Miracle-dz/UniFAR-FTUs huggingface dataset:
SCALABLE RECOMMENDATION WITH SOCIAL CONTEXTUAL INFORMATION

Recommender systems are used to achieve effective and useful results in a social networks. The social recommendation will provide a social network structure but it is challenging to fuse social contextual factors which are derived from user’s motivation of social behaviors into social recommendation. Here, we introduce two contextual factors in recommender systems which are used to adopt a useful results namely a) individual preference and b) interpersonal influence. Individual preference analyze the social interests of an item content with user’s interest and adopt only users recommended results. Interpersonal influence is analyzing user-user interaction and their specific social relations. Beyond this, we propose a novel probabilistic matrix factorization method to fuse them in a latent space. The scalable algorithm provides a useful results by analyzing the ranking probability of each user social contextual information and also incrementally process the contextual data in large datasets.
Fair share: Allocation of GPU resources for both performance and fairness

General-purpose computing on the GPU (GPGPU computing) is becoming widely adopted for an increasing variety of applications. However, it has been shown that as the available computing elements in the GPU increase with every generation some GPGPU applications fail to fully utilize the GPU resources. Spatial multitasking-subdividing GPU resources amongst concurrently-running applications-has been shown to increase overall system performance and utilization for GPGPU computing. However, dividing the computing resources among multiple applications to maximize system performance often results in one application having “unfair” access to GPU resources. Yet, evenly dividing resources among applications does not guarantee equal speedups to each application; nor does it take into account overall system performance. In this paper we examine several different ways to characterize “fairness” for GPGPU spatial multitasking, by balancing individual application's performance and overall system performance. We further present a run-time algorithm to predict and adjust the SM allocation at runtime to meet the desired fairness metric.
A pilot study of the effect of low level exposure to mercury on the health of dental surgeons.

OBJECTIVES--This project was conducted to examine whether the computerised analysis of psychomotor responses available from Cognitive Drug Research is appropriate for measuring an effect of low level exposure to mercury in dentists. METHODS--A computerised battery of psychomotor tests was given to two groups of dentists (older dentists and trainees) and to two age matched control groups. As well as the psychomotor tests, volunteers were required to complete a questionnaire to identify potential influences on psychomotor performance and to provide a sample for analysis of urinary mercury. RESULTS--Statistical analysis of the results showed that the older dentists had slightly higher concentrations of urinary mercury although most were around background levels and they were all within occupational limits. Five of the psychomotor tests showed no differences between the performance of the four groups. The older dentists showed significantly better performance on the simple reaction time test and significantly poorer performance in the immediate word recall and delayed word recall tests. CONCLUSIONS--Poorer performance in memory recall tests confirms previously reported studies. This together with the confirmation that this test system is a practical tool in the occupational setting suggests that a larger study of the effects of mercury exposure on dentists would be appropriate.
Inhibition of tumor growth by ribozyme-mediated suppression of aberrant epidermal growth factor receptor gene expression.

BACKGROUND Amplification and rearrangement of the epidermal growth factor receptor (EGFR) gene is frequently associated with malignant gliomas. One type of EGFR mutation in primary gliomas results in overexpression of an aberrant EGFR messenger RNA (mRNA) that lacks sequences of exons II through VI of the human EGFR gene. We observed that the aberrantly spliced EGFR mRNA contains a ribozyme cleavable sequence (5'-AAG GUA AUU-3') created by the joining of EGFR exon I to exon VII. We hypothesized that an appropriately designed ribozyme RNA could mediate site-specific cleavage of the aberrant EGFR mRNA and reduce the growth of aberrant EGFR-producing tumor cells. METHODS We synthesized aberrant EGFR mRNA substrates and a sequence-specific hammerhead ribozyme (abEGFR-rib) to examine the ribozyme's activity in vitro. We also constructed an abEGFR-rib plasmid and introduced it into ERM5-1 cells, which are murine NIH3T3 cells transfected to express an aberrant EGFR complementary DNA. We measured the growth potential of the cotransfected cells in culture and in nude mice. RESULTS The synthesized abEGFR-rib efficiently and specifically cleaved aberrant EGFR mRNA substrates in vitro. Expression of the transfected abEGFR-rib suppressed expression of aberrant EGFR mRNA in ERM5-1 cells and reduced the growth of tumors formed by the cotransfected cells in nude mice. Finally, the incorporation of bromodeoxyuridine, a measure of mitotic activity, was also decreased in abEGFR-rib-producing ERM5-1 cells in vivo. CONCLUSION Ribozymes targeted to aberrant EGFR mRNA can inhibit the growth of tumors formed by cells that express this mRNA.
Perceptually Optimized Coded Apertures for Defocus Deblurring

