Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Secure Embedded Web Interfaces

We address the challenge of building secure embedded web interfaces by proposing WebDroid: the first framework specifically dedicated to this purpose. Our design extends the Android Framework, and enables developers to create easily secure web interfaces for their applications. To motivate our work, we perform an in-depth study of the security of web interfaces embedded in consumer electronics devices, uncover significant vulnerabilities in all the devices examined, and categorize the vulnerabilities. We demonstrate how our framework's security mechanisms prevent embedded applications from suffering the vulnerabilities exposed by our audit. Finally we evaluate the efficiency of our framework in terms of performance and security.
A Review on Challenging Issues in Arabic Sentiment Analysis

Understanding what people think about an idea or how they evaluate a product, a service or a policy is important for individuals, companies and governments. Sentiment analysis is the process of automatically identifying opinions expressed in text on certain subjects. The accuracy of sentiment analysis has a direct effect on decision making in both business and government. Working with the Arabic language is very important because of the growing number of online contents in Arabic and the existing resources are limited and the accuracy of existing methods is low. In this study, we do a survey to highlight Arabic sentiment analysis challenging issues based on two main perspectives: Arabic-specific and general linguistic issues. The Arabic-specific challenges are mainly caused by Arabic morphological complexity, limited resources and dialects, while the general linguistic issues include polarity fuzziness, polarity strength, implicit sentiment, sarcasm, spam, review quality and domain dependence.
Multi-kernel collaborative representation for image classification

We consider the image classification problem via multiple kernel collaborative representation (MKCR). We generalize the kernel collaborative representation based classification to a multi-kernel framework where multiple kernels are jointly learned with the representation coefficients. The intrinsic idea of multiple kernel learning is adopted in our MKCR model. Experimental results show MKCR converges within reasonable iterations and achieves state-of-the-art performance.
From XSAT to SAT by Exhibiting Equivalencies

Given a Boolean formula in conjunctive normal form (CNF), the exact satisfiability problem (XSAT), a variant of the satisfiability problem (SAT), consists in finding an assignment to the variables such that each clause contains exactly one satisfied literal. Best algorithms to solve this problem runs in O(20.2325n) (O(20.1379n) for X3SAT) [12]. Another possibility is to transform each clause in a set of equivalent clauses for the Satisfiability problem and to use modern and powerful solvers (zChaff [14], Berkmin [6], MiniSat [5], RSat [16] etc.) to find such truth assignment. In this paper we introduce two new encoding from XSAT instances to SAT instances that leads to a lot of structural information (especially equivalencies) which is naturally hidden in the pairwise transformation. Some solvers (lsat[15], march dl [7], eqsatz [10]) can take into account this kinds of structural information to make simplifications as pretreatment and speed-up the resolution. Then we show the interest of dealing with the XSAT formalism by introducing an encoding of binary CSP and graph coloring problem into XSAT instances. Preliminary results on graph coloring problem show the importance of exhibiting equivalencies for the XSAT problem.
Proline Coordination with Fatty Acid Synthesis and Redox Metabolism of Chloroplast and Mitochondria1[OPEN]

A Proline Dehydrogenase1 promoter:luciferase screen and transcriptome of the proline synthesis mutant p5cs1-4 find coordination between proline and multiple redox-related metabolic pathways. Proline (Pro) accumulation is one of the most prominent changes in plant metabolism during drought and low water potential; however, the regulation and function of Pro metabolism remain unclear. We used a combination of forward genetic screening based on a Proline Dehydrogenase1 (PDH1) promoter-luciferase reporter (PDH1pro:LUC2) and RNA sequencing of the Pro synthesis mutant p5cs1-4 to identify multiple loci affecting Pro accumulation in Arabidopsis (Arabidopsis thaliana). Two mutants having high PDH1pro:LUC2 expression and increased Pro accumulation at low water potential were found to be alleles of Cytochrome P450, Family 86, Subfamily A, Polypeptide2 (CYP86A2) and Long Chain Acyl Synthetase2 (LACS2), which catalyze two successive steps in very-long-chain fatty acid (VLCFA) synthesis. Reverse genetic experiments found additional VLCFA and lipid metabolism-related mutants with increased Pro accumulation. Altered cellular redox status is a key factor in the coordination of Pro and VLCFA metabolism. The NADPH oxidase inhibitor diphenyleneiodonium (DPI) induced high levels of Pro accumulation and strongly repressed PDH1pro:LUC2 expression. cyp86a2 and lacs2 mutants were hypersensitive to diphenyleneiodonium but could be reverted to wild-type Pro and PDH1pro:LUC2 expression by reactive oxygen species scavengers. The coordination of Pro and redox metabolism also was indicated by the altered expression of chloroplast and mitochondria electron transport genes in p5cs1-4. These results show that Pro metabolism is both influenced by and influences cellular redox status via previously unknown coordination with several metabolic pathways. In particular, Pro and VLCFA synthesis share dual roles to help buffer cellular redox status while producing products useful for stress resistance, namely the compatible solute Pro and cuticle lipids.
Turing pattern formation with fractional diffusion and fractional reactions

