Miracle-dz/UniFAR-FTUs huggingface dataset:
TrafficAV: An effective and explainable detection of mobile malware behavior using network traffic

Android has become the most popular mobile platform due to its openness and flexibility. Meanwhile, it has also become the main target of massive mobile malware. This phenomenon drives a pressing need for malware detection. In this paper, we propose TrafficAV, which is an effective and explainable detection of mobile malware behavior using network traffic. Network traffic generated by mobile app is mirrored from the wireless access point to the server for data analysis. All data analysis and malware detection are performed on the server side, which consumes minimum resources on mobile devices without affecting the user experience. Due to the difficulty in identifying disparate malicious behaviors of malware from the network traffic, TrafficAV performs a multi-level network traffic analysis, gathering as many features of network traffic as necessary. The proposed method combines network traffic analysis with machine learning algorithm (C4.5 decision tree) that is capable of identifying Android malware with high accuracy. In an evaluation with 8,312 benign apps and 5,560 malware samples, TCP flow detection model and HTTP detection model all perform well and achieve detection rates of 98.16% and 99.65%, respectively. In addition, for the benefit of user, TrafficAV not only displays the final detection results, but also analyzes the behind-the-curtain reason of malicious results. This allows users to further investigate each feature's contribution in the final result, and to grasp the insights behind the final decision.
Biomass-dependent dynamics of fish spatial distributions characterized by geostatistical aggregation curves

I present here methods for describing how spatial distribution changes as population abundance varies. Four models for biomass-dependent spatial dynamics are described and characterized by geostatistical aggregation curves. These curves provide a simple way to choose between models when characterizing spatio-temporal variability of survey data. A test of significance is proposed based on a bootstrap resampling algorithm. The analysis is applied to two spatio-temporal series of monitoring surveys; a groundfish bottom trawl survey and a pelagic echointegration survey. Relative to the population mean, the relative histograms in both series are time invariant for medium and high observed abundances. But for low population abundance, the relative histogram is more skewed. I then discuss the use of commercial CPUE data for deriving time series of comparable abundance indices when the density histogram changes with abundance.
1 Real-Time Object Segmentation of the Disparity Map Using Projection-Based Region Merging Dongil

Robots have been mostly used in industrial environment, but modern developments of household robot-cleaner suggest the necessity of household robots as becoming in reality. Most industrial robots have been used for factory automation that perform simple and iterative tasks at high speed, whereas household robots need various interfaces with a man while moving in indoor environment like a household robot-cleaner does. Robots activate in indoor environment using various sensors such as vision, laser, ultrasonic sensor, or voice sensor to detect indoor circumstance. Especially robot’s routing plan and collision avoidance need three-dimensional information of robot’s surrounding environment. This can be obtained by using a stereo vision camera which provides a general and huge amount of 3-D information. But this computation is too big to solve in real-time with the existing microprocessor when using a stereo vision camera for capturing 3-D image information. High-level computer vision tasks, such as robot navigation and collision avoidance, require 3-D depth information of the surrounding environment at video rate. Current generalpurpose microprocessors are too slow to perform stereo vision at video rate. For example, it takes several seconds to execute a medium-sized stereo vision algorithm for a single pair of images using one 1 GHz general-purpose microprocessor. To overcome this limitation, designers in the last decade have built reprogrammable chips called FPGA(Field-Programmable Gate Arrays) hardware systems to accelerate the performance of the vision systems. These devices consist of programmable logic gates and routing which can be re-configured to implement practically any hardware function. Hardware implementations allow one to apply the parallelism that is common in image processing and vision algorithms, and to build systems to perform specific calculations quickly compared to software implementations. A number of methods of finding depth information in video-rate have been reported. Among others, multi-baseline stereo theory is developed and the video-rate stereo machine has the capability of generating a dense depth map of 256x240 pixels at the frame rate of 30 frames/sec in [1-2]. An algorithm proposed from parallel relaxation algorithm for disparity computation [3] results reduction of error rate and enhancement of computational complexity
Sequencing of Bacterial Genomes: Principles and Insights into Pathogenesis and Development of Antibiotics

