Miracle-dz/UniFAR-FTUs huggingface dataset:
Anomaly Handling in Visual Analytics

Visual analytics is an emerging field which uses visual techniques to interact with users in the analytical reasoning process. Users can choose the most appropriate representation that conveys the important content of their data by acting upon different visual displays. A visual analytics application helps users to formulate and view the patterns in the datasets by means of data visualization and methods to adjust the parameters of the algorithms or the technologies provided behind the visual displays. In the analytical discourse, users can combine their information or expertise in the domain to guide the exploration to save time and to produce more satisfactory results. The data itself has many features of interest, including clusters, trends (commonalities) and anomalies. Most visualization techniques currently focus on the discovery of trends and other relations, where uncommon phenomena are treated as outliers and are either removed from the datasets or de-emphasized on the visual displays. Much less work has been done on the visual analysis of outliers, or anomalies. In this thesis, we introduce a method to identify the different levels of " outlierness " by using interactive selection. We implemented a density-based outlier detection algorithm, where users have control over the density input parameter and the dimensions used in calculations through a graphical interface. For the visual analytics process, we developed two techniques for interacting with data regions of different outlier degrees. To compare the effectiveness of these approaches, we performed user studies on the usability of the two visual methods. The tools were developed based on XmdvTool version 7.0 and Xmdv-lite.
Consumer Demand for Mobile Phone Service in the US : An Examination beyond the Mobile Phone

Christian M. Dippon Abstract If casual observation is an accurate indicator, consumers make their mobile purchasing decisions based solely on the type of mobile phone that mobile service providers are offering as part of a bundle of services. This raises the question of whether other service bundle components matter to consumers. In light of increased competition and saturation in the US mobile sector, gaining a deeper understanding of consumer choice is critical not only for the development of effective market strategies but also for policymaking. The present study uses a stated-preference survey to offer direct insights into the demand determinants for mobile service bundles.
Use of Ontology-Based Multi-Agent Systems in the Biomedical Domain

Coordination, cooperation and exchange of information is important to the medical community. We design a new ontology, called Generic Human Disease Ontology (GHDO), by merging and aligning existing medical ontologies. The concepts of the GHDO are organized into the following four dimensions: Types, Symptoms, Causes and Treatments of human diseases. We also design a multi-agent system framework over different information resources. The multi-agent system uses the common GHDO ontology for query formulation, information retrieval and information integration. We conclude that this intelligent dynamic system provides opportunities to collect information from multiple information resources, to share data efficiently and to integrate and manage scientific results in a timely manner.
Designing Of radar systems for passive detection and ranging: Target aquisition without transmission

This paper is in live context with the improvement in the stealth technology that is designed by us for enhancing the surveilience strength of radar system. The idea about passive detection and ranging was projected as an research purpose for improvement in radar technology. We already have active radar but in active radar we get detected in the opponent radar once we switch on the radar since radar transmits and recieves the same. To enhance the security if the radar only recieves the signals of all the opponent and monitors them without transmitting then such radar will not be visible in the opponents radar. Since, this technique is now under-development in various countries. We have proposed our technique as well as provided the existing passive radar method i.e., WIMAX radar.
A MapReduce-based Algorithm for Motif Search

Motif search plays an important role in gene finding and understanding gene regulation relationship. Motif search is one of the most challenging problems in bioinformatics. In this paper, we present three data partitions for the PMSP algorithm and propose the PMSP MapReduce algorithm (PMSPMR) for solving the motif search problem. For instances of the problem with different difficulties, the experimental results on the Hadoop cluster demonstrate that PMSPMR has good scalability. In particular, for the more difficult motif search problems, PMSPMR shows its advantage because the speedup is almost linearly proportional to the number of nodes in the Hadoop cluster. We also present experimental results on realistic biological data by identifying known transcriptional regulatory motifs in eukaryotes as well as in actual promoter sequences extracted from Saccharomyces cerevisiae.
Influence of regional features of psycho- emotional state of the Russian society on road accidents severity

The article considers issues of assessment of the relation between road accidents severity and psychoemotional state of Russian society. In the context of the hypothesis about the significant impact of people’s awareness of the value of life on their ordinary behavior, four subtasks were solved. Firstly, the difference in road accidents severity between all road accidents and road accidents that happened in alcohol intoxication state was established. Secondly, indicators of the psychoemotional state of people from different Russian regions were identified. Thirdly, dependencies «Road accidents severity = f(Psychoemotional state of people from Russian region)» for two cases «All road accidents» and «Road accidents that happened in alcohol intoxication state» were defined. Finally, it was found that degree of impact of alcohol intoxication on road accidents severity depends on the psychoemotional state of people from different Russian regions. Produced results can be used in the development of regional programs of road safety management taking into account features of the psychoemotional background in different subjects of Russia.
Requirement Meta-model and Ontology-based Blogs Architecture for IS Requirements Elicitation

