Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of Motion EstimationAlgorithm for H.265/HEVC

The most essential part of almost all video coding standards such as H.262/MPEG-2, H.264/MPEG-4 and newly emerged High Efficiency Video Coding (H.265/HEVC) is Motion Estimation. HEVC provides better performance in compression and efficiency in coding for Beyond HD and UHD videos. The main drawback is its computationcomplexity. The complexity is mainly due to Motion Estimation (ME), as it consumes more than half of time to encode. Many fast motion estimation algorithms have been developed so as to reduce the complexity in encoding. This paper proposes the implementation of New Combined Three Step Search pattern for ME algorithm. The simulation result shows average time saving of 50.07%and slight improvement in quality compared with existing patterns.A System is designed using Altera System on a Programmable Chip (SOPC) builder and the algorithm is being implemented using Nios-II software build tools to get optimal performance
Korean Version of Mini Mental Status Examination for Dementia Screening and Its' Short Form

Objective We developed a Korean version of Mini-Mental Status Examination (MMSE) optimized for screening dementia (MMSE-DS) and its' short form (SMMSE-DS). Methods We constructed the MMSE-DS using the items of the two current Korean versions of MMSE and then construct the SMMSE-DS consisted of 13 items from the MMSE-DS based on the diagnostic accuracy of individual items for dementia. We investigated reliability and validity of MMSE-DS and SMMSE-DS on 1,555 subjects (1,222 nondemented controls, 333 dementia patients). We compared the diagnostic accuracy of the SMMSE-DS with that of the three full Korean versions of MMSE, and examined its' age- and education-specific optimal cutoff scores for dementia. Results The internal consistency obtained by Cronbach's coefficient alpha was 0.826. The inter-rater reliability and test-retest reliability were 0.968 (p<0.001) and 0.825 (p<0.001), respectively. It showed significant correlation with the Clinical Dementia Rating (CDR) (r=-0.698, p<0.05) and the three full Korean versions of MMSE (r=0.839-0.938, p<0.001). The area under the receiver operator curve for dementia of the SMMSE-DS was larger than those of the three full Korean versions of MMSE (p<0.001). Age, education and gender explained 19.4% of the total variance of SMMSE-DS scores. The optimal cutoff scores for dementia of the SMMSE-DS were estimated differently by age and educational attainment of the subjects. Conclusion The SMMSE-DS was found to be accurate, brief and portable instrument for screening dementia in Korean elders, and may be particularly useful for screening dementia in elderly populations with wide variation in educational levels.
Improvement of Ringing Artifact Reduction Using a K-Means Method for Color Moving Pictures

This paper proposes an improved method that uses a K-means method to effectively reduce the ringing artifacts in a color moving picture. To apply this improved K-method, we set the number of groups for the process to two (K=2) in the three dimensional R, G, B color space. We then improved the R, G, B color value of all of the pixels by moving the current R, G, Bcolor value of each pixel to calculated center values, which reduced the ringing artifacts. The results were verified by calculating the overshoot and the slope of the light luminance around the edges of test images that had been processed by the new algorithm. We then compared the calculated results with the overshoot and slope of the light luminance of the unprocessed image.
Turbo compressed channel sensing for millimeter wave communications with massive antenna arrays and RF chain constraints

With the abundant frequency spectrum available at millimeter wave (MMW) frequency bands, MMW communications can easily achieve multi-gigabit wireless transmission. One key challenge for MMW system is the design of an efficient and fast channel estimation algorithm with limited RF chains to facilitate the beamforming and coherent detection, in compensation for the severe propagation attenuation. In this paper, an efficient channel estimation algorithm is developed for MMW systems with massive antenna arrays and RF chain constrains to achieve: i) a significant reduction of the time slot consumption; ii) a great enhancement of the estimation reliability in the low signal-to-noise ratio (SNR) region. By fully exploiting the sparse structure of channel in MMW frequency bands, an efficient training method is designed to achieve the fast and reliable channel estimation based on the compressed sensing (CS) methods. An iterative soft decoding method, termed turbo compressed channel sensing (TCCS), is developed to estimate the channel state information (CSI) by iteratively updating the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner, which refines the estimation by exploiting the sparsity of CSI. Simulation results show that the proposed approach greatly outperforms existing approaches.
The effect of concomitant ecstasy-marijuana use on auditory verbal learning and memory performance

