Miracle-dz/UniFAR-FTUs huggingface dataset:
A data correlation method for anomaly detection systems using regression relations

Normal profiles have specific properties which would be changed when an attack occurs. The main property we have considered for each behavior is the correlation between the parameters of it. We compute a correlation matrix for normal sessions in the training phase. Then we select effective security parameters for our detection engine using an equivalent class with a graphical illustration namely Correlation Relation Graph (CRG). These extracted parameters among all parameters of each normal behavior have a relation with each other which could be computed by regression relations. Each behavior has some pairs of selected parameters including the independent parameter and the dependent one. As an inline detection process, we look at the value of selected parameters of each current session and put them into their computed regression relation. If the computed value of the dependent parameter of each pair has a value greater then what we compute by their regression relation, it will be considered as a deviation. Number of deviations per session and the combination of them is used to label a session as normal or attack. The results show that our proposed method has suitable detection rate and false alarm.
VOLATILITY SPILLOVER ACROSS EXCHANGE RATE MARKETS

This paper estimates a model for the transmission of exchange rate volatility from a country to another. The model is based on the assumption that the unmet demand for dollars in a given country may cause individuals to purchase dollars in a neighbor country, thus causing the latter's dollar price in local currency to rise, independently of the situation of its macroeconomic fundamental variables. This phenomenon may eventually lead to spreading a currency crisis from a country to another. The paper presents first, a review of the literature on contagion and volatility spillover effects. Next, a Garch model for Guatemala's black market exchange rate is estimated and the resulting time varying variance is employed as an explanatory variable in a Garch equation that explains El Salvador's exchange rate dynamics. Next, a probit model that explains the occurrence of a currency crisis in El Salvador is estimated, including as explanatory variables the time varying variance of Guatemala's exchange rate, as well as the shocks to its exchange rate. The results indicate that Guatemala's exchan ge rate volatility contributes to the eruption of a currency crisis in El Salvador. The paper ends with a series of conclusions and recommendations.
Computation offloading in wireless multi-hop networks: Energy Minimization via multi-dimensional knapsack problem

Computation offloading is an upcoming approach to increase battery life of mobile devices overburdened by resource-consuming applications. In multi-hop networks, computation offloading poses new challenges since intermediate devices are required to relay tasks of others along the path to the server. The decision of a device about whether to offload or not depends thus on the provided energy of relay devices and on the decisions of other offloading devices since relay resources need to be shared. This also implies that for energy minimization, optimal decisions are topology-dependent. This paper introduces a novel theoretical framework for energy minimization of computation offloading in multi-hop wireless networks which formulates the energy minimization problem as a binary linear problem. Proving its equivalence to a multi-dimensional knapsack problem allows us to specify a greedy heuristic, which shows very good performance, with a maximal deviation of less than 5% from the optimal results. From simulations and analytical results for different topologies, we derive under which conditions computation offloading in multi-hop networks is beneficial.
Private employment agencies in South Africa

This paper, written by Debbie Budlender, presents the findings of a study into the work of private employment agencies in South Africa, focusing on empirical and statistical aspects. The study covers the temporary agency work industry (known as “labour broking” in South Africa) as well as the recruitment and placement of individuals in permanent or temporary employment. It draws attention to the shortcomings regarding data on agency work in South Africa, and provides some reflections on how knowledge on this topic could be improved. It is one of several research studies prepared in 2013 for SECTOR on the impact of the Private Employment Agencies Convention, 1997 (No. 181); the framework for operation of private employment agencies; employment conditions; and treatment as regards such issues as pay, social protection, leave and pensions in selected countries, providing sectoral information as appropriate.
The human factors of computer graphics interaction techniques

An organization of interaction techniques, based on the user tasks for which the techniques are used, is proposed. It is suggested that task requirements limit the set of techniques that can be considered for a particular application. The characteristics of a variety of techniques are enumerated and many of the considerations important to their effectiveness are discussed. Relevant experimental and experiential comparisons are tabulated.
NEDD1-dependent recruitment of the γ-tubulin ring complex to the centrosome is necessary for centriole duplication and spindle assembly

The centrosome is the major microtubule organizing structure in somatic cells. Centrosomal microtubule nucleation depends on the protein gamma-tubulin. In mammals, gamma-tubulin associates with additional proteins into a large complex, the gamma-tubulin ring complex (gammaTuRC). We characterize NEDD1, a centrosomal protein that associates with gammaTuRCs. We show that the majority of gammaTuRCs assemble even after NEDD1 depletion but require NEDD1 for centrosomal targeting. In contrast, NEDD1 can target to the centrosome in the absence of gamma-tubulin. NEDD1-depleted cells show defects in centrosomal microtubule nucleation and form aberrant mitotic spindles with poorly separated poles. Similar spindle defects are obtained by overexpression of a fusion protein of GFP tagged to the carboxy-terminal half of NEDD1, which mediates binding to gammaTuRCs. Further, we show that depletion of NEDD1 inhibits centriole duplication, as does depletion of gamma-tubulin. Our data suggest that centriole duplication requires NEDD1-dependent recruitment of gamma-tubulin to the centrosome.
Transposition-Driven Scheduling in Parallel Two-Player State-Space Search

