Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling continuous changes of the user's dynamic behavior in the WWW

Understanding the characteristics of the users' workload is an important aspect when designing and providing web services. The majority of current workload characterization techniques introduce some limitations when representing the dynamism of the client behavior and the continuous changes in its role. This fact implies that the majority of the existing workload generators model these characteristics in a simple an improperly way. This paper focuses on the dynamism of WWW in general, and the new techniques to characterize the user behavior. Our work is addressed to develop a dynamic workload generator that considers the new behavior of the web clients, and the continuous changes in their role.
RomaDroid: A Robust and Efficient Technique for Detecting Android App Clones Using a Tree Structure and Components of Each App’s Manifest File

There are various types of Android apps, such as entertainment apps, health and fitness apps, travel apps, educational apps, business apps, and so on. Android apps can contain business logic, maintain sensitive personal information, and act as a bridge between IoT devices and cloud servers. Since illegal users frequently make a copy of a legitimate Android app and redistribute the plagiarized app for commercial or malicious purposes, many studies have been conducted to detect repackaged/cloned apps and make the Android ecosystem safer. A malicious attacker might apply code obfuscation to avoid app clone detection. Therefore, it is necessary to consider the effects of code obfuscation when detecting cloned apps. In this paper, we design and implement a tool called RomaDroid, which can detect efficiently cloned apps based on features inherent in each app’s AndroidManifest.xml file. The manifest file is XML structure defined by tags or attributes and its XML document can be modeled as an ordered labeled tree. The RomaDroid creates a string from the hierarchical tree structure of tags as well as the class name of the components related to intent-filter tags in the manifest file, which are robust to code obfuscation. That is, we create a string from each manifest file of two apps to be compared and measure the similarity between the created two strings with the longest common subsequence (LCS) algorithm. If the measured similarity exceeds a certain threshold, the two apps are determined to be a clone pair (or similar app pair). To validate the RomaDroid, we perform various experiments with both non-obfuscated apps and their obfuscated versions generated by three obfuscation tools. The experimental results show that the RomaDroid detects accurately cloned apps even in the cases code obfuscation has been applied.
Homologous recombination is involved in the diversity of replacement flexible genomic islands in aquatic prokaryotes

Different strains of the same prokaryotic species, even very similar ones, vary in large regions of their genomes. This flexible genome represents a huge reservoir of diversity that allows prokaryotes to exploit their environment efficiently. Most of the flexible genome is concentrated in genomic islands, some of which are present in all the strains and coding for similar functions but containing different genes. These replacement genomic islands are typically involved in exposed cellular structures, and their diversity has been connected to their recognition as targets by prokaryotic viruses (phages). We have compared genomes of closely related aquatic microbes from different origins and found examples of recent replacement of some of these flexible genomic islands. In all cases, that include Gram positive and negative bacteria and one archaeon, the replaced regions boundaries contain tell-tale peaks of increased, mostly synonymous, nucleotide substitutions. They tended to be sharper at the boundary closest to the origin of replication of the island. We will present the hypothesis that replacement flexible genomic islands are often exchanged by homologous recombination between different clonal frames. These recombination events are possibly selected due to the immediate reward provided by a change in the phage sensitivity spectrum.
A phonetic search approach to the 2006 NIST spoken term detection evaluation

This paper details the submission from the Speech and Audio Research Lab of Queensland University of Technology (QUT) to the inaugural 2006 NIST Spoken Term Detection Evaluation. The task involved accurately locating the occurrences of a specified list of English terms in a given corpus of broadcast news and conversational telephone speech. The QUT system uses phonetic decoding and Dynamic Match Lattice Spotting to rapidly locate search terms, combined with a neural network-based verification stage. The use of phonetic search means the system is open vocabulary and performs usefully (Actual Term-Weighted Value of 0.23) whilst avoiding the cost of a large vocabulary speech recognition engine.
Learning muscle activation patterns via nonlinear oscillators: Application to lower-limb assistance

