Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of Heterogeneous Computing in Computational and Simulation Science

As the size and complexity of scientific problems and datasets grow, scientists from a broad range of discipline areas are relying more and more on computational methods and simulations to help solve their problems. This paper presents a summary of heterogeneous algorithms and applications that have been developed by a large research organization (CSIRO) for solving practical and challenging science problems faster than is possible with conventional multi-core CPUs alone. The problem domains discussed include biological image analysis, computed tomography reconstruction, marine biogeochemical models, fluid dynamics, and bioinformatics. The algorithms utilize GPUs and multi-core CPUs on a scale ranging from single workstation installations through to large GPU clusters. Results demonstrate that large GPU clusters can be used to accelerate a variety of practical science applications, and justify the significant financial investment and interest being placed into such systems.
The free recall search process introduces errors in short term memory but apparently not in long term memory

Here it is reported that the free recall search process increases the error rate for short term memory (about 1% per second in data from Murdock & Okada (1970)) but not for long term memory (in data from McDermott (1996)). If the short term memory search process introduces random excitations, which would account for the search errors, the subjects should be unaware of making such errors. This is in agreement with DRM findings (Gallo, 2010) and the new finding that the error terminated distributions in Murdock (1962) are the same as those terminated by studied items.
A dataset for workflow recognition in industrial scenes

In this paper we introduce the WR (Workflow Recognition) dataset. Recorded in the production line of a major automobile manufacturer, this dataset consists of sequences that depict workers executing industrial workflows. The heavy occlusions, outliers, the visually complicated background and the human-machinery interaction are among the factors that make this dataset a very challenging testbed for computer vision and image processing algorithms. We provide the original video sequences together with event labeling, as well as feature vectors extracted through our proposed scene representation methodology, and we refer to our results so far in workflow recognition using this dataset.
Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) a Consistent Bending Model for Cloth Simulation with Corotational Subdivision Finite Elements

Wrinkles and folds play an important role in the appearance of real textiles. The way in which they form depends mainly on the bending properties of the specific material type. Existing approaches fail to reliably reproduce characteristic behaviour like folding and buckling for different material types or resolutions. It is therefore crucial for the realistic simulation of cloth to model bending energy in a physically accurate and consistent way. In this paper we present a new method based on a corotational formulation of subdivision finite elements. Due to the non-local nature of the employed subdivision basis functions a C 1-continuous displacement field can be defined. In this way, it is possible to use the governing equations of thin shell analysis leading to physically accurate bending behaviour. Using a corotated strain tensor allows the large displacement analysis of cloth while retaining a linear system of equations. Hence, known convergence properties and computational efficiency are preserved while convincing and detailed folding behaviour is obtained in the simualtion.
Intracerebroventricular Administration of Neuropeptide Y Induces Hepatic Insulin Resistance via Sympathetic Innervation

OBJECTIVE—We recently showed that intracerebroventricular infusion of neuropeptide Y (NPY) hampers inhibition of endogenous glucose production (EGP) by insulin in mice. The downstream mechanisms responsible for these effects of NPY remain to be elucidated. Therefore, the aim of this study was to establish whether intracerebroventricular NPY administration modulates the suppressive action of insulin on EGP via hepatic sympathetic or parasympathetic innervation. RESEARCH DESIGN AND METHODS—The effects of a continuous intracerebroventricular infusion of NPY on glucose turnover were determined in rats during a hyperinsulinemic-euglycemic clamp. Either rats were sham operated, or the liver was sympathetically (hepatic sympathectomy) or parasympathetically (hepatic parasympathectomy) denervated. RESULTS—Sympathectomy or parasympathectomy did not affect the capacity of insulin to suppress EGP in intracerebroventricular vehicle–infused animals (50 ± 8 vs. 49 ± 6 vs. 55 ± 6%, in hepatic sympathectomy vs. hepatic parasympathectomy vs. sham, respectively). Intracerebroventricular infusion of NPY significantly hampered the suppression of EGP by insulin in sham-denervated animals (29 ± 9 vs. 55 ± 6% for NPY/sham vs. vehicle/sham, respectively, P = 0.038). Selective sympathetic denervation of the liver completely blocked the effect of intracerebroventricular NPY administration on insulin action to suppress EGP (NPY/hepatic sympathectomy, 57 ± 7%), whereas selective parasympathetic denervation had no effect (NPY/hepatic parasympathectomy, 29 ± 7%). CONCLUSIONS—Intracerebroventricular administration of NPY acutely induces insulin resistance of EGP via activation of sympathetic output to the liver.
Optical See-Through Head Mounted Display Direct Linear Transformation Calibration Robustness in the Presence of User Alignment Noise

