Miracle-dz/UniFAR-FTUs huggingface dataset:
An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.
Performance analysis of local caching replacement policies for internet video streaming services

In this work, the performance of 5 representative caching replacement policies was investigated and compared for caching Internet video-on-demand (VoD) in local access networks. Two measured traces of end-user requests were used in the analyses for two typical VoD services: TV-on-demand and user generated content represented by YouTube. The studied policies range from simple least recently used (LRU) and least frequently used (LFU) algorithms to more advanced ones denoted as LFU-dynamic lifespan (LFU-DL), Adaptive replacement cache (ARC) and Greedy-dual size frequency (GDSF). Our results show that the ARC policy always outperforms the other policies due to its adaptive nature and its ability to track changes in the traffic patterns. On the other hand, the simple LRU policy can also achieve a caching performance which is comparable to that of the more advanced ARC policy especially for the TV-on-demand service when the potential caching gain is high. On the contrary, the simple LFU policy always shows the poorest performance. However, by applying a proper lifespan supplement under the LFU-DL policy, the caching performance can be effectively enhanced to the level achievable using ARC and LRU policies. Moreover, the GDSF policy does not outperform simple LRU or LFU-DL, especially for YouTube video clips when the potential caching gain is relatively low. The advantage of GDSF manifested in our analysis is, however, its outstanding cache space usage efficiency among the five studied caching algorithms.
Reliability Analysis of Component Software Based on Stochastic Petri Nets

The models suggested at present have certain application conditions and ranges, and most of them are not able to satisfy the requirements of complicated and volatile application environments. This paper presents a method based on stochastic Petri nets (SPNs) that evaluates component software reliability at the early stages of software development. The reliability model built with that method can describe the process of dynamic changes of software well and it also considers the factors that affect software reliability by analyzing the characteristic of software architecture. The major drawback of SPN models is the state space explosion with increasing model complexity. In this paper, the problem is resolved by the decomposition of software architecture and one kind of decomposition technique introduced by Koriem (1999). Finally, we illustrate and discuss the numerical reliability results obtained from the proposed method. It has been shown that the suggested method provides a powerful means of analyzing software reliability after software running for a period of time.
Shift control.

ALTHOUGH SIX out of ten nurses work shifts, 43 per cent do not work the shift pattern they would prefer, says the RCN's survey. Five years ago, nurses working in the intensive care unit at Doncaster and Bassetlaw Trust decided that rather than have someone else make the decisions, they would like to agree between themselves about when they worked and when they were off-duty.
Authorship Analysis on Dark Marketplace Forums

Anonymity networks like Tor harbor many underground markets and discussion forums dedicated to the trade of illegal goods and services. As they are gaining in popularity, the analysis of their content and users is becoming increasingly urgent for many different parties, ranging from law enforcement and security agencies to financial institutions. A major issue in cyber forensics is that anonymization techniques like Tor's onion routing have made it very difficult to trace the identities of suspects. In this paper we propose classification set-ups for two tasks related to user identification, namely alias classification and authorship attribution. We apply our techniques to data from a Tor discussion forum mainly dedicated to drug trafficking, and show that for both tasks we achieve high accuracy using a combination of character-level n-grams, stylometric features and timestamp features of the user posts.
On Tradeoffs Between Deterministic Structure and Randomness in Texture Simulation

The paper discusses today's techniques of simulating realistic images of natural textures. These techniques account for deterministic spatial structures of signal relationships in a given training sample and allow for random deviations of signals in the simulated texture. When simulation is based on random permutations of image tiles, these latter can be found for some periodic regular textures by using characteristic pixel neighbourhoods. The neighbourhoods are estimated by using Gibbs random field models with multiple pairwise pixel interactions, and the tiles determined from the neighbourhoods, serve as basic structural texture elements, or texels. To exclude spurious borders between the permuted tiles and suppress visually undesirable repetition of specific singularities of individual tiles, simulated images are post-processed by maximising conditional probabilities of signals in accord with the Gibbs model. 1 Center for Image Technology and Robotics Tamaki Campus, The University of Auckland, Auckland, New Zealand. g.gimelfarb@auckland.ac. nz You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the CITR Tamaki web site under terms that include this permission. All other rights are reserved by the author(s). On Tradeo s Between Deterministic Structure and Randomness in Texture Simulation
Gait fingerprinting-based user identification on smartphones

