Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting xebsite vulnerabilities based on Markov chains theory

The tremendous growth of the web-based applications has increased information security vulnerabilities over the Internet. Security administrators use Intrusion-Detection System (IDS) to monitor network traffic and host activities to detect attacks against hosts and network resources. The proposed solutions in the literature, actually achieved good results for the detection rate, while there is stillroom for reducing the false positive rate or even predict beforehand attack according to a website visitor behavior. For this purpose we propose a probabilistic approach applied for an “intelligent IDS” whose main role is to tell which pages of a website are subjects to most attacks and eventually present security weaknesses, according to a real time probabilistic calculation based on Markov chains.
Sourcing Patterns of FDI Activity and Their Impact on the Domestic Economy

In this paper, we describe sourcing patterns of FDI activity and test empirically whether their impact on the host economy is such as predicted by theoretical models. In the analysis, we focus on inter-industry interactions between a multinational enterprise (MNE) which enters the domestic market and other firms in the economy within the broader context of international trade flows. Our main purpose is to determine whether FDI inflow indeed boosts demand for intermediate goods, and whether the MNE uses domestic suppliers of intermediate goods or whether it purchases its supplies from abroad or from other MNEs entering the downstream sector. Our analysis covers the time period 2001–2007 and concerns both Western and Eastern European countries. Using an unbalanced panel of industries in these countries and the given time period, we come to the conclusion that even though FDI represents a positive shock to demand for intermediate goods, in countries of Eastern Europe this shock is better exploited by MNEs in the upstream sector and foreign importing firms than by domestic producers.
Model-Based Assessment of Climate Change Impact on Isaac River Catchment, Queensland

Isaac River catchment, which is located within Fitzroy basin in Central Queensland, Australia is mostly a semi-arid region, sparsely populated, but rife with economic activities such as mining, grazing, cropping and production forestry. Hydro-meteorological data over the past several decades reveal that the catchment is experiencing increasing variability in precipitation and streamflow contributing to more severe droughts and floods supposedly due to climate change. The exposure of the economic activities in the catchment to the vagaries of nature and the possible impacts of climate change on the stream flow regime are to be analyzed. For the purpose, SWAT model was adopted to capture the dynamics of the catchment. During calibration of the model 12 parameters were found to be significant which yielded a R2 value of 0.73 for calibration and 0.66 for validation. In the next stage, six GCMs from CMIP3 namely, CGCM3.1/T47, CNRM-CM3, GFDL-CM2.1, IPSLCM4, MIROC3.2 (medres) and MRI CGCM2.3. 2 were selected for climate change projections in the Fitzroy basin under a very high emissions scenario (A2), a medium emissions scenario (A1B) and a low emissions scenario (B1) for two future periods (2046-2064) and (2080-2100). All GCMs showed consistent increases in temperature, and as expected, highest rate for A2 and lowest rate for B1. Precipitation predictions were mixed-reductions in A2 and increases in A1B and B1, and more variations in distant future compared to near future. When the projected temperatures and precipitation were inputted into the SWAT model, and the model outputs were compared with the baseline period (1980-2010), the picture that emerged depicted worsening water resources variability.
Increasing Quality in Scenario Modelling with Model-Driven Development

Models, with different levels of detail, share similar abstractions that can be reused by means of model-driven techniques such as transformations. For example, scenarios are a well-known technique in requirements engineering to represent behavioral flows in a software system. When using UML, scenarios are typically represented with activity models in the early stages of software development, while sequence models are used to describe more detailed object interactions as modeling progresses. This paper defines transformation rules to automate the migration from activity to sequence models. We present a case study illustrating the application of our transformation rules. Our preliminary assessment of the impact of the benefits of using these transformations points to: (i) a reduction of around 50% in the effort building sequence models, (ii) increased trace ability among models, and (iii) error prevention when migrating from different scenario notations.
BioTagger-GM: a gene/protein name recognition system.

