Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Mining Approach for Intrusion Detection System

Intrusions are the activities that violate the security policy of the system, and intrusion detection is the process used to identify intrusions. This paper gives an overview of the existing intrusion detection techniques, including anomaly detection and misuse detection models, and identifies techniques related to intrusion detection in distributed systems. It includes topics like machine learning and data mining approaches. In this paper, we describe a data mining framework for adaptively building Intrusion Detection (ID) models. The central idea is to utilize auditing programs to extract an extensive set of features that describe each network connection or host session, and apply data mining programs to learn rules that accurately capture the behaviour of intrusions and normal activities. These rules can then be used for misuse detection and anomaly detection. Topics discuss the strengths of our data mining programs, namely, classification, meta-learning, association rules, and frequent episodes. We describe our approaches to address three types of issues: accuracy, efficiency, and usability. To improve accuracy, data mining programs are used to analyze audit data and extract features that can distinguish normal activities from intrusions. we use artificial anomalies along with normal and intrusion data to produce more effective misuse and anomaly detection models. To improve efficiency, the computational costs of features are analyzed and a multiple-model costbased approach is used to produce detection models with low cost and high accuracy.
Comparison of intelligent optimization algorithms for crack shape reconstruction from ECT signals

Intelligent optimization is a vibrant area of investigation, with some of the widely known and used approaches being Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization Algorithm. An inversion algorithm for the reconstruction of natural crack shape from eddy current testing signals is developed by using an artificial neural network based forward model and intelligent inversion algorithm. The true crack shapes and the measured eddy current testing signals are used to train the neural network. The parameters of the algorithms are modified, their effectiveness on crack shape inversion problem are compared and discussed. The reconstructed results verified the efficiency of neural network based forward model and the promising of intelligent optimization algorithms in crack shape inversion.
Flow and Transport in Regions with Aquatic Vegetation

This review describes mean and turbulent flow and mass transport in the presence of aquatic vegetation. Within emergent canopies, the turbulent length scales are set by the stem diameter and spacing, and the mean flow is determined by the distribution of the canopy frontal area. Near sparse submerged canopies, the bed roughness and near-bed turbulence are enhanced, but the velocity profile remains logarithmic. For dense submerged canopies, the drag discontinuity at the top of the canopy generates a shear layer, which contains canopy-scale vortices that control the exchange of mass and momentum between the canopy and the overflow. The canopy-scale vortices penetrate a finite distance into the canopy, δe, set by the canopy drag. This length scale segregates the canopy into two regions: The upper canopy experiences energetic turbulent transport, controlled by canopy-scale vortices, whereas the lower canopy experiences diminished transport, associated with the smaller stem-scale turbulence. The canopy-scale vortices induce a waving motion in flexible blades, called a monami.
Analyzing and predicting Lifetime of trends using social networks

Trending topics in any social networking site are those specific trends that are most popular and talked about at that point in time. The emergence, survival and eventual fading away of a trend are a function of various factors. In this paper, an exhaustive list of determinants is pioneered with respect to the survival of a trend. Using the first determinant, Interest Over Time, and utilizing sentiment analysis over the textual data associated with the trend, the longevity of a trend is predicted. Additionally, a modified and more accurate mathematical equation for Trend Survival Score is formulated where Predictive Analysis and Modeling with First Order Differential Equations is done with the other two determinants. In order to map the Lifetime Score to a timeframe relevant to real-world scenario, K-nearest neighbor approach is used (using k=3) considering how lifetime score of a trend converts to actual lifetime in the training data.
Retrieving Images of Scanned Text Documents

Information retrieval is the task of nding documents, usually text, which are relevant to a user's information need. A conventional approach to information management of paper documents is normally based on classifying them into a hierarchical classiication structure. More recently we have seen electronic document management systems which manage scanned images of documents in the same way as paper, or which do some OCR to determine machine-readable document content which may then be used for content-based information retrieval. In this paper we present an alternative to full-scale OCR of scanned document images in which words in scanned images of documents are represented as word shape tokens (WSTs) representing the approximate shape of words in text. We describe an approach to WST-based information retrieval that can be entirely automatic or can involve the user in reening the retrieval process. To measure the eeectiveness of WST-based retrieval we have implemented and reened it on two collections of documents/queries/relevance judgments, one in English, the other in French. Each of these has over 250 Mbytes of ASCII text and in indexing documents we have faithfully recreated the kind and frequency of errors expected in a WST recognition process. When compared to word-based retrieval, the eeectiveness of WST-based retrieval is surprisingly good, though erratic across diierent queries. We outline some of the directions we are pursuing in order to address this inconsistency of performance across queries and our results show real potential for WST-based retrieval of scanned document images.
THrombolysis for Acute Wake-up and unclear-onset Strokes with alteplase at 0·6 mg/kg (THAWS) Trial

