Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic flow classification using machine learning

Network standards are moving toward the quality-of-service (QoS) networking. Differentiated services (DiffServ) QoS model is adopted by many recent and upcoming networks standard. Applications running on these networks can specify suitable service classes to their connections or flows. The flows are then treated according to their service classes. However, current Internet applications are still designed based on best-effort scheme and, therefore, cannot benefit from QoS support from the network. An automatic flow classification framework, which can automatically classify non QoS-aware flows or legacy flows, has been proposed in our earlier work [2]. In this paper, we extend our framework by introducing new features that can be effectively used to classify legacy flows. The simplicity of these features allows the data to be collected in real-time. No packet-level data are required. Furthermore, the framework is evaluated using multiple data sets from different users. The results show that our framework works extremely well in general and it can be operated independently from any applications, networks or even machine learning algorithms. Average correctness up to 98.82% is achieved when the framework is used to learn and classify unseen flows from the same user. Cross-user classifications yield average correctness up to 74.15%.
UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)

One of the major research challenges in this field is the unavailability of a comprehensive network based data set which can reflect modern network traffic scenarios, vast varieties of low footprint intrusions and depth structured information about the network traffic. Evaluating network intrusion detection systems research efforts, KDD98, KDDCUP99 and NSLKDD benchmark data sets were generated a decade ago. However, numerous current studies showed that for the current network threat environment, these data sets do not inclusively reflect network traffic and modern low footprint attacks. Countering the unavailability of network benchmark data set challenges, this paper examines a UNSW-NB15 data set creation. This data set has a hybrid of the real modern normal and the contemporary synthesized attack activities of the network traffic. Existing and novel methods are utilised to generate the features of the UNSWNB15 data set. This data set is available for research purposes and can be accessed from the link.
Reconciling VAR-Based and Narrative Measures of the Tax-Multiplier

The currently available empirical evidence shows remarkable differences between various estimates of the effects on U.S. output of an exogenous shift in Federal tax liabilities. Shocks identified via the narrative method imply a multiplier of about three over an horizon of three years. Tax shocks identified in fiscal VAR models deliver a much smaller multiplier of about one. Is this heterogeneity real, or is it simply the result of different approaches to the identification of exogenous shifts in taxes? Or of different specifications of the empirical model used to estimate the tax multiplier? In this paper we reconcile this apparently contradictory evidence by showing that the large multiplier obtained via the narrative identification methods is generated by the choice of a limited information approach in their estimation and not by the different nature of the shocks. Using the shocks identified by a Narrative methods in a multivariate dynamic model delivers estimates of the tax multiplier very much in line with those obtained in the traditional fiscal VAR approach.
University ’ s repository of research publications and other research outputs Homometric point sets and inverse problems

The inverse problem of diffraction theory in essence amounts to the reconstruction of the atomic positions of a solid from its diffraction image. From a mathematical perspective, this is a notoriously difficult problem, even in the idealised situation of perfect diffraction from an infinite structure. Here, the problem is analysed via the autocorrelation measure of the underlying point set, where two point sets are called homometric when they share the same autocorrelation. For the class of mathematical quasicrystals within a given cut and project scheme, the homometry problem becomes equivalent to Matheron’s covariogram problem, in the sense of determining the window from its covariogram. Although certain uniqueness results are known for convex windows, interesting examples of distinct homometric model sets already emerge in the plane. The uncertainty level increases in the presence of diffuse scattering. Already in one dimension, a mixed spectrum can be compatible with structures of different entropy. We expand on this example by constructing a family of mixed systems with fixed diffraction image but varying entropy. We also outline how this generalises to higher dimension.
Identification and Recovery of the Blurred QR Code Image

This paper describes the basic information of QR Code. Especially for the blurred QR Code image, we put forward an improved NAS-RIF algorithm which makes bimodal characteristic of the barcode image into it as a constraint. NAS-RIF algorithm itself has a good convergence speed. It will effectively improve the recovery effect of barcode image after combining with bimodal limit. The experiment shows that the improved algorithm not only enhances PSNR but improves the visual effect of the restored barcode image.
Towards Dynamic Provenance Tracking in Web Feed Mash-Ups