This thesis describes the design and implementation of a parallel two-player statespace searcher called DARKSIGHT. The program uses principal variation search as its main search algorithm with numerous additional techniques and heuristics. The young-brothers-wait concept is used as the splitting strategy. Transpositiondriven scheduling is used as its load-balancing scheme, which achieved near-linear speedups in parallel one-player state-space search. Our experiments show that transposition-driven scheduling is used successful with performance results that are comparable to those achieved by other parallel two-player state-space searchers. Additionally, we present new experimental results on the deep search behaviour of two-player state-space searchers, and results that indicate that the commonly used constant-sized aspiration windows are not optimal.
Figural After-Effects and Apparent Size

Sutherland (1954) obtained results which suggest that when the retinal size of test and inspection figures is equal, the direction of the FAE may be determined by the relative apparent sizes of the two figures. Other investigators have reproduced this result when exactly the same conditions were used: when the conditions were changed the result was not obtained. In the present paper these results are discussed and an attempt is made to determine why the effect is not obtained with small variations in the experimental conditions. It is further shown that some FAE phenomena cannot be explained by the two main existing theories; these phenomena could be explained if some analysis of the stimulus is being performed before the stage of the nervous system at which the process underlying FAEs occurs. Some recent physiological evidence (Hubel and Wiesel, 1959) supports this hypothesis. If this hypothesis is correct, it is likely that further work on FAEs determined by apparent size may help to throw light on the physiological mechanisms underlying size constancy, and some further experiments are suggested.
Analgesic Effect of Low-dose Intrathecal Morphine after Spinal Fusion in Children

Background This study was designed to assess the postoperative analgesic effect of low-dose intrathecal morphine after scoliosis surgery in children. Methods Thirty children, 9–19 yr of age, scheduled for spinal fusion, were randomly allocated into three groups to receive a single dose of 0 (saline injection), 2, or 5 &mgr;g/kg intrathecal morphine. After surgery, a patient-controlled analgesia device (PCA) provided free access to additional intravenous morphine. Children were monitored for 24 h in the postanesthesia care unit. Results The three groups were similar for age, weight, duration of surgery, and time to extubation. The time to first PCA demand was dose-dependently delayed by intrathecal morphine. The first 24 h of PCA morphine consumption was 49 ± 17, 19 ± 10, and 12 ± 12 mg (mean ± SD) in the saline, 2 &mgr;g/kg morphine, and 5 &mgr;g/kg morphine groups, respectively. Pain scores at rest were significantly lower over the whole study period after 2 and 5 &mgr;g/kg intrathecal morphine than after saline, but there was no difference between intrathecal doses. Pain scores while coughing and the incidence of side effects were similar in the three groups. Conclusions These data demonstrate that low-dose intrathecal morphine supplemented by PCA morphine provides better analgesia than PCA morphine alone after spinal fusion in children. The doses of 2 and 5 &mgr;g/kg seem to have similar effectiveness and side-effect profiles, whereas a reduction of intraoperative bleeding was observed in patients who received 5 &mgr;g/kg but not 2 &mgr;g/kg intrathecal morphine.
The Logic of the Partial λ-Calculus With Equality

We investigate the logical aspects of the partial λ-calculus with equality, exploiting an equivalence between partial λ-theories and partial cartesian closed categories (pcccs) established here. The partial λ-calculus with equality provides a full-blown intuitionistic higher order logic, which in a precise sense turns out to be almost the logic of toposes, the distinctive feature of the latter being unique choice. We give a linguistic proof of the generalization of the fundamental theorem of toposes to pcccs with equality; type theoretically, one thus obtains that the partial λ-calculus with equality encompasses a Martin-Löf-style dependent type theory. This work forms part of the semantical foundations for the higher order algebraic specification language HasCasl.
A Novel Bidirectional DC-DC Converter with high Step-up and Step-down Voltage Gains

A bidirectional dc-dc converter with high step-up and step-down voltage gain is handling in this paper. High voltage gains are obtained by employing a coupled inductor with same primary and secondary winding turns in the converter. Beside from high voltage gain, its average value of switch current and voltage stress on switches are lower compared to conventional dc-dc converter. The steady state analysis and operating principles in continuous conduction mode are discussed. Pulse width modulation (PWM) is used to control the switches. To study the performance of the proposed converter, simulations has been carried out in MATLAB2010 environment. Feedback is also given to the circuit using a pi controller and relational operator to get a constant output voltage for such applications.
Surveys in Combinatorics 2009: Embedding large subgraphs into dense graphs