The Effect of Concomitant Ecstasy-Marijuana Use on Auditory Verbal Learning and Memory Performance by Kimberly M. Cramer Dr. Douglas Ferraro, Examination Committee Chair Professor of Psychology University o f Nevada, Las Vegas Previous research indicates that ecstasy users exhibit deficits of verbal learning and memory. This research has not considered polydrug use in ecstasy users, especially marijuana. Marijuana is an important confound because 90 percent of ecstasy users also use marijuana. Several studies have suggested that marijuana use alters verbal memory functioning; consequently, it is difficult to ascertain whether the observed memory deficits in ecstasy users are attributable to ecstasy, marijuana, or other drug use. The present study examined the effects of marijuana and ecstasy on verbal memory function. Marijuana use was accounted for by recruiting concurrent ecstasy-marijuana users’ and ecstasy-naïve marijuana-only users. Furthermore, the extent of marijuana use was controlled for in the combined ecstasy-marijuana and marijuana-only groups by assigning marijuana users to either the marijuana light or marijuana heavy experimental groups. Recent animal findings suggest that at low frequencies marijuana may exert neuroprotective effects against ecstasy-induced neurotoxicity. Alternatively, other animal
Applications of graph theory in chemistry

Graph theoretical (GT) applications in chemistry underwent a dramatic revival lately. Constitutional (molecular) graphs have points (vertices) representing atoms and lines (edges) symbolizing malent bonds. This review deals with definition. enumeration. and systematic coding or nomenclature of constitutional or steric isomers, valence isomers (especially of annulenes). and condensed polycyclic aromatic hydrocarbons. A few key applications of graph theory in theoretical chemistry are pointed out. The complete set of all poasible monocyclic aromatic and heteroaromatic compounds may be explored by a mmbination of Pauli's principle, P6lya's theorem. and electronegativities. Topological indica and some of their applications are reviewed. Reaction graphs and synthon graphs differ from constitutional graphs i n their meaning of vertices and edges and find other kinds of chemical applications. This paper ends with a review of the use of GT applications for chemical nomenclature (nodal nomenclature and related areas), coding. and information processing/storage/retrieval
Creating high-quality , large-scale bilingual knowledge bases using minimal resources

We describe a complete production cycle for the semi-automatic development of bilingual knowledge bases. The methodology is based on the optional availability of a source language monolingual corpus and on employing lexicographers who only need to be bilingual and computer literate. Bilingual resources (corpora, Machine Readable Dictionaries, etc.) are not required, and the employment of skilled and trained personnel is minimized, thus making the approach suitable for minority languages. The methodology is language independent and has been extensively used in generating an English-Spanish bilingual lexicon for Machine Translation.
Absorbing Boundary Conditions for Compact Finite-Difference Modeling of Acoustic and Elastic Wave Propagation in the 2 D TI Medium by

This article presents decoupling n-times absorbing boundary conditions designed to model acoustic and elastic wave propagation in a 2D transversely isotropic (TI) medium. More general n-times boundary conditions with absorbing parameters are also obtained by cascading first-order differential operators with parameters. These boundary conditions are approximated with simple finite-difference schemes for numerical simulations. The numerical results show that the absorbing for the reflection waves strengthens with increasing the absorbing times n and the discretization boundary formulas are stable. Specially, the n-times absorbing boundary condition with absorbing parameters is better than that without the absorbing parameters under the case of same absorbing order. Elastic wave fields and threecomponent synthetic seismograms, generated by using the compact finite-difference and the decoupling n-times absorbing boundary, also illustrate that the n-times absorbing boundary condition can eliminate effectively the spurious numerical reflections in the acoustic and elastic wave modeling for the TI medium case.
of Women ' s Status A Multilevel Factor Model for Mixed Binary and Ordinal Indicators

can be found at: Sociological Methods & Research Additional services and information for http://smr.sagepub. com/cgi/alerts Email Alerts: http://smr.sagepub. com/subscriptions Subscriptions: http://www.sagepub. com/journalsReprints.nav Reprints: http://www.sagepub. com/journalsPermissions.nav Permissions: http://smr.sagepub. com/cgi/content/refs/35/1/137 SAGE Journals Online and HighWire Press platforms): (this article cites 10 articles hosted on the Citations
Dynamic Spectrum Sensing for Energy Harvesting Wireless Sensor

Energy harvesting wireless sensors are driven by electric power extracted from hidden environmental source of energy, such as imperceptible vibrations of walls and floors. It has been shown that radio transmitter system can be powered by energy harvesters with substituting ring for crystal oscillators, which, however, causes frequency instability in oscillator. In order to receive message from such sensors, a receiver must be able to accurately detect transmitted frequencies that may differ among respective sensors. Fast wideband radio frequency sensing schemes using filter-based energy detectors were proposed. These schemes were designed to detect radio devices operating according to known specifications, this paper proposes a dynamic spectrum sensing scheme using a fast fourier transform (FFT) based energy detector for radio devices without knowing radio frequencies. The experimental and theoretical results of this study demonstrate that dynamic spectrum sensing with an FFT-based energy detector can retrieve signal frequencies faster than traditional schemes. It is also shown that it is possible to calculate a suitable set of parameters for minimizing the total sensing time associated with any given pairing of frequency missing rate and resolution.
Multiple‐change‐point detection for auto‐regressive conditional heteroscedastic processes

