to create a customized guitar score.
A convolutional neural network for predicting transcriptional regulators of genes in Arabidopsis transcriptome data reveals classification based on positive regulatory interactions

Gene Regulatory networks that control gene expression are widely studied yet the interactions that make them up are difficult to predict from high throughput data. Deep Learning methods such as convolutional neural networks can perform surprisingly good classifications on a variety of data types and the matrix-like gene expression profiles would seem to be ideal input data for deep learning approaches. In this short study I compiled training sets of expression data using the Arabidopsis AtGenExpress global stress expression data set and known transcription factor-target interactions from the Arabidopsis PLACE database. I built and optimised convolutional neural networks with a best model providing 95 % accuracy of classification on a held-out validation set. Investigation of the activations within this model revealed that classification was based on positive correlation of expression profiles in short sections. This result shows that a convolutional neural network can be used to make classifications and reveal the basis of those calssifications for gene expression data sets, indicating that a convolutional neural network is a useful and interpretable tool for exploratory classification of biological data. The final model is available for download and as a web application.
Analysis, Comparison, and Optimization of Routing Protocols for Energy Harvesting Wireless Sensor Networks

Energy harvesting has been steadily gaining interest in the wireless sensor network community. Instead of minimizing the energy consumption and maximizing a network’s operational time, the main challenge in energy harvesting sensor networks is to maximize the utility of the application subject to the harvested energy. One major challenge is to maximize the data delivery rates by exploiting the spatial variations of environmental energy. While there exists a multiplicity of energy-aware routing protocols for sensor networks without energy harvesting capabilities, only a small number of routing protocols have been published which explicitly account for energy harvesting. In this paper, we analyze and compare three state-of-the-art routing algorithms. While the original algorithms assume an idealized medium access control (MAC), a lossless wireless channel and global knowledge, we show that these assumptions lead to delusive results. We detail these findings by showing the influence of a low-power MAC protocol, a realistic wireless channel and the protocol overhead. Moreover, we show how to optimize the parameters of the MAC protocol for a given network configuration. By conducting various evaluations, we identify that our modified version of the R-MPRT algorithm outperforms the evaluated algorithms in scenarios where little energy is harvested from the environment.
Citrate Synthase Mutants of Sinorhizobium fredii USDA257 Form Ineffective Nodules with Aberrant Ultrastructure

ABSTRACT The tricarboxylic acid (TCA) cycle plays an important role in generating the energy required by bacteroids to fix atmospheric nitrogen. Citrate synthase is the first enzyme that controls the entry of carbon into the TCA cycle. We cloned and determined the nucleotide sequence of the gltA gene that encodes citrate synthase in Sinorhizobium fredii USDA257, a symbiont of soybeans (Glycine max [L.] Merr.) and several other legumes. The deduced citrate synthase protein has a molecular weight of 48,198 and exhibits sequence similarity to citrate synthases from several bacterial species, including Sinorhizobium meliloti and Rhizobium tropici. Southern blot analysis revealed that the fast-growing S. fredii strains and Rhizobium sp. strain NGR234 contained a single copy of the gene located in the bacterial chromosome. S. fredii USDA257 gltA mutant HBK-CS1, which had no detectable citrate synthase activity, had diminished nodulation capacity and produced ineffective nodules on soybean. Light and electron microscopy observations revealed that the nodules initiated by HBK-CS1 contained very few bacteroids. The infected cells contained large vacuoles and prominent starch grains. Within the vacuoles, membrane structures that appeared to be reminiscent of disintegrating bacteroids were detected. The citrate synthase mutant had altered cell surface characteristics and produced three times more exopolysaccarides than the wild type produced. A plasmid carrying the USDA257 gltA gene, when introduced into HBK-CS1, was able to restore all of the defects mentioned above. Our results demonstrate that a functional citrate synthase gene of S. fredii USDA257 is essential for efficient soybean nodulation and nitrogen fixation.
Joint Beat and Downbeat Tracking with Recurrent Neural Networks

In this paper we present a novel method for jointly extracting beats and downbeats from audio signals. A recurrent neural network operating directly on magnitude spectro-grams is used to model the metrical structure of the audio signals at multiple levels and provides an output feature that clearly distinguishes between beats and downbeats. A dynamic Bayesian network is then used to model bars of variable length and align the predicted beat and down-beat positions to the global best solution. We ﬁnd that the proposed model achieves state-of-the-art performance on a wide range of different musical genres and styles.
Proximity extension of circular DNA aptamers with real-time protein detection

Multivalent circular aptamers or ‘captamers’ have recently been introduced through the merger of aptameric recognition functions with the basic principles of DNA nanotechnology. Aptamers have strong utility as protein-binding motifs for diagnostic applications, where their ease of discovery, thermal stability and low cost make them ideal components for incorporation into targeted protein assays. Here we report upon a property specific to circular DNA aptamers: their intrinsic compatibility with a highly sensitive protein detection method termed the ‘proximity extension’ assay. The circular DNA architecture facilitates the integration of multiple functional elements into a single molecule: aptameric target recognition, nucleic acid hybridization specificity and rolling circle amplification. Successful exploitation of these properties is demonstrated for the molecular analysis of thrombin, with the assay delivering a detection limit nearly three orders of magnitude below the dissociation constants of the two contributing aptamer–thrombin interactions. Real-time signal amplification and detection under isothermal conditions points towards potential clinical applications, with both fluorescent and bioelectronic methods of detection achieved. This application elaborates the pleiotropic properties of circular DNA aptamers beyond the stability, potency and multitargeting characteristics described earlier.
GP-SIMD Processing-in-Memory

