Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering of Evolving Data Stream with Multiple Adaptive Sliding Window

Clustering of data streams has received much attention in recent years. Many algorithms have been proposed in order to discover clusters in data streams efficiently and effectively. Most of these algorithms are devoted to discover the clusters with high density, correlation and low intra-cluster distance. Especially, many methods are considered to balance the memory, the time consumption and the clustering effects. However, few related works focus on the important characteristic of evolving data stream that the distribution of the data items is dense and partially concentrative on the timeline, and one data item usually just has influence to other items in limited range of time. In this paper, we present a novel algorithm called MawStream (clustering with Multiple Adaptive sliding Window). In MawStream each data item in potential cluster associates with an adaptive time window. Instead of fixed length of window, the window length of a data item is computed according to its influence. Once one data item’s window length becomes zero, it’s called unactive and needs not further processing. Such mechanism avoids dealing with too many data in clustering data streams. MawStream can handle detailed correlations among finite points in a time bucket and find high quality clusters in period of time. At the same time, MawStream allows users to submit offline queries to determine whether some potential clusters are similar to the specified cluster in order to cope with in-definability of the number of potential clusters. The result of experiment using both actual and synthetic datasets shows that our algorithm could cluster data streams efficiently with high quality.
Network Intrusion Detection using Data Mining Technique

In recent years, most of the research has been done in the field of Intrusion Detection System (IDS) to detect attacks in network traffic indicating malicious activity. IDS can be built in two different ways: Signature based and Anomaly based. This paper presents anomaly based network intrusion detection model using Density Based Spatial Clustering for Applications with Noise (DBSCAN) technique called DNIDS (DBSCAN based Network Intrusion Detection System) for the identification of abnormality in the network traffic dataset. In case of detecting attacks the rule generation algorithm is utilized to frame a new attack and attacks are identified using detection model. The generated rules for normal and abnormal data are used to form a new abnormal record in the dataset. DNIDS uses less memory space and gives better performance comparing with other techniques. This is achieved by reducing the features present in the network intrusion dataset. Feature extraction is done using the Correlation Feature Selection (CFS) method. The proposed DNIDS is validated using well known KDD Cup1999 Data (KDD 99) and the performance is compared with k-means, Expectation Maximization (EM) based on their accuracy in clustering the data and the time they take to detect intrusion. It is found that DNIDS gives better accuracy in detecting anomalies.
Genome Wide Analysis of Nucleotide-Binding Site Disease Resistance Genes in Brachypodium distachyon

Nucleotide-binding site (NBS) disease resistance genes play an important role in defending plants from a variety of pathogens and insect pests. Many R-genes have been identified in various plant species. However, little is known about the NBS-encoding genes in Brachypodium distachyon. In this study, using computational analysis of the B. distachyon genome, we identified 126 regular NBS-encoding genes and characterized them on the bases of structural diversity, conserved protein motifs, chromosomal locations, gene duplications, promoter region, and phylogenetic relationships. EST hits and full-length cDNA sequences (from Brachypodium database) of 126 R-like candidates supported their existence. Based on the occurrence of conserved protein motifs such as coiled-coil (CC), NBS, leucine-rich repeat (LRR), these regular NBS-LRR genes were classified into four subgroups: CC-NBS-LRR, NBS-LRR, CC-NBS, and X-NBS. Further expression analysis of the regular NBS-encoding genes in Brachypodium database revealed that these genes are expressed in a wide range of libraries, including those constructed from various developmental stages, tissue types, and drought challenged or nonchallenged tissue.
Parallel Training Data Selection for Conversational Machine Translation

We describe data selection strategies for an English-French Skype conversation translation task without in-domain training data. Selection methods based on language modeling and text formality criterion are evaluated. Our main finding is that translating conversation transcripts turned out to not be as challenging as we expected: while translation quality is of course not perfect, a straightforward phrase-based system trained on movie subtitles yields high BLEU scores, and small improvements are obtained by using a simple heuristic to select more Skype-like examples.
BINGE EATING IN OBESITY : MAINLAND PORTUGAL AND SÃO MIGUEL , AZORES

