Miracle-dz/UniFAR-FTUs huggingface dataset:
BodyRC: Exploring Interaction Modalities Using Human Body as Lossy Signal Transmission Medium

With the increasing popularity of wearable computing devices, new sensing techniques that enable always-available interaction are highly demanded. In this paper, we propose Body RC, a novel body-based device using human body as lossy signal transmission medium. This device supports on-body interaction and body gesture recognition. In particular, Body RC recognizes the operations of on-body interaction and body gestures by analyzing the electrical properties when transmitting single high frequency analog signal through human body. We evaluate the capabilities and performance of Body RC through two controlled experiments showing robust classification of both on-body interaction and body gesture recognition. In addition, we design a real-time recognition system demonstrating the utility of our technique.
Synoptic-Scale Controls of Summer Precipitation in the Southeastern United States

Abstract Past climatological research has not quantitatively defined the synoptic-scale circulation deviations responsible for anomalous summer-season precipitation totals in the southeastern United States. Therefore, the objectives of this research were to determine the synoptic-scale controls of wet and dry multiday periods during the summer within a portion of the southeastern United States as well as to assess the linkages between synoptic-scale circulation and multidecadal variations in precipitation characteristics for the study domain. Daily precipitation data from 30 stations for June, July, and August from 1953 to 2002 were converted into 13-day totals. Using standardized principal components analysis (PCA), the study domain was divided into three precipitation regions (i.e., South, Northwest, and Northeast). Wet and dry periods for each region were composed of the top 56 and bottom 56 thirteen-day periods. Composite circulation maps for 500 and 850 mb revealed the following: wet periods were gen.
Modeling and Simulated Annealing Optimization of Surface Roughness in CO2 Laser Nitrogen Cutting of Stainless Steel

This paper presents a systematic methodology for empirical modeling and optimization of surface roughness in CO2 laser nitrogen cutting of stainless steel. The surface roughness prediction model was developed in terms of laser power, cutting speed, assist gas pressure and focus position by using the artificial neural network (ANN). To cover a wider range of laser cutting parameters and obtain an experimental database for the ANN model development, Taguchi’s L27 orthogonal array was implemented in the experimental plan. The developed ANN model was expressed as an explicit nonlinear function, while the influence of laser cutting parameters and their interactions on surface roughness were analyzed by generating 2D and 3D plots. The final goal of the experimental study focuses on the determination of the optimal laser cutting parameters for the minimization of surface roughness. Since the solution space of the developed ANN model is complex, and the possibility of many local solutions is great, simulated annealing (SA) was selected as a method for the optimization of surface roughness. © 2013 Published by Faculty of Engineering Corresponding author:
Subtyping in Alloy by Emina Torlak

ly, a RelationType is an immutable, non-empty sequence of BasicTypes. The implementation of RelationType maintains the representation invariant that the BasicType function isEmpty must return the same value for all BasicTypes in a RelationType. This prevents the creation of nonsensical RelationTypes such as [EmptyType -Obj ec t]. RelationTypes support operations isEmpty, isSubsetOf, and intersect (Figure 4-5), which are analogous to the corresponding operations on BasicTypes with the restriction that two RelationTypes of different arities (number of BasicTypes) cannot be intersected. The worst case running times for these operations are constant for isEmpty and O(a*dax) for isSubsetOf and intersect where a is the common arity of the functions' operands.
During my service in the United States Congress , I took the initiative in creating the Internet

Acknowledgements My supervisor Sandra Halverson For introducing me to the field of cognitive linguistics in the first place, for her clear vision, firm guidance and inspiration, and for dragging me along this 'bumpy road'. Espen Aarseth & Jan Rune Holmevik For inspiration, encouragement and luring me into Cyberspace. The virtual champagne did the trick, Jan! Marianne Kirkhorn For valuable discussions along the road, listening to complaints, and being a friend. Irene Vold For filling the breaks with Violent Irony, hilarious fun and meta epiphanies. Hanne Aas For her interest and cheering.
Prunus persica Crop Management Differentially Promotes Arbuscular Mycorrhizal Fungi Diversity in a Tropical Agro-Ecosystem

