Miracle-dz/UniFAR-FTUs huggingface dataset:
NetSTAT: A Network-based Intrusion Detection System

Network-based attacks are becoming more common and sophisticated. For this reason, intrusion detection systems are now shifting their focus from the hosts and their operating systems to the network itself. Network-based intrusion detection is challenging because network auditing produces large amounts of data, and different events related to a single intrusion may be visible in different places on the network. This paper presents a new approach that applies the State Transition Analysis Technique (STAT) to network intrusion detection. Network-based intrusions are modeled using state transition diagrams in which states and transitions are characterized in a networked environment. The target network environment itself is represented using a model based on hypergraphs. By using a formal model of both the network to be protected and the attacks to be detected the approach is able to determine which network events have to be monitored and where they can be monitored, providing automatic support for configuration and placement of intrusion detection components.
Multiobjective optimal design of high frequency transformers using genetic algorithm

This paper deals with the multiobjective optimization (MO) design of high frequency (HF) transformers using genetic algorithms (GAs). In its most general form, the design problem requires minimizing the mass or overall dimensions of the core and windings as well as the loss of the transformer while ensuring the satisfaction of a number of constraints. In this contribution, the area product (i.e. the product of the core cross section and the winding area) and the power loss are used as objective functions whereas the operating frequency and the maximum flux density are chosen as optimization variables. The constraints include, as for them, appropriate limits on efficiency, maximum surface temperature rise and maximum ratio no-load/full load current. The area product is optimized in place of weight or volume of the transformer because these two quantities can be easily expressed in terms of area product. It is an elegant mean to limit the number of objective functions. The major advantage of the suggested design procedure is that it proposes to the designer a set of optimal transformers — instead of a single solution — so he can choose a posteriori which of them best fits the application under consideration. Finally, in order to illustrate the design procedure, the optimal design of a transformer supplied with square voltage waveform is performed and the results are discussed.
Secure k-NN computation on encrypted cloud data without sharing key with query users

In cloud computing, secure analysis on outsourced encrypted data is a significant topic. As a frequently used query for online applications, secure k-nearest neighbors (k-NN) computation on encrypted cloud data has received much attention, and several solutions for it have been put forward. However, most existing schemes assume the query users are fully trusted and all query users share the total key which is used to encrypt and decrypt data owner's outsourced data. It is constitutionally not feasible in lots of real-world applications. In this paper, we propose a novel secure and efficient scheme for k-NN query on encrypted cloud data in which the key of data owner to encrypt and decrypt ousourced data will not be completely disclosed to any query user. Therefore, our scheme can efficiently support the secure k-NN query on encrypted cloud data even when query users are not trustworthy enough.
The Shaker Potassium Channel Is No Target for Xenon Anesthesia in Short-Sleeping Drosophila melanogaster Mutants

Background. Xenon seems to be an ideal anesthetic drug. To explore if next to the antagonism at the NMDA-receptor other molecular targets are involved, we tested the xenon requirement in short sleeping Drosophila shaker mutants and in na[har 38]. Methods. The Drosophila melanogaster strains wildtype Canton-S, na[har 38], sh 102 and sh mns, were raised and sleep was measured. Based on the response of the flies at different xenon concentrations, logEC50 values were calculated. Results. The logEC50-values for WT Canton-S were 1.671 (1.601–1.742 95%-confidence intervall; n = 238; P versus sh 102 > 0,05), for sh mns 1.711 (1.650–1.773; n = 242; P versus WT Canton-S > 0,05). The logEC50-value for sh 102 was 1.594 (1.493–1.694; n = 261; P versus sh mns > 0.05). The logEC-value of na[har 38] was 2.076 (1.619–2.532; n = 207; P versus sh mns < 0.05, versus sh 102 < 0.05, versus WT Canton-S < 0.05). P values for all shaker mutants were P > 0.05, while na[har 38] was found to be hyposensitive compared to wildtype (P < 0.05). Conclusions. The xenon requirement in Drosophila melanogaster is not influenced by a single gene mutation at the shaker locus, whereas a reduced expression of a nonselective cation channel leads to an increased xenon requirement. This supports the thesis that xenon mediates its effects not only via an antagonism at the NMDA-receptor.
Human action recognition using late fusion and dimensionality reduction