The correct spatial registration between virtual and real objects in optical see-through augmented reality implies accurate estimates of the user's eyepoint relative to the location and orientation of the display surface. A common approach is to estimate the display parameters through a calibration procedure involving a subjective alignment exercise. Human postural sway and targeting precision contribute to imprecise alignments, which in turn adversely affect the display parameter estimation resulting in registration errors between virtual and real objects. The technique commonly used has its origin in computer vision, and calibrates stationary cameras using hundreds of correspondence points collected instantaneously in one video frame where precision is limited only by pixel quantization and image blur. Subsequently the input noise level is several order of magnitudes greater when a human operator manually collects correspondence points one by one. This paper investigates the effect of human alignment noise on view parameter estimation in an optical see-through head mounted display to determine how well a standard camera calibration method performs at greater noise levels than documented in computer vision literature. Through Monte-Carlo simulations we show that it is particularly difficult to estimate the user's eyepoint in depth, but that a greater distribution of correspondence points in depth help mitigate the effects of human alignment noise.
Quadrocopter pole acrobatics

We present the design of a system that allows quadrocopters to balance an inverted pendulum, throw it into the air, and catch and balance it again on a second vehicle. Based on first principles models, a launch condition for the pole is derived and used to design an optimal trajectory to throw the pole towards a second quadrocopter. An optimal catching instant is derived and the corresponding position is predicted by simulating the current position and velocity estimates forward in time. An algorithm is introduced that generates a trajectory for moving the catching vehicle to the predicted catching point in real time. By evaluating the pole state after the impact, an adaptation strategy adapts the catch maneuver such that the pole rotates into the upright equilibrium by itself. Experimental results demonstrate the performance of the system.
On the Design of a Fault-Tolerant Photonic Network-on-Chip

Optical Network-on-Chip is a solution to for power and throughput bottlenecks of current technology. The higher bandwidth is achieved by the light speed transmissions, and the power required to transmit data in the optical domain is much lower. This is a disruptive technology solution to problems arising from silicon-based computing. In this paper, we present a fault-tolerant optical router (FTTDOR) with its electrical control module towards the design of a highly-reliable low-power three dimensional Networks-on-Chip (PHENIC). FTTDOR uses redundancy only in critical locations, to assure accuracy of the packet transmission even after a faulty ring resonator appears. The proposed optical router is decomposed non-blocking, with minimal ring resonators, and requires no resonators for straight travel (East to West, North to South, and Up to Down, as well as their inverses). Simulation results show that the network can maintain a 98% throughput after 3% faults, and 89% after 20% faults. These results come with a reduction of micro-ring resonators to 65% of the amount present in a conventional crossbar router. Simulation of the electrical control module and router show that it has a total area of around 20,000 μm2 and consumes 3.8mW at 600MHz.
Last significant trend change detection method for offline poisson distribution datasets

Trend change detection methods find trends in a dataset. Datasets based on Poisson distribution are important to analyze since they mimic many different applications such as computer networks. Our use-cases are simulations of computer networks. The last significant trend is the last predominant trend in a time-series dataset. Our method is a matrix based trend change detection that can analyze datasets with variable sizes. Reducing the time complexity and increasing the accuracy when determining the last significant trend are the goals of our method. We compare our method with RuLSIF, a basic change point detection method, to illustrate the benefits of our approach.
Audio or tactile feedback: which modality when?

When designing interfaces for mobile devices it is import-ant to take into account the variety of contexts of use. We present a study that examines how changing noise and dis-turbance in the environment affects user performance in a touchscreen typing task with the interface being presented through visual only, visual and tactile, or visual and audio feedback. The aim of the study is to show at what exact environmental levels audio or tactile feedback become inef-fective. The results show significant decreases in perform-ance for audio feedback at levels of 94dB and above as well as decreases in performance for tactile feedback at vibration levels of 9.18g/s. These results suggest that at these levels, feedback should be presented by a different modality. These findings will allow designers to take advantage of sensor enabled mobile devices to adapt the provided feed-back to the user's current context.
SINAI at WePS-3: Online Reputation Management

The online reputation management systems help to the consumers to make buying decisions looking for opinions in the web about many products oﬀered by companies, also interested in the same opinions. This paper presents the system developed by the SINAI research group at the WEPS-3 task, called Online Reputation Management. Given a Twitter entry and a company name, the goal is to decide if the entry talks about this company. Our system is based on the use of linguistic information in Twitters entries for extracting information and creating an XML data collection about companies referred in the Twitter entries. This XML collection is ﬁlled extracting information from Internet web pages, like Wikipedia, and the use of the DBpedia ontology. Using this collection and some logical rules we have developed a promising system, with a very good precision and easily extensible with the addition of new rules and other Internet resources.
Expressing and checking intended changes via software change contracts

