Miracle-dz/UniFAR-FTUs huggingface dataset:
Throughput analysis for TCP NewReno

Today's Internet suffers from a very complex problem-congestion. It is one of the top-ten listed fundamentally important problems in networking. It causes many important data to be lost. Wastage of network resources results from this. It makes the network easily become gridlocked, with little or no data being transported end-to-end. To protect data transfer from this problem various models of TCP are proposed. These variants differ from each other based on the congestion control algorithm and segment loss recovery techniques they use. One of the techniques is TCP NewReno. In this paper throughput analysis of a simple stochastic model for TCP NewReno is described as a mathematical relation of time that it takes for a signal to be sent plus the length of time it takes for an acknowledgment of that signal to be received and also loss behavior which is based on some previous work done over TCP Reno. It has dissimilarity in three characteristics: model for fast recovery, formulation of timeout behavior, and use of loss event. Here a two-parameter loss model is used that can better represent the diverse packet loss framework encountered by TCP on the Internet. The significant performance advantages of TCP NewReno over TCP Reno are shown using the ns-2 simulator. This performance evaluation is considered in case of two queue management mechanisms-DropTail and RED. The main outcomes from the experiments are: 1) In a wide range of network conditions for TCP NewReno there is an analysis of proposed model which can exactly forecast the stable state throughput 2) At the time of congestion TCP NewReno perform better than the Reno and 3) The packet loss against time during data transmission suffers from less loss rate than the existing Reno model.
Context Free Frequently Asked Questions Detection Using Machine Learning Techniques

FAQs are the lists of common questions and answers on particular topics. Today one can find them in almost all web sites on the internet and they can be a great tool to give information to the users. Questions in FAQs are usually identified by the site administrators on the basis of the questions that are asked by their users. While such questions can respond to required information about a service, topic, or particular subject, they can not easily be distinguished from non-FAQ questions. This paper describes machine learning based parsing and question classification for FAQs. We demonstrate that questions for FAQs can be distinguished from other types of questions. Identification of specific features is the key to obtaining an accurate FAQ classifier. We propose a simple yet effective feature set including bag of words, lexical, syntactical, and semantic features. To evaluate our proposed methods, we gathered a large data set of FAQs in three different contexts, which were labeled by humans from real data. We showed that the SVM and Naive Bayes reach the accuracy of 80.3%, which is an outstanding result for the early stage research on FAQ classification. Experimental results show that the proposed approach can be a practical tool for question answering systems. To evaluate the accuracy of our classifier we have conducted an evaluation process and built the questionnaire. Therefore, we compared our classifier ranked questions with user rates and almost 81% similarity of the question ratings gives some confidence.
Software Safety Engineering Education

This paper describes the Software Safety Engineering Process utilized by students enrolled in the University of Alabama in Huntsville's Software Safety Engineering course. The process consists of an industrystandard software engineering development process augmented to produce the safety-related artifacts as required for certification of a safety-critical product by a regulatory agency. The additional artifacts include Functional Hazard Assessments, Fault Tree Analyses, and Failure Modes and Effects Analyses. Students learn the impact of these new artifacts on the traditional development process as they follow our software safety engineering process to implement a representative safety-critical system, a model railroad controller.
The impact of cross-functional teams on operational performance after the implementation of intelligent information systems

This study examines cross-functional teams and their impact in line with operational performance and system effectiveness after the implementation of intelligent information and retrieval systems in organisations. Multiple regression analysis was used to determine the structural relationships and look for the phenomenon of cross-functional teams, operational effectiveness, and system effectiveness in the betterment of operational performance. Preliminary findings suggest that the quality and speed from operational effectiveness and the quality of information and quality of the services from systems effectiveness are the two key factors for cross-functional teams to enhance operational performance.
J an 2 00 6 Absolute – Magnitude Distributions and Light Curves of Stripped – Envelope