A new breed of applications and services that combines data and content from diverse sources which we refer to as "mash-ups" has grown significantly all across the Internet. One of the most popular mash-ups comes in the form of web feed mash-ups relying on syndication technologies such as RSS and Atom. This kind of mash-ups aggregates web feeds derived from multiple news websites or blogs and then timely presents them in a single web-based interface. In such systems, it is difficult to know exactly how feed results in data mash-ups are generated. In particular, it is difficult for users to make determinations about whether information is trusted, considering that source feeds have to pass through several processing operations before the feed results are presented. Therefore, it is crucial that web feed mash-ups have to support a mechanism for recording and querying provenance information - the information about the process that led to result data. In this paper, we propose a provenance tracking solution that enables provenance functionality to be facilitated in web feed mash-ups. We demonstrate how the provenance of feed mash-up results to be determined by means of a provenance query algorithm. Finally, we evaluate our provenance tracking solution in terms of storage consumption for provenance collection, demonstrating predictable storage consumption and reasonable storage overheads.
A Robust and Efficient MTJ-based Spintronic IMP Gate for New Logic Circuits and Large-Scale Integration

A novel circuit topology of a spintronic stateful implication (IMP) logic gate based on a spin transfer torqueoperated magnetic tunnel junction (STT-MTJ) is proposed and analyzed. It is demonstrated that the proposed topology reduces the IMP error and also the energy consumption by about 60% as compared to the conventional one. Stateful IMP-based logic uses the nonvolatile memory unit (MTJ device) as the main computing element (logic gate) unlike the previously proposed MTJ-based logic-in-memory circuits, where MTJs are only ancillary devices in logical computations. Since the MTJ devices are CMOS compatible, the generalization of the spintronic IMP gate to a large-scale nonvolatile logic-in-memory system is compulsory. As an example we consider an IMP-based implementation of a full adder. In contrast to an earlier proposed IMP-based full adder with 37 operations, our design involves only 27 subsequent FALSE and IMP operations. Keywordsimplication (IMP) logic; nonvolatile logic-inmemory; magnetic tunnel junction (MTJ); spin transfer torque (STT)
A Maximum Likelihood Doppler Frequency Estimator for OFDM Systems

This paper derives a maximum likelihood Doppler frequency estimator for orthogonal frequency division multiplexing (OFDM) systems in time-varying multipath channels. The proposed scheme is a frequency-domain approach that utilizes pilot subcarriers, which are commonly implemented in most practical systems. Time-varying fading causes intercarrier interference (ICI) in OFDM systems. Thus, in the proposed estimator, the effect of ICI is taken into consideration with a proper model for accurate results. The estimator can be implemented using a finite impulse response (FIR) filter bank whose coefficients can be pre-calculated and stored in order to lower the computational complexity. We evaluate various methods to improve the estimation accuracy and analyze their complexity-performance tradeoffs. We also derive the Cramér-Rao bound and provide simulation results to quantify the performance of the proposed algorithm.
Discovering the best web service: A neural network-based solution

Differentiating between Web services that share similar functionalities is becoming a major challenge into the discovery of Web services. In this paper we propose a framework for enabling the efficient discovery of Web services using Artificial Neural Networks (ANN) best known for their generalization capabilities. The core of this framework is applying a novel neural network model to Web services to determine suitable Web services based on the notion of the Quality of Web Service (QWS). The main concept of QWS is to assess a Web service's behaviour and ability to deliver the requested functionality. Through the aggregation of QWS for Web services, the neural network is capable of identifying those services that belong to a variety of class objects. The overall performance of the proposed method shows a 95% success rate for discovering Web services of interest. To test the robustness and effectiveness of the neural network algorithm, some of the QWS features were excluded from the training set and results showed a significant impact in the overall performance of the system. Hence, discovering Web services through a wide selection of quality attributes can considerably be influenced with the selection of QWS features used to provide an overall assessment of Web services.
Synthesis and Characterization of bis[(2-ethyl-5-methyl-imidazo-4-yl)methyl]Sulfide and Its Coordination Behavior toward Cu(II) as a Possible Approach of a Copper Site Type I

The synthesis and characterization of a novel ligand, bis[(2-ethyl-5-methyl-imidazo-4-yl)methyl]sulfide (bemims), as well as a bemims-containing copper(II) coordination complex are described. In this complex, [Cu(bemims)X 2] with X = NO3 −, bemims acts as a tridentate ligand and two monodentate nitrate ions complete the coordination sphere. Both imidazole N atoms and the thioether S atom of bemims participate in coordination. The Cu(II) ion is five-coordinated with a slightly distorted square-pyramidal geometry (τ = .09). Electrochemical studies and spectroscopic data for this complex are compared with some blue copper proteins in order to assess its ability to mimic the copper center of type I copper proteins.
Fast and Exact Top-k Algorithm for PageRank

To obtain high PageRank score nodes, the original approach iteratively computes the Page-Rank score of each node until convergence by using the whole graph. If the graph is large, this approach is infeasible due to its high computational cost. The goal of this study is to find top-k Page\-Rank score nodes efficiently for a given graph without sacrificing accuracy. Our solution, F-Rank, is based on two ideas: (1) It iteratively estimates lower/upper bounds of Page\-Rank scores, and (2) It constructs subgraphs in each iteration by pruning unnecessary nodes and edges to identify top-k nodes. Our theoretical analysis shows that F-Rank guarantees result exactness. Experiments show that F-Rank finds top-k nodes much faster than the original approach.
The great Indian joint families of free-ranging dogs