We have investigated Turing pattern formation through linear stability analysis and numerical simulations in a two-species reaction–diffusion system in which a fractional order temporal derivative operates on both species, and on both the diffusion term and the reaction term. The order of the fractional derivative affects the time onset of patterning in this model system but it does not affect critical parameters for the onset of Turing instabilities and it does not affect the final spatial pattern. These results contrast with earlier studies of Turing pattern formation in fractional reaction–diffusion systems with a fractional order temporal derivative on the diffusion term but not the reaction term. In addition to elucidating differences between these two model systems, our studies provide further evidence that Turing linear instability analysis is an excellent predictor of both the onset of and the nature of pattern formation in fractional nonlinear reaction–diffusion equations.
Getting results from search-based approaches to software engineering

Like other engineering disciplines, software engineering is typically concerned with near optimal solutions or those which fall within a specified applicable tolerance. More recently, search-based techniques have started to find application in software engineering problem domains. This area of search-based software engineering has its origins in work on search-based testing, which began in the mid 1990s. Already, search-based solutions have been applied to software engineering problems right through the development life cycle.
A uniform meta-model for mediating formal electronic conferences

Formal electronic conferences (FEC) refers to online meetings for a geographically distributed group of people that are regulated by a rigorous set of rules. FEC technologies enable organizations to replace face-to-face business meetings with trustworthy virtual online meetings. In This work we present a Robert's rules of order (RRO)-compatible, motion-driven discussion-thread-centered meta-model, which is capable of uniformly modeling formal electronic conference activities. A tailored computerized mechanism, the collaboration description language (CODL) and its runtime environment, is also developed to formalize the model. The CODL virtual machine adds a layer of encapsulation that decouples FEC applications from underlying platforms: therefore, the development of FEC applications will become more reliable, efficient, and secure. Our preliminary experience with this meta-model is also reported.
Effects of Spray-Drying and Choice of Solid Carriers on Concentrations of Labrasol® and Transcutol® in Solid Self-Microemulsifying Drug Delivery Systems (SMEDDS)

Solid self-microemulsifying drug delivery systems (SMEDDS) have been used increasingly for improving the bioavailability of hydrophobic drugs. Labrasol® and Transcutol® are used widely as surfactant and solubilizer in the formulation of solid SMEDDS. We investigated the effects of spray-drying and the use of different solid carriers on concentrations of Labrasol® and Transcutol® in solid SMEDDS with scutellarin as the formulated drug. Liquid and gas chromatography tandem mass spectrometry (LC-MS and GC-MS) methods were developed for measuring low concentrations of Labrasol® and Transcutol®. In the preparation of solid SMEDDS, lactose, hydroxypropylmethyl cellulose (HPMC) and microcrystalline cellulose (MCC) were used as solid carriers. Judging from the retention ratios of Labrasol® and Transcutol®, the droplet size of solid SMEDDS increased after spray-drying of liquid SMEDDS, and concentrations of these excipients decreased after the solidifying procedure. In such reduction, Lactose and HPMC were found to preserve Labrasol® and Transcutol® better than MCC during spray-drying, and the resultant droplet sizes were smaller than that of MCC. Labrasol® and Transcutol® showed good thermal stability at 60 °C degree for 10 days. It can be concluded that spray-drying could increase the droplet size of solid SMEDDS and decreased the concentration of Labrasol® and Transcutol® therein, while water-soluble solid carriers could preserve Labrasol® and Transcutol® better than insoluble carriers in the solid SMEDDS.
The reinforcing functions of androgyny partial reinforcement

In the context of an escape conditioning paradigm,subjects listened to a male confederate give traditional,"masculine"responses to questions posed by an experimenter. Subjects then performed the instrumental response,the reinforcement for which wasthe opportunity to hear another male confederate deliver responses that were"androgynous" in content. As predicted,the speed of the instrumental response was an increasing function ofthe number of reinforced trials. Additionally,subjects who received only partial reinforcement responded slowerthan subjects whose instrumental response wascontinuously reinforced. Self-report measuresindicated that subjects judged the androgynousspeakerto be more likable and more moral,and found his commentsto be more honest and more appropriate compared to the masculine speaker. Discussion focused on the usefulness of escape conditioning methodology for investigations of complex social phenomenon.
Relationship Education for Low Income Couples and Individuals: New Research Directions

