Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting DDoS Attacks on ISP Networks

Most past solutions for detecting denial of service attacks (and identifying the perpetrators) have targeted end-node victims. However, little attention has been given to this problem from an ISP perspective. This paper explores the key challenges involved in helping an ISP network detect attacks on itself or attacks on external sites which use the ISP network. We propose a detection mechanism where each router detects traffic anamolies using profiles of normal traffic constructed using stream sampling algorithms. In addition, an ISP’s routers exchange information with each other to increase confidence in their detection decisions. Our initial results show that individual router profiles capture key characteristics of the traffic effectively and help identify anomalies with low false positive and false negative rates. We believe that profile construction can be extremely efficient, supporting even multi-gigabit speeds. We also believe that incremental deployment of such techniques is possible, although it may signficantly impact the effectiveness of the distributed reinforced decision making.
Experiments versus quasi-experiments: do they yield the same answer?

Life would be ever so much easier if quasi-experiments yielded just as good causal inferences as randomized experiments. Of course, the term "quasi-experiment" covers a multitude of designs. Here it refers to the workhorse of the quasi-experimental design literature: the nonequivalent control group design that includes a treatment group, a control group not receiving treatment, and a posttest for both, but where the assignment of subjects to conditions is not controlled by the researcher, and is certainly not random.
Evaluating Implementation Strategies for Location-Based Multicast Addressing

Location-based multicast addressing (LMA) yields an important building block for context-aware applications in mobile ad hoc networks (MANETs). In LMA, messages are routed based on their content as well as on the location of the sending and the receiving nodes. The same dynamism that motivates locations as part of the addressing mechanism for multicast applications in MANETs, makes such a multicast challenging to implement both efficiently and reliably across application scenarios. Different implementation strategies have been proposed in literature for abstractions similar to LMA, motivated and validated by specific applications. The goal of this paper is to devise specific implementation strategies for LMA and compare these strategies in the context of several application scenarios, in order to aid in the selection of a scheme for a given application. To that end, we first detail three algorithms for implementing LMA. The first, message-centric, strategy uses geographically scoped gossiping to propagate messages. The second, query-centric, strategy propagates queries of receivers to subsequently route messages. The third, hybrid, strategy strives for the best of both worlds through a restricted multicasting of both messages and queries. We compare these algorithms both analytically and empirically. We pinpoint differences and break-even points among the approaches based on communication patterns, contrasting our findings with common expectations and our analysis. Our evaluations show that the hybrid approach invariably outperforms at least one of the other approaches, making it a safe choice for settings with varying or unknown communication patterns.
Helium-induced Preconditioning in Young and Old Rat Heart: Impact of Mitochondrial Ca2+-sensitive Potassium Channel Activation

Background: The noble gas helium induces cardiac preconditioning. Whether activation of mitochondrial K+ channels is involved in helium preconditioning (He-PC) is unknown. The authors investigated whether He-PC (1) is mediated by activation of Ca2+-sensitive potassium channels, (2) results in mitochondrial uncoupling, and (3) is age dependent. Methods: Anesthetized Wistar rats were randomly assigned to six groups (n = 10 each). Young (2–3 months) control (Con) and aged (22–24 months) control animals (Age Con) were not treated further. Preconditioning groups (He-PC and Age He-PC) inhaled 70% helium for 3 × 5 min. The Ca2+-sensitive potassium channel blocker iberiotoxin was administered in young animals, with and without helium (He-PC+Ibtx and Ibtx). Animals underwent 25 min of regional myocardial ischemia and 120 min of reperfusion. In additional experiments, cardiac mitochondria were isolated, and the respiratory control index was calculated (state 3/state 4). Results: Helium reduced infarct size in young rats from 61 ± 7% to 36 ± 14% (P < 0.05 vs. Con). Infarct size reduction was abolished by iberiotoxin (60 ± 11%; P < 0.05 vs. He-PC), whereas iberiotoxin alone had no effect (59 ± 8%; not significant vs. Con). In aged animals, helium had no effect on infarct size (Age Con: 59 ± 7% vs. Age He-PC: 58 ± 8%; not significant). Helium reduced respiratory control index in young animals (2.76 ± 0.05 to 2.43 ± 0.15; P < 0.05) but not in aged animals (Age Con: 2.87 ± 0.17 vs. Age He-PC: 2.87 ± 0.07; not significant). Iberiotoxin abrogated the helium effect on respiratory control index (2.73 ± 0.15; P < 0.05 vs. He-PC) but had no effect itself on mitochondrial respiration (2.75 ± 0.05; not significant vs. Con). Conclusion: Helium causes mitochondrial uncoupling and induces preconditioning in young rats via Ca2+-sensitive potassium channel activation. However, these effects are lost in aged rats.
A system for sign language recognition using fuzzy object similarity tracking