The absolute visual magnitudes of three Type IIb, 11 Type Ib and 13 Type Ic supernovae (collectively known as stripped–envelope supernovae) are studied by collecting data on the apparent magnitude, distance, and interstellar extinction of each event. Weighted and unweighted mean absolute magnitudes of the combined sample as well as various subsets of the sample are reported. The limited sample size and the considerable uncertainties, especially those associated with extinction in the host galaxies, prevent firm conclusions regarding differences between the absolute magnitudes of supernovae of Type Ib and Ic, and regarding the existence of separate groups of overluminous and normal-luminosity stripped–envelope supernovae. The spectroscopic characteristics of the events of the sample are considered. Three of the four overluminous events are known to have had unusual spectra. Most but not all of the normal luminosity events had typical spectra. Light curves of stripped–envelope supernovae are collected and compared. Because SN 1994I in M51 was very well observed it often is regarded as the prototypical Type Ic supernova, but it has the fastest light curve in the sample. Light curves are modeled by means of a simple analytical technique that, combined with a constraint on E/M from spectroscopy, yields internally consistent values of ejected mass, kinetic energy, and nickel mass. Subject headings: supernovae: individual
Encapsulation and composition as orthogonal operators on mixins: a solution to multiple inheritance problems

In class-based multiple inheritance systems, interpretations as different as duplication, sharing and specialization are associated with the single phenomenon of name collisions. To deal with those name collisions, various mechanisms have been proposed, but these solutions generally restrain software reusability which is considered to be one of the key features of OO systems. On top of this, most multiple inheritance systems do not completely cover all the different interpretations of name collisions. This paper shows that the entire multiple inheritance dilemma can and should be seen as a conﬂict between inheritance and data encapsulation only. Orthogonalizing these two concepts in a mixin-based framework permits appropriate solutions of all the problems listed above. To this extent a formal model is proposed together with its denotational semantics. This minimal multiple inheritance model establishes a valuable basis for OO languages and software engineering systems.
Clinicopathological correlation of polypoidal choroidal vasculopathy revealed by ultrastructural study

Aims: To describe the clinical and histopathological findings in a patient with polypoidal choroidal vasculopathy. Methods: A 76 year old Japanese man had a discrete, orange-red lesion of 1 disc diameter in the macula, with the fluorescein and indocyanine green angiographic and optical coherence tomographic findings compatible with polypoidal choroidal vasculopathy. He underwent a surgical removal of the macular lesion, followed by light and electron microscopic examinations. Results: The histopathological examination revealed that the specimen consisted of degenerated retinal pigment epithelium-Bruch’s membrane-choriocapillaris complex and inner choroid. A tortuous, unusually dilated venule was present adjacent to an arteriole with marked sclerotic changes, appearing to form arteriovenous crossing. These vessels seemed to represent native inner choroidal vessels, and had haemorrhage per diapedesis. Blood cells and fibrin filled the lumina of the vessels and accumulated in the extravascular spaces, indicating vascular stasis. Conclusion: Hyperpermeability and haemorrhage due to stasis of a dilated venule and an arteriole involved by sclerosis at the site where they cross in the inner choroid might cause oedema and degeneration of the tissue. Voluminous accumulation of blood cells and fibrin might generate elevation of tissue pressure sufficient to displace the weakened lesion anteriorly. The result suggests that the polypoidal vessels in this case represent abnormality in the inner choroidal vasculature.
Using Ontologies to Build Testbed for Peer-to-Peer Information Retrieval Systems

A branch of Distributed Information Retrieval(DIR) is Peer-to-Peer Information Retrieval (P2PIR). Peer-to-Peer (P2P) networks are a recently evolved paradigm for distributed computing and many researchers are developing new algorithms for such systems. Evaluate algorithms performance, in a P2P network, is already a challenging task caused by the lack of realistic test beds. The construction of standard test beds to evaluate search approaches and to compare them is a major open problem. Indeed, the poverty of documents and queries representation, in test bed, limits retrieval opportunities. This study addresses the lack of an adequate test bed that can be used to evaluate peer-to-peer information retrieval approaches. In particular, we propose, in this paper, a test bed based on an already existing test bedand on a semantic resource enrichment.
Development of aggression and impulsivity: modulation by adolescent social stress?