Collecting requirements from large number of online stakeholders is one of success factors of information systems on Internet. However, unstructured and fragmental requirements are difficult to be seamlessly integrated. Distributed stakeholders are difficult to deliver and discuss requirements in an effective and efficient way. This paper proposes a meta-model to structuralize requirements. This paper argues that stakeholders can use ontologies to fill in the meta-model to composite a requirement summary. Based on the proposed meta-model and ontologies, this paper proposes an improved blogs system to assist stakeholders to send, receive, and manage requirements and ontologies. A system architecture is depicted. Finally, a scenario as an illustrative example is also provided to explain how the proposed system architecture works.
Efficient detection of flow anomalies with limited monitoring resources

Real time detection of flow anomalies is a critical part of wide range of management and security applications in many Cloud and NFV systems. Solutions based on per-flow records have become impossible due to the increasing traffic volumes and the limited available resources such as TCAM entries and fast counters. In this paper we study a novel dynamic control mechanism that allows detecting flow anomalies using only a limited number of counters. Starting from the simple observation that it is impossible to guarantee instantaneous detection of flow anomalies with a limited amount of counters, we study the trade-off between the time required to detect the anomaly and the number of available counters. We implemented the scheme in an OpenFlow enabled switch, where the logic is implemented in the controller, and demonstrate that it can be used to detect a single flow anomaly within large real traffic volume. To further reduce the detection time, we also implemented the scheme logic inside the switch and used the controller only for configuration. This implementation indeed yielded a faster detection and lower monitoring communication overhead while not introducing any significant observable costs at the switch itself.
Underdetermined Blind Separation of Nondisjoint Sources in the Time-Frequency Domain

This paper considers the blind separation of nonstationary sources in the underdetermined case, when there are more sources than sensors. A general framework for this problem is to work on sources that are sparse in some signal representation domain. Recently, two methods have been proposed with respect to the time-frequency (TF) domain. The first uses quadratic time-frequency distributions (TFDs) and a clustering approach, and the second uses a linear TFD. Both of these methods assume that the sources are disjoint in the TF domain; i.e., there is, at most, one source present at a point in the TF domain. In this paper, we relax this assumption by allowing the sources to be TF-nondisjoint to a certain extent. In particular, the number of sources present at a point is strictly less than the number of sensors. The separation can still be achieved due to subspace projection that allows us to identify the sources present and to estimate their corresponding TFD values. In particular, we propose two subspace-based algorithms for TF-nondisjoint sources: one uses quadratic TFDs and the other a linear TFD. Another contribution of this paper is a new estimation procedure for the mixing matrix. Finally, then numerical performance of the proposed methods are provided highlighting their performance gain compared to existing ones
Eradication of Hepatitis C Virus Infection and the Development of Hepatocellular Carcinoma

BACKGROUND Hepatitis C virus (HCV) is a leading cause of hepatocellular carcinoma (HCC). In the United States, this form of cancer occurs in approximately 15 000 persons annually. A systematic review of the evidence is needed to assess the benefits of treatment of HCV-infected persons on development of HCC. PURPOSE To systematically review observational studies to determine the association between response to HCV therapy and development of HCC among persons at any stage of fibrosis and those with advanced liver disease. DATA SOURCES MEDLINE, EMBASE, CINAHL, the Cochrane Library, Web of Science, and the Database of Abstracts of Reviews and Effectiveness from inception through February 2012. STUDY SELECTION English-language observational studies that compared therapy-derived sustained virologic response (SVR) with no response to therapy among HCV-infected persons, targeted an adult population, and had an average follow-up of at least 2 years. DATA EXTRACTION Two investigators independently extracted data into uniform relative risk measures. The Grading of Recommendations Assessment, Development and Evaluation framework was used to determine the quality of the evidence. DATA SYNTHESIS Thirty studies fulfilled the inclusion criteria, and 18 provided adjusted effect estimates that were used to calculate pooled relative risks. Among HCV-infected persons, SVR was associated with reduced risk for HCC (relative risk for all persons, 0.24 [95% CI, 0.18 to 0.31], moderate-quality evidence; advanced liver disease hazard ratio, 0.23 [CI, 0.16 to 0.35], moderate-quality evidence). LIMITATION In the meta-analyses, some variables could not be controlled for because of the observational design of the included studies. CONCLUSION Sustained virologic response after treatment among HCV-infected persons at any stage of fibrosis is associated with reduced HCC. The evidence was determined to be of moderate quality.
Joint multi-view foreground segmentation and 3D reconstruction with tolerance loop