Smartphones have ubiquitously integrated into our home and work environments. It is now a common practice for people to store their sensitive and confidential information on their phones. This has made it extremely important to authenticate legitimate users of a phone and block imposters. In this paper, we demonstrate that the motion dynamics of smartphones, captured using their built in accelerometers, can be used for accurate user identification. We call this mechanism gait fingerprinting. To this end, we first collected the acceleration data from multiple users as they walked with a smartphone placed freely in their pants pockets. Next, we studied the application of different feature extraction, feature selection and classification techniques from the machine learning literature on these data. Through extensive experimentation, demonstrated is that simple time domain features extracted from these data, which are further optimized using stepwise linear discrimination analysis, can be used to train artificial neural networks to identify legitimate user and block imposter with an average accuracy of 95%.
Face Photo-Sketch Synthesis and Recognition

In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications for both digital entertainment and law enforcement. We assume that faces to be studied are in a frontal pose, with normal lighting and neutral expression, and have no occlusions. To synthesize sketch/photo images, the face region is divided into overlapping patches for learning. The size of the patches decides the scale of local face structures to be learned. From a training set which contains photo-sketch pairs, the joint photo-sketch model is learned at multiple scales using a multiscale MRF model. By transforming a face photo to a sketch (or transforming a sketch to a photo), the difference between photos and sketches is significantly reduced, thus allowing effective matching between the two in face sketch recognition. After the photo-sketch transformation, in principle, most of the proposed face photo recognition approaches can be applied to face sketch recognition in a straightforward way. Extensive experiments are conducted on a face sketch database including 606 faces, which can be downloaded from our Web site (http://mmlab.ie.cuhk.edu.hk/facesketch.html).
A computational approach to microarray universal reference sample

The choice of a reference material in two-colour microarray experiments is an important issue of the experimental design. We consider a number of cell lines derived from a variety of primary tissues in order to construct a reference material. The aim of the present study is to understand the correlation structure of the data and develop a common reference that would enable comparison of expression levels in multiple microarray hybridizations with high coverage. We analyze 22 cultured cell line samples using a common reference pool. After estimating the coverage for each cell line or combinations of cell lines based on methods suggested by the literature, we employ stochastic optimization techniques to estimate the optimal set of cell lines in the reference sample. We found that only a subset of cell lines is necessary to achieve coverage as high or higher than that of the original reference sample used. We tested experimentally the performance of the new reference sample suggested and found that its coverage outperforms the coverage achieved by Stratagenepsilas human reference sample for the particular platform.
A SOA-Based Mobile Guide to Augment Tourists' Experiences with User-Generated Content and Third-Party Services

Several mobile guides exist providing tourists with location-based content delivery. This paper presents a novel mobile application, named InfoTour, aiming at enriching tourists’ experiences by supporting social interactions among tourists and by enabling seamless interaction with third-party service and data providers. The proposed system is based on Service Oriented Architecture principles, and we describe here the main issues related to the system prototype design and development.
Rapid parameter determination for induction motor analysis and control

The paper describes the implementation of a rapid on line parameter determination method for three-phase induction motors. The technique is based on data sampling during a normal run up to speed test. The method has been refined such that even the normal locked rotor and synchronous speed data are measured during the run up test. Furthermore the technique takes into account rotor parameter variations with frequency due to skin effect (mainly due to double-cage or deep-bar rotor), and other nonlinear imperfections such as heating and main flux path saturation. Moreover the system can be used for condition monitoring of any electrical drive system and can be permanently or temporarily connected to such a system for diagnosis.
Using old Spam and Ham Samples to Train Email Filters

Email spam filters are commonly trained on a sample of recent spam and ham (non-spam) messages. We investigate the effect on filter performance of using samples of spam and ham messages sent months before those to be filtered. Our results show that filter performance deteriorates with the overall age of spam and ham samples, but at different rates. Spam and ham samples of different ages may be mixed to advantage, provided temporal cues are elided.
A Quantum Reinforcement Learning Method for Repeated Game Theory