As a part of natural language understanding, sign language recognition is considered an important area of research. The applications of such a system range from human-computer interaction in virtual reality systems to auxiliary tools for deaf-mute to communicate with ordinary people through computer. A great deal of research is done so far but fewer researchers have extended it to Arabic sign language recognition. In this paper, we have presented a system that performs vision based isolated Arabic sign language recognition using hidden Markov models together with EM algorithm for parameters estimation. An approach to track hands in subsequent frames is proposed using a fuzzy object similarity measure based on a number of geometrical features of hands. Moreover, we have used the centroid of the signer's face to centralize the body coordinates instead of fixing the signer's position or using position tracker device. The overall accuracy of the recognition task is 98% over a dataset of 50 signs including single hand and two-handed signs.
Thromboprophylaxis Does Not Protect Severely Injured Patients against Pulmonary Embolism

The existing evidence on the effectiveness of thromboprophylaxis after trauma is conflicting. Although prophylaxis with heparin and/or sequential compression devices is practiced widely, many studies failed to document a clear benefit. A recent meta-analysis suggests that prophylaxis does not reduce posttraumatic deep venous thrombosis rates compared to no prophylaxis. The objective of this prospective study is to examine if the use of thromboprophylaxis prevents posttraumatic pulmonary embolism (PE). Sixty-four critically injured patients with clinical evidence of PE were studied by computed tomographic pulmonary angiography and/or conventional pulmonary angiography. PE was diagnosed in 24 (37.5%) patients. Patients with PE were similar to patients without PE with regard to demographics, injury type and severity, operations, and mortality. Thromboprophylaxis was used with equal frequency between PE and no-PE patients (71% vs 80%, P = 0.4). The type of prophylaxis used was similar between patients with PE (17% heparin, 71% sequential compression devices, 17% combination) and patients without PE (32%, 57%, and 10%, respectively; P = 0.16, 0.28, 0.69, respectively). Current methods of posttraumatic thromboprophylaxis may be inadequate. Practices from nontrauma populations have been erroneously extrapolated to the unique trauma population. To reduce the rate of PE after trauma, new methods of thromboprophylaxis should be considered.
A Text-based Query Interface to OWL Ontologies

Accessing structured data in the form of ontologies requires training and learning formal query languages (e.g., SeRQL or SPARQL) which poses significant difficulties for non-expert users. One of the ways to lower the learning overhead and make ontology queries more straightforward is through a Natural Language Interface (NLI). While there are existing NLIs to structured data with reasonable performance, they tend to require expensive customisation to each new domain or ontology. Additionally, they often require specific adherence to a pre-defined syntax which, in turn, means that users still have to undergo training. In this paper we present Question-based Interface to Ontologies (QuestIO) - a tool for querying ontologies using unconstrained language-based queries. QuestIO has a very simple interface, requires no user training and can be easily embedded in any system or used with any ontology or knowledge base without prior customisation.
Model-Based Analysis of Context-Specific Cognitive Control

Interference resolution is improved for stimuli presented in contexts (e.g., locations) associated with frequent conflict. This phenomenon, the context-specific proportion congruent (CSPC) effect, has challenged the traditional juxtaposition of “automatic” and “controlled” processing because it suggests that contextual cues can prime top-down control settings in a bottom-up manner. We recently obtained support for this “priming of control” hypothesis with functional magnetic resonance imaging by showing that CSPC effects are mediated by contextually cued adjustments in processing selectivity. However, an equally plausible explanation is that CSPC effects reflect adjustments in response caution triggered by expectancy violations (i.e., prediction errors) when encountering rare events as compared to common ones (e.g., incongruent trials in a task context associated with infrequent conflict). Here, we applied a quantitative model of choice, the linear ballistic accumulator (LBA), to distil the reaction time and accuracy data from four independent samples that performed a modified flanker task into latent variables representing the psychological processes underlying task-related decision making. We contrasted models which differentially accounted for CSPC effects as arising either from contextually cued shifts in the rate of sensory evidence accumulation (“drift” models) or in the amount of evidence required to reach a decision (“threshold” models). For the majority of the participants, the LBA ascribed CSPC effects to increases in response threshold for contextually infrequent trial types (e.g., congruent trials in the frequent conflict context), suggesting that the phenomenon may reflect more a prediction error-triggered shift in decision criterion rather than enhanced sensory evidence accumulation under conditions of frequent conflict.
Physically-Based Shading at Disney