Achieving coordination between a lower-limb exoskeleton and its user is challenging because walking is a dynamic process that involves multiple, precisely timed muscle activations. Electromyographical (EMG) feedback, in spite of its drawbacks, provides an avenue for assistance by enabling users to reduce the level of muscle activation required for walking. As an alternative to direct EMG feedback, we present a method for exoskeleton control based on learning the activation pattern of specific muscles during cyclic movements. Using the example of pendular leg motion, the torque profile of one muscle group (hip flexors) is learned in a two-step process. First, the estimated torque profile is indexed to the phase of the swing movement using an adaptive frequency oscillator (AFO). The profile is then encoded using linear weighted regression. In the algorithm's assistive mode, the learned profile is reconstructed by means of the AFO and without need for additional EMG input. The reconstructed profile is converted into a torque profile to be physically delivered by the exoskeleton. We tested our method on a single-actuator exoskeleton that assists the hip joint during stationary leg swing. The learning and assistance functions were built on top of an admittance controller that enhances the exoskeleton's mechanical transparency. Initial tests showed a high level of coordination, i.e. simultaneous positive work, between the subjects' hip flexor torque and the exoskeleton's assistive torque. This result opens the door for future studies to test the users' ability to reduce their muscle activation in proportion to the assistance delivered by the exoskeleton.
Social Disadvantage and Social Isolation Are Associated With a Higher Resting Heart Rate: Evidence From The Irish Longitudinal Study on Ageing.

OBJECTIVES A high resting heart rate (RHR) represents a major risk factor for cardiovascular disease and individuals from poorer backgrounds have a higher RHR compared with their more advantaged peers. This study investigates the pathways through which low socioeconomic status (SES) contributes to a higher RHR. METHOD The sample involved data for 4,888 respondents who were participating in the first wave of The Irish Longitudinal Study on Ageing. Respondents completed a detailed interview at home and underwent a 5-min baseline electrocardiograph recording as part of a clinic-based health assessment. SES was indexed using household income. RESULTS The mean difference in RHR between those at polarized ends of the income distribution was 2.80 beats per minute (bpm) (95% CI = 1.54, 4.06; p < .001), with the magnitude of the socioeconomic differential being greater for men (4.15 bpm; 95% CI = 2.18, 6.12; p < .001) compared with women (1.57 bpm; 95% CI = 0.04, 3.10; p < .05). Psychosocial factors including social network size and loneliness accounted for a sizeable proportion of the socioeconomic differential in RHR, particularly among men. DISCUSSION The finding that poorer people have a higher RHR reinforces the need for additional research exploring the pathways through which social inequalities are translated into biological inequalities.
Deblocking filter for artifact reduction in distributed compressive video sensing

The distributed compressive video sensing (DCVS) poses itself as a very promising framework for future video coding on mobile devices due to its very low complexity at the encoder not only in sampling but also in compression. However its blocking artifacts and oscillatory artifacts especially in high-frequency components seriously degrade perceptual quality. In this paper, we try to solve both problems of the high-frequency oscillatory and blocking artifacts as a whole by a proposed deblocking filter. By differentiating those well-decoded blocks from poorly-decoded blocks using concept of reliability, the proposed method can improve DCVS framework in both objective and subjective qualities.
Probabilities and polarity biases in conditional inference.

A probabilistic computational level model of conditional inference is proposed that can explain polarity biases in conditional inference (e.g., J. St. B. T. Evans, 1993). These biases are observed when J. St. B. T. Evans's (1972) negations paradigm is used in the conditional inference task. The model assumes that negations define higher probability categories than their affirmative counterparts (M. Oaksford & K. Stenning, 1992); for example, P(not-dog) > P(dog). This identification suggests that polarity biases are really a rational effect of high-probability categories. Three experiments revealed that, consistent with this probabilistic account, when high-probability categories are used instead of negations, a high-probability conclusion effect is observed. The relationships between the probabilistic model and other phenomena and other theories in conditional reasoning are discussed.
Dietary supplementation of ferulic acid improves performance and alleviates oxidative stress of lambs in a cold environment