The impact of bacterial diseases on public health has become enormous, and is partly due to the increasing trend of antibiotic resistance displayed by bacterial pathogens. Sequencing of bacterial genomes has significantly improved our understanding about the biology of many bacterial pathogens as well as identification of novel antibiotic targets. Since the advent of genome sequencing two decades ago, about 1,800 bacterial genomes have been fully sequenced and these include important aetiological agents such as Streptococcus pneumoniae, Mycobacterium tuberculosis, Escherichia coli O157:H7, Vibrio cholerae, Clostridium difficile and Staphylococcus aureus. Very recently, there has been an explosion of bacterial genome data and is due to the development of next generation sequencing technologies, which are evolving so rapidly. Indeed, the field of microbial genomics is advancing at a very fast rate and it is difficult for researchers to be abreast with the new developments. This highlights the need for regular updates in microbial genomics through comprehensive reviews. This review paper seeks to provide an update on bacterial genome sequencing generally, and to analyze insights gained from sequencing in two areas, including bacterial pathogenesis and the development of antibiotics.
Atomic-Level Structure Characterization of an Ultrafast Folding Mini-Protein Denatured State

Atomic-level analyses of non-native protein ensembles constitute an important aspect of protein folding studies to reach a more complete understanding of how proteins attain their native form exhibiting biological activity. Previously, formation of hydrophobic clusters in the 6 M urea-denatured state of an ultrafast folding mini-protein known as TC5b from both photo-CIDNP NOE transfer studies and FCS measurements was observed. Here, we elucidate the structural properties of this mini-protein denatured in 6 M urea performing 15N NMR relaxation studies together with a thorough NOE analysis. Even though our results demonstrate that no elements of secondary structure persist in the denatured state, the heterogeneous distribution of R 2 rate constants together with observing pronounced heteronuclear NOEs along the peptide backbone reveals specific regions of urea-denatured TC5b exhibiting a high degree of structural rigidity more frequently observed for native proteins. The data are complemented with studies on two TC5b point mutants to verify the importance of hydrophobic interactions for fast folding. Our results corroborate earlier findings of a hydrophobic cluster present in urea-denatured TC5b comprising both native and non-native contacts underscoring their importance for ultra rapid folding. The data assist in finding ways of interpreting the effects of pre-existing native and/or non-native interactions on the ultrafast folding of proteins; a fact, which might have to be considered when defining the starting conditions for molecular dynamics simulation studies of protein folding.
On Asymptotic Stability of Noncharacteristic Viscous Boundary Layers

We extend our recent work with K. Zumbrun on long-time stability of multi-dimensional noncharacteristic viscous boundary layers of a class of symmetrizable hyperbolic-parabolic systems. Our main improvements are (i) to establish the stability for a larger class of systems in dimensions $d\ge 2$, yielding the result for certain magnetohydrodynamics (MHD) layers; (ii) to drop a technical assumption on the so--called glancing set which was required in previous works. We also provide a different proof of low-frequency estimates by employing the method of Kreiss' symmetrizers, replacing the one relying on detailed derivation of pointwise bounds on the resolvent kernel.
We need great “followers”, not just great leaders: a brief questionnaire for followership development

Purpose Business schools, executive training programs, and best-selling books all recognize the importance of leadership, while followership has received limited attention in management training. The purpose of this paper is to present a brief questionnaire, which might be particularly useful for followership development. Design/methodology/approach A brief questionnaire is presented. Findings Part of the answers will establish the view that many of us are followers. This will help recognize that both followership and leadership roles are important for organizational success Originality/value It is a major challenge to bring followership out of the closet and this tool may help to introduce practical followership development programs in organizations
Mantra: a Multi-level Hybrid Knowledge Representation System

The intelligent behavior of a system is based upon its represented knowledge and inference capabilities. In this paper we report on a knowledge representation and reasoning system, developed at the University of Karlsruhe, called Mantra. The system provides four diierent knowledge representation methods { rst-order logic, terminological language, semantic networks, and production rules { distributed into a three levels architecture. The rst three methods form the lowest level of the architecture, the epistemological level. The supported hybrid inferences as well as the management of knowledge bases form the second level, called logical level. Finally, the third level, the heuristic level, provides representation of procedural knowledge of a domain, and the introduction of ad hoc rules. This knowledge is represented in terms of production rules which are processed by a Ops5-like rule interpreter. This paper mainly describes the introduction of this level into the hybrid system. The semantics of the knowledge representation methods of the epistemological level is deened according to a four-valued logic approach. This deenition insures that all inference algorithms are sound, complete and decidable. The system has been implemented in Common Lisp using the object-oriented extension CLOS, and the graphical user interface was implemented in C with XToolkit.
An Object-Oriented Framework for Building Software Agents