Cooperative breeding is an excellent example of cooperation in social groups. Domestic dogs have evolved from cooperatively hunting and breeding ancestors but have adapted to a facultatively social scavenging lifestyle on streets, and solitary living in human homes. Pets typically breed and reproduce under human supervision, but free-ranging dogs can provide insights into the natural breeding ecology of dogs. We conducted a five year-long field based behavioural study on parental care of free-ranging dogs in India. 23 mother-litter units, belonging to 15 groups were observed, which revealed the presence of widespread allo-parenting by both adult males and females. While all the females were known to be related to the pups receiving care, the relatedness with the males could not be determined. Hence, we coined the term “putative father” for caregiving males. Allomothers provided significantly less care than the mothers, but the putative fathers showed comparable levels of care with the mothers. Mothers invested more effort in nursing and allogrooming, while the putative fathers played and protected more. Our observations provide support for both the “benefit-of-philopatry” and “assured fitness returns” hypotheses. Free-ranging dogs are not cooperative breeders like wolves but are rather communal breeders; their breeding biology bearing interesting similarities with the human joint family system. This breeding strategy is likely to have played an important role in increasing pup survival in a stochastic environment and helping to adapt to living among humans during the domestication of dogs.
Traffic balancing in wireless MESH networks

Several access points may be put into wireless ad hoc networks for people connecting to WWW or other Internet services. This kind of wireless network is called wireless mesh networks (WMNs) that still needs users to relay packets for other users. The meshed topology provides good reliability, market coverage, and scalability, as well as low upfront investment. However, due to the nature of routing algorithm the traffic load for a access point may be extremely heavy during particular periods while the other access points are in very light load. Consequently, the overall performance of the network are poor even the total traffic load is far below the system capacity. Traffic balancing proposed for wireless ad hoc networks provides an efficient solution to this problem. With right placement of the access points, the performance can be improved dramatically by traffic balancing.
A multifunctional grid tied solar energy conversion system with ANF based control approach

This paper presents a two stage, three-phase grid interfaced SPV (Solar Photovoltaic) energy conversion system with an ANF (Adaptive Notch Filter) based control algorithm. The proposed SPV system is a multi-function grid-interfaced solar PV energy conversion system, which along with conversion of dc-power from SPV to AC mains, is capable of reactive power compensation, harmonics current elimination and load balancing in a three-phase AC distribution system. Compared to multiple devices with different functionalities, a multifunction grid-interfaced SPV energy conversion system is capable to save substantially capital investment, space and maintenance cost. The ANF successfully extracts a single sinusoid of a possibly non-stationary nature from harmonics corrupted load currents at PCC (Point of Common Coupling). The control algorithm is adaptive with respect to the fundamental frequency of the system compared to other methods; and provides instantaneous values of the fundamental signals. Simulation and experimental results verify the validity of the presented algorithm and confirms its desirable transient and steady state performances. The THD (Total Harmonics Distortion) of grid currents is found well under IEEE-519 standard even under nonlinear loads.
On estimating the exponential decay rate for linear systems with interval time-varying delay

This paper presents a delay-dependent approach to studying the exponential stability of linear systems with interval time-varying delay. It is assumed that the upper and lower bounds of the time delay are known. Delay-dependent stability conditions are derived based on an integral inequality, and the exponential decay rate can be obtained by means of the feasibility of a linear matrix inequality. By fully considering the information of the delayed states and introducing slack variables, the conservatism in some existing results is further reduced. Two numerical examples are finally provided to demonstrate the effectiveness of the proposed approach.
Un)Reliable Concessions in Static and Dynamic Bargaining Experiments

A two-persons bargaining problem often consists of initially incompatible demands that can be unilaterally reduced by sequential concessions. In a 2 x 2 x 2 - factorial design we distinguish between reliable and unreliable concessions, between a static and dynamic settings and between symmetric and asymmetric initial demands. Whereas reliable concessions change the threat point, unreliable concessions do not. In the dynamic setting each player's concession can be conditional on the previous history of play; in the static setting a player's concessions for all bargaining trials are determined at the beginning of the game. In all situations conflict is triggered if neither gives in, or if a maximum number of trials is reached without a feasible agreement. Although our results indicate that conflict is more likely if concessions are reliable, the overall effciency of both institutions is similar.
Nonlinear stability analysis of DFIG wind generators in voltage oriented control operation