GP-SIMD, a novel hybrid general-purpose SIMD computer architecture, resolves the issue of data synchronization by in-memory computing through combining data storage and massively parallel processing. GP-SIMD employs a two-dimensional access memory with modified SRAM storage cells and a bit-serial processing unit per each memory row. An analytic performance model of the GP-SIMD architecture is presented, comparing it to associative processor and to conventional SIMD architectures. Cycle-accurate simulation of four workloads supports the analytical comparison. Assuming a moderate die area, GP-SIMD architecture outperforms both the associative processor and conventional SIMD coprocessor architectures by almost an order of magnitude while consuming less power.
IPC-4 Probabilistic Planning Track : FAQ 1 . 01 November 1 , 2003

The 2004 International Planning Competition, IPC-4, will include a probabilistic planning track for the first time. This document provides some of the high level decisions that have been made concerning how the competition will be run. The 2004 International Planning Competition, IPC-4, will include a probabilistic planning track for the first time. This document lays out some of the high level decisions that have been made concerning how the competition will be run. The details are still in flux at the time of this writing, and we hope to get feedback from the participants to spelled them out more precisely during the fall. The overriding goal of the probabilistic planning track is to bring together two communities converging on a similar set of research issues and aid them in creating comparable tools and approaches. One community consists of Markov decision process (MDP) researchers interested in developing algorithms that apply to powerfully expressive representations of environments. The other consists of planning researchers incorporating probabilistic and decision theoretic concepts into their planning algorithms. Cross fertilization has begun, but the probabilistic planning track promises a set of shared benchmarks and evaluation metrics that could crystallize efforts in this domain of study. This document represents a snapshot of the ongoing development of the IPC-4 probabilistic track. For the latest developments, please visit: http://www.cs. rutgers.edu/ ∼mlittman/topics/
Effects of function translation and dimensionality reduction on landscape analysis

Exploratory Landscape Analysis (ELA) measures have been shown to predict algorithm performance; hence, they are being applied on critical tasks such as automatic algorithm selection and problem generation. This paper provides a cautionary examination on their use in black-box continuous optimization. We explore the effect that translations have on the measures, when the cost function is defined within a bound-constrained region. Furthermore, we examine the robustness of the neighborhood structure after dimensionality reduction. The results demonstrate that a measure may transition abruptly due a translation. Therefore, we should not generalize the measures of an instance nor report average values of a measure as belonging to the generating function. Moreover, dimensionality reduction could alter the neighborhood structure, such that the regions corresponding to significantly different functions overlap.
The Relationship Between Tongue Pressure and Oral Dysphagia in Stroke Patients

Objective To evaluate the relationships between tongue pressure and different aspects of the oral-phase swallowing function. Methods We included 96 stroke patients with dysphagia, ranging in age from 40 to 88 years (mean, 63.7 years). Measurements of tongue pressure were obtained with the Iowa Oral Performance Instrument, a device with established normative data. Three trials of maximum performance were performed for lip closure pressure (LP), anterior hard palate-to-tongue pressure (AP), and posterior hard palate-to-tongue pressure (PP); buccal-to-tongue pressures on both sides were also recorded (buccal-to-tongue pressure, on the weak side [BW]; buccal-to-tongue pressure, on the healthy side [BH]). The average pressure in each result was compared between the groups. Clinical evaluation of the swallowing function was performed with a videofluoroscopic swallowing study. Results The average maximum AP and PP values in the intact LC group were significantly higher than those in the inadequate lip closure group (AP, p=0.003; PP, p<0.001). AP and PP showed significant relationships with bolus formation (BF), mastication, premature bolus loss (PBL), tongue to palate contact (TP), and oral transit time (OTT). Furthermore, LP, BW, and BH values were significantly higher in the groups with intact mastication, without PBL and intact TP. Conclusion These findings indicate that the tongue pressure appears to be closely related to the oral-phase swallowing function in post-stroke patients, especially BF, mastication, PBL, TP and OTT.
Enabling Strategic Transformations with Enterprise Systems: Beyond Operational Efficiency

The last few decades have seen the widespread adoption of large-scale, integrated, packaged software suites collectively called Enterprise Systems. However, most studies done so far have largely focused on the operational efficiency achieved by using these systems. This paper reports on research-in-progress that seeks to explore the strategic potential of Enterprise Systems to enable business transformations. In doing so, a new model is proposed that places the emphasis on the potential of Enterprise Systems to achieve innovation and reshape business strategy, rather than merely focusing on operational benefits. This model proposes that Enterprise Systems, when used to integrate, optimise and informate, can help firms achieve alliance innovation, process innovation and reshaped business strategy. The paper also provides preliminary empirical evidence that supports the propositions. This model will be tested further through primary case studies and a survey. This research, once completed, will assess the strategic role of Enterprise Systems in enabling business transformations beyond operational benefits.