What conditions ensure that a graph G contains some given spanning subgraph H? The most famous examples of results of this kind are probably Dirac's theorem on Hamilton cycles and Tutte's theorem on perfect matchings. Perfect matchings are generalized by perfect F-packings, where instead of covering all the vertices of G by disjoint edges, we want to cover G by disjoint copies of a (small) graph F. It is unlikely that there is a characterization of all graphs G which contain a perfect F-packing, so as in the case of Dirac's theorem it makes sense to study conditions on the minimum degree of G which guarantee a perfect F-packing. The Regularity lemma of Szemeredi and the Blow-up lemma of Komlos, Sarkozy and Szemeredi have proved to be powerful tools in attacking such problems and quite recently, several long-standing problems and conjectures in the area have been solved using these. In this survey, we give an outline of recent progress (with our main emphasis on F-packings, Hamiltonicity problems and tree embeddings) and describe some of the methods involved.
On a Family of Minimal Candidate One-way Functions and One-way Permutations

In order to achieve computational workload equivalent to the exhaustive key search of an n-bit key for inversion of RSA or Di‐e-Hellman one-way candidate functions the length of their arguments have to have from 10n to 60n bits. One-way functions based on Elliptic Curves in this moment are holding the record, demanding only 2n bits for their arguments. In this paper we propose a deflnition and construction of a new family of one-way candidate functions RN : Q N ! Q N , where Q = f0;1;:::;s i 1g is an alphabet with s elements. Special instances of these functions can be permutations (i.e. one-way permutations). These one-way functions have the property that for achieving the security level equivalent of exhaustive key search of n-bit key, only n bits of input are needed.
Visualising the Inner Workings of a Self Learning Classifier: Improving the Usability of Intrusion Detection Systems∗

Current advanced intrusion detection systems that benefit from utilising machine learning principles are not as easy to use as one might hope. As a result the user has difficulties in judging the quality of the output, i.e. identifying false and true alarms. Problems in training the system might also go unnoticed. To counteract this we propose to use principles of information visualisation to make the state of a self learning classifier visible and hence more accessible to the user. The resulting system was tested on two corpora of data: Web access logs and system call trace data. The experiment supported the hypothesis that the visualisation capabilities of the detector helps the user correctly differentiate between false and true alarms and provide insight into the training process of the classifier.
Rational approaches to human cancer immunotherapy

Over most of the 20th century, immunotherapy for cancer was based on empiricism. Interesting phenomena were observed in the areas of cancer, infectious diseases, or transplantation. Inferences were made and extrapolated into new approaches for the treatment of cancer. If tumors regressed, the treatment approaches could be refined further. However, until the appropriate tools and reagents were available, investigators were unable to understand the biology underlying these observations. In the early 1990s, the first human tumor T cell antigens were defined and dendritic cells were discovered to play a pivotal role in antigen presentation. The current era of cancer immunotherapy is one of translational research based on known biology and rationally designed interventions and has led to a rapid expansion of the field. The beginning of the 21st century brings the possibility of a new era of effective cancer immunotherapy, combining rational, immunological treatments with conventional therapies to improve the outcome for patients with cancer.
A mono surrogate for multiobjective optimization

Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective Optimization Algorithm (EMOA) in lieu of the actual objectives, without modifying the underlying EMOA; or to filter out points that the models predict to be uninteresting. In contrast, the proposed approach aims at building a global surrogate model defined on the decision space and tightly characterizing the current Pareto set and the dominated region, in order to speed up the evolution progress toward the true Pareto set. This surrogate model is specified by combining a One-class Support Vector Machine (SVMs) to characterize the dominated points, and a Regression SVM to clamp the Pareto front on a single value. The resulting surrogate model is then used within state-of-the-art EMOAs to pre-screen the individuals generated by application of standard variation operators. Empirical validation on classical MOO benchmark problems shows a significant reduction of the number of evaluations of the actual objective functions.
The 590 Day Long-Term Periodicity of the Microquasar GRS 1915+105

We report on the discovery of a 590 day long-term periodicity in the hard X-ray component of the microquasar GRS 1915+105 found from a comprehensive study of more than 4 years of Rossi X-Ray Timing Explorer observations. The periodicity is also observed in the hard X-ray flux observed by BATSE and in the radio flux as seen with the Green Bank Interferometer and the Ryle Telescope. We discuss various possible explanations, including the precession of a radiation-induced warped accretion disk.
The Konkoly Blazhko Survey: is light-curve modulation a common property of RRab stars?