Software errors often originate from incorrect changes, including incorrect program fixes, incorrect feature updates and so on. Capturing the intended program behavior explicitly via contracts is thus an attractive proposition. In our recent work, we had espoused the notion of "change contracts" to express the intended program behavior changes across program versions. Change contracts differ from program contracts in that they do not require the programmer to describe the intended behavior of program features which are unchanged across program versions. In this work, we present the formal semantics of our change contract language built on top of the Java Modeling Language (JML). Our change contract language can describe behavioral as well as structural changes. We evaluate the expressivity of the change contract language via a survey given to final year undergraduate students. The survey results enable us to understand the usability of our change contract language for purposes of writing contracts, comprehending written contracts, and modifying programs according to given change contracts. Finally, we discuss the tool support developed for our change contract language. The tool support enables (i) test generation to witness contract violation, as well as (ii) automated repair of certain tests which are broken due to program changes.
ISCOMATRIX Adjuvant Induces Efficient Cross-Presentation of Tumor Antigen by Dendritic Cells via Rapid Cytosolic Antigen Delivery and Processing via Tripeptidyl Peptidase II1

Cancer vaccines aim to induce antitumor CTL responses, which require cross-presentation of tumor Ag to CTLs by dendritic cells (DCs). Adjuvants that facilitate cross-presentation of vaccine Ag are therefore key for inducing antitumor immunity. We previously reported that human DCs could not efficiently cross-present the full-length cancer/testis Ag NY-ESO-1 to CTL unless formulated as either an immune complex (NY-ESO-1/IC) or with ISCOMATRIX adjuvant. We now demonstrate that NY-ESO-1/ICs induce cross-presentation of HLA-A2- and HLA-Cw3-restricted epitopes via a proteasome-dependent pathway. In contrast, cross-presentation of NY-ESO-1/ISCOMATRIX vaccine was proteasome independent and required the cytosolic protease tripeptidyl peptidase II. Trafficking studies revealed that uptake of ICs and ISCOMATRIX vaccine by DCs occurred via endocytosis with delivery to lysosomes. Interestingly, ICs were retained in lysosomes, whereas ISCOMATRIX adjuvant induced rapid Ag translocation into the cytosol. Ag translocation was dependent on endosomal acidification and IL-4-driven differentiation of monocytes into DCs. This study demonstrates that Ag formulation determines Ag processing and supports a role for tripeptidyl peptidase II in cross-presentation of CTL epitopes restricted to diverse HLA alleles.
Development of an Annotation Scheme for Emotionally Relevant Behavior in Multiparty Meeting Speech

We present the development of an annotation scheme for labeling emotions and emotion-related phenomena in multi-party meetings. Our initial experiments suggest that when attempting to characterize emotional episodes, people show preference for describing the intentions and coping behaviors of speakers rather than inferring their emotional state. Accordingly, we propose a pragmatic annotation scheme for emotionally relevant behavior, in addition to a simple assessment of valence on a separate tier. The aim of the annotation is to produce a two-part label per speaker utterance, suitable for subsequent browsing of meeting corpora, machine intervention in meetings, and computational modeling of multi-party discourse in general. We explore interlabeler agreement and correlation between the two tiers.
On-line estimation of unit hydrographs using the wavelet-based LMS algorithm / Estimation en ligne des hydrogrammes unitaires grâce à l'algorithme des moindres carrés moyens à base d'ondelettes

Abstract This study applies the discrete wavelet transform (DWT) to decompose the unit hydrograph, thereby generating parsimonious reparameterizations of the unit hydrograph. A model compression method is then employed to significantly compress the unit hydrograph requiring that fewer coefficients be estimated. Moreover, a wavelet-based linearly constrained least mean squares (WLCLMS) algorithm is also used to estimate on-line the wavelet coefficients of the unit hydrograph. The updated wavelet coefficients of the unit hydrograph, convoluted with effective rainfall input in the wavelet domain, allow for accurate prediction of one-step-ahead runoff in the time domain. The proposed approach allows the unit hydrographs to vary in time and accurately predicts runoff from a basin in Taiwan, thus making it highly promising for flood forecasting.
Myoglobinemia and endurance exercise: A study of twenty-five participants in a triathlon competition

Twenty-five athletes competing in a triathlon, an endur ance competition, were studied to determine the rela tionship of sustained muscle exertion with myoglobin emia and clinical rhabdomyolysis. Of 24 athletes who completed the event, each individual demonstrated a dramatic rise and fall in serum myoglobin over a 24 hour period, with an average peak level of 842 ng/ml. While all subjects exhibited symptoms of myalgia after exertion, none required hospitalization. A significant correlation was demonstrated with average serum my oglobin and finishing time (P < 0.0125) and postexer cise temperature (P < 0.05). Appropriate training of individuals, whether athletes or military recruits, ap pears to be an important factor in reducing myoglobin emia. Exercise-induced myoglobinemia appears to be dependent on intensity of athletic performance, meas ured as a function of time, distance, and activity per formed. The athletes who finished first had the highest levels of myoglobinemia.
Complex Event Processing Under Uncertainty: A Short Survey