OBJECTIVES Biomedical named entity recognition (BNER) is a critical component in automated systems that mine biomedical knowledge in free text. Among different types of entities in the domain, gene/protein would be the most studied one for BNER. Our goal is to develop a gene/protein name recognition system BioTagger-GM that exploits rich information in terminology sources using powerful machine learning frameworks and system combination. DESIGN BioTagger-GM consists of four main components: (1) dictionary lookup-gene/protein names in BioThesaurus and biomedical terms in UMLS Metathesaurus are tagged in text, (2) machine learning-machine learning systems are trained using dictionary lookup results as one type of feature, (3) post-processing-heuristic rules are used to correct recognition errors, and (4) system combination-a voting scheme is used to combine recognition results from multiple systems. MEASUREMENTS The BioCreAtIvE II Gene Mention (GM) corpus was used to evaluate the proposed method. To test its general applicability, the method was also evaluated on the JNLPBA corpus modified for gene/protein name recognition. The performance of the systems was evaluated through cross-validation tests and measured using precision, recall, and F-Measure. RESULTS BioTagger-GM achieved an F-Measure of 0.8887 on the BioCreAtIvE II GM corpus, which is higher than that of the first-place system in the BioCreAtIvE II challenge. The applicability of the method was also confirmed on the modified JNLPBA corpus. CONCLUSION The results suggest that terminology sources, powerful machine learning frameworks, and system combination can be integrated to build an effective BNER system.
Location Estimation Technique using Extended 3-D LANDMARC Algorithm for Passive RFID Tag

The Radio Frequency Identification (RFID) is not designed primarily for indoor location sensing. However, location can be sensed in a viable and cost effective way by employing some algorithm. This paper is an attempt to extend the current LANDMARC Algorithm by introducing the 'z' coordinate. The presented work utilizes the passive tag instead of active, which essentially cuts the cost of RFID tracking system drastically. The Received Signal Strength Indicator (RSSI) is provided by Intel R1000 transceiver directly, it eliminates the scanning time of existing LANDMARC algorithm. The presented result shows the correctness and the efficiency of the simulation. The error rate in the estimation of location is . 5 only, which is acceptable in any tracking system. Furthermore, this algorithm can be coined with other route-tracking algorithm to give exact path of the tag.
Serotonin Transporter Polymorphism (5-HTTLPR) and Citalopram Effectiveness in Iranian Patients with Major Depressive Disorder

Objective Several studies have implicated the 5-HTTLPR polymorphism in treatment outcomes of selective serotonin re-uptake inhibitors in patients with major depression. The aim of this study was to examine the association between polymorphism in the serotonin transporter gene and citalopram effectiveness in Iranian patients suffering from major depressive disorder (MDD). Methods The sample consisted of 104 patients, with Fars ethnic background, who were diagnosed according to DSM-IV-TR criteria. Beck Depression inventory was used to evaluate the severity of the symptoms during the follow-up, and to determine clinical response of the patients at 4th and 8th week, respectively. Results Our results showed a correlation between the genotype and response to antidepressant drug citalopram, (odds ratios for L/S and L/L were 3.90 (95 percent CI: 1.29- 11.80) and 1.90 (95 percent CI: 0.72-5.08), respectively). Conclusion In conclusion, our results reveal that genetic variation of serotonin transporter is involved in clinical remission of major depressive episodes in Iranian patients after citalopram treatment.
1 “ Design for Classroom Orchestration ” , position paper