Due to the important role of arbuscular mycorrhizal fungi (AMF) in ecosystem functioning, determination of the effect of management practices on the AMF diversity in agricultural soils is essential for the sustainability of these agro-ecosystems. The objective of this study was to compare the AMF diversity in Prunus persica roots under two types of fertilisation (inorganic, with or without manure) combined with integrated or chemical pest management in a Venezuelan agro-ecosystem. The AM fungal small-subunit (SSU) rRNA genes were subjected to PCR, cloning, sequencing and phylogenetic analyses. Twenty-one different phylotypes were identified: 15 belonged to the genus Glomus, one to Claroideoglomus, two to Paraglomus, one to Acaulospora, one to Scutellospora and one to Archaeospora. The distribution of the AMF community composition differed as a consequence of the treatment effects. The treatment combining organic and inorganic fertilisation with chemical pest control had the highest AMF richness and the treatment combining inorganic fertilisation with chemical pest had the lowest. The real causes and effects of these differences in the AMF community are very difficult to establish, since the crop management regimes tested were composed of several interacting factors. In conclusion, the crop management practices can exert a significant influence on the populations of AMF. The treatment combining organic and inorganic fertilisation with chemical pest control appears to be the most suitable agricultural management strategy with respect to improving the AMF diversity in this crop under tropical conditions, and thus for maintaining the agricultural and environmental sustainability of this agro-ecosystem.
A Collection of Comparable Corpora for Under-resourced Languages

This paper presents work on collecting comparable corpora for 9 language pairs: Estonian-English, Latvian-English, Lithuanian-English, Greek-English, Greek-Romanian, Croatian-English, Romanian-English, Romanian-German and Slovenian-English. The objective of this work was to gather texts from the same domains and genres and with a similar level of comparability in order to use them as a starting point in defining criteria and metrics of comparability. These criteria and metrics will be applied to comparable texts to determine their suitability for use in Statistical Machine Translation, particularly in the case where translation is performed from or into under-resourced languages for which substantial parallel corpora are unavailable. The size of collected corpora is about 1 million words for each under-resourced language.
OneQL: An Ontology-based Architecture to E ﬃ ciently Query Resources on the Semantic Web

The widespread explosion of Web accessible resources has led to new problems on the traditional tasks of query evaluation and e ﬃ cient data access. With this is mind, we have developed the ontology-based OneQL system which provides optimization and query evaluation techniques to scale up to large RDF / RDFS documents and complex queries, i.e., queries of any shape and with a large number of triple patterns. E ﬃ ciency of OneQL relies on the following components:
A comparison of CS reconstruction algorithms for multicomponent nonlinear phase signals

This paper analyzes the performance of different compressive sensing algorithms applied to signals with polynomial and cosine modulated phases, that usually appear in radar communications. In order to provide sparsity in the Fourier transform domain, the signal components are firstly demodulated by a direct parameter search method. In this way, the signals are sparsified in the DFT domain. The performance of reconstruction algorithms are compared using small number of measurements. The results are illustrated on examples.
Understanding and Changing Software Organizations: An Exploration of Four Perspectives on Software Process Improvement

In this article we discuss four different perspectives on software process improvement, which are all based on quite different assumptions. The objective is to expand the views on software process improvement and contribute to a wider understanding of software process improvement. This might facilitate the application of software process improvement and assist in further spreading the approach. The different perspectives are expressed through four different metaphors for the work of process agents. These describe process agents as (1) technical experts, (2) facilitating participants, (3) political agents, and (4) individual therapists. We argue that the four perspectives do not preclude each other and that they can be applied to more or less effect to understand different process improvement situations. The advantages and disadvantages of each perspective for improvement work will be discussed and illustrated by examples from an ongoing software process improvement project.
Nonstationarity in regression-based spatial interpolation models First Draft ( July – August 2002 ) Revised ( April – May , 2003 )

The existence of nonstationarity, or spatial variability in geographical relationships, is a topic that has received some attention in the geographical literature in recent years. Its effect in regression-based spatial interpolation methods, however, remains an open research question. In order to explore this question, the paper describes a general regression model which can be used to derive a number of standard interpolation methods, and also a new approach capable of accommodating geographical nonstationarity. The approach proposed, it will be seen, is a synthesis of concepts derived from the methods of kriging and geographically weighted regression (GWR). Application to a case study suggests that potentially useful performance improvements may result from using the new approach.
Distortion Model Based on Word Sequence Labeling for Statistical Machine Translation