The emergence of the recent financial crisis, during which markets frequently underwent changes in their statistical structure over a short period of time, illustrates the importance of non‐stationary modelling in financial time series. Motivated by this observation, we propose a fast, well performing and theoretically tractable method for detecting multiple change points in the structure of an auto‐regressive conditional heteroscedastic model for financial returns with piecewise constant parameter values. Our method, termed BASTA (binary segmentation for transformed auto‐regressive conditional heteroscedasticity), proceeds in two stages: process transformation and binary segmentation. The process transformation decorrelates the original process and lightens its tails; the binary segmentation consistently estimates the change points. We propose and justify two particular transformations and use simulation to fine‐tune their parameters as well as the threshold parameter for the binary segmentation stage. A comparative simulation study illustrates good performance in comparison with the state of the art, and the analysis of the Financial Times Stock Exchange FTSE 100 index reveals an interesting correspondence between the estimated change points and major events of the recent financial crisis. Although the method is easy to implement, ready‐made R software is provided.
Generating and Analyzing Test cases from Software Requirements using NLP and Hadoop

Software testing is the most critical step of software development since it ensures that the system under developments free of errors and unprecedented faults and matches the expectation and requirements elicited from users and stakeholders. However, the process of testing is currently a manual process and is thus prone to mistakes by human testers and timeconsuming and arduous. This paper proposes the automation of the task of generating test cases from software requirements written in natural language. This solves the problems of human errors and requirement of manual effort in ensuring coverage of requirements specified during requirements elicitation. It also enables test cases to be generated early on in the software development lifecycle based on requirements documents. The method we propose involves taking software requirements expressed in natural language as input and processing them using natural language processing techniques such as POS tagging and parsing. These NLP constructs are used to represent the requirements in the form of tree structures, which are used to generate knowledge graphs that depict the essential flow of the system. These paths can be traversed using methods such as boundary value analysis, etc. to obtain a suite of test cases.
Noncommutative general relativity

We define a theory of noncommutative general relativity for canonical noncommutative spaces. We find a subclass of general coordinate transformations acting on canonical noncommutative spacetimes to be volume-preserving transformations. Local Lorentz invariance is treated as a gauge theory with the spin connection field taken in the so(3,1) enveloping algebra. The resulting theory appears to be a noncommutative extension of the unimodular theory of gravitation. We compute the leading order noncommutative correction to the action and derive the noncommutative correction to the equations of motion of the weak gravitation field.
Characterological Correlates of Selfie Taking Behavior

Few researchers have examined selfie taking behavior. To address this gap, 235 participants (age 18 - 60) completed an online questionnaire assessing a variety of psychological factors, personality traits, and selfie taking activities (i.e., frequency of selfies posted to social networking sites [SNSs], time spent editing selfies, and number of selfie takes prior to posting). A number of statistically significant correlations emerged. For example, participants’ levels of neuroticism, social physique anxiety, body-related shame, and concern about physical appearance correlated positively with the amount of time spent editing selfies. As well, group comparisons between selfie (n = 193) and non-selfie takers (n = 42) suggest that the former exhibit higher levels of certain facets of vanity. The implications of these findings and directions for future research are outlined.
Adhesion and Invasion of Gastric Mucosa Epithelial Cells by Helicobacter pylori

Helicobacter pylori is the main pathogenic bacterium involved in chronic gastritis and peptic ulcer and a class 1 carcinogen in gastric cancer. Current research focuses on the pathogenicity of H. pylori and the mechanism by which it colonizes the gastric mucosa. An increasing number of in vivo and in vitro studies demonstrate that H. pylori can invade and proliferate in epithelial cells, suggesting that this process might play an important role in disease induction, immune escape and chronic infection. Therefore, to explore the process and mechanism of adhesion and invasion of gastric mucosa epithelial cells by H. pylori is particularly important. This review examines the relevant studies and describes evidence regarding the adhesion to and invasion of gastric mucosa epithelial cells by H. pylori.
Statistical study of the night-time F-layer dynamics at the magnetic equator in West Africa during the solar minimum period 1995-1997