Orchestration refers to how a teacher manages, in real time, multi-layered activities in a multi-constraints context. Many pedagogical scenarios integrate individual activities (e.g. reading), teamwork (e.g. problem solving) and class-wide activities (e.g. lectures). Some of these activities are computer-based, some not; some are face-to-face while others are online. This pedagogical integration is mirrored by the technical integration of different tools (simulations, quizzes, wikis, etc.) distributed over multiple artifacts (laptops, sensors, tablets). These integrated scenarios require forms of management referred to as orchestration. Orchestration originates with some frustration. Why are technologies under-exploited in schools, despite the fact that, in Western countries, computers and Internet access are ubiquitous, teachers are computer literate and educational software is available? Obviously, teacher training and learning culture are key explanatory factors. But, let me for instance consider the necessity for learners to login into a system: do the 3 to 5 minutes lost for login in (e.g. due to forgotten passwords), i.e. up to 10% of a standard lesson, bring a pedagogical added-value around 10%? Instead of blaming teachers and institutions, it makes sense to ask if is there something about the technology we develop that discourages its usage? This paper addresses formal education 1 from an evolutionary hypothesis (technologies could incrementally improve school efficiency), not from a revolutionary hypothesis (technologies could radically change schools). Is orchestration different from instructional design? Extrinsic activities Designing effective learning scenarios is and will remain a priority. However, classroom life is populated by activities or events that are not part of the scenario, such as collecting response sheets. There is indeed a continuum of activities from those intrinsic to the scenario to activities extrinsic to learning. From the center to the periphery, this continuum includes the following: 1. Core activities (designed as adaptive): The activities of the scenario are pre-defined, with certain adaptations to be performed by the system or by the teacher. Adapting the activities to the learner behavior is the first layer of orchestration, but is not novel. What maybe novel is that orchestration tools collect data that is simple enough to analyze that the teacher can cope with information about twenty or thirty students. Therefore orchestration tools tend to produce shallow learner modeling such as whether the student is active or attentive. 2. Emergent activities (designed as contingent): Some scenarios include activities whose contents are not predictable because they build upon what learners have produced in earlier …
Participatory Classification in a System for Assessing Multimodal Transportation Patterns

Abstract : There has been an increasing trend of performing inference on data collected by smartphones to provide context-aware location-based services. When this inference is performed using supervised analysis, these services need ground truth if high accuracies are desired. While accuracy is less of a concern for services targeted at individuals, it is important when individual data is aggregated for semantic analysis of a population. However, traditional techniques for obtaining ground truth such as paid crowdsourcing are challenging in this domain since the ground truth is uniquely available to the user. Therefore, the user needs to be the source of ground truth for these services. This motivates the need for Participatory Classification, a framework that is able to satisfy the need for minimally invasive ongoing, ground truth collection from regular users at scale. We present an architecture that can be used to enable this framework for such services, and evaluate the framework in the context of an end-to-end prototype that we built. The prototype minimizes the burden on the user while classifying trips by travel mode, and uses the classified trips to generate a personalized carbon footprint for the user and aggregate data such as commute mode share, for use by urban planners. With this prototype, we collected 7439 labelled sections from 44 unpaid volunteers over a total period of 3 months.
"Nobody wins, but nobody loses either" - understanding different institutional logics in IT public-private partnerships

Information and communication technologies (ICT) are becoming increasingly important for the provision of public services. Therefore, public-private partnerships (PPP) have become a valuable alternative for implementing, maintaining, and modernizing public ICT infrastructures. However, information technology (IT) partnerships between public and private parties are difficult endeavours due to different organizational values and practices. We present the results of an exploratory, interpretive case study that analyzes one of the few working IT PPPs in Germany, and explain how the different parties interacted to succeed in establishing a working partnership. In particular, using institutional logics as meta-theoretical lens, we present a model that emerged from the data and explains the difficulties of public-private cooperation influencing the successful establishment of IT partnerships. Furthermore, we analyzed which management procedures are necessary for enhancing the understanding between public and private parties to build a joint partnership and enable IT PPP success.
A Collision Detection Framework for Deformable Objects