This article proposes a new distortion model for phrase-based statistical machine translation. In decoding, a distortion model estimates the source word position to be translated next (subsequent position; SP) given the last translated source word position (current position; CP). We propose a distortion model that can simultaneously consider the word at the CP, the word at an SP candidate, the context of the CP and an SP candidate, relative word order among the SP candidates, and the words between the CP and an SP candidate. These considered elements are called rich context. Our model considers rich context by discriminating label sequences that specify spans from the CP to each SP candidate. It enables our model to learn the effect of relative word order among SP candidates as well as to learn the effect of distances from the training data. In contrast to the learning strategy of existing methods, our learning strategy is that the model learns preference relations among SP candidates in each sentence of the training data. This leaning strategy enables consideration of all of the rich context simultaneously. In our experiments, our model had higher BLUE and RIBES scores for Japanese-English, Chinese-English, and German-English translation compared to the lexical reordering models.
Acceptance / Rejection Rule Based Algorithm for Multiple Face Detection in Color Images

Face recognition has been grown as a prime security idea since last decade. Face detection is the basic step in face recognition. In this paper, we have discussed the approach to detect faces from the 2D color images with single or multiple faces. Proposed algorithm work in three steps, skin color segmentation, morphological operations and last step is face rejection or acceptance. The beauty of this algorithm is that it is scale independent and orientation invariant. Skin color segmentation works as a preprocessing step to reduce the processing space. Accuracy of this algorithm is checked against various images with dynamic condition, which shows accuracy range of 90% to 100 %.
Ultra-thin metal and dielectric layers for nanophotonic applications

In our talk we first give an overview of the various thin films used in the field of nanophotonics. Then we describe our own activity in fabrication and characterization of ultra-thin films of high quality. We particularly focus on uniform gold layers having thicknesses down to 6 nm fabricated by e-beam deposition on dielectric substrates and Al-oxides/Ti-oxides multilayers prepared by atomic layer deposition in high aspect ratio trenches. In the latter case we show more than 1:20 aspect ratio structures can be achieved.
RIM Promotes Calcium Channel Accumulation at Active Zones of the Drosophila Neuromuscular Junction

Synaptic communication requires the controlled release of synaptic vesicles from presynaptic axon terminals. Release efficacy is regulated by the many proteins that comprise the presynaptic release apparatus, including Ca2+ channels and proteins that influence Ca2+ channel accumulation at release sites. Here we identify Drosophila RIM (Rab3 interacting molecule) and demonstrate that it localizes to active zones at the larval neuromuscular junction. In Drosophila RIM mutants, there is a large decrease in evoked synaptic transmission because of a significant reduction in both the clustering of Ca2+ channels and the size of the readily releasable pool of synaptic vesicles at active zones. Hence, RIM plays an evolutionarily conserved role in regulating synaptic calcium channel localization and readily releasable pool size. Because RIM has traditionally been studied as an effector of Rab3 function, we investigate whether RIM is involved in the newly identified function of Rab3 in the distribution of presynaptic release machinery components across release sites. Bruchpilot (Brp), an essential component of the active zone cytomatrix T bar, is unaffected by RIM disruption, indicating that Brp localization and distribution across active zones does not require wild-type RIM. In addition, larvae containing mutations in both RIM and rab3 have reduced Ca2+ channel levels and a Brp distribution that is very similar to that of the rab3 single mutant, indicating that RIM functions to regulate Ca2+ channel accumulation but is not a Rab3 effector for release machinery distribution across release sites.
A TURKISH AUTOMATIC TEXT SUMMARIZATION SYSTEM

The system developed in this study uses a Turkish text as input, and after the implementation of a sequence of procedures the summary results accomplishing the target sentence length. The study has been specialized to obtain more significant results for the articles on economic matters. We converted the context of all papers into HTML documents to provide the formal structures. The training system comprehends a corpus including 50 different articles. Moreover, it is possible to add the summarized document to the corpus in case of demand. The choice of the summarization percentage has been made by the user. We have utilized the Internet both for the development environment of the system and its running platform. The program interface runs on the Web through browsers. This study principally depends on the statistical analysis of the paragraphs, sentences and words in the document according to predefined specific weighting factors. Although these weight points determine the skeleton of summary, the sentences for the summarization are primarily chosen to emphasize the semantic integrity.
Managing the Iterative Requirements Process in a Multi-national Project Using an Issue Tracker

Today's software development is becoming more and more international. With involved stakeholders being distributed over several remote locations in the world, particularly the management of software requirements becomes complex and difficult to handle. In this paper, we report on a Web-based computer-aided requirements elicitation process that decreases the number of necessary face-to-face meetings and reduces communication overhead. It is thus possible to distribute requirements elicitation efforts to partners or contractors that may be situated anywhere in the world.
Real-time identification of electromyographic signals from hand movement