Agent technology is a new approach of Distributed Artificial Intelligence to implement autonomous entities driven by beliefs, goals, capabilities and plans, and other agency properties such as adaptation, interaction, and mobility. Software agents are the focus of considerable research in the artificial intelligence community, but not much has been done in the field of software engineering. In this paper, we present an object-oriented framework for building software agents in a distributed environment. The design of the framework also allows an easy mapping of the models developed in the analysis and design phase of the Gaia Methodology to object-oriented code. We believe that objectoriented framework technology can reduce not only the development time but also the complexity of implementing multi-agent systems. We present an instantiated application that uses this framework to illustrate an implementation.
Inactions and Spikes of Investment in Ethiopian Manufacturing Firms: Empirical Evidence on Irreversibility and Non-convexities

This paper provides empirical evidence on the effect of irreversibility and non-convexities in adjustment costs on firm investment decision based on 1996-2002 firm level data from the Ethiopian manufacturing. It relies on a rich census based panel data set that gives the advantage of disaggregating investment into different types of fixed assets. We document evidence of a large percentage of inaction intermitted with lumpy investment, which is consistent with irreversibility and fixed costs but not with the standard convex adjustment costs. The inaction is higher and investment lumpier for small firms. We complement the descriptive analysis with two econometric methods: a capital imbalance approach and a machine replacement model. With the capital imbalance approach we estimate the investment response of firms to their capital imbalance using a non-parametric Nadaraya-Watson kernel smoothing method. With the machinery replacement approach using a proportional hazard model that takes unobserved heterogeneity into account, we estimate the probability of an investment spike conditional on the length of the interval from the last investment spike.
Multiple mapping method: A novel approach to the sequence‐to‐structure alignment problem in comparative protein structure modeling

A major bottleneck in comparative protein structure modeling is the quality of input alignment between the target sequence and the template structure. A number of alignment methods are available, but none of these techniques produce consistently good solutions for all cases. Alignments produced by alternative methods may be superior in certain segments but inferior in others when compared to each other; therefore, an accurate solution often requires an optimal combination of them. To address this problem, we have developed a new approach, Multiple Mapping Method (MMM). The algorithm first identifies the alternatively aligned regions from a set of input alignments. These alternatively aligned segments are scored using a composite scoring function, which determines their fitness within the structural environment of the template. The best scoring regions from a set of alternative segments are combined with the core part of the alignments to produce the final MMM alignment. The algorithm was tested on a dataset of 1400 protein pairs using 11 combinations of two to four alignment methods. In all cases MMM showed statistically significant improvement by reducing alignment errors in the range of 3 to 17%. MMM also compared favorably over two alignment meta‐servers. The algorithm is computationally efficient; therefore, it is a suitable tool for genome scale modeling studies. Proteins 2006. © 2006 Wiley‐Liss, Inc.
A new approach to path-finding by possibilities search

This paper presents a new approach to the path-finding in video games. Path-finding algorithms, are used to find a path between two positions of a map. The standard way consists to search for a specific path. However it appears that in actual games, where the allowed computation time becomes smaller and the game-plays and maps are more complex, it should not be the best way to proceed. Therefore, this new approach to the path-finding considers the global possibilities of movement instead of searching for a specific path. This paper describes the concept of possibility and details the procedure used to search them. The appreciable experiments results prove the validity and efficiency of this approach.
Social orienting of children with autism to facial expressions and speech: a study with a wearable eye-tracker in naturalistic settings

This study investigates attention orienting to social stimuli in children with Autism Spectrum Conditions (ASC) during dyadic social interactions taking place in real-life settings. We study the effect of social cues that differ in complexity and distinguish between social cues produced by facial expressions of emotion and those produced during speech. We record the children's gazes using a head-mounted eye-tracking device and report on a detailed and quantitative analysis of the motion of the gaze in response to the social cues. The study encompasses a group of children with ASC from 2 to 11-years old (n = 14) and a group of typically developing (TD) children (n = 17) between 3 and 6-years old. While the two groups orient overtly to facial expressions, children with ASC do so to a lesser extent. Children with ASC differ importantly from TD children in the way they respond to speech cues, displaying little overt shifting of attention to speaking faces. When children with ASC orient to facial expressions, they show reaction times and first fixation lengths similar to those presented by TD children. However, children with ASC orient to speaking faces slower than TD children. These results support the hypothesis that individuals affected by ASC have difficulties processing complex social sounds and detecting intermodal correspondence between facial and vocal information. It also corroborates evidence that people with ASC show reduced overt attention toward social stimuli.
Minimization of Utterance Verification Error Rate as a Constrained Optimization Problem