In this paper the damping and stability properties of Doubly-Fed Induction Generator (DFIG) wind systems are studied. First the complete 5th order nonlinear system of a DFIG in the synchronously rotating dq reference frame is introduced. Assuming operation under the grid voltage oriented control mode, it is possible to control reactive and active power separately through the d and q controlled voltage inputs, respectively. After that, a simple cascaded controller design is adopted for each input, comprising of proportional inner-loop and proportional-integral outer-loop controllers. A passivity analysis is conducted for both the open- and closed-loop systems with the dynamics of the proportional inner-loop controllers taken into account. The analysis shows that the damping of the system can be modulated by the inner-loop controllers while it provides an appropriate storage function for the nonlinear stability analysis. This constitutes the main contribution of the paper since it is the first time that stability and convergence to the equilibrium is proven for the complete machine model in the face of unknown torque inputs, without needing any estimation or adaptive mechanism. Finally, the analysis and the performance of the closed-loop DFIG wind system are verified through extensive simulation results.
Wavelet Transform Based Classification of Invasive Brain Computer Interface Data

The input signals of brain computer interfaces may be either electroencephalogram recorded from scalp or electrocorticogram recorded with subdural electrodes. It is very important that the classifiers have the ability for discriminating signals which are recorded in different sessions to make brain computer interfaces practical in use. This paper proposes a method for classifying motor imagery electrocorticogram signals recorded in different sessions. Extracted feature vectors based on wavelet transform were classified by using k-nearest neighbor, support vector machine and linear discriminant analysis algorithms. The proposed method was successfully applied to Data Set I of BCI competition 2005, and achieved a classification accuracy of 94 % on the test data. The per- formance of the proposed method was confirmed in terms of sensitivity, specificity and Kappa and compared with that of other studies used the same data set. This paper is an extended version of our work that won the Best Paper Award at the 33rd International Conference on Telecom- munications and Signal Processing.
A hybrid Lagrangean metaheuristic for single machine scheduling problem with sequence-dependent setup times and due dates

In this article, a hybrid Lagrangean metaheuristic is proposed for single machine scheduling problems with sequence-dependent setup times and due dates. The objective function considered throughout this work, is to minimize the total tardiness. Related works and taxonomies for hybrid metaheuristics are analyzed, through a thorough historical overview. The proposed hybrid Lagrangean metaheuristic is a Lagrangean relaxation integrated with a metaheuristic. The algorithm uses the information of the Lagrangean multipliers to construct and perturb feasible solutions. The algorithm performance is compared with previous works and we find that the upper bounds obtained were particularly good, proving optimality for several instances and tight gaps for others. Furthermore, to the best of our knowledge, the proposed methodology presents generally better results than previous related works.
PHYSICAL AGENTS

Acknowledgments I would like to thank my advisor Dr. Gal A. Kaminka that followed me every step of the way and pushed me on when I needed. Supported my research with his vast knowledge and helped me formulate my ideas into coherent research. Gal is a great research partner, an amazing friend, a superb mentor and was always a pleasure to work with. I feel deep gratitude to my MAVERICK colleagues for their contribution in excellent advices, insightful ideas and unfailing enthusiasm. Among them, I would like to thank Dan Erusalimchick for his contribution to the BITE'M experiments, building the first running version of BITE with Maintenance, and Nirom Choen Nov, for being my co-author on the Maintenance paper. We thank our Elbit Systems partners for many useful discussions and feedback: I want to thank my parents Yochi and Doron Yakir for listening to my lectures, presentations and practice talks all along the way. I think their knowledge in the field is by now substantial. Last but not least Meytal my love and wife, who was always beside me and not only tolerated the long hours at the lab but even provided snacks.
Synonymy in collocation extraction

This paper describes the use of WordNet in a new technique for collocation extraction. The approach is based on restrictions on the possible substitutions for synonyms within candidate phrases. Following a general discussion of collocations and their applications, current extraction methods are briefly described. This is followed by a detailed description of the new approach and results and evaluation of experiments that utilise WordNet as a source of synonymic information.
An Automated System for Integrated Service Management in Emergency Situations

The integration of Wireless Communications and Computer Science can lead to the development of advanced systems and services. This paper presents the development of an automated management system for road traffic control in emergency situations. This system consists of a Wireless Sensor Network (WSN) and a centralized control system. The performance evaluation of the system is accomplished through various scenarios of use.
Virtual Touch Sensations in an Online Shopping Context: An Experimental Approach

We present ongoing research on mediated touch in virtual stores and aim to extend this line of research in several ways. First, we will test whether (a sense of) touch is feasible in the context of the virtual store. We will then investigate if user control is the main driver in touch sensations. Third, we will test if touch devices will reinforce effects.