Miracle-dz/UniFAR-FTUs huggingface dataset:
AS-CRED: Reputation and Alert Service for Interdomain Routing

As the backbone routing system of the Internet, the operational aspect of the interdomain routing is highly complex. Building a trustworthy ecosystem for interdomain routing requires the proper maintenance of trust relationships among tens of thousands of peer IP domains called autonomous systems (ASes). ASes today implicitly trust any routing information received from other ASes as part of border gateway protocol (BGP) updates. Such blind trust is problematic given the dramatic rise in the number of anomalous updates being disseminated, which pose grave security consequences for the interdomain routing operation. In this paper, we present AS-CRED, an AS reputation and alert service that not only detects anomalous BGP updates, but also provides a quantitative view of AS' tendencies to perpetrate anomalous behavior. AS-CRED focuses on detecting two types of anomalous updates: 1) hijacked updates where ASes announcing a prefix that they do not own, and 2) vacillating updates that are part of a quick succession of announcements and withdrawals involving a specific prefix, rendering the information practically ineffective for routing. AS-CRED works by analyzing the past updates announced by ASes for the presence of these anomalies. Based on this analysis, it generates AS reputation values that provide an aggregate and quantitative view of the AS' anomalous behavior history. The reputation values are then used in a tiered alert system for tracking any subsequent anomalous updates observed. Analyzing AS-CRED's operation with real-world BGP traffic over six months, we demonstrate the effectiveness and improvement of the proposed approach over similar alert systems.
Analysis of H-S/MRC in correlated Nakagami fading

We present an analysis of a hybrid selection/maximal-ratio combining (H-S/MRC) diversity system over an evenly correlated slow frequency-nonselective Nakagami fading channel. In this system, the L branches with the largest instantaneous signal-to-noise ratio (SNR) out of N available branches are selected and combined using maximal-ratio combining. From the joint characteristic function (c.f.) of the instantaneous branch SNR, we obtain an expression for the c.f. of the combiner output SNR as a series of elementary c.f. 's. The expression can be conveniently used to obtain the symbol error probability of coherent detection of different M-ary modulation schemes.
Perfecting Protection for Interactive Multimedia: A survey of forward errror correction for low-delay interactive applications

Many current and emerging applications require low-latency communication, including interactive voice and video communication, multiplayer gaming, multiperson augmented/virtual reality, and various Internet of Things (IoT) applications. Forward error correction (FEC) codes for low-delay interactive applications have several characteristics that distinguish them from traditional FEC. The encoding and decoding operations must process a stream of data packets in a sequential fashion. Strict latency constraints limit the use of long block lengths, interleaving, or large buffers. Furthermore, these codes must achieve fast recovery from burst losses and yet be robust to other types of loss patterns.
A Connectionist Model of Reflective Reasoning Using Temporal Properties of Node Firing

This paper presents a connectionist model of human reasoning that uses temporal relations between node firing. Temporal synchrony is used for representing variable binding and concepts. Temporal succession serves to represent rules by linking antecedent to consequent parts of the rule. The number of successive synchronies i s affected by two well-known neurobiological parameters, the frequency of neural rythmic activity and the precision of neural synchronization. Reasoning is predicted to be constrained by these variables. An experiment manipulating the amount of successive synchronies i s presented. Experimental results would seem to confirm the predictions.
Increased Corticospinal Tract Fractional Anisotropy Can Discriminate Stroke Onset Within the First 4.5 Hours

