Miracle-dz/UniFAR-FTUs huggingface dataset:
Denial of Service Attack Detection using Multivariate Correlation Analysis

Denial of Service (DoS)/ DDoS attack is a common and severe problem for network security researchers and practitioners. Attackers often generate attack traffic that behaves similar to normal network traffic using sophisticated attacking tools. Many intrusion detection systems fail to detect anomalous packets in real time. In this paper, we use a Multivariate Correlation Analysis (MCA) approach to distinguish attack traffic from normal traffic. This statistical measure is used to analyze the behavior of network traffic for attack detection. Since DDoS attack traffic behaves differently from legitimate network traffic, statistical properties of various parameters reflect the changed behavior of network traffic. We extract three basic parameters of network traffic, viz., entropy of source IPs, variation of source IPs and packet rate to analyze the behavior of network traffic during attack detection. The method is validated using several benchmark datasets.
The Hiccup: a dynamical coupling process during the autumn transition in the Northern Hemisphere - similarities and differences to sudden stratospheric warmings

Abstract. Sudden stratospheric warmings (SSWs) are the most prominent vertical coupling process in the middle atmosphere, which occur during winter and are caused by the interaction of planetary waves (PWs) with the zonal mean flow. Vertical coupling has also been identified during the equinox transitions, and is similarly associated with PWs. We argue that there is a characteristic aspect of the autumn transition in northern high latitudes, which we call the "hiccup", and which acts like a "mini SSW", i.e. like a small minor warming. We study the average characteristics of the hiccup based on a superimposed epoch analysis using a nudged version of the Canadian Middle Atmosphere Model, representing 30 years of historical data. Hiccups can be identified in about half the years studied. The mesospheric zonal wind results are compared to radar observations over Andenes (69° N, 16° E) for the years 2000–2013. A comparison of the average characteristics of hiccups and SSWs shows both similarities and differences between the two vertical coupling processes.
Generic rules for logic representation transformations

Programs expressed using logic representations can be more easily analysed and transformed. Transformations will depend on the target language semantics. A field encapsulation refactorization will be different for a Java program and an Eiffel program. Logic based representations of programs and its metamodel allows writing generic rules capable of performing some language independent transformations like: syntactical and semantical checking, searching specific nodes, cloning node structures, replacing references, generating fact visualizations. An example is given in this sense related to the implementation of feature body exheritance mechanism of reverse inheritance class relationship in the context of Eiffel language.
DNA Replication Stress Is a Determinant of Chronological Lifespan in Budding Yeast

The chronological lifespan of eukaryotic organisms is extended by the mutational inactivation of conserved growth-signaling pathways that regulate progression into and through the cell cycle. Here we show that in the budding yeast S. cerevisiae, these and other lifespan-extending conditions, including caloric restriction and osmotic stress, increase the efficiency with which nutrient-depleted cells establish or maintain a cell cycle arrest in G1. Proteins required for efficient G1 arrest and longevity when nutrients are limiting include the DNA replication stress response proteins Mec1 and Rad53. Ectopic expression of CLN3 encoding a G1 cyclin downregulated during nutrient depletion increases the frequency with which nutrient depleted cells arrest growth in S phase instead of G1. Ectopic expression of CLN3 also shortens chronological lifespan in concert with age-dependent increases in genome instability and apoptosis. These findings indicate that replication stress is an important determinant of chronological lifespan in budding yeast. Protection from replication stress by growth-inhibitory effects of caloric restriction, osmotic and other stresses may contribute to hormesis effects on lifespan. Replication stress also likely impacts the longevity of higher eukaryotes, including humans.
Vector quantization by companding a union of Z-lattices

An encoding scheme is presented based on random coding theory in conjunction with companding techniques. This combination provides an easy design, and a low-storage quantizer. The groundwork of the study is Gaussian sources. The motivation is the attractive properties of Gaussian and Gaussian mixtures (GMs), and their applications in data compression. Here, codebooks are generated by companding a union of randomly translated cubic lattices. The compander functions operate scalar wise, providing an affordable encoding complexity that is rate independent. For such a codebook, an optimal search, and the indexing of the codevectors are addressed. Performance close to finite-dimensional random coding is achieved, while the complexity is not far from scalar coding. The structure of the codebook balances between complexity and performance. In comparison to some other methods, the advantage of the proposed scheme is more distinct for correlated sources.
Survey on Application of Geostatistical Methods for Estimation of Rainfall in Arid and Semiarid Regions in South West Of Iran