Rationale Because of lack of information regarding timing of stroke, patients who suffer stroke during sleep are generally ineligible for intravenous thrombolysis, although many of these patients could potentially recover with this treatment. Magnetic resonance image findings with positive diffusion-weighted imaging and no marked parenchymal hyperintensity on fluid-attenuated inversion recovery (negative pattern) can identify acute ischemic stroke patients within 4·5 h from symptom onset. Aims The THrombolysis for Acute Wake-up and unclear-onset Strokes with alteplase at 0·6 mg/kg trial aims to determine the efficacy and safety of intravenous thrombolysis with alteplase at 0·6 mg/kg body weight, the approved dose for Japanese stroke patients, using magnetic resonance image-based selection in ischemic stroke patients with unclear time of symptom onset, and compare findings with standard treatment. Design This is an investigator-initiated, multicenter, prospective, randomized, open-treatment, blinded-end-point clinical trial. The design is similar to the Efficacy and Safety of MRI-based Thrombolysis in Wake-up Stroke trial. Patients with unclear-onset time of stroke symptoms beyond 4·5 h and within 12 h after the time of the last-known-well period and within 4·5 h after symptom recognition, who showed a negative fluid-attenuated inversion recovery pattern, are randomized to either intravenous thrombolysis or standard treatment. Study outcomes The primary efficacy end-point is modified Rankin Scale 0–1 at 90 days. The safety outcome measures are symptomatic intracranial hemorrhage at 22–36 h, and major bleeding and mortality at 90 days. Discussion This trial may help determine if low-dose alteplase at 0·6 mg/kg should be recommended as a routine clinical strategy for ischemic stroke patients with unclear-onset time.
Modular robotics for playful physiotherapy

We developed modular robotic tiles to be used for playful physiotherapy, which is supposed to motivate patients to engage in and perform physical rehabilitation exercises. We tested the modular robotic tiles for an extensive period of time (3 years) in daily use in a hospital rehabilitation unit e.g. for cardiac patients. Also, the tiles were tested for performing physical rehabilitation of stroke patients in their private home. In all pilot test cases qualitative feedback indicate that the patients find the playful use of modular robotic tiles engaging and motivating for them to perform the rehabilitation. Also, initial pilot test data suggest that some playful exercises on the tiles demand an average heart rate of 75% and 86% of the maximum heart rate.
International Journal of Innovative Research in Computer and Communication Engineering Fused Index Code Based Multibiometric Pattern Retrieval Security System

Biometric authentication has been receiving extensive attention over the past decade with increasing demands in automated personal identification. Biometrics is to identify individuals using physiological or behavioral characteristics, such as fingerprint, face, iris, retina, palm-print, etc. Among all the biometric techniques, fingerprint and face recognition [1] is the most popular methods and is successfully used in many applications.Biometric identification system have huge underlying biometric database. In this large identification system, the goal is to determine the identity of a subject from a large set of users already enrolled in biometric database. Though the state-of-art biometric identification algorithm work well for small database in terms of accuracy and response time but fail to scale well for large databases.Classification and indexing can be used to filter the search space during identification process. Classification is procedure where data points are placed into different groups called classes, based on therequantitive information and already classified data points.In identification, the class of query biometric is first identified and then it is compared to each biometric present in the class. In indexing, feature extraction techniques are used and assigned the index value to them using different indexing techniques. The given query is only compared to templates which have comparable index.In this paper we propose an indexing technique for multimodal database which is capable of reducing the response time of biometric identification systems by reducing the search space during identification.
A laser power management method for on-Chip photonic interconnect

Photonic interconnects can provide huge bandwidths and have emerged as a promising communication backbones for future many-core systems. However, the static power dissipated in the laser source may limit the performance of future photonic NoC (Network-on-Chip) by dominating the stringent network power budget. In this paper, a laser power supply scheme based on Single-Write-Multi-Read (SWMR) crossbar is proposed. The laser power is dynamically adjusted by predicting the future network requirement at runtime. The evaluation shows that the laser power consumption is effectively reduced compared with the static power supply method.
Spring phenology and timing of breeding in short-distance migrant birds: phenotypic responses and offspring recruitment patterns in common goldeneyes