The field of computational photography, and in particular the design and implementation of coded apertures, has yielded impressive results in the last years. In this paper we introduce perceptually optimized coded apertures for defocused deblurring. We obtain near‐optimal apertures by means of optimization, with a novel evaluation function that includes two existing image quality perceptual metrics. These metrics favour results where errors in the final deblurred images will not be perceived by a human observer. Our work improves the results obtained with a similar approach that only takes into account the L2 metric in the evaluation function.
Future transport concepts: in a supply chain learning perspective

This paper presents an action research project carried out in co-operation with two Danish transport companies. The project is part of a larger project ‘Future Transport Concepts’ which is running simultaneously in four different transport companies with the purpose of initiating a concept driven process towards the development of future transport concepts. The paper discusses how the concept of action research may be a desirable method for installing organisational learning processes along the supply chains with the focal focus on the transport companies and their networks. It discusses the results, the method and the researchers’ roles as active facilitators in initiating learning processes. It is shown how the actors within the organisations formed arenas for learning across old boundaries, space and time in order to develop processes of supply chain learning.
Model-based tracking of self-occluding articulated objects

Computer sensing of hand and limb motion is an important problem for applications in human computer interaction and computer graphics. We describe a framework for local trading of self occluding motion, in which one part of an object obstructs the visibility of another. Our approach uses a kinematic model to predict occlusions and windowed templates to track partially occluded objects. We present offline 3D tracking results for hand motion with significant self occlusion. <<ETX>>
A New Specification-based Test Data Generation Strategy for OSEK OS

Specification-based test is used to test a software application to check if it conforms to its design specification. Writing adequate test suites is very challenging and labor-intensive. Producing Specification-based tests for Real-Time Operating System (RTOS) is more challenging than for generic applications since specifications of RTOS only provide resource management mechanisms rather than specific application functionality descriptions. In this paper, we investigate whether Genetic Algorithms (GAs) can generate qualified tests for RTOS, and we present an effective GA approach with an optimization of Kuhn-Munkres maximum weighted algorithm. Experiment results demonstrate the effectiveness of our approach. It is able to generate 100% state coverage tests within 200 generations.
on Automation and Robotics in Construction ( ISARC 2010 ) MODEL-BASED 3 D TRACKING IN MULTIPLE CAMERA VIEWS

We present a method for tracking objects in 3D by comparing views from multiple video cameras against a 3D model. Camera-based object tracking is a vast field that until recently has been limited to the 2D (image) domain. With the falling cost of sensors in recent years, the research community has been shifting its focus to 3D tracking using networks of calibrated cameras. The standard approach has been to run traditional 2D tracking in each video and fuse the results. The algorithm described below tracks objects directly in 3D to give increased precision and to overcome limitations inherent in the standard approach. We demonstrate the effectiveness in tracking construction personnel in video sequences of a construction site mock-up, resulting in a reduction in tracking error over current methods.
Classification of high resolution urban satellite images combining SVM and graph cuts

The classification of remotely sensed images knows a large progress seen the availability of images of different resolutions as well as the abundance of the techniques of classification. Moreover a number of works showed promising results by the fusion of spatial and spectral information. For this purpose we propose a methodology allowing to combine this two information to refine an SVM classification, The approach uses graph cuts to improve the SVM algorithm, as graph cuts introduce spatial domain information of the image that is lacking in the SVM. The proposed approach is tested on common scenes of urban imagery. The experimental results show satisfactory values and are very promising.
An outpatient parenteral antibiotic therapy (OPAT) map to identify risks associated with an OPAT service.

