nils-herrmann/clean_scirepeval huggingface dataset:
An Efficient Distributed Trust Model for Wireless Sensor Networks

Trust models have been recently suggested as an effective security mechanism for Wireless Sensor Networks (WSNs). Considerable research has been done on modeling trust. However, most current research work only takes communication behavior into account to calculate sensor nodes' trust value, which is not enough for trust evaluation due to the widespread malicious attacks. In this paper, we propose an Efficient Distributed Trust Model (EDTM) for WSNs. First, according to the number of packets received by sensor nodes, direct trust and recommendation trust are selectively calculated. Then, communication trust, energy trust and data trust are considered during the calculation of direct trust. Furthermore, trust reliability and familiarity are defined to improve the accuracy of recommendation trust. The proposed EDTM can evaluate trustworthiness of sensor nodes more precisely and prevent the security breaches more effectively. Simulation results show that EDTM outperforms other similar models, e.g., NBBTE trust model.
Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: Simulations and application to finger tapping data

Today, the concept of brain connectivity plays a central role in the neuroscience. While functional connectivity is defined as the temporal coherence between the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally between cortical sites. The most used method to estimate effective connectivity in neuroscience is the structural equation modeling (SEM), typically used on data related to the brain hemodynamic behavior. However, the use of hemodynamic measures limits the temporal resolution on which the brain process can be followed. The present research proposes the use of the SEM approach on the cortical waveforms estimated from the high-resolution EEG data, which exhibits a good spatial resolution and a higher temporal resolution than hemodynamic measures. We performed a simulation study, in which different main factors were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). Such factors were the signal-to-noise ratio and the duration of the simulated cortical activity. Since SEM technique is based on the use of a model formulated on the basis of anatomical and physiological constraints, different experimental conditions were analyzed, in order to evaluate the effect of errors made in the a priori model formulation on its performances. The feasibility of the proposed approach has been shown in a human study using high-resolution EEG recordings related to finger tapping movements.
iTransformer: Using SSD to Improve Disk Scheduling for High-performance I/O

The parallel data accesses inherent to large-scale data-intensive scientific computing require that data servers handle very high I/O concurrency. Concurrent requests from different processes or programs to hard disk can cause disk head thrashing between different disk regions, resulting in unacceptably low I/O performance. Current storage systems either rely on the disk scheduler at each data server, or use SSD as storage, to minimize this negative performance effect. However, the ability of the scheduler to alleviate this problem by scheduling requests in memory is limited by concerns such as long disk access times, and potential loss of dirty data with system failure. Meanwhile, SSD is too expensive to be widely used as the major storage device in the HPC environment. We propose iTransformer, a scheme that employs a small SSD to schedule requests for the data on disk. Being less space constrained than with more expensive DRAM, iTransformer can buffer larger amounts of dirty data before writing it back to the disk, or prefetch a larger volume of data in a batch into the SSD. In both cases high disk efficiency can be maintained even for concurrent requests. Furthermore, the scheme allows the scheduling of requests in the background to hide the cost of random disk access behind serving process requests. Finally, as a non-volatile memory, concerns about the quantity of dirty data are obviated. We have implemented iTransformer in the Linux kernel and tested it on a large cluster running PVFS2. Our experiments show that iTransformer can improve the I/O throughput of the cluster by 35% on average for MPI/IO benchmarks of various data access patterns.
A flexible stream architecture for ASR using articulatory features

Recently, speechrecognitionsystemsbasedon articulatory featuressuchas“voicing” or thepositionof lips andtonguehave gainedinterest,becausethey promiseadvantageswith respectto robustnessandpermitnew adaptationmethodsto compensatefor channel,noise,andspeakervariability. Theseapproachesarealso interestingfrom a generalpoint of view, becausetheir modelsuse phonological andphoneticconcepts,which allow for a richerdescriptionof a speechactthanthesequenceof HMM-states,which is theprevalentASRarchitecturetoday. In thiswork, wepresenta multi-streamarchitecture,in which CD-HMMS aresupportedby detectorsfor articulatoryfeatures,usinga linear combinationof log-likelihood scores.Thismulti-streamapproachresultsin a15% reductionof WER on a readBroadcast-Ne ws (BN) taskand improvesperformanceon a spontaneouschedulingtask(ESST)by 7%. Theproposedarchitecturepotentiall y allows for new speaker andchanneladaptationschemes, includingstreamasynchronicity .
Finding shell company accounts using anomaly detection