Following our success with physically-based hair shading on Tangled [27], we began considering physicallybased shading models for a broader range of materials. With the physically-based hair model, we were able to achieve a great degree of visual richness while maintaining artistic control. However, it proved challenging to integrate the lighting of the hair with the rest of the scene which had still used traditional “ad-hoc” shading models and punctual lights. For subsequent films we wanted to increase the richness of all of our materials while making lighting responses more consistent between materials and environments and also wanted to improve artist productivity through the use of simplified controls. When we began our investigation it wasn’t obvious which models to use or even how physicallybased we wanted to be. Should we be perfectly energy conserving? Should we favor physical parameters like index-of-refraction? For diffuse, Lambert seemed to be the accepted norm, while specular seemed to get most of the attention in the literature. Some models such as Ashikhmin-Shirley (2000) [3] aimed to be intuitive and practical while physically plausible, while others such as He et al. (1991) [12] provided a more comprehensive physical model. Still others aimed at improved data fitting [15, 14, 22, 17, 4], but few of these are appropriate for direct manipulation. We could have implemented several models and let the artists choose and combine them, but then we’d have been back to the parameter explosion we were trying to get away from. One study of a large variety of measured materials was Ngan et al. (2005) [21] which compared five popular models. Some models fared better than others overall, but interestingly, there was a strong correlation between the models’ performances – some materials were well represented by all the models, and for others, no model proved suitable. Adding an additional specular lobe helped in only a few of the cases. This begs the question, what is not being represented in the difficult materials? To answer this question and to evaluate BRDF models more intuitively we developed a new BRDF viewer that could display and compare both measured and analytic BRDFs. We discovered new, intuitive ways to view measured BRDF data and we found interesting features in the measured materials that weren’t well-represented by known models. In these course notes we will share observations from studying measured materials along with insights we’ve gleaned about which models fit the measured data and where they fall short. We will then present our new model which is now being used on all current productions. We will also describe our experience of adopting this new model in production and discuss how we were able to add the right level of artistic control while preserving simplicity and robustness.
Circadian Clock Gene Expression in the Ovary: Effects of Luteinizing Hormone1

Abstract A molecular device that measures time on a daily, or circadian, scale is a nearly ubiquitous feature of eukaryotic organisms. A core group of clock genes, whose coordinated function is required for this timekeeping, is expressed both in the central clock and within numerous peripheral organs. We examined expression of clock genes in the rat ovary. Transcripts for core oscillator elements (Arntl, Clock, Per1, Per2, and Cry1) were present in the ovary as indicated by quantitative real-time RT-PCR. Rhythmic expression patterns ofArntl and Per2 transcripts and protein products were out of phase with respect to the central oscillator and in complete antiphase to each other. Expression of Arntl was significantly elevated after the LH surge on the day of proestrus. Finally, hCG treatment induced cyclic expression of both Arntl and Per2 gene products in hypophysectomized, immature rats primed with eCG. Collectively, these data suggest that the core underpinnings of the transcriptional/translational feedback loop that drives circadian rhythmicity is present in the rat ovary. Furthermore, the study identifies LH as a potential regulator of circadian clock gene rhythms in the ovary.
Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.
Conference on the Political Economy of Cameroon: Historical Perspectives

This collection comprises the papers, opening speeches, and discussants' notes presented at the conference 'The political economy of Cameroon - historical perspectives', which was held at Leiden from 1-4 June, 1988. The 34 papers were presented in ten sessions, dealing respectively with: The economy of labour and State intervention (3 papers) - Political economy, aspects (4) - Agricultural development: cooperatives and government interventions (3) - Plantation and peasant production (3) - Women's culture and political economic changes (4) - Accumulation: historical perspectives (4) - Accumulation in agriculture (4) - Rural development: case studies (4) - Political culture and national mobilisation (3) - State and civil society (2).
Optimization based coordinated UGV-MAV exploration for 2D augmented mapping