This paper addresses the problem of action recognition. We introduce local feature representations which are HOG, HOF, MBH, trajectory descriptor based on paper [1]. We extract those features only used one scale while Wang's paper has eight spatial scales. Our method can save memory and computation cost while guarantee the accuracy. Firstly, we apply a PCA on the HOG, HOF, MBH, trajectory descriptors to reduce the number of features. Secondly, we use Fisher kernel (FK) to aggregate each descriptor into a Fisher vector (FV) or vector of locally aggregated descriptors (VLAD) and then use improved LDA technique for FV or VLAD before being fed into the linear SVM. Thirdly, we apply late fusion for all kinds of descriptors. We evaluate our descriptor on the KTH and Youtube dataset, and as a result, observe improved performance in terms of mean average precise (mAP). Our method not only significantly reduces computational cost but improves accuracy.
3D-segmentation of traffic environments with u/v-disparity supported by radar-given masterpoints

3D-segmentation of a traffic scene with two-dimensional row- and column-disparity-histograms, namely u/v-disparities, has become more and more popular for modern stereo-camera-based driver assistance systems due to its fast computation in real-time, few memory requirements and robustness against noisy or intermittent data. In this paper, we present a novel approach to support this pure vision-based method by projecting preprocessed radar-signals directly to u-disparity-space. We called the projection result “masterpoints”. This data fusion on low feature-level improved the segmentation process and increased the obstacle detection rate significantly. No assumptions about obstacle-type or -size are needed. Furthermore, the algorithms can be parallelized easily and run in real-time.
Venture Capital Funds and Post-IPO Performance in Booms and Busts: Evidence from Israeli IPO’s in the US in the 1990s1

______ ______________ 1 We are extremely grateful to Vladimir Lifschitz for his extraordinary contribution to the construction of the database, and to Konstantin Kosenko for excellent research assistance. We also thank Gil Avnimelech, Marco Da Rin, Saul Lach, Sigal Ribon, Yona Rubinstein, Efrat Tolkowsky, Manuel Trajtenberg, Oved Yosha, Haim Zazak and seminar participants at the Bank of Israel and Tel Aviv University for very helpful comments. ∗ Bank of Israel, Research Department. ∗ ∗ The Hebrew University of Jerusalem and the University of Montreal.
Teleoperation performance using excavator with tactile feedback

Teleoperation systems have been used in various situations such as space tasks, rescue activities, military missions, undersea operations and unmanned constructions. Compared to direct operation, teleoperation performance is limited by a lack of awareness of remote location environments. In this paper, tactile feedback on construction machine teleoperation performance is discussed. We measured the effectiveness in a study of three-dimensional pointing tasks using Fitt's law paradigm with a tactile feedback. The way of the tactile feedback is that operator can notice an approaching excavator's bucket to ground by vibration before touching the bucket to ground. We found that total movement time was reduced by the tactile feedback.
Abnormal Cortical Plasticity in Youth with Autism Spectrum Disorder: A Transcranial Magnetic Stimulation Case–Control Pilot Study