Money laundering refers to activities pertaining to hiding the true income, evading taxes, or converting illegally earned money for normal use. These activities are often performed through shell companies that masquerade as real companies but where actual the purpose is to launder money. Shell companies are used in all the three phases of money laundering, namely, placement, layering, and integration, often simultaneously. In this paper, we aim to identify shell companies. We propose to use only bank transactions since that is easily available. In particular, we look at all incoming and outgoing transactions from a particular bank account along with its various attributes, and use anomaly detection techniques to identify the accounts that pertain to shell companies. Our aim is to create an initial list of potential shell company candidates which can be investigated by financial experts later. Due to lack of real data, we propose a banking transactions simulator (BTS) to simulate both honest as well as shell company transactions by studying a host of actual real-world fraud cases. We apply anomaly detection algorithms to detect candidate shell companies. Results indicate that we are able to identify the shell companies with a high degree of precision and
MAPS: Multiresolution Adaptive Parameterization of Surfaces

We construct smooth parameterizations of irregular connectivity triangulations of arbitrary genus 2-manifolds. Our algorithm uses hierarchical simplification to efficiently induce a parameterization of the original mesh over a base domain consisting of a small number of triangles. This initial parameterization is further improved through a hierarchical smoothing procedure based on Loop subdivision applied in the parameter domain. Our method supports both fully automatic and user constrained operations. In the latter, we accommodate point and edge constraints to force the align∗wailee@cs.princeton.edu †wim@bell-labs.com ‡ps@cs.caltech.edu §cowsar@bell-labs.com ¶dpd@cs.princeton.edu ment of iso-parameter lines with desired features. We show how to use the parameterization for fast, hierarchical subdivision connectivity remeshing with guaranteed error bounds. The remeshing algorithm constructs an adaptively subdivided mesh directly without first resorting to uniform subdivision followed by subsequent sparsification. It thus avoids the exponential cost of the latter. Our parameterizations are also useful for texture mapping and morphing applications, among others.
Multiple Sequence Alignment Using MATLAB

Sequence alignment is an important task in bioinformatics which involves typical database search where data is in the form of DNA, RNA or protein sequence. For alignment various methods have been devised starting from pairwise alignment to multiple sequence alignment (MSA). To perform multiple sequence alignment various methods exists like progressive, iterative and concepts of dynamic programming in which we use Needleman Wunsch and Smith Waterman algorithms. This paper discusses various sequence alignment methods including their advantages and disadvantages. The alignment results of DNA sequence of chimpanzee and gorilla are shown.
The "Art" Of Log Correlation - Tools And Techniques For Correlating Events And Log Files

Log file correlation is related to two distinct activities: Intrusion Detection and Network Forensics. It is more important than ever that these two disciplines work together in a mutualistic relationship in order to avoid Points of Failure. This paper, intended as a tutorial for those dealing with such issues, presents an overview of log analysis and correlation, with special emphasis on the tools and techniques for managing them within a network forensics context. In particular it will cover the most important parts of Log Analysis and correlation, starting from the Acquisition Process until the analysis.
A new Bagrid catfish species, Rita bakalu (Siluriformes: Bagridae), from the Godavari River basin, India

Rita bakalu, a new species, is described from the Godavari river system in peninsular India. With this finding, the genus Rita is enlarged to include seven species, comprising six species found in South Asia, R. rita, R. macracanthus, R. gogra, R. chrysea, R. kuturnee, R. bakalu, and one species R. sacerdotum from Southeast Asia. R. bakalu is distinguished from its congeners by a combination of the following characters: eye diameter 28–39% HL and 20–22 caudal fin rays; teeth in upper jaw uniformly villiform in two patches, interrupted at the midline; palatal teeth well-developed villiform, in two distinct patches located at the edge of the palate. The mtDNA cytochrome C oxidase I sequence analysis confirmed that the R. bakalu is distinct from the other congeners of Rita. Superficially, R. bakalu resembles R. kuturnee, reported from the Godavari and Krishna river systems; however, the two species are discriminated due to differences in the structure of their teeth patches on upper jaw and palate, anal fin originating before the origin of adipose fin, comparatively larger eye diameter, longer mandibular barbels, and vertebral count. The results conclude that the river Godavari harbors a different species of Rita, R. bakalu which is new to science.
Antialiasing recovery

We present a method for restoring antialiased edges that are damaged by certain types of nonlinear image filters. This problem arises with many common operations such as intensity thresholding, tone mapping, gamma correction, histogram equalization, bilateral filters, unsharp masking, and certain nonphotorealistic filters. We present a simple algorithm that selectively adjusts the local gradients in affected regions of the filtered image so that they are consistent with those in the original image. Our algorithm is highly parallel and is therefore easily implemented on a GPU. Our prototype system can process up to 500 megapixels per second and we present results for a number of different image filters.
Introduction to Computing and Programming in Python - a Multimedia Approach, 4th Edition