In this paper, a quantum reinforcement learning method is proposed for repeated game theory. First, the quantum reinforcement learning algorithm is introduced based on quantum state superposition principle and its superiority is analyzed. Then, it is applied to repeated games and the experiments show its effectiveness. Related issues are also discussed before the conclusion is given
Firm Role, Innovation Capability and Alliance Network: An Empirical Analysis Based on Chinese Communication Equipment Industry

Considering the structural characteristic and resource characteristic of firm in alliance network, this paper defines and divides the firm role into four categories, including the "poor", the "warehouse", the "hub" and the "trump". What's more, this paper takes the firm alliance of Chinese communication equipment industry between 2000 and 2008 as research object to analyze ea ch firm role's innovation capability, and also gives advices to improve innovation accordingly. The results show that the innovation capability of different firm role is different significantly. The "poor" firm has the weakest innovation capability, and whether the "trump" is strongest at innovation can't be verified. The "warehouse" firm has stronger innovation capability than the "hub", that is, the positive effect of resource characteristic on innovation capability is more than structural characteristic's.
Resonant Cavity Imaging: A Means Toward High-Throughput Label-Free Protein Detection

The resonant cavity imaging biosensor (RCIB) is an optical technique for detecting molecular binding interactions label free at many locations in parallel that employs an optical resonant cavity for high sensitivity. Near-infrared light centered at 1512.5 nm couples resonantly through a Fabry-Perot cavity constructed from dielectric reflectors (Si/SiO2), one of which serves as the binding surface. As the wavelength is swept using a tunable laser, a near-infrared digital camera monitors cavity transmittance at each pixel. A wavelength shift in the local resonant response of the optical cavity indicates binding. Positioning the sensing surface with respect to the standing wave pattern of the electric field within the cavity controls the sensitivity with which the presence of bound molecules is detected. Transmitted intensity at thousands of pixel locations is recorded simultaneously in a 10 s, 5 nm scan. An initial proof-of-principle setup has been constructed. A test sample was fabricated with 25,100-mum wide square features, each with a different density of 1-mum square depressions etched 12 nm into the SiO2 surface. The average depth of each etched region was found with 0.05 nm rms precision. In a second test, avidin, bound selectively to biotin conjugated bovine serum albumin, was detected.
Biomedical Event Extraction by Multi-class Classification of Pairs of Text Entities

This paper describes the HDS4NLP en- try to the BioNLP 2013 shared task on biomedical event extraction. This system is based on a pairwise model that transforms trigger classification in a simple multi-class problem in place of the usual multi-label problem. This model facilitates inference compared to global models while relying on richer information compared to usual pipeline approaches. The HDS4NLP system ranked 6th on the Genia task (43.03% f-score), and after fixing a bug discovered after the final submission, it outperforms the winner of this task (with a f-score of 51.15%).
Finite Element Modeling of FRP Wrapped High Strength Concrete Reinforced with Axial and Helical Reinforcement

The most general use of high-strength concrete is for construction of high-rise buildings. High strength concrete has highly advantageous structural properties which can lead to significant cost and also time savings in heavily loaded concrete structures. In this paper a methodology is proposed for deriving a non-linear finite element model to analyse the behaviour of high strength concrete columns wrapped with carbon-fibre-reinforced-polymer (CFRP) jackets and reinforced with axial and helical steel bars. In the finite element analysis, the material and geometric nonlinearities are taken into consideration and the results of material testing of the constituent materials (concrete, steel and FRP) are explored to set up the model. Due to lack of axis of symmetry in this complex model, creating the whole column has had the most precise result among all the alternatives which were examined to achieve an appropriate model as a representative of the true specimens. There was a good correlation between the axial load-deflection results of the experimental tests and the finite element model of the concentrically loaded columns proving the accuracy of the developed model.
 -CUT FUZZY ANALYTIC NETWORK PROCESS BASED APPROACH TO EVALUATE SIMULATION SOFTWARE PACKAGES