Since utterance verification (UV) may be treated as a two-class classification problem, it may be improved with discriminative training such as minimum verification error training or minimum verification error rate training. However, since in practice, one usually has to pick a specific false-acceptance or false-rejection rate for one's system, it is more desirable to optimize UV performance at a particular operating point. In this letter, we show that further improvement can be achieved by treating UV at a specific operating point as a constrained optimization problem
Large rotating AdS black holes from fluid mechanics

We use the AdS/CFT correspondence to argue that large rotating black holes in global AdSD spaces are dual to stationary solutions of the relativistic Navier-Stokes equations on SD−2. Reading off the equation of state of this fluid from the thermodynamics of non-rotating black holes, we proceed to construct the nonlinear spinning solutions of fluid mechanics that are dual to rotating black holes. In all known examples, the thermodynamics and the local stress tensor of our solutions are in precise agreement with the thermodynamics and boundary stress tensor of the spinning black holes. Our fluid dynamical description applies to large non-extremal black holes as well as a class of large non-supersymmetric extremal black holes, but is never valid for supersymmetric black holes. Our results yield predictions for the thermodynamics of all large black holes in all theories of gravity on AdS spaces, for example, string theory on AdS5 × S5 and M theory on AdS4 × S7 and AdS7 × S4.
Mentally ill, HIV-positive, or sexual predator? Determining myths perceived as representative of transgender people

The present study explored possible stereotypical beliefs, or myths, related to prejudice and discrimination toward transgender individuals in the US. In a 5 x 2 x 3 mixed factorial design, Amazon Mechanical Turk workers (N = 1,450) read a description of a target depicted as a sexual predator, HIV-positive, having a mental illness, an ally of transgender people, or unfair to others. They then completed an intuitive judgment task regarding the target’s gender (male or female) and identity stigma detail (transgender, sexual minority, or no stigmatized detail), and provided feeling thermometer ratings for various groups. Results indicated that participants perceived mental illness as relatively representative of transgender people, but not HIV-status or sexual predation. Feeling thermometer ratings for transgender people were significantly lower than those for other gender/stigma categories and were negatively correlated with participant religiosity and conservatism. We discuss these findings in terms of gendered assumptions and present implications for gender-related stigma and the role of perceived mental illness in antitransgender prejudice.
Efficient method for multiple compressed audio streams spatialization

This paper deals with the spatialization of multiple compressed audio streams. A new approach is proposed based on the combination of subband-domain filtering methods with linear decomposition methods of HRTFs filters, and more generally the filters used by sound spatialization techniques (binaural, transaural, ambisonic, etc). Such a combination allows both computation complexity reduction and memory size saving for sound spatialization systems of multiple compressed audio signals. These advantages are very useful for any implementation on limited capabilities terminals (computation power and memory size) which is the case of mobile and portable devices.
Integrated visualization of functional and anatomic brain data: a validation study.

UNLABELLED Two-dimensional SPECT display and three methods for integrated visualization of SPECT and MRI patient data are evaluated in a multiobserver study to determine whether localization of functional data can be improved by adding anatomical information to the display. METHODS SPECT and MRI data of 30 patients were gathered and presented using four types of display: one of SPECT in isolation, two integrated two-dimensional displays and one integrated three-dimensional display. Cold and hot spots in the peripheral cortex were preselected and indicated on black-and-white hard copies of the image data. Nuclear medicine physicians were asked to assign the corresponding spots in the image data on the computer screen to a lobe and a gyrus and give a confidence rating for both localizations. Interobserver agreement using kappa statistics and average confidence ratings were assessed to interpret the reported observations. RESULTS Both the interobserver agreement and the confidence of the observers were greater for the integrated two-dimensional displays than for the two-dimensional SPECT display. An additional increase in agreement and confidence was seen with the integrated three-dimensional display. CONCLUSION Integrated display of SPECT and MR brain images provides better localization of cerebral blood perfusion abnormalities in the peripheral cortex in relation to the anatomy of the brain than single-modality display and increases the confidence of the observer.