What do you do to start reading introduction to computing and programming in python a multimedia approach 2nd edition? Searching the book that you love to read first or find an interesting book that will make you want to read? Everybody has difference with their reason of reading a book. Actuary, reading habit must be from earlier. Many people may be love to read, but not a book. It's not fault. Someone will be bored to open the thick book with small words to read. In more, this is the real condition. So do happen probably with this introduction to computing and programming in python a multimedia approach 2nd edition.
Azo dyes – biological activity and synthetic strategy

Azo dyes – a fatal threat or a new generation of drugs? In 1858 Griss developed the azo coupling reaction and obtained first azo dye – Aniline Yellow. Nowadays, around 10 thousands of these compounds are described and more than 2 thousands are applied to color various materials. Azo dyes are characterized by the presence of the azo moiety (–N=N–) in their structure, conjugated with two, distinct or identical, monoor polycyclic aromatic systems. Because of their specific physico-chemical properties and biological activities, they have found a broad application in pharmaceutical, cosmetic, food, dyeing/textile industry and analytical chemistry. However, the most typical and popular field of utility remains their coloring function. Azo dyes are the largest and the most versatile class of dyes. They possess intense bright colors, in particular oranges, reds and yellows. In addition, azo dyes exhibit a variety of interesting biological activities. Medical importance of these compounds is well known for their antibiotic, antifungal and anti-HIV properties. On the other hand they bring a certain danger for health and environment because of canceroand mutagenicity. In this review, selected synthetic strategies and biological activities of azo dyes are presented, the latter in the context of a therapeutic potential and a hazard connected with their production and application.
Evaluation of candidate genes MAP2K4, MADH4, ACVR1B, and BRCA2 in familial pancreatic cancer: deleterious BRCA2 mutations in 17%.

It is estimated that familial aggregation and genetic susceptibility play a role in as many as 10% of pancreatic ductal adenocarcinomas. To investigate the role of germ-line mutations in the etiology of pancreatic cancer, we have analyzed samples from patients with pancreatic cancer enrolled in the NFPTR for mutations in four tumor suppressor candidate genes: (a) MAP2K4; (b) MADH4; (c) ACVR1B; and (d) BRCA2 by direct sequencing of constitutional DNA. These genes are mutated in clinically sporadic pancreatic cancer, but germ-line mutations are either not reported or anecdotal in familial pancreatic cancer. Pancreatic cancer patient samples were selected from kindreds in which three or more family members were affected with pancreatic cancer, at least two of which were first-degree relatives. No mutations were identified in mitogen-activated protein kinase kinase 4 (0 of 22), MADH4 (0 of 22), or ACVR1B (0 of 29), making it unlikely that germ-line mutations in these genes account for a significant number of inherited pancreatic cancers. BRCA2 gene sequencing identified five mutations (5 of 29, 17.2%) that are believed to be deleterious and one point mutation (M192T) unreported previously. Three patients harbored the common 6174delT frameshift mutation, one had the splice site mutation IVS 16-2A > G, and one had the splice site mutation IVS 15-1G > A. Two of the five BRCA2 mutation carriers reported a family history of breast cancer, and none reported a family history of ovarian cancer. These findings confirm the increased risk of pancreatic cancer in individuals with BRCA2 mutations and identify germ-line BRCA2 mutations as the most common inherited genetic alteration yet identified in familial pancreatic cancer.
Algorithms for subset selection in linear regression

We study the problem of selecting a subset of k random variables to observe that will yield the best linear prediction of another variable of interest, given the pairwise correlations between the observation variables and the predictor variable. Under approximation preserving reductions, this problem is equivalent to the "sparse approximation" problem of approximating signals concisely. The subset selection problem is NP-hard in general; in this paper, we propose and analyze exact and approximation algorithms for several special cases of practical interest. Specifically, we give an FPTAS when the covariance matrix has constant bandwidth, and exact algorithms when the associated covariance graph, consisting of edges for pairs of variables with non-zero correlation, forms a tree or has a large (known) independent set. Furthermore, we give an exact algorithm when the variables can be embedded into a line such that the covariance decreases exponentially in the distance, and a constant-factor approximation when the variables have no "conditional suppressor variables". Much of our reasoning is based on perturbation results for the R2 multiple correlation measure, which is frequently used as a natural measure for "goodness-of-fit statistics". It lies at the core of our FPTAS, and also allows us to extend our exact algorithms to approximation algorithms when the matrix "nearly" falls into one of the above classes. We also use our perturbation analysis to prove approximation guarantees for the widely used "Forward Regression" heuristic under the assumption that the observation variables are nearly independent.
Wideband Circularly Polarized E-Shaped Patch Antenna for Wireless Applications [Wireless Corner]