OBJECTIVES Administering parenteral antibiotics outside the confines of a ward setting is becoming an attractive way of treating infections in the UK. However, as well as having many advantages, an outpatient parenteral antibiotic therapy (OPAT) service potentially introduces new risks to staff and patients involved. In the United States, healthcare organizations are now prospectively analysing processes to try and prevent errors occurring using the Healthcare Failure Mode Effect Analysis (HFMEA) tool. The objectives of this study were to map out and agree the OPAT process and sub-processes and to identify potential OPAT system failures using steps 1-3 of the HFMEA tool, so that the resulting OPAT map can be used to design an OPAT service where risk is minimized. METHODS The study was undertaken using a consensus development panel to which the HFMEA process was applied. Key stakeholders in the local OPAT process were invited to join the HFMEA team with the aim of describing and agreeing (defined as 100% participant agreement) an OPAT map, its sub-processes and potential OPAT system failures. RESULTS The HFMEA team identified 6 processes, 67 sub-processes and 217 possible failures over the course of four meetings. Key areas identified in the OPAT map concerned identifying and checking patient suitability for an OPAT service, involvement of a multidisciplinary team and robust communication channels. CONCLUSIONS An OPAT map was developed, which may serve as a practical model for other organizations setting up a similar service.
Cell-Cycle Analyses Using Thymidine Analogues in Fission Yeast

Thymidine analogues are powerful tools when studying DNA synthesis including DNA replication, repair and recombination. However, these analogues have been reported to have severe effects on cell-cycle progression and growth, the very processes being investigated in most of these studies. Here, we have analyzed the effects of 5-ethynyl-2′-deoxyuridine (EdU) and 5-Chloro-2′-deoxyuridine (CldU) using fission yeast cells and optimized the labelling procedure. We find that both analogues affect the cell cycle, but that the effects can be mitigated by using the appropriate analogue, short pulses of labelling and low concentrations. In addition, we report sequential labelling of two consecutive S phases using EdU and 5-bromo-2′-deoxyuridine (BrdU). Furthermore, we show that detection of replicative DNA synthesis is much more sensitive than DNA-measurements by flow cytometry.
Internal dynamics and particle acceleration in Tycho's SNR

Aims. The consequences of a newly suggested value for the SN explosion energy E sn = 1.2 $\times$ 10 51 erg are explored for the case of Tycho's supernova remnant (SNR). Methods. A nonlinear kinetic theory of cosmic ray (CR) acceleration in supernova remnants (SNRs) is employed to investigate the properties of Tycho's SNR and their correspondence to the existing experimental data. Results. It is demonstrated that the high mean ratio between the radii of the contact discontinuity and the forward shock is consistent with the very effective acceleration of nuclear energetic particles at the forward shock. It is also argued that consistency of the value E sn = 1.2 $\times$ 10 51 erg with the gas dynamics, acceleration theory, and the existing γ -ray measurements requires the source distance ${ d}$ to be greater than 3.3 kpc. The corresponding ambient gas number density is lower than 0.4 cm -3 . Since the expected γ -ray flux strongly depends on the source distance, $F_{\gamma}\propto d^{-7}$, a future experimental determination of the actual γ -ray flux from Tycho's SNR will make it possible to determine the values of the source distance ${ d}$ and of the mean ambient gas density. A simple inverse Compton model without a dominant population of nuclear CRs is not compatible with the present upper limit for the γ -ray emission for any reasonable ambient interstellar B -field. Conclusions. Given the consistency between acceleration theory and overall, as well as internal, gas dynamics, a future γ -ray detection would make the case for nuclear particle acceleration in Tycho's SNR incontrovertible in our view.
Bayesian decision aggregation in collaborative intrusion detection networks