Background and Purpose— The role of diffusion tensor imaging in determining stroke age remains unclear. We tested the ability of diffusion tensor imaging metrics to discriminate ischemic stroke <4.5 hours of onset. Methods— We enrolled 60 consecutive patients for multimodal 1.5 T MRI within 12 hours of middle cerebral artery ischemic stroke onset. We measured fractional anisotropy (FA), mean diffusivity (MD), apparent diffusion coefficient (ADC), and T2-weighted signal intensity in affected ipsilateral and unaffected contralateral deep gray matter, cortical gray matter, deep white matter in the corticospinal tract (CST), and subcortical white matter and calculated ipsilateral-to-contralateral ratios (r). Hyperintensity in infarcted tissue was considered fluid-attenuated inversion recovery-positive. Results— We analyzed the 48 patients (17 women; mean age, 68±14 years) with known onset. In 25 (52.1%) patients, onset was ⩽4.5 hours (mean, 182.3±65.6 minutes). Variables differing significantly between infarcts <4.5 hours and >4.5 hours were rFA CST (P=0.001), rMD cortical gray matter (P=0.036), rADC cortical gray matter (P=0.009), rT2 CST (P=0.006), and fluid-attenuated inversion recovery (P<0.001). rFA at CST was the most reliable to discriminate infarcts <4.5 hours (Goodman-Kruskal=0.76). The sensitivity, specificity, and positive and negative predictive values for infarct <4.5 hours of onset by rFA at CST >0.970 were 93.8%, 84.6%, 88.2%, and 91.7%, respectively. Conclusions— These preliminary results suggest rFA at CST may be a surrogate marker of acute stroke age.
State Failure and the Political Violence Phenomenon : A Comparative Analysis of Iraq and Syria Cases

The concept of failed state came to the fore with the end of the Cold War, the collapse of the USSR and the disintegration of Yugoslavia. Political violence is central in these discussions on the definition of the concept or the determination of its dimensions (indicators). Specifically, the level of political violence, the type of political violence and intensity of political violence has been broached in the literature. An effective classification of political violence can lead us to a better understanding of state failure phenomenon. By using Tilly’s classification of collective violence which is based on extent of coordination among violent actors and salience of short-run damage, the role played by political violence in state failure can be understood clearly. In order to do this, two recent cases, Iraq and Syria will be examined.
Multi-Modal Music Information Retrieval - Visualisation and Evaluation of Clusterings by Both Audio and Lyrics

Navigation in and access to the contents of digital audio archives have become increasingly important topics in Information Retrieval. Both private and commercial music collections are growing both in terms of size and acceptance in the user community. Content based approaches relying on signal processing techniques have been used in Music Information Retrieval for some time to represent the acoustic characteristics of pieces of music, which may be used for collection organisation or retrieval tasks. However, music is not defined by acoustic characteristics only, but also, sometimes even to a large degree, by its contents in terms of lyrics. A song's lyrics provide more information to search for or may be more representative of specific musical genres than the acoustic content, e.g. 'love songs' or 'Christmas carols'. We therefore suggest an improved indexing of audio files by two modalities. Combinations of audio features and song lyrics can be used to organise audio collections and to display them via map based interfaces. Specifically, we use Self-Organising Maps as visualisation and interface metaphor. Separate maps are created and linked to provide a multi-modal view of an audio collection. Moreover, we introduce quality measures for quantitative validation of cluster spreads across the resulting multiple topographic mappings provided by the Self-Organising Maps.
Pre-clinical efficacy and synergistic potential of the MDM2-p53 antagonists, Nutlin-3 and RG7388, as single agents and in combined treatment with cisplatin in ovarian cancer

Ovarian cancer is the fifth leading cause of cancer-related female deaths. Due to serious side effects, relapse and resistance to standard chemotherapy, better and more targeted approaches are required. Mutation of the TP53 gene accounts for 50% of all human cancers. In the remaining malignancies, non-genotoxic activation of wild-type p53 by small molecule inhibition of the MDM2-p53 binding interaction is a promising therapeutic strategy. Proof of concept was established with the cis-imidazoline Nutlin-3, leading to the development of RG7388 and other compounds currently in early phase clinical trials. This preclinical study evaluated the effect of Nutlin-3 and RG7388 as single agents and in combination with cisplatin in a panel of ovarian cancer cell lines. Median-drug-effect analysis showed Nutlin-3 or RG7388 combination with cisplatin was additive to, or synergistic in a p53-dependent manner, resulting in increased p53 activation, cell cycle arrest and apoptosis, associated with increased p21WAF1 protein and/or caspase-3/7 activity compared to cisplatin alone. Although MDM2 inhibition activated the expression of p53-dependent DNA repair genes, the growth inhibitory and pro-apoptotic effects of p53 dominated the response. These data indicate that combination treatment with MDM2 inhibitors and cisplatin has synergistic potential for the treatment of ovarian cancer, dependent on cell genotype.
Intweetive Text Summarization