Abstract Objective: This case–control study investigated the use of a low-intensity repetitive transcranial magnetic stimulation (rTMS) protocol to measure motor cortex (M1) plasticity in youth with autism spectrum disorder (ASD) compared with typically developing children (TDC). We hypothesized that impairments in long-term potentiation-like properties represent a neurophysiological biomarker of abnormal cortical function in ASD. Methods: We studied youth with ASD aged 11–18 years and matched controls (TDC). Intermittent theta burst stimulation (iTBS) was delivered to the dominant M1 at an intensity of 70% of resting motor threshold. Suprathreshold single-pulse TMS was performed to compare amplitudes of motor-evoked potentials (MEP) measured from surface electromyography electrodes on a target muscle before (20 pulses) and after (10 pulses/time point) iTBS at predefined timepoints (up to 30 minutes) to measure any potentiation effects. A linear mixed model was used to examine group differences in MEP amplitudes over time following iTBS. Results: Nine youth with ASD (mean age 15.6; 7 males; 6 right-hand dominant) and 9 TDC (mean age 14.5; 5 males; 9 right-hand dominant) participated. All subjects tolerated the procedure well. Both groups had a mean increase in excitability after iTBS for 30 minutes; however, the time course of excitability changes differed (F9,144 = 2.05; p = 0.038). Post-hoc testing identified a significant decrease in amplitude of the ASD group at 20 minutes following iTBS compared with the TDC after correcting for multiple comparisons. Conclusion: In this study, we demonstrate early evidence for a potential physiological biomarker of cortical plasticity in youth with ASD using a rapid low-intensity rTMS protocol with a discriminate measure at 20 minutes following stimulation. The procedure was well tolerated by all 18 participants. Future work will include modification of the protocol to improve the ability to distinguish subtypes of ASD based on behavioral and cognitive testing.
Interlimb neural connection is not required for gait transition in quadruped locomotion

Quadrupeds transition spontaneously to various gait patterns (e.g., walk, trot, pace, gallop) in response to the locomotion speed. The generation of these gait patterns has been the subject of debate for a long time. We propose a coupled oscillator model that is coupled with the physical interactions of the body. The results of this study showed that the gait pattern transitions spontaneously to walking/trotting/pacing/bounding in manner similar to that of real quadruped animals when the resonating portion of the body is changed according to the speed of leg movement. We also observed that pacing is expressed exclusively instead of trotting by changing the physical characteristics. In addition to leading to understanding of the principles of locomotion in living things, the coupled oscillator model proposed in this study is expected to lead to the creation of a legged robot that can select an energy-efficient gait and transition to it spontaneously.
43 3 v 1 2 3 O ct 1 99 9 Numerical simulations of relativistic wind accretion on to black holes using Godunov-type methods

We have studied numerically the so-called Bondi-Hoyle (wind) accretion on to a rotating (Kerr) black hole in general relativity. We have used the Kerr-Schild form of the Kerr metric, free of coordinate singularities at the black hole horizon. The ‘test-fluid’ approximation has been adopted, assuming no dynamical evolution of the gravitational field. We have used a recent formulation of the general relativistic hydrodynamic equations which casts them into a first-order hyperbolic system of conservation laws. Our studies have been performed using a Godunov-type scheme based on Marquina’s flux-formula. We find that regardless of the value of the black hole spin the final accretion pattern is always stable, leading to constant accretion rates of mass and momentum. The flow is characterized by a strong tail shock which is increasingly wrapped around the central black hole as the hole angular momentum increases. The rotation induced asymmetry in the pressure field implies that besides the well known drag, the black hole will experience also a lift normal to the flow direction.
A New Method for Robust Damping and Tracking Control of Scanning Probe Microscope Positioning Stages

This paper demonstrates a simple second-order controller that eliminates scan-induced oscillation and provides integral tracking action. The controller can be retrofitted to any scanning probe microscope with position sensors by implementing a simple digital controller or operational amplifier circuit. The controller is demonstrated to improve the tracking bandwidth of an NT-MDT scanning probe microscope from 15 Hz (with an integral controller) to 490 Hz while simultaneously improving gain-margin from 2 to 7 dB. The penalty on sensor induced positioning noise is minimal. A unique benefit of the proposed control scheme is the performance and stability robustness with respect to variations in resonance frequency. This is demonstrated experimentally by a change in resonance frequency from 934 to 140 Hz. This change does not compromise stability or significantly degrade performance. For the scanning probe microscope considered in this paper, the noise is marginally increased from 0.30 to 0.39 nm rms. Open and closed-loop experimental images of a calibration standard are reported at speeds of 1, 10, and 31 lines per second (with a scanner resonance frequency of 290 Hz). Compared with traditional integral controllers, the proposed controller provides a bandwidth improvement of greater than 10 times. This allows faster imaging and less tracking lag at low speeds.
An incremental genetic algorithm approach to multiprocessor scheduling