A new technique to achieve a circularly polarized probe-fed single-layer microstrip-patch antenna with a wideband axial ratio is proposed. The antenna is a modified form of the conventional E-shaped patch, used to broaden the impedance bandwidth of a basic patch antenna. By letting the two parallel slots of the E patch be unequal, asymmetry is introduced. This leads to two orthogonal currents on the patch and, hence, circularly polarized fields are excited. The proposed technique exhibits the advantage of the simplicity of the E-shaped patch design, which requires only the slot lengths, widths, and position parameters to be determined. Investigations of the effect of various dimensions of the antenna have been carried out via parametric analysis. Based on these investigations, a design procedure for a circularly polarized E-shaped patch was developed. A prototype has been designed, following the suggested procedure for the IEEE 802.11big WLAN band. The performance of the fabricated antenna was measured and compared with simulation results. Various examples with different substrate thicknesses and material types are presented and compared with the recently proposed circularly polarized U-slot patch antennas.
High dynamic range video

Typical video footage captured using an off-the-shelf camcorder suffers from limited dynamic range. This paper describes our approach to generate high dynamic range (HDR) video from an image sequence of a dynamic scene captured while rapidly varying the exposure of each frame. Our approach consists of three parts: automatic exposure control during capture, HDR stitching across neighboring frames, and tonemapping for viewing. HDR stitching requires accurately registering neighboring frames and choosing appropriate pixels for computing the radiance map. We show examples for a variety of dynamic scenes. We also show how we can compensate for scene and camera movement when creating an HDR still from a series of bracketed still photographs.
Cryptography on Android Message Applications - A Review

Short Message Service (SMS) is a text messaging service component of phone, web, or mobile communication systems, using standardized communications protocols that allow the exchange of short text messages between fixed line or mobile phone devices. Security of SMS’s is still an open challenging task. Various Cryptographic algorithms have been applied to secure the mobile SMS. The success of any cryptography technique depends on various factors like complexity, time, memory requirement, cost etc. In this paper we survey the most common and widely used SMS Encryption techniques. Each has its own advantages and disadvantages. Recent trends on Cryptography on android message applications have also been discussed. The latest cryptographic algorithm is based on lookup table and dynamic key which is easy to implement and to use and improve the efficiency. In this paper, an improvement in lookup table and dynamic algorithm is proposed. Rather than using the Static Lookup Table, Dynamic Lookup Table may be used which will improve the overall efficiency. KeywordsSMS, AES, DES, Blowfish, RSA, 3DES, LZW.
Cultural Suppression of Female Sexuality

Four theories about cultural suppression of female sexuality are evaluated. Data are reviewed on cross-cultural differences in power and sex ratios, reactions to the sexual revolution, direct restraining influences on adolescent and adult female sexuality, double standard patterns of sexual morality, female genital surgery, legal and religious restrictions on sex, prostitution and pornography, and sexual deception. The view that men suppress female sexuality received hardly any support and is flatly contradicted by some findings. Instead, the evidence favors the view that women have worked to stifle each other’s sexuality because sex is a limited resource that women use to negotiate with men, and scarcity gives women an advantage.
A compact quasi-millimeter-wave microstrip wideband bandpass filter

In this paper, a quasi-millimeter-wave wideband bandpass filter (BPF) is designed by using a microstrip dual-mode ring resonator and two folded half-wavelength resonators. Based on the transmission line equivalent circuit of the filter, variations of the frequency response of the filter versus the circuit parameters are investigated first by using the derived formulas and circuit simulators. Then a BPF with a 3dB fractional bandwidth (FBW) of 20% at 25.5 GHz is designed, which realizes the desired wide passband, sharp skirt property, and very wide stopband. Finally, the designed BPF is fabricated, and its measured frequency response is found agree well with the simulated result.
Exploring User-Specific Information in Music Retrieval

With the advancement of mobile computing technology and cloud-based streaming music service, user-centered music retrieval has become increasingly important. User-specific information has a fundamental impact on personal music preferences and interests. However, existing research pays little attention to the modeling and integration of user-specific information in music retrieval algorithms/models to facilitate music search. In this paper, we propose a novel model, named User-Information-Aware Music Interest Topic (UIA-MIT) model. The model is able to effectively capture the influence of user-specific information on music preferences, and further associate users' music preferences and search terms under the same latent space. Based on this model, a user information aware retrieval system is developed, which can search and re-rank the results based on age- and/or gender-specific music preferences. A comprehensive experimental study demonstrates that our methods can significantly improve the search accuracy over existing text-based music retrieval methods.