This study aimed to investigate if binge eating-BE in individuals with obesity is influenced by their eating behaviour, social support satisfaction, healthcare, lifestyle and sociodemographical variables. It also aimed to compare BE and body mass index-BMI between individuals from mainland Portugal (n=117) and São Miguel, Azores (n=70) – cluster of islands with the largest national obesity incidence. Participants completed the Binge Eating Scale, the Dutch Eating Behaviour Questionnaire and the Social Support Satisfaction Scale. It was used as a modelling of structural equations to construct the structural model, having BE as dependent variable. Emotional eating (β=.26;p<.001), external eating (β=.2;p<.001) and satisfaction with support from friends (β=-.14;p=.004) predict the severity of BE. Also the level of educational level was associated to BE (β=-.11;p<.001). There was no association between BE and BMI (β=.003;p=.68) or between individuals from mainland Portugal and São Miguel (t(115,897)=1.38;p=. 17), contrary to the BMI (t(184,538)=3.57;p=. 001). Interventions that promote adaptive strategies for management of emotional and external eating are suggested and also the development of friends network support in combination with health activities to attenuate the severity of BE. The absence of differences between the samples from mainland Portugal and the islands in relation to BE raises the hypothesis of other variables being able to explain the differences between the prevalence of obese individuals, other than the ones studied.
The influence of empathic concern on prosocial behavior in children

This research explored the influence of empathic distress on prosocial behavior in a resource allocation task with children. Children were randomly assigned to one of two conditions before engaging in a sticker sharing task; watching either a video of a girl upset that her dog had gone missing (emotion induction condition), or a video of the same girl preparing for a yard sale (control condition). In study one, 5–6 year old children in the emotion induction condition rated the emotional state of both the protagonist and the self more negatively, and also exhibited more prosocial behavior; sharing more in advantageous inequity (AI) trials, and less often withholding a benefit in disadvantageous inequity trials, than the control group. Prosocial behavior was significantly correlated with ratings of the emotional state of the protagonist but not with own emotional state, suggesting that empathic concern rather than personal distress was the primary influence on prosocial behavior. In study two, 3-year-olds were tested on AI trials alone, and like the 5 and 6-year-olds, showed more prosocial behavior in the emotion induction condition than the control.
Genome-Wide Generation of Yeast Gene Deletion Strains

In the year 2001 a collection of yeast strains will be completed that are deleted in the 6000 open reading frames selected as putative genes by the initial bioinformatic analysis of the Saccharomyces cerevisiae genome. The collection was produced by the transatlantic yeast gene deletion project, a collaboration involving researchers in the USA, Canada and Europe. The European effort was part of EUROFAN (European Functional Analysis Network) where some of the strains could feed into various functional analysis nodes dealing with specific areas of cell biology. With approximately 40% of human genes involved in heritable disease having a homologue in yeast and with the use of yeast in various drug discovery strategies, not least due to the dramatic increase in fungal infections, these strains will be valuable in trans-genomic studies and in specialised interest studies in individual laboratories. A detailed analysis of the project by the consortium is in preparation, here we discuss the yeast strains, reported findings and approaches to using this resource.
Prevention of traffic analysis attack in friend in the middle using dummy traffic approach

Online social network is a platform which makes each individual to be connected with their friends and colleagues. This connectivity encourages the users to share their private information all the way through social networking sites but sharing of personal information on this open platform leads to concern of privacy issues. Personal information available in social networking sites makes the adversary to take undue advantage of data and harm the user by embarrassing them or ruining their reputation. Traffic Analysis is one of the privacy issues which mean pilfering the personal communication between two users. Friend in the Middle (FiM) approach focuses on providing privacy awake social network architecture and extends the current OSNs in such a way that it restricts unnecessary access to the information but it is prone to traffic analysis attacks. In the proposed scheme, dummy traffic approach is used to prevent traffic analysis attack in Friend in the Middle (FiM). Comparison between the existing FiM and the proposed FiM is made using various parameters and enhanced accuracy of the proposed approach with the existing technique is achieved.
B Cell Responses to HIV Antigen Are a Potent Correlate of Viremia in HIV-1 Infection and Improve with PD-1 Blockade

Infection with Human Immunodeficiency Virus Type 1 (HIV-1) induces defects of both cellular and humoral immune responses. Impaired CD4+ T cell help and B cell dysfunction may partially explain the low frequency of broadly neutralizing antibodies in HIV-infected individuals. To understand the extent of B cell dysfunction during HIV infection, we assessed the level of B cell activation at baseline and after stimulation with a variety of antigens. Increased levels of viremia were associated with higher baseline expression of the activation marker CD86 on B cells and with decreased ability of B cells to increase expression of CD86 after in vitro stimulation with inactivated HIV-1. In a series of cell isolation experiments B cell responses to antigen were enhanced in the presence of autologous CD4+ T cells. HIV infected individuals had a higher frequency of PD-1 expression on B cells compared to HIV- subjects and PD-1 blockade improved B cell responsiveness to HIV antigen, suggesting that inhibitory molecule expression during HIV-1 infection may contribute to some of the observed B cell defects. Our findings demonstrate that during chronic HIV infection, B cells are activated and lose full capacity to respond to antigen, but suppression of inhibitory pressures as well as a robust CD4+ T cell response may help preserve B cell function.
The Acute Impact of Ingestion of Sourdough and Whole-Grain Breads on Blood Glucose, Insulin, and Incretins in Overweight and Obese Men