The current study implemented and evaluated an adapted version of the Within Our Reach program called FRAME. Participants were 173 low-income couples in committed relationships and caring for at least one child together. Participating couples were randomly assigned to one of the four study conditions (couples group, female group, male group, or control group). The impact of the program was investigated on a range of relationship and mental health outcomes. The present findings suggest that the FRAME workshop was helpful in reducing negative communication and improving positive bonding for our sample. Couples were able to benefit in some areas when only one partner attended the workshop. Overall the FRAME project was viewed as helpful and was well received by both male and female participants from various ethnic backgrounds. Associations between key variables were also examined and the results highlighted the negative impact of economic strain on individual and relationship functioning for men and women. Implications for future relationship education programs and research with low-income and ethnically diverse populations are discussed.
Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows

We address two important issues in causal discovery from nonstationary or heterogeneous data, where parameters associated with a causal structure may change over time or across data sets. First, we investigate how to efficiently estimate the "driving force" of the nonstationarity of a causal mechanism. That is, given a causal mechanism that varies over time or across data sets and whose qualitative structure is known, we aim to extract from data a low-dimensional and interpretable representation of the main components of the changes. For this purpose we develop a novel kernel embedding of nonstationary conditional distributions that does not rely on sliding windows. Second, the embedding also leads to a measure of dependence between the changes of causal modules that can be used to determine the directions of many causal arrows. We demonstrate the power of our methods with experiments on both synthetic and real data.
Fuzzy modeling of drivers' actions at intersections

Advanced Driver Assistance systems (ADAS) are systems that assist the driver during the driving task. This technology has great potentials in improving driver and traffic safety. It is very important for an ADAS to predict human drivers' behaviors at urban environment to avoid crashes. Because of the complexity of human-vehicle interaction, it is difficult to obtain an explicit model for analyzing the drivers' behaviors. Instead, models are developed for various driver decisions and driving scenarios (such as lane change decisions and intersection scenarios) which can then be integrated using switch models. Intersections are one of the major scenarios that require special attention in driver behavior modeling. This paper uses Takagi-Sugeno as a data driven technique to model and predict drivers' behaviors at intersections. In the proposed technique, a Takagi-Sugeno model is trained for each maneuver using a Gath-Geva fuzzy clustering algorithm. The proposed models are then evaluated with naturalistic real-world driving data collected in urban traffic, and the estimation results are presented. The results suggest that the proposed technique can correctly estimate the drivers' actions at intersections with high accuracy. This technique uses fewer numbers of maneuver models for training that leads to less computational complexity.
Optimal Distributed Generation and Capacitor Placement for Loss Minimization and Voltage Profile Improvement using Symbiotic Organisms Search Algorithm

In the present day power systems, Distributed generation (DG) technologies are becoming more significant due to the increased demand for electrical power. Integration of DG affects the performance of distribution network significantly. DG placement key benefits are power loss reduction and improved voltage profiles which are the objectives in this problem. This paper presents a new efficient technique called Symbiotic Organisms Search (SOS) which is based on the symbiotic interactions of the ecosystem living organisms for optimal location and sizing of DG and capacitor to achieve the objectives. IEEE 33-bus, 69-bus test systems are considered to validate the results of proposed technique and the simulation is carried out in MATLAB.
NORMALIZED CUTS BASED SEGMENTATION OF GASTROENTROLOGY IMAGES USING VISUAL FEATURES

This project propose a segmentation of gastroenterology image of cancer infected stomach which is taken using Chromo endoscopy (CH). Traditional computer system segmentation do not detect the characteristics of infected region. Gastroentrology imaging is an essential tool to detect gastrointestinal cancer in patients. From the gastroenterology physician can analysis the internal organs. Initially finding the boundary of the infected area by the process called active contour or snakes. By using the various visual features like edge maps, creaseness and colour in normalised cuts segmentation framework we are segmenting the affected area in stomach. On integration of these visual features gives the best image segmentation performance resulting in high quality. KeywordsClustering, Cancer, Chromo endoscopy, Normalized Cuts, Gastroentrology.
Peculiarities of the Correlation between Local and Global News Popularity of Electronic Mass Media

One of the approaches to the solution of the navigation problem in current information flows is ranking the documents according to their popularity level. The definition of local and global news popularity which is based on the number of similar-in-content documents, published within local and global time interval, was suggested. Mutual behavior of the documents of local and global popularity levels was studied. The algorithm of detecting the documents which received great popularity before new topics appeared was suggested.
Pycket: a tracing JIT for a functional language

We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket's JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for Racket proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites. The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop---we discuss two strategies for identifying loops and measure their impact.
"Singing in the rain": The effect of perspective taking on music preferences as mood management strategies