Cooperation between intrusion detection systems (IDSs) allow collective information and experience from a network of IDSs to be shared for improving the accuracy of detection. A critical component of a collaborative network is the mechanism of feedback aggregation in which each IDS makes an overall security evaluation based on peer opinions and assessments. In this paper, we propose a collaboration framework for intrusion detection networks (CIDNs) and use a Bayesian approach for feedback aggregation by minimizing the combined costs of missed detection and false alarm. The proposed model is highly scalable, robust, and cost effective. Experimental results demonstrate an improvement in the true positive detection rate and a reduction in the average cost of our mechanism compared to existing models.
An efficient texture feature extraction method for classification of liver sonography based on Gabor Wavelet

In this paper we proposed a new method for texture classification of ultrasonic liver images based on Gabor wavelet. It is well known that Gabor wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction in which the conflicting objectives of accuracy in texture representation and texture spatial localization are both important. This fact has been explored in our results as it shows that the classification rate obtained by Gabor wavelet is higher that those obtained using dyadic wavelets. The fearure vector consists of . parameters from Gabor wavelets which is relatively small compared to other methods. This has a significant impact on the speed of retrieval process. The proposed algorithm applied to discriminate ultrasonic liver images into three disease states that are normal liver, liver hepatits and cirrhosis. In our experiment 45 liver sample images from each three disese states which already proven by needle bioposy were used. We achieved the classification rate 85% in the distinction between normal and abnormal liver images and 80% in the distinction between cirrhosis and hepatitis liver images. Based on our experiments, the Gabor wavelet is more appropriate than dyadic wavelets for texture classification as it leads to higher classification accuracy.
The Effect of a Cold Environment on Physical Activity Profiles in Elite Soccer Match-Play

In this study, the effect of cold temperature on the physical activity profiles of professional soccer players in official match-play was investigated. Computerised motion-analysis was used to analyse performance in 9 players (4 defenders and 5 midfielders) in 4 temperature ranges: ≤ 5°C (29 matches), 6-10°C (62 matches), 11-20°C (48 matches) and ≥ 21°C (27 matches). Performance was analysed per minute for total distance covered and distance run in 3 categories: 0.0-14.3 km/h (walking/low/moderate); 14.4-19.7 km/h (running); ≥ 19.8 km/h (high-intensity). Results showed that while total distance run per minute was unaffected in colder conditions, midfielders ran significantly shorter distances in warmer temperatures: ≥21°C = 118.7 ± 6.9 m vs. ≤ 5°C=124.2 ± 7.1 m, p < 0.01; 6-10°C = 123.6 ± 6.8 m, p < 0.01; and, 11-20°C = 123.4 ± 5.4, p < 0.05). The total distance covered at 3 intensities and across halves was unaffected by temperature. Similarly, high-intensity efforts across match halves and in the first and final 5-min periods in each half of normal time were unaffected by temperature. In contrast, high-intensity efforts in midfielders across 15-min intervals were affected by temperature with greater distances covered per minute in the 30-45 min period in matches played in temperatures ≤ 5°C vs. the corresponding period in those played in temperatures ≥ 21°C (9.1 ± 3.8 m vs. 6.2 ± 3.0 m, p < 0.05). The present findings generally suggest that physical performance in professional soccer does not decrease in cold temperatures.
A Linear Classifier Outperforms UCT in 9 x 9 Go