Estimation of rainfall data is necessary in many natural resources and agricultural studies. There are several methods to estimate rainfall along which interpolation are useful in this regards. In this research, three interpolation methods were used to estimate monthly and annual rainfall. These methods are: thin plate smoothing splines (TPSS), with and without co-variable (TPSS-CO), weighted moving average (WMA), and kriging (ordinary, cokriging and logkriging). The data of 167 climatic stations in south west of Iran with 22 years records were used in this study. Based on elevation, the studied area was divided into sub catchments. In the cases which a few stations exist in the catchments or regression coefficient between elevation and rainfall for two sites was the same, those two sub catchments was combined. Finally, 3 sub regions were used for analysis. Regression coefficient between rainfall and elevation was low in one of the sub catchments (R=0.12) and in two others was better (0.72 and 0.82). In general, for monthly data, this coefficient was less than 0.5. These results show that the regression coefficient between rainfall and elevation must be grater than 0.6 in order to improve interpolation accuracy using elevation as co variable. These results also show that TPSS with elevation as co-variable is the most precise method to estimate annual rainfall (MAE=13-38 mm). TPSS with power of 2 was the most precise method to estimate monthly (MAE=1.1 to 20.2 mm) and annual rainfall (MAE=13-38) mm. INTRODUCTION Knowledge about the rainfall is essential for environmental projects, and policymakers in such activities as pattern and trend analysis of rainfall, and monitor network design. According to Boughton (1981), there are two main source of possible error in the estimation of aerial catchment rainfall, the measurement of point samples and extrapolation /interpolation from point to aerial rainfall. Rainfall variability is a major factor limiting the accuracy of rainfall runoff models. Errors may be additive because of the compounding effects of measurement deficiencies due to wind, and biased because of location of gauges at lower elevations leading to underestimating catchment rainfall in hilly or mountainous terrain (Boughton, 1981). Aerial estimates of rainfall based on point measurements should be regarded, as an index of the true mean rainfall over a catchement and errors between 10 to 20 percent can be considered as normal. Where strong wind effects or mountainous catchements are being considered, errors up to 60 percent can be experienced (Hall and Barklay, 1975).
Estimating Annual Average Daily Bicyclists

Cities around the United States are investing in bicycle infrastructure, and to secure additional transportation funding, cities are reporting bicycle use and safety improvements. Data on bicyclist traffic volume is necessary for performing safety studies and reporting facility use. Meeting the need for data, available manual bicycle counting programs count cyclists for a few hours per year at designated locations. A key issue in the design of counting programs is determining the timing and frequency of counts needed to obtain a reliable estimate of annual average daily bicyclists (AADB). In particular, in which days of the week, hours of the day, and months of the year should counts be collected? And, most important to program cost, how many hours should be counted? This study used continuous bicycle counts from Boulder, Colorado, to estimate AADB and analyze the estimation errors that would be expected from various bicycle-counting scenarios. AADB average estimation errors were found to range from 15% with 4 weeks of continuous count data to 54% when only 1 h of data was collected per year. The study found that the most cost-effective length for short-term bicycle counts is one full week when automated counting devices specifically calibrated for bicycle counting are used. Seasons with higher bicycle volumes have less variation in bicycle counts and thus more accurate estimates.
Bank Indonesia and the Crisis: An Insider's View

Written by a major public figure and player in the events, this important book documents and evaluates a turning point in the political and economic history of Southeast Asia's most populous country, Indonesia. Controversial issues such as the infamous bank closures are analysed, and there is a wealth of detail on a range of topics during this turbulent period in Indonesia's recent history. This book contains a vast amount of original and valuable material, including the workings of the International Monetary Fund (IMF) at a critical juncture. It also details the various domestic responses to the crisis against the swift and ferocious behaviour of the international markets. Part autobiography and part treatise, this volume candidly examines the Bank Indonesia crisis and has important lessons and insights into the way the economy was managed in the last years of the Soeharto era. A must-read for economists, government analysts and scholars of Southeast Asia and Indonesia in particular which is destined to itself generate much more debate about the events of that period.
Introducing tempest, a modular platform for in situ data collection