Complex Event Recognition (CER) applications exhibit various types of uncertainty, ranging from incomplete and erroneous data streams to imperfect complex event patterns. We review CER techniques that handle, to some extent, uncertainty. We examine both automata-based techniques, which are the most often, and logic-based ones, which are less frequently used. A number of limitations are identiﬁed with respect to the employed languages, their probabilistic models and their performance, as compared to the purely deterministic cases.
Expression of an exogenous interleukin 6 gene in human Epstein Barr virus B cells confers growth advantage and in vivo tumorigenicity

The biological role of interleukin 6 (IL-6) molecules in human B cell tumorigenesis was studied by using an episomal expression vector, pHEBoSV-IL6, to introduce stably the human IL-6 gene into human Epstein Barr virus (EBV)-transformed B lymphoblasts. The gene was present in the IL-6-transfected cells in a high copy number and was efficiently expressed, resulting in the secretion of consistent levels of IL-6 molecules. The constitutive expression of the IL-6 gene led to an altered pattern of growth and to a malignant phenotype, as shown by clonogenicity in to an altered pattern of growth and to a malignant phenotype, as shown by clonogenicity in soft agar cultures and tumorigenicity in nude mice. These data suggest that the combined action of EBV, which exerts an immortalizing function, and of the growth-promoting activity of IL-6 molecules, can give rise to fully transformed B cell tumors in immunodeficient subjects.
Web Topic Summarization

In this paper, we present our online summarization system of web topics. The user defines the topic by a set of keywords. Then the system searches the Web for the relevant documents. The top ranked documents are returned and passed on to the summarization component. The summarizer produces a summary which is finally shown to the user. The proposed architecture is fully modular. This enables us to quickly substitute a new version of any module and thus the quality of the system’s output will get better with module improvements. The crucial module which extracts the most important sentences from the documents is based on the latent semantic analysis. Its main property is independency of the language of the source documents. In the system interface, one can choose to search a news site in English or Czech. The results show a very good search quality. Most of the retrieved documents are fully relevant, only a few being marginally relevant. The summarizer is comparable to state-of-the-art systems.
Information-Theoretic Measures on Intrinsic Mode Function for the Individual Identification Using EEG Sensors

In spite of recent advances, the interest in extracting knowledge hidden in the electroencephalogram (EEG) signals is rapidly growing, as well as their application in the computational neuroengineering field, such as mobile robot control, wheelchair control, and person identification using brainwaves. The large number of methods for the EEG feature extraction demands a good feature for every task. Digging up the most unique feature would be worthy for the identification of individual using EEG signal. This research presents a novel approach for feature extraction of EEG signal using the empirical mode decomposition (EMD) and information-theoretic method. The EMD technique is applied to decompose an EEG signal into a set of intrinsic mode function. These decomposed signals are of the same length and in the same time domain as the original signal. Hence, the EMD method preserves varying frequencies in time. To measure the performance of the features, we have used hybrid learning for classification where we have selected learning vector quantization neural network with fuzzy algorithm. In order to test the performance of proposed classifier based on fuzzy theory, we have tested classification accuracy of each cognitive task over all participated subjects. The results are compared with the past methods in the literature for feature extraction and classification methods. Results confirm that the proposed features present a satisfactory performance.
Performance Analysis of Malicious Node Aware Routing for MANET using Two-Hop Authentication

The inherent features of the MANET [1] make it vulnerable to a wide range of attacks. There is no guarantee that a communication path is free from malicious and compromised nodes which deliberately wish to disrupt the network communication. In this paper, we present a security mechanism that provides message integrity, mutual authentication and twohop authentication mechanism without the assistance of online certification authority. Our mechanism not only prevents identity impersonation, replay attacks, but also enables node to regulate the behavior of its neighbors to foil active attacks. The effectiveness of the proposed scheme is analyzed to DSR and OLSR routing using simulator NS2.34
Predictive torque control of interior permanent magnets synchronous motors in stator co-ordinates

This paper proposes a possible approach to control the synchronous machines with interior (buried) permanent magnets (IPM SM). If properly controlled, this construction allows for an increase in torque through a reluctance component that adds to the main torque caused by the permanent magnets. Since the overall torque depends on the load angle and stator current magnitude, the optimal relationship between these two variables can be pre-calculated prior to the machine start. The inverse procedure allows a determination of the unique load angle and current reference, which, in turn, form a stator flux. The latter is calculated from discretized basic voltage equation in each sampling interval. This procedure is called Predictive Torque Control (PTC). An output variable (reference stator flux) is then passed to the block for Immediate Flux Control (IFC), already tested on induction machines. Its aim is to generate the actual stator flux by selecting proper inverter voltage vectors and determining their application time. The results have been verified on experimental model of a real machine.