A systematic survey to establish the true incidence rate of Blazhko modulation among short-period, fundamental-mode, Galactic field RR Lyrae stars has been carried out. The Konkoly Blazhko Survey (KBS) was initiated in 2004. Since then, more than 750 nights of observation have been devoted to this project. A sample of 30 RRab stars was extensively observed, and light-curve modulation was detected in 14 cases. The 47 per cent occurrence rate of the modulation is much larger than any previous estimate. The significant increase of the detected incidence rate is mostly a result of the discovery of small-amplitude modulation. Half of the Blazhko variables in our sample show the modulation with such a small amplitude that they would definitely have been missed in previous surveys. We have found that the modulation can be very unstable in some cases; for example, RY Com showed regular modulation during only one part of the observations, and had a stable light curve with abrupt, small changes in the pulsation amplitude during two observing seasons. This type of light-curve variability is hard to detect in the data from other surveys. The higher frequency of the light-curve modulation of RRab stars makes it even more important to find an explanation for the Blazhko phenomenon. The validity of the [Fe/H](P, ϕ31) relationship using the mean light curves of Blazhko variables is checked in our sample. We found that the formula gives accurate result for small-modulation-amplitude Blazhko stars, and this is also the case for large-modulation-amplitude stars if the light curve has complete phase coverage. However, if the data for large-modulation-amplitude Blazhko stars are not extended enough (e.g. fewer than 500 data points from fewer than 15 nights), the formula may give false result owing to the distorted shape of the mean light curve used.
Mastering Timing Challenges for the Design of Multi-Mode Applications on Multi-Core Real-Time Embedded Systems

Driven by the increasing demand for computational power and by the rising applications' complexity in various embedded application domains, multi-core solutions emerge as the predominant platform for embedded real-time applications. In this context, designers have to face new challenges generated by the need to accommodate applications with complex timing behaviour, e.g. multi-mode applications that can switch between different operational modes at runtime. Consequently the availability of appropriate timing analysis methods for the prediction of the timing behaviour is essential for the design of multi-core real- time systems. Relying on current automotive practice and on related work of the real-time research community we explain and exemplify how tool supported formal analysis methods can be applied to current and upcoming industrial design. We present recent progress in the field of scheduling analysis methods and discuss challenges and new options in the design of multi-mode applications on multi-core real-time systems.
A Low-Carbon Dispatch Model in a Wind Power Integrated System Considering Wind Speed Forecasting and Energy-Environmental Efficiency

This paper introduces the “Energy-Environmental Efficiency” concept of building a low-carbon dispatch model of wind-incorporated power systems from the perspective of environmental protection and low-carbon dispatch promotion based on the existing economic environmental dispatch. A rolling auto-regressive and moving-average model is adopted to forecast wind speeds for the next 24 h and reduce the disadvantages brought about to the power system dispatch by wind speed fluctuations. A fuzzy satisfaction-maximizing approach is employed to convert the multi-objective decision-making problem in the low-carbon dispatch model into a single nonlinear one. Particle swarm optimization with a simulated annealing algorithm hybrid is used for better solutions. Simulation results show that the energy-environmental efficiency concept benefits the optimization of the proposed power system dispatch, and the proposed low-carbon dispatch model is reasonable and practical.
Energy and Resource Allocation: A Dynamic Model of the "Dutch Disease"

It is well known that a domestic-response discovery gives rise to wealth effects that cause a squeeze of the tradeable-good sector of an open economy. The decline of the manufacturing sector following an energy discovery has been termed the Dutch disease, and has been investigated in many recent studies. The authors' model extends the principally static analyses to date by allowing for: (1) short-run capital specificity and long-run capital mobility; (2) international capital flows; and (3) far-sighted intertemporal optimzing behavior by households and firms. The model is solved by numerical simulation. 9 references, 4 figures, 6 tables.
Improving executive function in childhood: evaluation of a training intervention for 5-year-old children

Executive function (EF) refers to a set of higher order cognitive processes that control and modulate cognition under continuously changing and multiple task demands. EF plays a central role in early childhood, is associated and predictive of important cognitive achievements and has been recognized as a significant aspect of school readiness. This study examines the efficacy of a group based intervention for 5-year-old children that focuses on basic components of EF (working memory, inhibitory control, cognitive flexibility). The intervention included 12 sessions, lasted 1 month and used low-cost materials. Seventy-five children took part in the study. The results indicate that the children who attended the intervention outperformed controls in simple and more complex EF tasks. Specifically, these children exhibited increased abilities to delay gratification, to control on-going responses, to process and update information, and to manage high cognitive conflict. These results suggest the possibility that this intervention, which may be easily implemented in educational services, can promote EF during preschool period before the entrance in primary school.