In this paper we present Tempest, a tool for conducting studies that rely on in situ data collection, such as the Experience Sampling and Diary methods. It implements a modular architecture and relies on interchangeable parts to allow for increased suitability for multiple purposes and long-term reliability. Tempest focuses on ease of use and deployment, and on making use of participants' own devices.
The 26th International Conference on Computational Linguistics (COLING 2016) Sixth Workshop on Hybrid Approaches to Translation

fast align is a simple and fast word alignment tool which is widely used in state-of-the-art machine translation systems. It yields comparable results in the end-to-end translation experiments of various language pairs. However, fast align does not perform as well as GIZA++ when applied to language pairs with distinct word orders, like English and Japanese. In this paper, given the lexical translation table output by fast align, we propose to realign words using the hierarchical sub-sentential alignment approach. Experimental results show that simple additional processing improves the performance of word alignment, which is measured by counting alignment matches in comparison with fast align. We also report the result of final machine translation in both English-Japanese and Japanese-English. We show our best system provided significant improvements over the baseline as measured by BLEU and RIBES.
Ancestry and diversity of the HMG box superfamily.

The HMG box is a novel type of DNA-binding domain found in a diverse group of proteins. The HMG box superfamily comprises a.o. the High Mobility Group proteins HMG1 and HMG2, the nucleolar transcription factor UBF, the lymphoid transcription factors TCF-1 and LEF-1, the fungal mating-type genes mat-Mc and MATA1, and the mammalian sex-determining gene SRY. The superfamily dates back to at least 1,000 million years ago, as its members appear in animals, plants and yeast. Alignment of all known HMG boxes defined an unusually loose consensus sequence. We constructed phylogenetic trees connecting the members of the HMG box superfamily in order to understand their evolution. This analysis led us to distinguish two subfamilies: one comprising proteins with a single sequence-specific HMG box, the other encompassing relatively non sequence-specific DNA-binding proteins with multiple HMG boxes. By studying the extent of diversification of the superfamily, we found that the speed of evolution was very different within the various groups of HMG-box containing factors. Comparison of the evolution of the two boxes of ABF2 and of mtTF1 implied different diversification models for these two proteins. Finally, we provide a tree for the highly complex group of SRY-like ('Sox' genes), clustering at least 40 different loci that rapidly diverged in various animal lineages.
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees

The C-bound, introduced in Lacasse et al. [2006], gives a tight upper bound on the risk of the majority vote classifier. Laviolette et al. [2011] designed a learning algorithm named MinCq that outputs a dense distribution on a finite set of base classifiers by minimizing the C-bound, together with a PACBayesian generalization guarantee. In this work, we design a column generation algorithm that we call CqBoost, that optimizes the C-bound and outputs a sparse distribution on a possibly infinite set of voters. We also propose a PAC-Bayesian bound for CqBoost that holds for finite and two cases of continuous sets of base classifiers. Finally, we compare the accuracy and the sparsity of CqBoost with MinCq and other state-of-the-art boosting algorithms.
Sex-Specific Effects of Chronic Fluoxetine Treatment on Neuroplasticity and Pharmacokinetics in Mice

Neurogenesis is a mechanism through which antidepressants may produce therapeutic effects. There is a dearth of information regarding the effects of antidepressants on neurogenesis and neurotrophin mobilization in females. This study examined sex differences in the alteration of cell proliferation and survival in multiple regions of the brain. Additional experiments examined brain-derived neurotrophic factor (BDNF) levels and pharmacokinetics of fluoxetine to determine whether they mediate sex differences. MRL/MpJ mice were treated with fluoxetine (5 and 10 mg/kg b.i.d.) for 21 days and received injections of 5-bromo-2′-deoxyuridine (200 mg/kg) to measure DNA synthesis. In the hippocampus, fluoxetine increased cell proliferation at both doses; females treated with 10 mg/kg produced more new cells than males. Fluoxetine did not alter survival in males, but 10 mg/kg reduced survival in females. In the frontal cortex, fluoxetine increased cell proliferation and survival in males treated with 10 mg/kg. In the cerebellum and amygdala, 10 mg/kg fluoxetine increased cell proliferation in both sexes but did not alter the incorporation of the new cells. Fluoxetine increased BDNF levels in the hippocampus of both sexes. BDNF levels correlated with cell proliferation in males but not females. Brain and plasma levels indicated that females metabolized fluoxetine faster than males and produced more of the metabolite norfluoxetine. These data suggest that fluoxetine acts on multiple areas of the brain to increase cell proliferation, and the pattern of activation differs between males and females. Sex-specific effects of fluoxetine on neurotrophin mobilization and pharmacokinetics may contribute to these differences in neural plasticity.
Predicting maize phenology: intercomparison of functions for developmental response to temperature

Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26 degrees C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range.
Constructing the composite indicator "quality of work" from the third European survey on working conditions

The composite indicator "Quality of work" for comparing European countries is con- structed from data of the Third European Survey on Working Conditions. The main findings are as follows: (a) European countries differ with respect to working conditions statistically more significantly than with respect to earnings; it implies a quite accurate discrimination threshold in ranking countries with respect to quality of work, (b) working conditions and earnings positively depend over the whole of Europe but little correlate within single countries; it indicates at the prevailing role of national determinants over professional or social specificities as contributing to the average quality of work, (c) earnings play no role in subjective satisfaction from work which exclusively depends on working conditions; consequently, more attention should be paid to improving the latter, (d) working conditions of women are significantly better than that of men, which is explained by their inclination to service occupations. Processing ordinal rather than metrical data requires an addendum to the methodology of composite indicators. The corresponding mathematical model is proposed.
Human information behaviour and design, development and evaluation of information retrieval systems

Purpose – The purpose of this paper is to introduce the concept of human information behaviour and to explore the relationship between information behaviour of users and the existing approaches dominating design and evaluation of information retrieval (IR) systems and also to describe briefly new design and evaluation methods in which extensive attention is dedicated to the users and their behaviours and conditions.Design/methodology/approach – The paper takes the form of a literature review with particular concentration on the efforts made by information science researchers.Findings – The paper finds that there are four classic approaches to IR systems design: system‐centred, user‐centred, interactive and cognitive. Not enough research has been carried out to explore the relationship between information behaviour and information systems design to date. Contextual design and participatory design are among the new methods where users' behaviour, factors and contexts are considered more proactively than pre.
Mining Billion-Scale Graphs : Patterns and Algorithms

Graphs are everywhere: social networks, the World Wide Web, biological networks, and many more. The sizes of graphs are growing at unprecedented rate, spanning millions and billions of nodes and edges. What are the patterns in large graphs, spanning Giga, Tera, and heading toward Peta bytes? What are the best tools, and how can they help us solve graph mining problems? How do we scale up algorithms for handling graphs with billions of nodes and edges? These are exactly the goals of this tutorial. We start with the patterns in real-world static, weighted, and dynamic graphs. Then we describe important tools for large graph mining, including singular value decomposition, and Hadoop. Finally, we conclude with the design and the implementation of scalable graph mining algorithms on Hadoop. This tutorial is complementary to the related tutorial ”Managing and Mining Large Graphs: Systems and Implementations”.
The Money Demand Behaviour in Bangladesh, 1973-2003: An Application of the Cointegration and Error-Correction Methods

By applying the methods of cointegration and error-correction, this paper investigates the money demand behaviour in Bangladesh with annual data for the period 1973 to 2003. The empirical results suggest that real money balances (narrow or broad), real permanent income and the deposit rate of interest formed a cointegral relationship for the sample period of study. The dynamic money demand behaviour has been investigated by estimating an error-correction model within a general-to-specific modelling framework. The preferred error-correction model has been found stable. Having identified a stable money demand function, the paper has examined whether there was any structural break in the long-run money demand function during the sample period of study. For this purpose, the Quandt Likelihood Ratio test has been conducted for the period 1982 to 1993 when most financial deregulation and reform measures were undertaken. The test results suggest that there was a structural break in the narrow money demand relationship in 1987 and that there was a structural break in the broad money demand relationship in 1983.
Continuous Target Shift Adaptation in Supervised Learning

Supervised learning in machine learning concerns inferring an underlying relation between covariate x and target y based on training covariate-target data. It is traditionally assumed that training data and test data, on which the generalization performance of a learning algorithm is measured, follow the same probability distribution. However, this standard assumption is often violated in many real-world applications such as computer vision, natural language processing, robot control, or survey design, due to intrinsic non-stationarity of the environment or inevitable sample selection bias. This situation is called dataset shift and has attracted a great deal of attention recently. In the paper, we consider supervised learning problems under the target shift scenario, where the target marginal distribution p(y) changes between the training and testing phases, while the target-conditioned covariate distribution p(x|y) remains unchanged. Although various methods for mitigating target shift in classification (a.k.a. class prior change) have been developed so far, few methods can be applied to continuous targets. In this paper, we propose methods for continuous target shift adaptation in regression and conditional density estimation. More specifically, our contribution is a novel importance weight estimator for continuous targets. Through experiments, the usefulness of the proposed method is demonstrated.