Abstract: Ferulic acid (FA) has been regarded as an antioxidant in domestic animals’ feed. This study was to investigate whether dietary FA supplementation could improve growth performance by decreasing oxidative stress of lambs in cold environment. Thirty-two 3-mo-old crossbred male lambs (Dorper × Small-tail Han sheep; 30.49 ± 0.46 kg) were randomly assigned into one of the following dietary treatments: CON (control, no FA), FA80 (80 mg FA kg-1 of diet), FA400 (400 mg FA kg-1 of diet), and FA2000 (2000 mg FA kg-1 of diet). Lambs fed the FA80 had higher (P < 0.05) average daily gain and lower (P < 0.05) feed efficiency than those fed CON and FA2000. The dry matter, organic matter, and neutral detergent fiber apparent digestibility was lower (P < 0.05) for FA2000 lambs than for lambs from other treatments. Serum total protein and albumin concentrations were greater (P < 0.05) for FA80 group than other groups. Lambs fed FA80 had higher (P < 0.05) plasma glutathione peroxidase and catalase activities and lower (P < 0.05) malondialdehyde (MDA) content than lambs fed CON. However, FA2000 group showed higher (P < 0.05) plasma MDA content than CON group. In conclusion, dietary supplementation of 80 mg FA kg-1 diet could improve growth performance by decreasing oxidative stress of lambs in cold environment.
On the judgement of full-period sequences and a novel congruential map with double modulus on Z(pn)

This paper studies the judgement problem of full-period maps on Z(pn) and proposes a novel congruential map with double modulus on Z(pn). The full-period properties of the sequences generated by the novel map are studied completely. We prove some theorems including full-period judgement theorem on Z(pn) and validate them by some numerical experiments. In the experiments, full-period sequences are generated by a full-period map on Z(pn). By the binarization, full-period sequences are transformed into binary sequences. Then, we test the binary sequences with the NIST SP 800-22 software package and make the poker test. The passing rates of the statistical tests are high in NIST test and the sequences pass the poker test. So the randomness and statistic characteristics of the binary sequences are good. The analysis and experiments show that these full-period maps can be applied in the pseudo-random number generation (PRNG), cryptography, spread spectrum communications and so on.
Hepatic Proliferation and Angiogenesis Markers Are Increased after Portal Deprivation in Rats: A Study of Molecular, Histological and Radiological Changes

Background & Aims To determine the pathogenesis of liver nodules, and lesions similar to obliterative portal venopathy, observed after portosystemic shunts or portal vein thrombosis in humans. Methods We conducted an experimental study comparing portacaval shunt (PCS), total portal vein ligation (PVL), and sham (S) operated rats. Each group were either sacrificed at 6 weeks (early) or 6 months (late). Arterial liver perfusion was studied in vivo using CT, and histopathological changes were noted. Liver mRNA levels were quantified by RT-QPCR for markers of inflammation (Il10, Tnfa), proliferation (Il6st, Mki67, Hgf, Hnf4a), angiogenesis: (Vegfa, Vegfr 1, 2 and 3; Pgf), oxidative stress (Nos2, and 3, Hif1a), and fibrosis (Tgfb). PCS and PVL were compared to the S group. Results Periportal fibrosis and arterial proliferation was observed in late PCS and PVL groups. CT imaging demonstrated increased arterial liver perfusion in the PCS group. RT-QPCR showed increased inflammatory markers in PCS and PVL early groups. Tnfa and Il10 were increased in PCS and PVL late groups respectively. All proliferative markers increased in the PCS, and Hnf4a in the PVL early groups. Mki67 and Hnf4a were increased in the PCS late group. Nos3 was increased in the early and late PCS groups, and Hif1a was decreased in the PVL groups. Markers of angiogenesis were all increased in the early PCS group, and Vegfr3 and Pgf in the late PCS group. Only Vegfr3 was increased in the PVL groups. Tgf was increased in the PCS groups. Conclusions Portal deprivation in rats induces a sustained increase in intrahepatic markers of inflammation, angiogenesis, proliferation, and fibrosis.
Association between sustained virological response and all-cause mortality among patients with chronic hepatitis C and advanced hepatic fibrosis.