Many collision detectionmethodshave beenproposed. Most of themcanonly be appliedto rigid objects. In general,these methodsprecomputesomegeometricinformation of eachobject, suchasboundingboxes,to be usedfor run-timecollision detection. However, if the object deforms, the precomputed informationmay not be valid anymore andhenceneedsto be recomputedin every framewhile theobjectis deforming.In this paper , wepresentsanefficientcollisiondetectionframework for deformableobjects,which considersboth inter-collisions and self-collisionsof deformableobjectsmodeledby NURBS surfaces.Towardstheendof thepaper , weshow someexperimental resultsto demonstratetheperformanceof thenew method. Categoriesand SubjectDescriptors I.3. 5 [Computer Graphics]: Computational GeometryandObjectModeling—Geometricalgorithms,languages,andsystems; Curve, surface, solid,andobjectrepresentations ; I.3. 6[Computer Graphics]: MethodologyandTechniques—Interactiontech-
Evaluating OWL 2 Reasoners in the context of Clinical Decision Support in Lung Cancer Treatment Selection

This paper evaluates the performances of the OWL 2 reasoners HermiT, FaCT++ and Pellet in the context of an ontological clinical decision support system in lung cancer care. In the first set of experiments, we compare how the classification and realisation times of the LUCADA and LUCADA-SNOMED CT ontologies vary as we expand their TBoxes with additional guideline rule knowledge. In the second set of experiments, we investigate the effect of increasing the ABox of the LUCADA ontology on the realisation times.
Military Service and Physical Capital: Framing Musculoskeletal Disorders Among American Military Veterans Using Pierre Bourdieu’s Theory of Cultural Capital

There are 22 million veterans in the U.S. Armed Forces. Past research on the musculoskeletal health of military veterans has explored the prevalence of musculoskeletal disorders (MSDs) but largely avoids situating findings within a theoretical framework. This article uses Pierre Bourdieu’s theory of cultural capital to contextualize veteran’s greater rates of MSDs compared to nonmilitary civilians. Cultural capital consists of objectified, institutional, and embodied capital that can be transubstantiated to capital in other areas. Embodied or physical capital is central to military service, and military veteran status is beneficial in accessing social and institutional capital. Using the 2012–2014 National Health Interview Survey, we show veterans are more likely to report activity-limiting MSDs, and at younger ages, compared to nonveterans. Physical capital is central to, and impaired by, status as a veteran.
Increasing rule extraction accuracy by post-processing GP trees

Genetic programming (GP), is a very general and efficient technique, often capable of outperforming more specialized techniques on a variety of tasks. In this paper, we suggest a straightforward novel algorithm for post-processing of GP classification trees. The algorithm iteratively, one node at a time, searches for possible modifications that would result in higher accuracy. More specifically, the algorithm for each split evaluates every possible constant value and chooses the best. With this design, the post-processing algorithm can only increase training accuracy, never decrease it. In this study, we apply the suggested algorithm to GP trees, extracted from neural network ensembles. Experimentation, using 22 UCI datasets, shows that the post-processing results in higher test set accuracies on a large majority of datasets. As a matter of fact, for two setups of three evaluated, the increase in accuracy is statistically significant.
Blind Signal Separation Methods for Integration of Neural Networks Results

In this paper it is proposed to apply blind signal separation methods to improve a neural network prediction. Results generated by any regression model usually include both constructive and destructive components. In case of a few models, some of the components can be common to all of them. Our aim is to find the basis elements and distinguish the components with the constructive influence on the modelling quality from the destructive ones. After rejecting the destructive elements from the models results it is observed the enhancement of the results in terms of some standard error criteria. The validity and high performance of the concept is presented on the real problem of energy load prediction
Distributed Multi-Probe LSH : Tackling Real World Data