Psychische problemen hebben een grote invloed op het leven van miljoenen mensen. Negatieve ervaringen in de vroege jeugd zijn van invloed op de ontwikkeling van psychopathologie later in het leven. Het onderzoek heeft zich daarbij vooral gericht op de ontwikkeling van depressie en angststoornissen. De invloed van sociale stress in de jeugd op anti-sociale persoonlijkheidsstoornissen en excessief agressief gedrag is veel minder onderzocht. Attentieproblemen en impulsiviteit zijn persoonlijkheidseigenschappen die bijdragen aan de overgang van agressie in geweld. Deze eigenschappen zijn gerelateerd aan een slecht functionerende prefrontale cortex. De prefrontale cortex ondergaat tijdens de adolescentie grote veranderingen. Verstoring van deze ontwikkeling door blootstelling aan sociale stress zou een sleutelrol kunnen spelen in de ontwikkeling van gewelddadig gedrag. Het doel van dit onderzoek was om bij de rat de interactie tussen persoonlijkheid en sociale omgeving tijdens de adolescentie op het volwassen sociale gedrag te bestuderen. De studies tonen aan dat adolescent sociaal verlies leidt tot neurobiologische veranderingen in de prefrontale cortex en tot een verstoring van de ontwikkeling van agressief en impulsief gedrag. Impulsiviteit blijkt tevens een belangrijke factor te zijn bij het ontstaan van geweld. De studies ondersteunen de idee dat sociale stress in de adolescentie fase sommige individuen vatbaarder maakt voor het ontwikkelen van psychopathologie. Daarnaast blijkt echter dat andere individuen het juist beter doen onder stressvolle condities na een eerdere ervaring met sociale stress. Het is daarom van belang om niet alleen naar psychopathologie als gevolg van stress te kijken, maar ook naar de vraag welke individuen juist weerbaarder worden en onder welke omstandigheden dit het geval is.
Ghost Domain Names: Revoked Yet Still Resolvable

Attackers often use domain names for various malicious purposes such as phishing, botnet command and control, and malware propagation. An obvious strategy for preventing these activities is deleting the malicious domain from the upper level DNS servers. In this paper, we show that this is insufficient. We demonstrate a vulnerability affecting the large majority of popular DNS implementations which allows a malicious domain name to stay resolvable long after it has been removed from the upper level servers. Our experiments with 19,045 open DNS servers show that even one week after a domain name has been revoked and its TTL expired, more than 70% of the servers will still resolve it. Finally, we discuss several strategies to prevent this attack.
Automatic Movie Summarization Based on the Visual-Audio Features

Automatic movie summarization based on the visual-audio features is introduced. The importance evaluation model for video clips chooses face detection and atwitter shot detection as the basis. Against the difficult of movie's speech endpoint detection, speech endpoint detection based on subtitles of movie is introduced, which can help detect the captions' start or end time exactly. Compared with other summarization algorithm, the introduced algorithm is suitable for movie summarization.
Cholesterol Levels and Risk of Hemorrhagic Stroke: A Systematic Review and Meta-Analysis