The dominant paradigm in computer Go is Monte-Carlo Tree Search (MCTS). This technique chooses a move by playing a series of simulated games, building a search tree along the way. After many simulated games, the most promising move is played. This paper proposes replacing the search tree with a neural network. Where previous neural network Go research has used the state of the board as input, our network uses the last two moves. In experiments exploring the effects of various parameters, our network outperforms a generic MCTS player that uses the Upper Confidence bounds applied to Trees (UCT) algorithm. A simple linear classifier performs even better.
Information theft through covert channel by exploiting HTTP post method

Covert channel is a known vulnerability in most of the network protocols that makes it possible for peers to communicate non-legitimately using known channels. This papers aims at demonstrating information theft scenario by means of covert channel in which it is used as a carrier for transmitting information that is stolen by exploiting HTTP Post method. The paper describes and demonstrates a mechanism of information theft through covert channel exploitation. Some potential countermeasure techniques are suggested on the basis of observed covert channels which is part of our future work.
Building Scalable Lazy Rough Classifiers

We present a lazy classification method, which is equivalent to the rough set based method for construction of classifiers, but is scalable and applicable for large data sets. The proposed method is based on our previous papers Nguyen (2002) Nguyen (2006), where the relationship between rough sets methods and association learning methods were discovered. In this method the set of decision rules matching the test object is generated directly from the training data set. To make it scalable, we adopted the idea of the FP-growth algorithm for frequent item-sets Han et al. (2000), Han and Kamber (2000). Except the classification task, this method can be applied for construction of adaptive rule generation system where data are growing up in time.
Compressed UWB signal detection with narrowband interference mitigation

Operating at sub-Nyquist rate, compressed sensing (CS) has been successfully applied to the design of impulse ultra-wideband (I-UWB) receivers where Nyquist sampling is a formidable challenge. However, strong narrowband interference (NBI) can easily jam and saturate the receiver front-end and greatly degrade the system performance. In this paper, CS is applied to the design of I-UWB receivers with NBI mitigation. By exploiting the sparsity of the NBI within the pulse UWB spectrum, a compressive measurement matrix can be designed that is not only efficient at collecting signal energy, but also nulls out the NBI effectively. The performance analysis of the proposed receiver is provided. Simulation results show the effectiveness of the proposed method for UWB signal detection and NBI mitigation.
Spatial min-Hash for similar image search

We propose a spatial min-Hash algorithm that groups the minimal hashing functions into an s-tuples called a sketch depending on the spatial context. We use the bag-of-words technology to represent an image in a spatial pyramid way, and generate a minimal hashing function for each spatial location of the corresponding level. These minimal hashing functions are bundled to form a sketch. Furthermore, we implement the proposed algorithm to similar image searching. We use the binary SIFT combined with Hamming distance to verify the candidate images obtained by the spatial min-Hash in order to improve the retrieval performance. There are two advantages of our method: 1) the spatial min-Hash is more discriminative than the standard min-Hash in term of image representation; 2) the feature matching based on the binary SIFT in the verification stage improves the performance of image retrieval with a low computational cost. We implement our method on Oxford building dataset, and the experimental results demonstrate that the spatial min-Hash is a stronger representation method than the standard min-Hash, and the spatial min-Hash is superior to the standard min-Hash in term of retrieval performance.
Pointing as an Instrumental Gesture: Gaze Representation Through Indication

We call those gestures “instrumental” that can enhance certain thinking processes of an agent by offering him representational models of his actions in a virtual space of imaginary performative possibilities. We argue that pointing is an instrumental gesture in that it represents geometrical information on one’s own gaze direction (i.e., a spatial model for attentional/ocular fixation/orientation), and provides a ritualized template for initiating gaze coordination and joint attention. We counter two possible objections, asserting respectively that the representational content of pointing is not constitutive, but derived from language, and that pointing directly solicits gaze coordination, without representing it. We consider two studies suggesting that attention and spatial perception are actively modified by one’s own pointing activity: the first study shows that pointing gestures help children link sets of objects to their corresponding number words; the second, that adults are faster and more accurate in counting when they point.