In this work, we have demonstrated a novel on-line technology for real-time acquisition and identification of electromyographic (EMG) signals from hand movement. EMG signal were measured using standard surface electrodes from forearm muscles at three major points including Wrist extensor, Flexor Carpi Radialis and Wrist Flexor groups, respectively. The EMG acquisition system consists of an instrumentation amplifier, filter circuit, isolator, an amplifier with gain adjustment and a commercial embedded system called FiO board. The commercial FiO embedded system is interfaced with the computer and EMG is represented, analyzed and stored in real-time on computer by Simulink program. EMG signals are identified by RMS and SD feature extraction methods and k-mean clustering algorithm. The result revealed that both RMS and SD can be used with k-mean clustering algorithm to obtain the distinct Euclidean distance characteristic of EMG signal for each movement. The minimum Euclidean distance with RMS and SD for each hand movement uniquely occurs at a distinct Euclidean distances between real EMG data and extracted features.
An Evaluation of Different Features and Learning Models for Anomalous Event Detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned 'normal' model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.
School Design and Students' Relationships with the Natural World

Abstract:This qualitative study is an exploration of intermediate students' experience of the natural world as mediated by indoor/outdoor elements. The fieldwork for this project was conducted in the spring of 2009 at Bowen Island Community School in British Columbia. The research includes data collected from two focus groups, semi-structured interviews, photographs and fieldnotes. Using thematic analysis, the research found that indoor/outdoor interfaces and the presence of both gardens and forest as play environments provided students with a sense of freedom, joy, social cohesiveness and aesthetic pleasure in relation to their physical learning environment. Results are discussed in terms of future school design and other relevant student impacts.
Long-Term Cardiovascular Fitness Is Associated with Auditory Attentional Control in Old Adults: Neuro-Behavioral Evidence

It has been shown that healthy aging affects the ability to focus attention on a given task and to ignore distractors. Here, we asked whether long-term physical activity is associated with lower susceptibility to distraction of auditory attention, and how physically active and inactive seniors may differ regarding subcomponents of auditory attention. An auditory duration discrimination task was employed, and involuntary attentional shifts to task-irrelevant rare frequency deviations and subsequent reorientation were studied by analysis of behavioral data and event-related potential measures. The frequency deviations impaired performance more in physically inactive than active seniors. This was accompanied by a stronger frontal positivity (P3a) and increased activation of anterior cingulate cortex, suggesting a stronger involuntary shift of attention towards task-irrelevant stimulus features in inactive compared to active seniors. These results indicate a positive relationship between physical fitness and attentional control in elderly, presumably due to more focused attentional resources and enhanced inhibition of irrelevant stimulus features.
A GPU based interactive modeling approach to designing fine level features

In this paper we propose a GPU based interactive geometric modeling approach to designing fine level features on subdivision surfaces. Displacement mapping is a technique for adding fine geometric detail to surfaces by using two-dimensional height map to produce photo-realistic surfaces. Due to space inefficiency and time consuming to render displacement map, this technique is generally limited in offline cinematic content creation packages. We propose a new approach to designing fine level features on subdivision surfaces via displacement mapping interactively on the latest GPU. Our method can reduce the bandwidth of the graphics channel by generating complex geometric detail on GPU, without feeding a large number of vertices to the AGP or PCI-E. Moreover, we introduce feature modification tools to flexibly control and adjust the created features. Designers can preview the features at the rendering stage, saving the time to generate the satisfying features on surfaces. The proposed approach is efficient and robust, and can be applied in many interactive graphics applications such as computer gaming, geometric modeling and computer animation.
NCTF Control for Friction Compensation of Underactuated Fingers

An appropriate control scheme must be used to alleviate nonlinearities and uncertainties for the plant system. However, this is not a trivial task due to the fact that modeling the nonlinearities such as friction and stiction are always inaccurate. For this, adaptive and robust control approaches are preferable. Thus, this paper investigates a new suggested controller scheme namely Nominal Charactersitic Trajectory Following Contoller (NCTF) to mitigate the nonlinearities and/or uncertaintites in particular to counteract the friction of the servo mechanism for the Bristol Elumotion Robot Hand (BERUL). The NCTF control performance will be compared with an adaptive control in simulation. Comparative performance characteristics have shown that the NCTF control has produced lower total control energy than the adaptive control when controlling the tracking and positioning for underactuated fingers. Keywords—NCTF control, adaptive control and underactuated fingers.