In this paper we present a novel foreground segmentation and 3D reconstruction system for multi-view scenarios. The system achieves correct 3D object reconstruction even when foreground segmentation presents critical misses in some of the views. We introduce the spatial redundancy of the multi-view data into the foreground segmentation process by combining segmentation and the 3D reconstruction in a two steps workflow. First, the segmentation of the objects in each view uses a monocular, region-based foreground segmentation in a MAP-MRF framework for foreground, background and shadow classes. Next, we compute an iterative volume reconstruction in a 3D tolerance loop, obtaining an iteratively enhanced SfS volume. Foreground segmentation is improved by updating the foreground model of each view at each iteration. The results presented in this paper show the improved foreground segmentation and the reduction of errors in the reconstruction of the volume.
Millimeter-wave design and fabrication of GaAs micromachined patch antenna

A patch antenna at Ka-band frequency based on GaAs micromachined technologies is presented in this paper. The antenna fabricated on 300μm-thick GaAs substrate with a cavity etched in it produces a low effective dielectric region around the patch leading to improvement of bandwidth and radiation. The bandwidth of 4.1%, gain of 7.27dB and radiation efficiency of 79.5% at 36.3GHz have been simulated. The experimental results show that the bandwidth is 4.4% at 36.29GHz.
The evolutionary status of activity-selected solar-type stars and of T Tauri stars as derived from Hipparcos parallaxes: evidence for long-lived T Tauri disks? ?

We have used the Hipparcos parallaxes to study the evolutionary status of a sample of stars with spectral types from late F to M0 (hereafter "solar-type stars"), selected on the basis of their activity, mainly from Einstein-based surveys. The par- allaxes have been used to place the objects in the H-R diagram, determining their age by comparison with theoretical evolution- ary tracks and observational main sequences. This age is com- pared with age estimates derived from the lithium abundance, the activity level and the presence of circumstellar disks. To complement our sample at the young end we have also studied the Hipparcos-determined distances of a sample of optically- selected pre-main sequence stars, mostly classical T Tauri stars (CTTS). Some CTTS appear to be much nearer to us than previ- ously determined, and far away from their putative parent cloud. This implies a significantly larger age providing observational evidence for the existence of long-lived T Tauri disks which could produce slow rotators on the Zero-Age Main Sequence (ZAMS). None of the above-mentioned age proxies appears to reliably and unambiguously select very young stars in the range of spectral types considered here, with some apparently very young objects effectively lying onto or very close to the main sequence. The attribution of ages to young solar-type stars on the basis of any of the standard proxies may thus significantly under- or over-estimate the evolutionary age of the object. Caution must therefore be exercised when attributing ages to individual stars, and claims about the large number of PMS stars found in X-ray based surveys may need to be at least in part reconsidered in this light.
Transition to attack in elite soccer

Since the pioneering work of Reep and Benjamin (1968) on regained possessions, there has been a lack of detailed, informative research in the area. The aim of this study was to analyse all elements of transitions to attack in elite football. The influence of turnover zone, turnover type and ‘on the ball’ player actions upon scoring goals and creating scoring opportunities (S.O.’s) were examined. A total of 3,077 transitions from all 29 games of the 2014-15 Champion’s League knockout stages were coded. Multidimensional qualitative data using 11 ordered categorical variables were obtained to characterise each transition. Data were analysed using chi-square analysis. Winning turnovers in offensive areas increased the chance of scoring a goal and creating a S.O. (p < .001). Nearly half of all turnovers in the offensive zone, 49.45% (n=45) resulted in a S.O. , and 7.69% (n=7) lead to goals. The tackle was the most productive way to turnover the ball (p < .05). Teams created significantly more S.O. s and scored more goals when the first and second actions after the turnover were forward (p < .05); successful dribbles, runs with the ball and long passes were the optimal player actions. Further analysis revealed that successful teams (top 4) created more S.O. ’s from the defensive, defensive midfield and offensive midfield but not the offensive zone (p < .01). Finally teams created more S.O. s from turnovers in the offensive half, but not the defensive half, when losing or drawing the tie (p < .05). It was concluded that teams should press high to win turnovers and create S.O. ’s, supporting the findings of Reep and Benjamin (1968). It was further concluded that the immediate player actions after winning the turnover are critical to the outcome of the transition.
Energy-efficient three-phase task scheduling heuristic for supporting distributed applications in cyber-physical systems