Understanding how organisms adjust breeding dates to exploit resources that aff ect fi tness can provide insights into impacts of climate change on avian demography. For instance, mismatches have been reported in long-distance migrant bird species when environmental cues experienced during spring migration are decoupled from conditions on breeding grounds. Short-distance migrant bird species that store reproductive nutrients prior to breeding may avoid or buff er adverse phenological eff ects. Furthermore, reduced short-term reproductive success could be off set by higher future recruitment of surviving off spring. We evaluated whether recruitment of locally-hatched female off spring was related to hatching date alone or strength of mismatched breeding date for 405 individually-marked adult female common goldeneyes Bucephala clangula (a short-distance migrant) and their ducklings from a site in central Finland where ice-out date has advanced by ∼ 2 weeks over 24 yr. Path analyses revealed that older, early-nesting females with good body condition and larger broods recruited the most female off spring. Off spring recruitment decreased strongly among females that bred late relative to other females in the population each year; the extent of mismatched breeding date, i.e. hatching date scaled to annual ice-out date, was less infl uential. Overall, most females advanced breeding dates when ice-out occurred earlier in spring, but some females exhibited greater fl exibility in response to ice-out conditions than did others. In general, directional selection favoured early breeding over a wide range of ice-out dates. Our results seem most consistent with a hypothesis that some short-distance migrant species like goldeneyes have the capacity to track and respond appropriately to changing environmental conditions prior to onset of breeding.
Modeling sharp wave‐ripple complexes through a CA3‐CA1 network model with chemical synapses

The hippocampus, and particularly the CA3 and CA1 areas, exhibit a variety of oscillatory rhythms that span frequencies from the slow theta range (4–10 Hz) up to fast ripples (˜200 Hz). Various computational models of different complexities have been developed in an effort to simulate such population oscillations. Nevertheless the mechanism that underlies the so called Sharp Wave‐Ripple complex (SPWR), observed in extracellular recordings in CA1, still remains elusive. We present here, the combination of two simple but realistic models of the rat CA3 and CA1 areas, connected together in a feedforward scheme mimicking Schaffer collaterals. Both network models are computationally simple one‐dimensional arrays of excitatory and inhibitory populations interacting only via fast chemical synapses. Connectivity schemes and postsynaptic potentials are based on physiological data, yielding a realistic network topology. The CA3 model exhibits quasi‐synchronous population bursts, which give rise to sharp wave‐like deep depolarizations in the CA1 dendritic layer accompanied by transient field oscillations at ∼150–200 Hz in the somatic layer. The frequency and synchrony of these oscillations is based on interneuronal activity and fast‐decaying recurrent inhibition in CA1. Pyramidal cell spikes are sparse and come from a subset of cells receiving stronger than average excitatory input from CA3. The model is shown to accurately reproduce a large number of basic characteristics of SPWRs and yields a new mechanism for the generation of ripples, offering an interpretation to a range of neurophysiological observations, such as the ripple disruption by halothane and the selective firing of pyramidal cells during ripples, which may have implications for memory consolidation during SPWRs. © 2011 Wiley Periodicals, Inc.
Numerical Approximation of Relaxed Variational Problems

Non-quasiconvex variational problems require, in general, a relaxation to ensure existence of their solutions. Here a relaxation by (generalized) Young functionals is used and then a nite-element method for a direct numerical approximation of the relaxed problems is developed. Beside a mere convergence, also some error estimates are analysed and a comparison with other methods is discussed.
Effects of Animations in Zooming and Panning Operations on Web maps: A Web-based Experiment

Abstract The presentation of graphics and maps on the Internet has led to the development of several new techniques. The use of dynamics and animations in maps has increased, and new types of applications are emerging frequently. Recently, several map providers on the web have introduced zooming in maps as an animated operation. In this paper, we look closer into how the animated zoom is perceived by participants in an experiment, and compare these observations with a corresponding test where the map scale is changed in more abrupt steps. The results indicate significant preference for the animated zoom. The experiment itself is carried out through the World Wide Web and all the participants made their contribution from their own computers.
Extending SPARQL for Recommendations

For processing data on the Web, recommender systems and SPARQL are two popular paradigms, which however have rather different characteristics. SPARQL is a declarative language on RDF graphs which allows a user to precisely specify the desired information. In contrast, a recommender system suggests certain items to a user, based on similarity to other users or items. As the data to be processed by a recommender may be an RDF graph as well, the question arises whether both processing paradigms can benefit from each other. RecSPARQL fills this gap by extending the syntax and semantics of SPARQL to enable a generic and flexible way for collaborative filtering and content-based recommendations over arbitrary RDF graphs. Our experiments on the MovieLens data set demonstrate the applicability of our approach.
Liposome Technology for Industrial Purposes

Liposomes, spherical vesicles consisting of one or more phospholipid bilayers, were first described in the mid 60s by Bangham and coworkers. Since then, liposomes have made their way to the market. Today, numerous lab scale but only a few large-scale techniques are available. However, a lot of these methods have serious limitations in terms of entrapment of sensitive molecules due to their exposure to mechanical and/or chemical stress. This paper summarizes exclusively scalable techniques and focuses on strengths, respectively, limitations in respect to industrial applicability. An additional point of view was taken to regulatory requirements concerning liposomal drug formulations based on FDA and EMEA documents.
A scheme of primary path switching for mobile terminals using SCTP handover