The amount of user generated contents from various social medias allows analyst to handle a wide view of conversations on several topics related to their business. Nevertheless keeping up-to-date with this amount of information is not humanly feasible. Automatic Summarization then provides an interesting mean to digest the dynamics and the mass volume of contents. In this paper, we address the issue of tweets summarization which remains scarcely explored. We propose to automatically generated summaries of Micro-Blogs conversations dealing with public figures E-Reputation. These summaries are generated using key-word queries or sample tweet and offer a focused view of the whole Micro-Blog network. Since state-of-the-art is lacking on this point we conduct and evaluate our experiments over the multilingual CLEF RepLab Topic-Detection dataset according to an experimental evaluation process.
Intelligent learning system for online learning

The paper presents an Adaptive Intelligent Learning System (AILS) designed to be used with any Learning Management System (LMS). The adaptiveness provides uniquely identifying and monitoring the learner's learning process according to the learner's profile. AILS has been implemented as a multi-agent system. The agents were developed as JADE agents. The paper presents the learning model, system components, agent behavior in learner scenarios, the ontologies used in agent communications, and the adaptive strategies. The sample application of the AILS to a dummy LMS is also given.
Performance Evaluation for Training a Distributed BackPropagation Implementation

This paper presents the results of some experiments in parallelizing the training phase of a feed-forward, artificial neural network. More specifically, we develop and analyze a parallelization strategy of the widely used neural net learning algorithm called back-propagation. We describe an approach for parallelizing the back- propagation algorithm. We implemented these algorithms on several LANs, permitting us to evaluate and analyze their performances based on the results of actual runs. We were interested on the qualitative aspect of the analysis, in order to achieve a fair understanding of the factors determining the behavior of this parallel algorithms. We were interested in discovering and dealing with some of the specific circumstances that have to be considered when a parallelized neural net learning algorithm is to be implemented on a set of workstations in a LAN. Part of our purpose is to investigate whether it is possible to exploit the computational resources of such a set of workstations.
ClusterFetch: A Lightweight Prefetcher that Responds to Intensive Disk Read Patterns

Application launch and loading times are important determinants of user experience in the personal computing environment. Since these delays largely depend on the performance of secondary storage, they can be reduced by prefetching disk blocks. However, existing prefetching schemes for general workloads incur a significant overhead in analyzing correlations between blocks so as to choose the blocks to prefetch, and, more significantly, these analyses lack accuracy. We propose a lightweight prefetcher called ClusterFetch which records the sequences of I/O requests that are triggered by file requests during launch and loading. When the same application is run again, the disk blocks that correspond to the stored sequences of I/O requests are prefetched when the related files are opened. Experimental results show that ClusterFetch can reduce application launch times by up to 30.9%, and loading times by up to 15.9%.
A Background Modeling Algorithm Based on Improved Adaptive Mixture Gaussian

For better background modeling in scenes with nonstationary background, a background modeling algorithm based on adaptive parameter adjustment of the Mixture Gaussian is proposed. Mixture Gaussians is applied to learn the distribution of per-pixel in the temporal domain and to control the adaptive adjustment of number K of Gaussian components through increasing, deleting or merging similar Gaussian components adaptively. The new parameters C k and φ k are introduced in the adaptive parameter model. According to the actual situation, the adaptive adjustment of ρ can accurate track the real-time changes with the pixel, which improves the robustness and convergence. Experimental results show that the algorithm can rapidly response when the scene changes in the sequence of video with many uncertain factors, and realize adaptive background modeling with accurate target detection.
Department of Economics Working Paper Series Card Check or Mandatory Representation Vote? How the Type of Union Recognition Procedure Affects Union Certification Success.*