This paper presents a novel optimization formulation for coordinated exploration between unmanned ground vehicles (UGV) and micro-aerial vehicles (MAV). The exploration is posed as an Integer Programming (IP) problem and the allotment of these vehicles(agents) to frontier locations is specified as an integer constraint. The optimization provides a one shot solution for the allotment of all such active agents to possible frontier locations thereby guaranteeing substantial performance gain over previous approaches where the allotment proceeds in an incremental fashion. We also show a practical realization of such an exploration where an UGV-MAV team efficiently builds a map of an indoor environment.
IITG-Indigo System for NIST 2016 SRE Challenge

This paper describes the speaker verification (SV) system submitted to the NIST 2016 speaker recognition evaluation (SRE) challenge by Indian Institute of Technology Guwahati (IITG) under the fixed training condition task. Various SV systems are developed following the idea-level collaboration with two other Indian institutions. Unlike the previous SREs, this time the focus was on developing SV system using non-target language speech data and a small amount unlabeled data from target language/dialects. For addressing these novel challenges, we tried exploring the fusion of systems created using different features, data conditioning, and classifiers. On NIST 2016 SRE evaluation data, the presented fused system resulted in actual detection cost function (actDCF) and equal error rate (EER) of 0.81 and 12.91%, respectively. Post-evaluation, we explored a recently proposed pairwise support vector machine classifier and applied adaptive S-norm to the decision scores before fusion. With these changes, the final system achieves the actDCF and EER of 0.67 and 11.63%, respectively.
Source coding and graph entropies

A sender wants to accurately convey information to a receiver who has some, possibly related, data. We study the expected number of bits the sender must transmit for one and for multiple instances in two communication scenarios and relate this number to the chromatic and Korner (1973) entropies of a naturally defined graph.
Clustering functional data with the SOM algorithm

In many situations, high dimensional data can be consid- ered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by approximating a theo- retical SOM on functions thanks to basis expansion. We illustrate the proposed method on real world spectrometric data for which functional preprocessing is very successful.
Uniqueness and how it impacts privacy in health-related social science datasets

Social scientists, like those performing research at the Kinsey Institute for Research in Sex, Gender and Reproduction, may use surveys to gather large amounts of sensitive data. Unlike purely medical-related datasets, these social science datasets tend to be sparse and high-dimensional, which presents opportunities to characterize participants in the dataset in unique ways. These unique characterizations may enable individuals to be linked to external data in ways that have not been previously considered. Therefore, traditional approaches to de-identifying data, such as fulfilling HIPAA requirements, may not be sufficient for preventing the re-identification of participants in large social science datasets. In this paper, we evaluate the statistical characteristics of two high-dimensional social science datasets to better understand how unique features impact privacy. We apply a class of statistical de-anonymization attacks in an attempt to achieve theoretical re-identification of participants. We assume that an attacker has exact knowledge of a subset of attribute values for a particular record, and wants to link this subset of data to the actual record to discover the remaining content. We show that although 98% of the records within the dataset are unique given any three attributes, re-identification of the records may not be easily achieved. We attribute limited re-identification to the inherent similarity in the human behavior that the scientists measure. This work is the first to characterize re-identification risks in high-dimensional data that is collected in surveys designed to capture the various behaviors and experiences of groups of individuals.
A Model-driven Approach to Representing and Checking RBAC Contextual Policies

Among the various types of Role-based access control (RBAC) policies proposed in the literature, contextual policies take into account the user's location and the time at which she requests an access. The precise characterization of the context in such policies and the definition of an access decision procedure for them are non-trivial ntasks, since they have to take into account the various facets of the temporal and spatial expressions occurring in these policies. Existing approaches for modeling contextual policies do not support all the various spatio-temporal concepts and often do not provide an access decision procedure. In this paper, we propose a model-driven approach to representing and checking RBAC contextual policies. We introduce GemRBAC+CTX, an extension of a generalized conceptual model for RBAC, which contains all the concepts required to model contextual policies. We formalize these policies as constraints, using the Object Constraint Language (OCL), on the GemRBAC+CTX model, as a way to operationalize the access decision for user's requests using model-driven technologies. We show the application of GemRBAC+CTX to model the RBAC contextual policies of an application developed by HITEC Luxembourg, a provider of situational-aware information management systems for emergency scenarios. The use of GemRBAC+CTX has allowed the engineers of HITEC to define several new types of contextual policies, with a fine-grained, precise description of contexts. The preliminary experimental results show the feasibility of applying our model-driven approach for making access decisions in real systems.