Stream Control Transmission Protocol (SCTP) is a new transport layer protocol for end-to-end data transport. SCTP can be used to support soft handover for mobile terminal with the help of the SCTP multihoming feature. For SCTP handover, a mobile terminal is required to switch the primary path to one of the promising alternative paths. This paper proposes a new scheme of the primary path switching for SCTP handover, which is based on the absolute gap and relative ratio of the Round Trip Times (RTTs) measured for the primary and alternative paths. For experiments, we consider the ping-pong movement pattern, which a mobile terminal moves around the two different IP networks. From the experiments we see that a conservative scheme is preferred for primary switching in the networks with relatively small absolute gaps of RTTs, whereas an aggressive scheme needs to be considered in the cases with large absolute RTT gaps.
Data Provenance, Evidence-Based Policy Assessment, and e-Social Science

This paper considers how the concept of data pro venance, developed in e-Science, can be applied to e-Social Science, specifically Evidence Based Policy Ass es ment. It considers what Evidence Based Policy Assessment is and wh at types of information can be used in such research. Quantitative and qualitative data a nd analytical/ interpretative approaches are outlined and the implications of these for the development of a provenance architecture/ model for Evidence Based Policy Assessment ar suggested. The schema for the implementation of an e-based provenance system, work undertaken as part of the wi der PolicyGrid project, is outlined. The paper concludes by off ering thoughts on the contributions that the application of data provenance co ncepts to Evidence Based Policy Assessment can make.
An ACO algorithm for graph coloring problem

Ant colony optimization (ACO) is a well-known metaheuristic in which a colony of artificial ants cooperate in exploring good solutions to a combinatorial optimization problem. In this paper, an ACO algorithm is presented for the graph coloring problem. This ACO algorithm conforms to max-min ant system structure and exploits a local search heuristic to improve its performance. Experimental results on DIMACS test instances show improvements over existing ACO algorithms of the graph coloring problem
Applying virtualization to avionics systems — The integration challenges

Multicore virtualization can offer significant benefits to embedded avionics systems with regard to enabling mixed real-time and guest operating system interoperability, legacy code migration, and hardware consolidation. Virtualization enabled architectures have evolved from a traditional Hypervisor Monolithic Model (VmWare and VirtualLogix), to a Hypervisor Console Guest Monolithic Model (Xen), and now to a High Assurance Microkernel Hypervisor RTOS Model. The ability to consolidate multiple legacy Single Board Computers (SBCs) with various guest operating systems and applications into a multicore, virtualized SBC is a critical enabler to next generation avionics. This paper describes an initial feasibility assessment toward applying the Microkernel Hypervisor RTOS Virtual Machine (VM) architecture to enable virtualization for a representative set of avionics applications requiring multiple guest OS environments. The specific notional configuration included: legacy application execution on a legacy RTOS guest OS in VM1, newer application execution on a more recently released level of RTOS on VM2, safety critical applications execution on an ARINC 653 OS on VM3, Global Information Grid (GIG) applications execution on a Linux guest OS on VM4, and MILS/MLS application execution on a high assurance OS on VM5, all executing on a Microkernel Hypervisor RTOS within a Multicore (X86 or Power PC) with hardware-based virtualization support. The paper identifies the current system design issues, limitations/restrictions, and feasibility of applying representative products in this representative hybrid legacy/next generation environment. The system design challenges identified included: 1. ) selection of communication mechanisms and scheduling for mixed operating system environments, 2. ) addressing current limitations/restrictions of current vendor products with regard to multicore, 3. ) properly scheduling the infrastructure to meet the safety and security requirements, 4. ) incorporating extensions for MultiLevel Security (MLS) components for networked GIG and local connectivity, and 5. ) consolidating I/O components without compromising safety, security, and redundancy considerations.
Low complexity tonality control in the Intelligent Gap Filling tool

When coding audio signals at low bitrates with a transform coder the most prominent artifacts are spectral holes resulting from spectral lines being quantized to zero. State of the art codecs circumvent this by Noise Filling [1] and Bandwidth Extension (BWE) [2]. Both methods have in common that they do not code parts of the waveform itself but code a coarse description of the signal. At decoder side a synthetic signal is generated and adjusted according to the coded parameters. The presented system called Intelligent Gap Filling (IGF) is a combination of both methods. Spectral holes are filled with random noise or with copied decoded signal components from lower frequency regions. In the latter case a control mechanism is required to adjust the tonality of the copied signal components to reach good audio quality. This paper describes the way of controlling the tonality of IGF. The presented approach is of low complexity and allows for selective application without producing additional algorithmic delay. IGF is part of the 3GPP standard Enhanced Voice Services (EVS) as well as MPEG-H standardized by Moving Picture Experts, Group (MPEG).