Cross-section time-series analysis of nine Canadian jurisdictions over nineteen years is used to identify the effect of mandatory votes/card check on certification success. The results indicate that mandatory votes reduce certification success rates by approximately 9 percentage points below what they would have been under card check. This result is robust across specifications and significant at above the 99 per cent confidence level. 1 Other terms used for card check are 'card-based recognition' and 'automatic recognition'. 2 An employer may also voluntarily recognize a union. Only a very small proportion of unions are voluntarily recognized. 3 All of the results presented in this paper exclude Prince Edward Island and the federal sector. PEI has a population of approximately 100,000. Certification data are not readily available for this province. The federal sector is omitted because data are not available that properly measure the explanatory variables for this sector.
Bragg Gratings Filter with Apodized Duty-Cycle for 10GHz Channel Spacing DWDM System

The main goal of this paper is to show that using Bragg grating filter with apodized duty cycle it is possible to realize a 10 GHz channel spacing DWDM system. The way to find the best configuration of the grating taking into consideration the lowest level of the first side lobe in the reflection spectrum is shown. Then the solution to eliminate crosstalk for the 10 GHz channel shift is explained and the method for dynamic selection of the channel is proposed.
A Macromarketing Perspective on Alternative Economies

Alternative economies respond to the precarious conditions underpinning the everyday lives of individuals, and their lack of access to and scarcity of resources and competences. Recently there has been increasing interest in the field of macromarketing towards such alternative forms of exchange and marketplaces. Nonetheless, current understandings of alternative economies remain fragmented. The objective of this special issue is to advance our understanding of alternative economies and stimulate future research within this domain. Seven articles are included in this special issue of the Journal of Macromarketing. Each article presents forwardlooking research exploring one of three aspects of alternative economies: (1) the paradigms used within alternative economies, (2) the institutional logics that guide action within these systems and (3) the implications to individuals, localities, markets, and society. The editors of the special issue briefly introduce the topic, provide a definition of alternative economies, and offer an overview of the articles and their contributions.
Do Parents Perceive The Technical Quality Of Public Schools? An Activity Analysis Approach

This paper analyzes the level of “technical” quality public schools and determines whether or not there are discrepancies between this indicator and parents’ subjective perception of quality. A sample of public schools in Catalonia is surveyed. The results show that parents correctly perceive the technical quality. Furthermore, there is a significant negative relationship between the concentration index and parental demand. The findings reveal that parents have some awareness of school quality when enrolling their children and try to obtain their choice based on quality considerations.
Facial feature detection with structure constraints

Human facial feature extraction is an important step in many facial image interpretation tasks. In this paper, an algorithm for detecting facial features is proposed, in which corner-based facial feature detectors are coupled with a statistical model of the spatial arrangement of facial features to yield a robust performance. Experimental results show that the proposed method is robust and can extract facial features with good accuracy.
Online loyalty programs viewed from a searchability perspective

While the amount of search that a consumer can undertake in a unit of time has increased due to the internet, the search space has exploded as well. Thus, compared to offline markets, for a fixed amount of search effort, the number of sellers that a customer can find relative to the number of sellers in a market is lower in online markets: searchability of online markets is low. This paper enumerates the logic behind searchability and proliferation of online loyalty programs to show why low searchability enhances the viability of online loyalty programs. Search aids, such as shopbots, influence searchability. The impact of shopbots on loyalty programs is examined. We find that shopbots in an online market can make a consumer worse off in the presence of a loyalty program, because shopbots list sellers on the basis of prices, and do not offer information on loyalty programs or discounts thereof. In this manner, we conclude that, the net impact of shopbots on searchability of an online market is low.
UvA-DARE ( Digital Academic Repository ) BeppoSAX observations of two unclassified LMXBs : X 1543-624 and X 1556