Background and Purpose— Cholesterol levels are inconsistently associated with the risk of hemorrhagic stroke. The purpose of this study is to assess their relationships using a meta-analytic approach. Methods— We searched PubMed and Embase for pertinent articles published in English. Only prospective studies that reported effect estimates with 95% confidential intervals (CIs) of hemorrhagic stroke for ≥3 categories of cholesterol levels, for high and low comparison, or for per 1 mmol/L increment of cholesterol concentrations were included. We used the random-effects model to pool the study-specific results. Results— Twenty-three prospective studies were included, totaling 1 430 141 participants with 7960 (5.6%) hemorrhagic strokes. In high versus low analysis, the summary relative risk of hemorrhagic stroke was 0.69 (95% CI, 0.59–0.81) for total cholesterol, 0.98 (95% CI, 0.80–1.19) for high-density lipoprotein cholesterol, and 0.62 (95% CI, 0.41–0.92) for low-density lipoprotein cholesterol. In dose–response analysis, the summary relative risk of hemorrhagic stroke for 1 mmol/L increment of total cholesterol was 0.85 (95% CI, 0.80–0.91), for high-density lipoprotein cholesterol was 1.11 (95% CI, 0.99–1.25), and for low-density lipoprotein cholesterol was 0.90 (95% CI, 0.77–1.05). The pooled relative risk for intracerebral hemorrhage was 1.17 (95% CI, 1.02–1.35) for high-density lipoprotein cholesterol. Conclusions— Total cholesterol level is inversely associated with risk of hemorrhagic stroke. Higher level of low-density lipoprotein cholesterol seems to be associated with lower risk of hemorrhagic stroke. High-density lipoprotein cholesterol level seems to be positively associated with risk of intracerebral hemorrhage.
Personalized Spam Filtering with Semi-supervised Classifier Ensemble

The proliferation of unsolicited emails, also known as spam, poses significant burden to email users worldwide. Recent researches on spam filtering have shown that high accuracies can be obtained if labeled emails examples are available from the particular user of the spam filter. However, the time consuming process of providing personalized labeled training examples is often inconvenient or impossible due to privacy issues. In this paper, a semi-supervised personalized spam filter based on classifier ensemble is proposed that classifies user's emails accurately by learning on both generic labeled emails and personalized unlabeled emails. The proposed multi-stage classification process begins learning a SVM model from labeled generic data. Unlabeled user's emails are then fed to this SVM to generate personalized labeled data for constructing personalized naive Bayes classifiers. Furthermore, some personalized labeled examples are generated by exploiting rare word distributions and then fed into a semi-supervised classifier. The multi-stage results are integrated with SVMs learned from generic labeled emails to produce the final classification results. Experimental results show that the proposed approaches can significantly increases the classification accuracy in spam filtering
Risk factors for nephrotoxicity after ifosfamide treatment in children: a UKCCSG Late Effects Group study

The aim of this multicentre study was to document the nephrotoxicity associated with ifosfamide and evaluate risk factors in 148 children and young people with sarcomas who underwent investigation of renal function on one occasion each, at a median of 6 (range 1–47) months after completion of ifosfamide (median dose 62.0 (range 6.1–165.0) g/m2). Investigations included glomerular filtration rate (GFR), serum bicarbonate (HCO3) and phosphate (PO4), and renal tubular threshold for phosphate (Tmp/GFR). A clinically relevant ‘nephrotoxicity score’ was derived. GFR was < 90 ml/min/1.73 m2in 61 of 123 evaluable patients, Tmp/GFR < 0.9–1.1 mmol/l (age-dependent) in 45/103, serum PO4< 0.9–1.mmol/l (age-dependent) in 28/135, and serum HCO3< 20 (< 18 in infants) mmol/l in 22/95. Of 76 fully evaluable patients: 50% had mild, 20% moderate and 8% severe nephrotoxicity. Higher total ifosfamide dose correlated significantly with greater glomerular and tubular toxicity (P< 0.01); other risk factors, including age at treatment, demonstrated no consistent significant independent effect. Chronic ifosfamide-related glomerular and proximal tubular toxicity were common in this large comprehensive study. Restriction of total ifosfamide dose to < 84 g/m2will reduce the frequency of, but not abolish, clinically significant nephrotoxicity, whilst doses > 119 g/m2are associated with a very high risk of severe toxicity. © 2000 Cancer Research Campaign
A pr 2 00 1 LAYER-BY-LAYER GROWTH FOR PULSED LASER DEPOSITION