CONTEXT Chronic hepatitis C virus (HCV) infection outcomes include liver failure, hepatocellular carcinoma (HCC), and liver-related death. OBJECTIVE To assess the association between sustained virological response (SVR) and all-cause mortality in patients with chronic HCV infection and advanced hepatic fibrosis. DESIGN, SETTING, AND PATIENTS An international, multicenter, long-term follow-up study from 5 large tertiary care hospitals in Europe and Canada of 530 patients with chronic HCV infection who started an interferon-based treatment regimen between 1990 and 2003, following histological proof of advanced hepatic fibrosis or cirrhosis (Ishak score 4-6). Complete follow-up ranged between January 2010 and October 2011. MAIN OUTCOME MEASURES All-cause mortality. Secondary outcomes were liver failure, HCC, and liver-related mortality or liver transplantation. RESULTS The 530 study patients were followed up for a median (interquartile range [IQR]) of 8.4 (6.4-11.4) years. The baseline median (IQR) age was 48 (42-56) years and 369 patients (70%) were men. The Ishak fibrosis score was 4 in 143 patients (27%), 5 in 101 patients (19%), and 6 in 286 patients (54%). There were 192 patients (36%) who achieved SVR; 13 patients with SVR and 100 without SVR died (10-year cumulative all-cause mortality rate, 8.9% [95% CI, 3.3%-14.5%] with SVR and 26.0% [95% CI, 20.2%-28.4%] without SVR; P < .001). In time-dependent multivariate Cox regression analysis, SVR was associated with reduced risk of all-cause mortality (hazard ratio [HR], 0.26; 95% CI, 0.14-0.49; P < .001) and reduced risk of liver-related mortality or transplantation (HR, 0.06; 95% CI, 0.02-0.19; P < .001), the latter occurring in 3 patients with SVR and 103 without SVR. The 10-year cumulative incidence rate of liver-related mortality or transplantation was 1.9% (95% CI, 0.0%-4.1%) with SVR and 27.4% (95% CI, 22.0%-32.8%) without SVR (P < .001). There were 7 patients with SVR and 76 without SVR who developed HCC (10-year cumulative incidence rate, 5.1%; 95% CI, 1.3%-8.9%; vs 21.8%; 95% CI, 16.6%-27.0%; P < .001), and 4 patients with SVR and 111 without SVR experienced liver failure (10-year cumulative incidence rate, 2.1%; 95% CI, 0.0%-4.5%; vs 29.9%; 95% CI, 24.3%-35.5%; P < .001). CONCLUSION Among patients with chronic HCV infection and advanced hepatic fibrosis, sustained virological response to interferon-based treatment was associated with lower all-cause mortality.
On Characteristic Pointsand Approximate Decision Algorithmsfor the Minimum Hausdor DistanceL

We investigate approximate decision algorithms for determining whether the minimum Hausdorr distance between two points sets (or between two sets of nonintersecting line segments) is at most ". An approximate decision algorithm is a standard decision algorithm that answers yes or no except when " is in an indecision interval where the algorithm is allowed to answer don't know. We present algorithms with indecision interval ? ; + ] where is the minimum Hausdorr distance and can be chosen by the user. In other words, we can make our algorithm as accurate as desired by choosing an appropriate. For two sets of points (or two sets of nonintersecting lines) with respective cardinalities m and n our approximate decision algorithms run in time O(("==) 2 (m + n) log(mn)) for Hausdorr distance under translation, and in time O(("==) 2 mn log(mn)) for Hausdorr distance under Euclidean motion.
INTELLIGENT SAFETY REGULATION AND WARNING METHOD FOR FISHING BOAT SECURITY