We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiprocessor systems. Our approach requires minimal problem specific information and no problem specific operators or repair mechanisms. Key features of our system include a flexible, adaptive problem representation and an incremental fitness function. Comparison with traditional scheduling methods indicates that the GA is competitive in terms of solution quality if it has sufficient resources to perform its search. Studies in a nonstationary environment show the GA is able to automatically adapt to changing targets.
Computational Intelligence Approaches for Improving Serviceability of Material Handling Systems

The level of the serviceability of material handling systems can be measured by the effectiveness of completing each service request in terms of time and cost, and the speed of auto-recovery from any unexpected disturbance to the process of completing a service. In this paper, computational intelligence approaches based on ant colony system and genetic algorithm are investigated to perform auto-recovery for the supervisory control of a complex automated material handling facility (AMHF) in a dynamic environment. In addition, Dijkstra's algorithm, is also introduced to evaluate the proposed computational intelligence approaches with positive results. The strengths and weaknesses of each algorithm are analyzed to determine the suitable applications of each algorithm. A single data representation of the actual AMHF database provided the comparison basis for evaluation of proposed approaches. The test results demonstrated the viability of using computational intelligence approaches to achieve optimal solutions within an acceptable computing time, and therefore can be successfully applied to improve the serviceability of AMHF.
Prediction of default probability by using statistical models for rare events

Prediction models in credit scoring usually involve the use of data sets with highly imbalanced distributions of the event of interest (default). Logistic regression, which is widely used to estimate the probability of default, PD, often suffers from the problem of separation when the event of interest is rare and consequently poor predictive performance of the minority class in small samples. A common solution is to discard majority class examples, to duplicate minority class examples or to use a combination of both to balance the data. These methods may overfit data. It is unclear how penalized regression models such as Firth's estimator, which reduces bias and mean‐square error relative to classical logistic regression, performs in modelling PD. We review some methods for class imbalanced data and compare them in a simulation study using the Taiwan credit card data. We emphasize the effect of events per variable for developing an accurate model—an often neglected concept in PD‐modelling. The data balancing techniques that are considered are the random oversampling examples and synthetic minority oversampling technique methods. The results indicate that the synthetic minority oversampling technique improved predictive accuracy of PD regardless of sample size. Among the penalized regression models that are analysed, the log‐F prior and ridge regression methods are preferred.
Evidence for Broadening Criteria for Atypical Depression Which May Define a Reactive Depressive Disorder

Objective. Arguing that additional symptoms should be added to the criteria for atypical depression. Method. Published research articles on atypical depression are reviewed. Results. (1) The original studies upon which the criteria for atypical depression were based cited fatigue, insomnia, pain, and loss of weight as characteristic symptoms. (2) Several studies of DSM depressive criteria found patients with atypical depression to exhibit high levels of insomnia, fatigue, and loss of appetite/weight. (3) Several studies have found atypical depression to be comorbid with headaches, bulimia, and body image issues. (4) Most probands who report atypical depression meet criteria for “somatic depression,” defined as depression associated with several of disordered eating, poor body image, headaches, fatigue, and insomnia. The gender difference in prevalence of atypical depression results from its overlap with somatic depression. Somatic depression is associated with psychosocial measures related to gender, linking it with the descriptions of atypical depression as “reactive” appearing in the studies upon which the original criteria for atypical depression were based. Conclusion. Insomnia, disordered eating, poor body image, and aches/pains should be added as criteria for atypical depression matching criteria for somatic depression defining a reactive depressive disorder possibly distinct from endogenous melancholic depression.
Evaluation of Electrocardiogram for Biometric Authentication