Pulsed laser deposition (PLD) is a popular growth method, which has been successfully used for fabricating thin films. Compared to continuous deposition (like molecular beam epitaxy) the pulse intensity can be used as an additional parameter for tuning the growth behavior , so that under certain circumstances PLD improves layer-by-layer growth. We present kinetic Monte-Carlo simulations for PLD in the submonolayer regime and give a description of the island distance versus intensity. Furthermore we discuss a theory for second layer nu-cleation and the impact of Ehrlich-Schwoebel barriers on the growth behavior. We find an exact analytical expression for the probability of second layer nucleation during one pulse for high Ehrlich-Schwoebel barriers.
A Robot that Teaches Itself to Clear Clutter

Outdoor robots, such as search-and-rescue robots and planetary rovers, often need to grasp and push objects such as debris and rocks that have irregular shapes. While most object manipulation techniques require mechanical or geometric models of the objects, objects that are encountered in outdoor environments do not typically have any known models. To grasp unknown novel objects, data-driven approaches are becoming increasingly popular. These approaches learn from examples statistical models that predict the success of grasping or pushing actions. The biggest drawback of statistical models is perhaps their inherent inaccuracies, the predicted values are always subject to an error unless the objects used during testing are identical to some of the objects used for training. To solve this issue, we introduce in this article two self-supervisory learning techniques that allow the robot to adapt to new objects by correcting online the predicted values. Using these techniques, we show how a robot can efficiently learn on the fly and in real-time to push and grasp novel objects. We test both techniques on the task of autonomously clearing piles of natural and man-made objects. Abdeslam Boularias Department of Computer Science Rutgers University New Brunswick, NJ 08901 USA E-mail: boularias@gmail.com J. Andrew Bagnell The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 USA Anthony Stentz The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 USA This work was done while all the authors were at the National Robotics Engineering Center of Carnegie Mellon University 2 Abdeslam Boularias et al. The first technique is used for clearing piles wherein grasping actions alone are enough for clearing the pile. The outcomes of the grasping actions are modeled as a Gaussian Process, and an entropy-guided method is used in order to learn where the best grasp is most likely to be found. The second technique is used for tight piles wherein grasping actions alone are not effective, the robot first needs to push obstacles away in a particular way that helps grasping by creating empty space around them to insert the robot’s fingers. We present a reinforcement learning approach that we use for selecting the best sequence of pushing and grasping actions to execute in order to clear a given pile. We also present a perception technique that we used, along with the online adaptation techniques, to build a fully autonomous system. The integrated system is tested on clearing various piles of objects using a Barrett WAM robot.
Functional Genomics of Stress Response in Pseudomonas putida KT2440

ABSTRACT The metabolically versatile soil bacterium Pseudomonas putida has to cope with numerous abiotic stresses in its habitats. The stress responses of P. putida KT2440 to 4°C, pH 4.5, 0.8 M urea, and 45 mM sodium benzoate were analyzed by determining the global mRNA expression profiles and screening for stress-intolerant nonauxotrophic Tn5 transposon mutants. In 392 regulated genes or operons, 36 gene regions were differentially expressed by more than 2.5-fold, and 32 genes in 23 operons were found to be indispensable for growth during exposure to one of the abiotic stresses. The transcriptomes of the responses to urea, benzoate, and 4°C correlated positively with each other but negatively with the transcriptome of the mineral acid response. The CbrAB sensor kinase, the cysteine synthase CysM, PcnB and VacB, which control mRNA stability, and BipA, which exerts transcript-specific translational control, were essential to cope with cold stress. The cyo operon was required to cope with acid stress. A functional PhoP, PtsP, RelA/SpoT modulon, and adhesion protein LapA were necessary for growth in the presence of urea, and the outer membrane proteins OmlA and FepA and the phosphate transporter PstBACS were indispensable for growth in the presence of benzoate. A lipid A acyltransferase (PP0063) was a mandatory component of the stress responses to cold, mineral acid, and benzoate. Adaptation of the membrane barrier, uptake of phosphate, maintenance of the intracellular pH and redox status, and translational control of metabolism are key mechanisms of the response of P. putida to abiotic stresses.