Consumption of whole-grain and sourdough breads is associated with improved glucose homeostasis. We examined the impact of commercial breads on biomarkers of glucose homeostasis in subjects at risk for glucose intolerance. In a randomized, crossover study, overweight or obese males ingested 11-grain, sprouted-grain, 12-grain, sourdough, or white bread on different occasions, matched for available carbohydrate (50 g) in part 1 (n = 12) and bread mass (107 g) in part 2 (n = 11), and blood glucose, insulin and glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) were determined for 3 h. In part 1, glucose response for sprouted-grain was lower than 11-grain, sourdough, and white breads. Insulin area under the curve (AUC) for sourdough and white was lower than 11-grain and sprouted-grain breads. GLP-1 response to sourdough was lower than all breads. In part 2, glucose and insulin AUC for sourdough was greater than 11-grain, sprouted-grain, and 12-grain breads. Sprouted-grain bread improved glycemia by lowering glucose response and increasing GLP-1 response. In overweight and obese men, the glycemic response to sprouted grain bread was reduced in both parts 1 and 2 while the other whole-grain test breads did not improve metabolic responses in the acute postprandial state.
A MATLAB toolbox for Hyperspectral Image Analysis

The Hyperspectral Image Analysis (HIA) toolbox is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIA Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. The HIA toolbox has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. The HIA toolbox provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years
Comparison of weighted-average and median filters for wireless retransmission timeout estimation

Estimation of retransmission timeout (RTO) in TCP networks is important in order to maximize throughput. If the RTO is too small, packets will be unnecessarily declared lost, thus resulting in a retransmission. If RTO is too large, applications will wait too long before declaring a packet to be lost, thus reducing throughput. The conventional method due to Karn and Jacobson for estimating RTO is using a smoothing filter, and this was later refined to utilize mean deviation measurements. In wireless links, the delay can often be impulsive, and weighted-average filters perform poorly. This paper presents results for mobile wireless transmission, and investigates the use of a median filter for timeout estimation in the presence of competing traffic flows. We demonstrate the applicability of this approach to estimating TCP round-trip times, and UDP packet jitter.
Simple Subpopulation Schemes

This paper considers a new method for maintaining diversity by creating subpopulations in a standard generational evolutionary algorithm. Unlike other methods, it replaces the concept of distance between individuals with tag bits that identify the subpopulation to which an individual belongs. Two variations of this method are presented, illustrating the feasibility of this approach.
Vegetation Cover Changes in Ngorongoro Conservation Area from 1975 to 2000: The Importance of Remote Sensing Images

Ngorongoro conservation area is a multiple land-use system established in 1959 to provide for both wildlife conservation and economic development of resident Maasai pastoralists. A study was conducted by analyzing remote sensing images (Landsat MSS 1975, Landsat TM 1991, and Landsat TM 2000) in order to determine trends in vegetation cover changes between 1975 and 2000. The results indicates that major changes in the study area from 1970 to 2000 involved increase in woody vegetation cover types including forest (+ 48.7%), bush land (+42.7%); and loss of scrubland (-29.1%) and grasslands (-37.0%). Other changes involved invasion of highland grassland by unpalatable grass species (-34.4%). The period covered was associated with restrictive conservation policies that disrupted traditional pastoral mobility restricting large herds of livestock on highland areas that induced range deterioration. It is concluded that pastoral land use system has preserved the savanna landscape in Ngorongoro area whereas land-use policies that disrupts traditional pastoral land use systems threaten a breakdown of savanna ecosystem that supports a tourism industry in the area.
On Shift Register Realization of Sequential Circuits II

This is the second of a series of intended reports on realization of sequential machines with shift registers and on properties of shift registers. Some of the pathological cases for the shift register realization algorithms SRR/GSRR reported in the previous report are investigated here. One of the pathological cases turned out to be simple cycles, and based on the work of Yoeli, an algorithm has been developed for finding a shift register code for them. Another case is simple cycles with one chord. It is shown that they can be realized with a shift register if their length n is a power of 2, and the cycle determined by their chord is of length n/4 or less, or equal to n/2. Also the realizability of sequential machines with bidirectional shift registers is studied. A necessary and sufficient condition has been found for the case when the number of states is a power of 2.
First Draft: September 1996 This Draft: November 1996 POLITICAL CONSENSUS, UNCERTAIN PREFERENCES AND CENTRAL BANK INDEPENDENCE