Cyber physical systems (CPS) have recently emerged as a promising approach to improve the synergy between physical and virtual worlds. CPS applications can be built on top of Wireless Sensor Networks (WSNs) exploiting the physical information collected by them to bridge real and cyber realms. In this paper, we investigated the emerging problem of how to schedule multiple applications onto cyber-physical systems encompassed of multiple WSNs, while meeting demands of these applications. Our goal is to find out an optimal scheduling scheme for each application so that: (i) it minimizes the overall energy consumption, (ii) it meets the application's deadline, (iii) it provides the required data accuracy to applications, and (iv) it balances the workload of the system. To achieve such goals, we developed a polynomial-time three phase task scheduling heuristic, named HTPTS. Experimental results show that the time and energy performance of HTPTS are close to the time and energy of the benchmark in most of the cases, while load balance is satisfied.
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices

We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact factorized representation without the need of specifying the rank beforehand. Moreover, we show that the framework can be easily generalized to the problem of learning multiple matrices and general spectral regularization. Empirically we show that we can recover a 10,000×10,000 matrix from 1.2 million observations in about 5 minutes. Furthermore, we show that in a brain-computer interface problem, the proposed method can speed-up the optimization by two orders of magnitude against the conventional projected gradient method and produces more reliable solutions.
Design Issues for SIGMA : Seamless IP diversity based Generalized Mobility Architecture

In this paper, we propose and evaluate a novel transport layer mobility management scheme: Seamless IP diversity based Generalized Mobility Architecture (SIGMA). SIGMA provides seamless handover for mobile hosts and is based on SCTP, which is a new reliable transport protocol introduced by IETF to transport SS7 signaling messages over IP network. We also show that our handover scheme can greatly reduce the handover latency, packet loss, signaling costs and improve the whole system’s throughput compared to the popular Mobile IP based handover schemes.
Thalamic Modulation of Cingulate Seizure Activity Via the Regulation of Gap Junctions in Mice Thalamocingulate Slice

The thalamus is an important target for deep brain stimulation in the treatment of seizures. However, whether the modulatory effect of thalamic inputs on cortical seizures occurs through the modulation of gap junctions has not been previously studied. Therefore, we tested the effects of different gap junction blockers and couplers in a drug-resistant seizure model and studied the role of gap junctions in the thalamic modulation on cortical seizures. Multielectrode array and calcium imaging were used to record the cortical seizures induced by 4-aminopyridine (250 µM) and bicuculline (5–50 µM) in a novel thalamocingulate slice preparation. Seizure-like activity was significantly attenuated by the pan-gap junction blockers carbenoxolone and octanol and specific neuronal gap junction blocker mefloquine. The gap junction coupler trimethylamine significantly enhanced seizure-like activity. Gap junction blockers did not influence the initial phase of seizure-like activity, but they significantly decreased the amplitude and duration of the maintenance phase. The development of seizures is regulated by extracellular potassium concentration. Carbenoxolone partially restored the amplitude and duration after removing the thalamic inputs. A two-dimensional current source density analysis showed that the sink and source signals shifted to deeper layers after removing the thalamic inputs during the clonic phase. These results indicate that the regulatory mechanism of deep brain stimulation in the thalamus occurs partially though gap junctions.
Clinical and molecular classification of cardiomyopathies

Abstract The term “cardiomyopathies” was used for the first time 55 years ago, in 1957. Since then awareness and knowledge of this important and complex group of heart muscle diseases have improved substantially. Over these past five decades a large number of definitions, nomenclature and schemes, have been advanced by experts and consensus panel, which reflect the fast and continued advance of the scientific understanding in the field. Cardiomyopathies are a heterogeneous group of inherited myocardial diseases, which represent an important cause of disability and adverse outcome. Although considered rare diseases, the overall estimated prevalence of all cardiomyopathies is at least 3% in the general population worldwide. Furthermore, their recognition is increasing due to advances in imaging techniques and greater awareness in both the public and medical community. Cardiomyopathies represent an ideal translational model of integration between basic and clinical sciences. A multidisciplinary approach is therefore essential in order to ensure their correct diagnosis and management. In the present work, we aim to provide a concise overview of the historical background, genetic and phenotypic spectrum and evolving concepts leading to the various attempts of cardiomyopathy classifications produced over the decades.