This research examines the relationship between the first-person (1P) and third-person (3P) perspective and subsequent music selections when considering a sad scenario. 195 undergraduates at the Ohio State University read a sad scenario involving either a funeral or a sad movie from the 1P or 3P perspective, and then rated preferences for 16 genres of music. I predicted that the 3P perspective would result in little variance in rated music preferences, reflecting an implicit theory about the type of music sad people in general would prefer. In contrast, the music preferences in the 1P perspective should vary more, based on both the specific sad scenario presented (funeral or sad movie) and each participant’s individual music preferences. As predicted, 3P preferences were stronger and showed less variance than 1P preferences, supporting our belief that people have implicit theories about responding to sadness. Participants did not, however, differentiate between types of sad scenarios in their music choices. Results for several specific genres of interest are also reported. Finally, theoretical implications and future directions are discussed.
A design of analysis model using feature weighting on CBR method

This paper is a principal idea of case-based reasoning to feature weighting. The feature weighting method called CaDFeW (CAse-based Dynamic FEature Weighting) stores classification performance of randomly generated feature weight vectors. Also it retrieve similar feature weighting success story from the feature weighting case base and then designs a better feature weight vector dynamically for the a new input problem while solving the problem. The CaDFeW is wrapper modelbased feature weighting method that uses classifier error rate as evaluation procedure. To explain the results of applications, this paper is introduced a new definition of input dependency of feature relevance and measured the new concept in the application domains. The empirically measured results showed that relative performance of a local feature weighting method to a global feature weighting method.
Slack Allocation Based Co-Synthesis and Optimization of Bus and Memory Architectures for MPSoCs

In this paper, we present a bus and memory architectures co-synthesis technique. The co-synthesis problem is formulated as an optimization problem, where scheduling, allocation, and binding of tasks are done simultaneously in order to optimize the bus widths, the number of buses, and the memory sizes. As a main contribution, bus and memory architectures are optimized simultaneously by allocating different amount of slacks to them during co-synthesis. The method finds a balance of slack allocation for both bus and memory optimization. While the previous co-synthesis approaches do not consider the slack allocation technique, the synthesized bus and memory architectures will not be optimal in terms of area and energy consumption. The experimental results carried out on real-life applications show 19% and 24% reduction in bus and memory area, respectively and 37% reduction in energy overhead due to a bridge in compared to the previous co-synthesis approach.
The ACS Virgo Cluster Survey. III. Chandra and Hubble Space Telescope Observations of Low-Mass X-Ray Binaries and Globular Clusters in M87

The ACIS instrument on board the Chandra X-Ray Observatory has been used to carry out the first systematic study of low-mass X-ray binaries (LMXBs) in M87, the giant elliptical galaxy near the dynamical center of the Virgo Cluster. These images—with a total exposure time of 154 ks—are the deepest X-ray observations yet obtained of M87. We identify 174 X-ray point sources, of which ~150 are likely LMXBs. This LMXB catalog is combined with deep F475W and F850LP images taken with ACS on the Hubble Space Telescope (HST) (as part of the ACS Virgo Cluster Survey) to examine the connection between LMXBs and globular clusters in M87. Of the 1688 globular clusters in our catalog, fX = 3.6% ± 0.5% contain an LMXB. Dividing the globular cluster sample by metallicity, we find that the metal-rich clusters are 3 ± 1 times more likely to harbor an LMXB than their metal-poor counterparts. In agreement with previous findings for other galaxies based on smaller LMXB samples, we find the efficiency of LMXB formation to scale with both cluster metallicity Z and luminosity, in the sense that brighter, more metal-rich clusters are more likely to contain an LMXB. For the first time, however, we are able to demonstrate that the probability pX that a given cluster will contain an LMXB depends sensitively on the dynamical properties of the host cluster. Specifically, we use the HST images to measure the half-light radius, concentration index, and central density ρ0 for each globular and define a parameter Γ, which is related to the tidal capture and binary-neutron star exchange rate. Our preferred form for pX is then pX ∝ Γρ(Z/Z☉)0.33±0.1. We argue that if the form of pX is determined by dynamical processes, then the observed metallicity dependence is a consequence of an increased number of neutron stars per unit mass in metal-rich globular clusters. Finally, we present a critical examination of the LMXB luminosity function in M87 and reexamine the published LMXB luminosity functions for M49 and NGC 4697. We find no compelling evidence for a break in the luminosity distribution of resolved X-ray point sources in any of these galaxies. Instead, the LMXB luminosity function in all three galaxies is well described by a power law with an upper cutoff at LX ~ 1039 ergs s-1.