This paper examines the robustness of institutional solutions to the credibility problem where there is no consensus about the relative costs of inflation and stabilisation policy. Models where monetary policy is delegated to an independent central b nk using contracts or targets assume that the preferences of the principal and the agent are known with certainty. However, if there are polarised views in society about the relative costs of inflation, the delegation solution may not produce a better outcome for the median voter. We also examine the related issue of whether political parties have an interest in moving towards central bank independence. JEL Codes: E52, E58, E63 Daniel Jack Professor of Political Economy, Department of Political Economy, University of Glasgow Adam Smith Building Glasgow G12 8RT e-mail: V.Muscatelli@udcf.gla. ac.uk Tel: +44 141 330 5062 +44 141 330 4618 Fax: +44 141 300 4940 (*) This paper is a further development of issues discussed in Muscatelli (1995), which was presented at workshops in Warwick, Oxford, Glasgow and Bari. I am indebted to Ali Al-Nowaihi, Tony Courakis, Martin Cripps, Robin Cubitt, Julia Darby, John Driffill, James Forder, Berthold Herrendorf, Haizhou Huang, Stan Hurn, Mervyn King, Paul Levine, Ben Lockwood, Jim Malley, Marcus Miller, Charles Nolan, Apostolis Philippopoulos, Neil Rankin, Eric Schaling, Andrew Stevenson, Lars Svensson, Yanis Varoufakis, Carl Walsh and Tony Yates for extremely useful comments on this earlier material which helped to shape the ideas in this paper. The usual disclaimer applies.
Artificial neural network ensembles and their application in pooled flood frequency analysis

Recent theoretical and empirical studies show that the generalization ability of artificial neural networks can be improved by combining several artificial neural networks in redundant ensembles. In this paper, a review is given of popular ensemble methods. Six approaches for creating artificial neural network ensembles are applied in pooled flood frequency analysis for estimating the index flood and the 10‐year flood quantile. The results show that artificial neural network ensembles generate improved flood estimates and are less sensitive to the choice of initial parameters when compared with a single artificial neural network. Factors that may affect the generalization of an artificial neural network ensemble are analyzed. In terms of the methods for creating ensemble members, the model diversity introduced by varying the initial conditions of the base artificial neural networks to reduce the prediction error is comparable with more sophisticated methods, such as bagging and boosting. When the same method for creating ensemble members is used, combining member networks using stacking is generally better than using simple averaging. An ensemble size of at least 10 artificial neural networks is suggested to achieve sufficient generalization ability. In comparison with parametric regression methods, properly designed artificial neural network ensembles can significantly reduce the prediction error.
Reputation Guided Genetic Scheduling Algorithm for Independent Tasks in Inter-clouds Environments

Evolutionary computing offers different methods to solve NP-hard problems, finding a near-optimal solution. Task scheduling is a complex problem for large environments like Clouds. Genetic algorithms are a good method to find a solution for this problem considering multi-criteria constrains. This is also a method used for optimization. In these type of environments service providers want to increase the profit and the customers (end-users) want to minimize the costs. So, its all about money and we have minimum two optimization constrains. On the other hand, a good technique to ensure the QoS is to use the reputation of resources offered. This aspect is very important for service providers because represents a ranking method for them. We present in this paper a reputation guided genetic scheduling algorithm for independent tasks in inter-Clouds environments. The reputation is considered in the selection phase of genetic algorithm as an evolutionary criteria for the algorithm. We evaluate the proposed solution considering load-balancing as a way to measure the optimization impact for providers and maxspan as a metric for user performance.
Comparative Analysis of Traditional and Object-Oriented Software Testing

Software testing is an important phase of the software development life cycle. Testing is the process of executing the program with the goal of finding errors. The purpose of testing is not only to find the bugs in software but also to improve the quality of software. This paper compares traditional and object-oriented software testing. Today, object-oriented concepts are used throughout software engineering. Testing of object-oriented software is different from testing of traditional software. Object-oriented software testing offers new challenges to the software testing team, because the object-oriented approach supports several new and powerful features. This paper focuses on the need for adopting an object-oriented software-testing approach and the challenges that occur in object-oriented testing.
Some New Results on Cordial Labeling in the Context of Arbitrary Supersubdivision of Graph

In this paper we discuss cordial labeling in the context of arbitrary supersubdivision of graph. We prove that the graphs obtained by arbitrary supersubdivision of path as well as star admit cordial labeling. In addition to this we prove that the graph obtained by arbitrary supersubdivision of cycle is cordial except when n and all mi are simultaneously odd numbers. Mathematics Subject Classiflcation: 05C78