Locality Sensitive Hashing (LSH) is a method of performing probabilistic dimension reduction of high-dimensional data. The basic idea is to hash the input items so that similar items are mapped to the same buckets with high probability (the number of buckets being much smaller than the universe of possible input items). This hashing scheme is widely used for the purposes of Image/Audio Similarity Identification and Near Duplicate Detection. A significant drawback of the basic LSH scheme is the requirement of a large number of hash tables to attain good search quality. Lv et al. have proposed a multi-probe LSH scheme which is built on the basic LSH indexing scheme and intends to counter the above drawback of the basic LSH scheme. The basic concept behind the multi-probe approach is that it searches in multiple buckets in parallel, which are likely to contain the query result. The reduction in space complexity can be attributed to the intelligent probing sequence followed by the Multi-Probe LSH scheme. We intend to take this multi-probe approach a step further by implementing a distributed version of the multi-probe approach described above. A distributed implementation would improve the time complexity as well as the space complexity by adding more computing power at our disposal. Thus our intended approach would guarantee scalability with respect to the real world scenario, without compromising on the efficiency of the multi-probe approach.
Magnetic monopoles, electric neutrality and the static Maxwell-Dirac equations

We study the full Maxwell-Dirac equations: Dirac field with minimally coupled electromagnetic field and Maxwell field with Dirac current as source. Our particular interest is the static case in which the Dirac current is purely time-like - the `electron' is at rest in some Lorentz frame. In this case we prove two theorems under rather general assumptions. Firstly, that if the system is also stationary (time independent in some gauge) and isolated (in the sense that the fields belong to a suitable weighted Sobolev space), then the system as a whole must have vanishing total charge, i.e. it must be electrically neutral. In fact, the theorem only requires that the system be asymptotically stationary and static. Secondly, we show, in the axially symmetric case, that if there are external Coulomb fields then these must necessarily be magnetically charged - all Coulomb external sources are electrically charged magnetic monopoles.
Poster : Expectations , Perceptions , and Misconceptions of Personal Firewalls

Personal firewalls are recognized as the first line of defense for personal computers. However, the protection they afford depends strongly on their correct configuration [4]. Therefore, their usability is key to their effectiveness. In particular, as users become increasingly mobile, it is important for them to be able to judge whether their computer is secure enough for the usage context at hand [2]. Our prior research [5] revealed that the lack of an accurate mental model about the firewall’s system model is one of the root causes of users’ errors when configuring the firewall. The results of a laboratory study showed that an improved user interface design that incorporated feedback about the state of the firewall in different network contexts could help users develop more effective mental models of the firewall and improve their understanding of firewall’s configuration, resulting in fewer dangerous errors. However, we also learned that a large proportion of users did not see the need for multiple profiles based on context. In this research, our goal is to better understand users’ knowledge, expectations, perceptions, and misconceptions of personal firewalls. We conducted interviews with 30 participants and analyzed the data using qualitative description [7]. The results from 10 interviews are presented in [6]. In this paper we present our aggregated results and examine their implications for the design of personal firewalls.
Uniformly Accurate Diffusive Relaxation Schemes for Multiscale Transport Equations

Many transport equations, such as the neutron transport, radiative transfer, and transport equations for waves in random media, have a diffusive scaling that leads to the diffusion equations. In many physical applications, the scaling parameter (mean free path) may differ in several orders of magnitude from the rarefied regimes to the hydrodynamic (diffusive) regimes within one problem, and it is desirable to develop a class of robust numerical schemes that can work uniformly with respect to this relaxation parameter. In an earlier work [Jin, Pareschi, and Toscani, SIAM J. Numer. Anal. , 35 (1998), pp. 2405--2439] we handled this numerical problem for discrete-velocity kinetic models by reformulating the system into a form commonly used for a relaxation scheme for conservation laws [Jin and Xin, Comm. Pure Appl. Math., 48 (1995), pp. 235--277]. Such a reformulation allows us to use the splitting technique for relaxation schemes to design a class of implicit, yet explicitly implementable, schemes that work with high resolution uniformly with respect to the relaxation parameter. In this paper we show that such a numerical technique can be applied to a large class of transport equations with continuous velocities, when one uses the even and odd parities of the transport equation.