Abstract. In this paper, we report on the night-time equatorial F-layer height behaviour at Korhogo (9.2° N, 5° W; 2.4° S dip lat), Ivory Coast, in the West African sector during the solar minimum period 1995–1997. The data were collected from quarter-hourly ionograms of an Ionospheric Prediction Service (IPS) 42-type vertical sounder. The main focus of this work was to study the seasonal changes in the F-layer height and to clarify the equinox transition process recently evidenced at Korhogo during 1995, the year of declining solar flux activity. The F-layer height was found to vary strongly with time, with up to three main phases. The night-to-night variability of these morphological phases was then analysed. The early post-sunset slow rise, commonly associated with rapid chemical recombination processes in the bottom part of the F layer, remained featureless and was observed regardless of the date. By contrast, the following event, either presented like the post-sunset height peak associated with the evening E × B drift, or was delayed to the midnight sector, thus involving another mechanism. The statistical analysis of the occurrence of these events throughout the solar minimum period 1995–1997 revealed two main F-layer height patterns, each characteristic of a specific season. The one with the post-sunset height peak was associated with the northern winter period, whereas the other, with the midnight height peak, characterized the northern summer period. The transition process from one pattern to the other took place during the equinox periods and was found to last only a few weeks. We discuss these results in the light of earlier works.
ToPoliNano: Nanoarchitectures design made real

Many facts about emerging nanotechnologies are yet to be assessed. There are still major concerns, for instance, about maximum achievable device density, or about which architecture is best fit for a specific application. Growing complexity requires taking into account many aspects of technology, application and architecture at the same time. Researchers face problems that are not new per se, but are now subject to very different constraints, that need to be captured by design tools. Among the emerging nanotechnologies, two-dimensional nanowire based arrays represent promising nanostructures, especially for massively parallel computing architectures. Few attempts have been done, aimed at giving the possibility to explore architectural solutions, deriving information from extensive and reliable nanoarray characterization. Moreover, in the nanotechnology arena there is still not a clear winner, so it is important to be able to target different technologies, not to miss the next big thing. We present a tool, ToPoliNano, that enables such a multi-technological characterization in terms of logic behavior, power and timing performance, area and layout constraints, on the basis of specific technological and topological descriptions. This tool can aid the design process, beside providing a comprehensive simulation framework for DC and timing simulations, and detailed power analysis. Design and simulation results will be shown for nanoarray-based circuits. ToPoliNano is the first real design tool that tackles the top down design of a circuit based on emerging technologies.
Enhancing stability of essential oils by microencapsulation for preservation of button mushroom during postharvest

Fresh button mushrooms (Agaricus bisporus L.) are sensitive to browning, water loss, and microbial attack. The short shelf-life of mushrooms is an impediment to the distribution and marketing of the fresh product. Essential oils outstand as an alternative to chemical preservatives and their use in foods meets the demands of consumers for natural products. To resolve controlled release of oil and increase in antioxidant and antimicrobial activities, the oil was incorporated into microcapsules. Effects of microcapsulated thyme (Thymus vulgaris L.) and rosemary (Rosmarinus officinalis L.) on quality of fresh button mushroom were compared. Physicochemical qualities were evaluated during 15 days of storage at 4 ± 0.5°C. All treatments prevented product weight loss and decrease in polyphenoloxidase and peroxidase activities during storage. Color and firmness, microbiological analysis, and total phenolic content caused the least change. With use of microencapsulated oils, mushrooms were within acceptable limits during 10 days of storage. Microencapsulated rosemary oil produced the highest beneficial effects and has potential to improve quality of button mushrooms and extend shelf-life.
Comparing Segmentation by Time and by Motion in Visual Search: An fMRI Investigation

Brain activity was recorded while participants engaged in a difficult visual search task for a target defined by the spatial configuration of its component elements. The search displays were segmented by time (a preview then a search display), by motion, or were unsegmented. A preparatory network showed activity to the preview display, in the time but not in the motion segmentation condition. A region of the precuneus showed (i) higher activation when displays were segmented by time or by motion, and (ii) correlated activity with larger segmentation benefits behaviorally, regardless of the cue. Additionally, the results revealed that success in temporal segmentation was correlated with reduced activation in early visual areas, including V1. The results depict partially overlapping brain networks for segmentation in search by time and motion, with both cue-independent and cue-specific mechanisms.
Organizational modelling and problem solving using object-oriented knowledge representation server and visual language

Object-oriented knowledge representation systems allow an organization to be modeled in an understandable way. User interaction with such a system is enhanced if the graphic representations normally used, such as organization charts and room layout plans, are supported through visual languages directly generating the underlying knowledge structures. The operational and problem-solving procedures of an organization expressed visually within this framework become overt and accessible, and their implementation and consequences can be automated and evaluated. This paper reports some experience in the design and implementation of a lightweight, objectoriented knowledge representation server, and its application to organizational modeling and problem solving. The primary user interface is through a formal visual language implemented as a drawing environment on graphic workstations. The open architecture implementation of the server allows it to be integrated with existing applications, such as corporate database and accounting systems, and also allows functionality to be added through self-contained modules requiring no changes in the kernel system.