This paper presents an evaluation of a new biometric electrocardiogram (ECG) for individual authentication. We report the potential of ECG as a biometric and address the research concerns to use ECG-enabled biometric authentication system across a range of conditions. We present a method to delineate ECG waveforms and their end fiducials from each heartbeat. A new authentication strategy is proposed in this work, which uses the delineated features and taking decision for the identity of an individual with respect to the template database on the basis of match scores. Performance of the system is evaluated in a unimodal framework and in the multibiometric framework where ECG is combined with the face biometric and with the fingerprint biometric. The equal error rate (EER) result of the unimodal system is reported to 10.8%, while the EER results of the multibiometric systems are reported to 3.02% and 1.52%, respectively for the systems when ECG combined with the face biometric and ECG combined with the fingerprint biometric. The EER results of the combined systems prove that the ECG has an excellent source of supplementary information to a multibiometric system, despite it shows moderate performance in a unimodal framework. We critically evaluate the concerns involved to use ECG as a biometric for individual authentication such as, the lack of standardization of signal features and the presence of acquisition variations that make the data representation more difficult. In order to determine large scale performance, individuality of ECG remains to be examined.
Particle Methods for Nonequilibrium Hypersonic and Plasma Flows

Kinetic modelling of nonequilibrium flows is described as it applies to hypersonic phenomenology. A Monte Carlo method is described for the study of species separation on shock wave fronts; a Particle in Cell with Monte Carlo Collisions (PIC/MCC) technique is described for the simulation of dust in plasma flows; modelling of nonequilibrium radiation in shock heated gases; implementation of slip models for the description of separation zones occurring in shock- boudary layer interactions.
Reinforcement Learning and Shaping: Encouraging Intended Behaviors

We explore dynamic shaping to integrate our prior beliefs of the final policy into a conventional reinforcement learning system. Shaping provides a positive or negative artificial increment to the native task rewards in order to encourage or discourage behaviors. Previously, shaping functions have been static: the additional rewards do not vary with experience. But some prior knowledge cannot be expressed as static shaping. We take an explanation-based approach in which the specific shaping function emerges from initial experiences with the world. We compare no shaping, static shaping, and dynamic shaping in the task of learning bipedal-walking on a simulator. We empirically evaluate the convergence rate and final performance among these conditions while varying the accuracy of the prior knowledge. We conclude that in the appropriate context, dynamic shaping can greatly improve the learning of action policies.
First Cognitive Radio Networking Standard for Personal/Portable Devices in TV White Spaces

Recent FCC rules allowing unlicensed use on a secondary basis of the Television White Spaces (TVWS) promise a whole new set of possible applications. The first step towards realizing these applications is the creation and adoption of industry standards. In this paper we present the first such standard for personal/portable devices in the TVWS that complies fully with the existing FCC rules while retaining flexibility for use with other regulatory domains. We describe the physical (PHY) and medium access control (MAC) layers specified in the standard and present performance results to demonstrate the robustness and spectral efficiency of the proposed protocols.
Soft sensor for apparent degree of calcination in NSP cement production line

Because it is difficult to measure the on-line apparent degree of calcination in New Suspension Preheater Dry Process (NSP) cement production line, a soft sensor model is established by using soft sensor technique and Least Squares Support Vector Machine (LS-SVM) with RBF kernel. The furnace temperature and pressure of the calciner, the outlet temperature and pressure of the calciner, the temperature of the tertiary air and the lay off quantity of cement raw are used as the inputs of soft sensor model. The apparent degree of calcination is the output. A realization scheme programmed by VC ++ based on DCS and OPC technique is presented. The results of the experiment show that the prediction accuracy of this soft sensor model for the apparent degree of calcination in NSP cement production line based on LS-SVM can reach 98.8%. So the on-line measurement of the apparent degree of calcination in NSP cement production line can be realized by this soft sensor model.