In parallel to computer technology drastically developing, various simulation software packages focusing on solving different kinds of engineering problems have been introduced to the world market. As the result of this, the selection of proper simulation software has been of considerable importance to any simulation analyst in a simulation project. On the other hand, the best satisfying simulation software selection from a possible set of alternatives in the market is a typical multiple criteria decision making (MCDM) problem in the presence of evaluation criteria, and there are many MCDM methods in the literature, which have been used to successfully carry out this difficult and time-consuming process. In this study, the analytic network process (ANP) method is used because it can accommodate the variety of interactions, dependencies and feedback between higher and lower level elements, rather than analytic hierarchy process (AHP). In addition, an  -cut fuzzy logic is integrated with the ANP method to model uncertain human preferences as input information in the decision-making process. Instead of using the classical eigenvector prioritization method in AHP, only employed in the prioritization stage of ANP, An  -cut fuzzy logic method providing more accuracy on judgments is applied. The resulting  -cut fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments.
Potential of coherent decompositions in SAR polarimetry and interferometry

A comparative study has indicated that coherent decompositions may have high potential in applications using fully polarimetric and interferometric SAR data, as an alternative or supplement to standard non-coherent techniques developed during the last decade. One important reason for this seems to be that the coherent techniques are better able to benefit from the coherent nature of the underlying data and scattering mechanisms. By avoiding averaging at the first processing stage, the coherent techniques can extract target features that may otherwise be lost in the early averaging process. On the other hand, averaging is indeed important in most cases for obtaining stable and reliable end results.
Analysis of the microphonic potential of the bullfrog's sacculus

The sensory epithelium from the bullfrog's sacculus was mounted between two chambers and stimulated by moving the otolithic membrane with a piezoelectric stimulator. The evoked response was measured as the transepithelial “microphonic” potential or, when the epithelium was voltage clamped, as the microphonic current. Microphonic responses were similar to those recorded in other preparations: the whole organ produced a “2f” response (i.e., a response of a frequency twice that of the stimulus) which could be changed to a single-polarity response by stimulating cells of a single polarity; the response saturated asymmetrically with displacement, producing a rectification; and the amplitude declined at high and low frequencies. To determine the cellular elements responsible for generation of the microphonic potential, the equivalent circuit of the epithelium was estimated from morphological and electrophysiological data, and responses to step displacement stimuli were recorded. Four elements in particular shape the microphonic potential: the complex impedance of the extracellular current path, the saturating displacement-conductance curve, an adaptation mechanism which shifts that curve, and a voltage-dependent K+ conductance in the basolateral hair cell membrane. A quantitative model incorporating these elements accurately reproduces the observed responses.
Crossing Qualitative and Quantitative Evaluation in the domain of Ubiquitous Computing

Ubiquitous computing (Ubicomp) applications are applications that are embedded seamlessly and ubiquitously into our everyday lives. The study of Ubicomp is concerned with enabling a future in which the most useful Ubicomp applications are feasible to build and pleasing to use. But what is useful? What is usable? What do people actually need? These questions are only beginning to be answered, partly because Ubicomp systems more difficult to evaluate, particularly at the early stages of design, than desktop applications. We argue that an effective evaluation of deployed Ubicomp technology should combine qualitative and quantitative methods, and should make use of as many unobtrusive methods for gathering data as possible.
Matrix analytic methods for stochastic fluid flows

We present an analysis of stochastic fluid flow models along the lines of matrix-analytic methods. The computation of the steady state distribution is reduced to the analysis of a discrete time, discrete state space quasi-birth-death model. This approach, which can be extended immediately to the infinite dimensional case, may enable the inclusion of heavy tails and self similarity in fluid models.
UCD GEARY INSTITUTE DISCUSSION PAPER SERIES Commodity futures hedging, risk aversion and the hedging horizon

This paper examines the impact of investor preferences on the optimal futures hedging strategy and associated hedging performance. Explicit risk aversion levels are often overlooked in hedging analysis. Applying a mean-variance hedging objective, the optimal futures hedging ratio is determined for a range of investor preferences on risk aversion, hedging horizon and expected returns. Wavelet analysis is applied to illustrate how investor time horizon shapes hedging strategy. Empirical results reveal substantial variation of the optimal hedge ratio for distinct investor preferences and are supportive of the hedging policies of real firms. Hedging performance is then shown to be strongly dependent on underlying preferences. In particular, investors with high levels of risk aversion and a short horizon reduce the risk of the hedge portfolio but achieve inferior utility in comparison to those with low risk aversion.