The data mining is carried out for the historical data to investigate and analyze crucial factors related to the causes of accidents of fishing boats. The vital factors, especially shipping time, weather and manipulation, etc. are extracted as the input variables of a BP neural network to establish a safety warning model for fishing boats. In addition, the Particle Swarm Optimization (PSO) is employed to develop the generalization ability of neural network and optimize the parameters of safety warning model. Experiments using the historical data have showed high efficiency of the proposed intelligent safety warning model. Hence, it is feasible for the design of waterborne traffic safety and warning system.
I2-Minimization Recovery Algorithm for Compressive Sensing in Cognitive Radio Networks

Compressive sensing (CS) is a novel sampling technique that can help Cognitive Radio (CR) for sampling the signals in an efficient way. This is done with taking in consideration that the spectrum is sparse in the frequency domain. Its operational way depends on using a suitable sensing matrix with the aid of an appropriate recovery algorithm. With respect to this point, this paper proposes a new recovery algorithm for determining the status of the different sub-channels in the spectrum. The proposed recovery algorithm is considered as a kind of optimization techniques since it depends on the use of the l2-minimization technique. To get the indices of the occupied sub-channels of the spectrum, the proposed recovery algorithm is accomplished with a new and simple extracted process. Comparing with one of the familiar greedy algorithms, Orthogonal Matching Pursuit (OMP), it can be seen that the proposed recovery algorithm has a better performance. Moreover, the results show that the proposed algorithm have high probability of detection at different Signal to Noise Ratio (SNR) for different number of the occupied sub-channels.
ESTIMATED RANK PRUNING FOR SPEECH RECOGNITION

Most speech recognition systems search through large finite state machines to find the most likely path, or hypothesis. Efficient search in these large spaces requires pruning of some hypotheses. Popular pruning techniques include probability pruning which keeps only hypotheses whose probability falls within a prescribed distance from the most likely one, and rank pruning which keeps only a prescribed number of the most probable hypotheses. Rank pruning provides better control over memory use and search complexity, but requires sorting of the hypotheses, a time consuming task that may slow the recognition process. We have recently proposed an estimated rank pruning (ERP) technique which combines the search-space and memory consumption advantages of rank pruning with the efficiency of probability pruning. Given a prescribed number n of hypotheses, ERP estimates the probability of the n-th most likely one and prunes all the less likely ones. In this paper we outline two improvements of ERP: a more accurate rank estimation, and a method for avoiding over-pruning.
Joining user profiles across online social networks: From the perspective of an adversary

Being the anchor points for building social relationships in the cyberspace, online social networks (OSNs) play an integral part of modern peoples life. Since different OSNs are designed to address specific social needs, people take part in multiple OSNs to cover different facets of their life. While the fragmented pieces of information about a user in each OSN may be of limited use, serious privacy issues arise if a sophisticated adversary pieces information together from multiple OSNs. To this end, we undertake the role of such an adversary and demonstrate the possibility of “splicing” user profiles across multiple OSNs and present associated security risks to users. In doing so, we develop a scalable and systematic profile joining scheme, Splicer, that focuses on various aspects of profile attributes by simultaneously performing exact, quasi-perfect and partial matches between pairs of profiles. From our evaluations on three real OSN data, Splicer not only handles large-scale OSN profiles efficiently by saving 87% computation time compared to all-pair profile comparisons, but also far exceeds the recall of generic distance measure based approach at the same precision level by 33%. Finally, we quantify the amount of information “lift” attributed to joining of OSNs, where on average 22% additional profile attributes can be added to 24% of users.
Interactive Graph Clustering based on User Hints

Graph clustering is a difficult optimization problem that arises in Software Engineering. This paper presents a framework for graph clustering where users play a strong role. In the framework, a soft computing method produces a clustering of the graph and a visualization of it is provided using some graph drawing techniques. Through the visualization the user can then analyze the clustering and give “hints” that help the soft computing method to find better solutions. Hints include a variety of constraints for solutions, as well as direct manipulation of the previously computed clustering. The framework is flexible: it can accommodate several kinds of hints, clustering algorithms, and visualization techniques.