Observations of two unclassified Low Mass X–ray Binaries, X1543–624 and X1556–605, are presented. In the 2– 10 keV band the first of the two sources is a factor of two stronger than the other. Both sources do not show X–ray bursts, dips or eclipses in their X–ray light curves. We find that both spectra are described by a two–component model consisting of emission from a cool accretion disk plus a Comptonized blackbody with kTbb ∼ 1.5 keV in a low opacity plasma. The spectrum of X1543–624 hardens from the first to the second observation, when the source slowly moves from right to left in the colour–colour diagram. The spectrum of X1556–605 can also be described by a model consisting of a blackbody plus an unsaturated Comptonization with electron energy kTe ∼ 4 keV. In the first observation, X1543–624 shows evidence of a Fe K emission line at 6.4 keV. Moreover, in both observations, the source spectrum exhibits an emission feature around 0.7 keV, which is interpreted as due to the superposition of the K edge absorption features of O and Ne elements with uncommon relative abundances with respect to the solar one (O /O ∼ 0.3, Ne/Ne ∼ 2.5). In the spectrum of X1556–605 no emission lines are observed. We discuss these results and their implications for the source classification and the accretion geometry of the compact object.
Information Content Extraction on Quad Trees for Active Spatial Image Clustering

Spatial Mining differs from regular data mining in parallel with the difference in spatial and non-spatial data. The attributes of a spatial object is influenced by the attributes of the spatial object and moreover by the spatial location. In this paper, we propose a new algorithm for spatial mining by applying an image extraction method on hierarchical Quad tree spatial data structure. Homogeneity of the grid is the entropy measure which decides the further subdivision of the quadrant. Finally, the algorithm proceeds by applying low level image extraction on domain dense nodes of the quad tree.
Pancreatic involvement in Von Hippel-Lindau disease: the role of integrated imaging.

Von Hippel-Lindau disease is a rare dominant autosomal genetic disease determined by the inactivity of an onco-suppressor gene identified in 1993 and located on the short arm of chromosome 3 [1]. This gene has a role of crucial importance in the regulation of the vascular endothelial growth factor (VEGF); therefore, its inactivation promotes an overexpression of the VEGF and the angiogenesis of the tumor characterizing this syndrome [2]. The main clinical and radiological manifestations of the disease are hemangioblastoma of the retina and of the nervous central system, clear cell renal tumors, pheochromocytoma, cystadenoma of the epididymis, tumors of the endolymphatic sack, carcinoid tumors, pancreatic tumors, and multiple cystic formations of the pancreas as well as of the kidneys and the epididymis [2, 3]. Pancreatic gland involvement ranges from 15 to 77% of the cases [1]. An ultrasound scan (US), computed tomography (CT), and magnetic resonance imaging (MRI) play a crucial role both in the initial evaluation of the various manifestations of the disease as well as in the follow-up of these patients [4]. We herein show an integrated imaging study using CT and MRI in evaluating the involvement of the pancreatic gland in Von Hippel-Lindau syndrome. A 58-year-old female patient, suffering from Von Hippel-Lindau syndrome diagnosed ten years earlier, without any symptom of possible pancreatic localization was admitted to our hospital because of decompensated type 2 diabetes. When she was 47-year-old, she underwent surgery for a cerebellar hemangioblastoma, the first illness manifestation. Subsequently, the patient underwent an imaging follow-up with US and CT. Eight years later, due to the presence of two renal lesions at US, the patient underwent a CT scan. This examination confirmed the presence of two renal lesions, with a partially exophytic development, hypodense at examination without contrast medium but showing a meaningful enhancement after the administration of the iopamidol (Iopamiro, Bracco S.p.A., Milan, Italy). One lesion (the larger having a diameter of 4 cm) was located in the middle part of the right kidney and the smaller one in the upper part of the left