Miracle-dz/UniFAR-FTUs huggingface dataset:
A method of wavelet selection in phoneme recognition

In this paper a method is proposed for choosing between different wavelets, and their corresponding parameters, and it is applied to TIMIT phoneme classification. The method involves the use of a Kohonen network to extract prototypes for each class. Distance measures between them are used as criteria for choosing the best wavelet. In the case of phoneme classification, a time delay neural network is used as the classifier. A high correlation is found between results of the proposed method and the classification accuracy obtained by the network.
Design and Implementation of a Hybrid Digital Phase-Locked Loop With a TMS 320 C 25 mAn Application to a Transponder Receiver

Design, modeling, analysis, and simulation of a phase-locked loop (PLL) with a digital loop filter are presented in this article. A TMS320C25 digital signal processor (DSP) is used to implement this digital loop filter, irn order to keep the compatibility, the main design goal was to replace the analog PLL (APLL) of the Deep-Space Transponder (DST) receiver breadboard's loop filter with a digital loop filter without changing anything else. This replacement results in a hybrid digital PLL (HDPLL). Both the original APLL and the designed HDPLL are Type I second-order systems. The real-time performance of the HDPLL and the receiver is provided and evaluated.
Psycholinguistic Approaches to Vocabulary

A psycholinguistic approach to vocabulary is aimed at understanding how individuals store words in their mental dictionary, how they retrieve those words, and how their level of proficiency in each language affects lexical processing. The cornerstone of psycholinguistic approaches to vocabulary is the use of behavioral methods to measure how quickly (using reaction times in milliseconds) and accurately individuals process language. The nature of the questions and the experimental tasks vary when investigating individuals at beginning stages of bilingualism (i.e., language learners) and more skilled individuals (i.e., proficient bilinguals). Keywords: psycholinguistics; second language acquisition; vocabulary
Positive versus Negative Neuroimaging in Relation to Mild Traumatic Brain Injury Outcome : A Meta-Analysis

Positive versus Negative Neuroimaging in Relation to Mild Traumatic Brain Injury Outcome: A Meta-Analysis Thomas J. Farrer Department of Psychology Master of Science Mild Traumatic Brain Injury (mTBI) can be broken into two categories; complicated and uncomplicated. These categories are based on structural imaging scans during the assessment of the injury. If abnormalities appear in the scan, we refer to it as complicated. The present research aims at determining whether there are differences in the neuropsychological deficits in the presences of positive neuroimaging as opposed to negative neuroimaging. This was accomplished with meta-analytic techniques. It was found that neuroimaging does not predict neuropsychological functioning in the chronic state of mTBI.
Spatial Active Learning For Cost-Effective Sensing and Feature Extraction

Pool-based active learning methods have historically been used as a means to reduce the amount of supervised data necessary to learn accurate inference models. However, such methods assume that the pool of unsupervised instances from which the active learner chooses is known a priori. More specifically, the active learner must have access to the features of these instances that will be used for learning. In many practical learning scenarios there is a cost in obtaining these features. For instance, feature extraction methods may be computationally expensive, or simply observing instances can be expensive when state-of-the-art sensors are required. Hence pool-based active learning methods, while cost effective in supervision, can be deemed data inefficient due to the need for a pool of fully descriptive data instances.
Internet over direct broadcast satellites

High-powered direct broadcast television satellites can be used to broadcast high volumes of data directly to home terminals. Using the telephone network or a similar low-speed network, an asymmetrical system can be implemented which offers interactive Internet services. Two such interactive data broadcast systems are described which have been implemented as demonstration platforms for interactive multimedia services; one is based on digital subcarrier techniques for analog television channels, the other on the MPEG-2 and DVB standards. The architecture of the hardware and software is presented, particularly the solutions available for carrying Internet datagrams over MPEG-2 transport systems. A multicast transport protocol with selectable reliability is described which is the basis of a generic distribution application. It exploits the potential benefits of direct broadcast satellites for delivering data to large groups of local caches.
Enhanced modeling : real-time simulation and modeling of graph based problems on interactive workbenches

This thesis presents a methodology and framework for designing systems that apply real-time simulation of computational models throughout the modeling and parameter modification stages of problem solving for graph based broblems. An interactive problem solving technique is presented where the lines between problem modeling and simulation are blurred, enhancing the outcome of traditional problem solving. To demonstrate the versatility of the framework and methodology, two applications not normally thought of as graph problems a circuit design application and an airport passenger flow application are developed and tested. Three user studies test various parts of the framework, as well as the overall concept of real-time simulation on an interactive workbench. The first study provides quantitative support for the efficacy of the interaction technique chosen for manipulating graph structures. The second provides observational results of using the circuit design application to teach physics. The third addresses whether blurred lines of modeling and analysis enhance problem solving. Thesis Supervisor: Hiroshi Ishii Title: Associate Professor of Media Arts and Sciences
I. Diversification of membrane trafficking pathways associated with the acquisition of novel machinery components

Membrane traffic between single membrane-bounded organelles plays an integral role in various activities in eukaryotic cells. Recent comparative genomics has indicated that membrane trafficking pathways are diversified among eukaryotic lineages, which are associated with the lineage-specific acquisition of new trafficking pathways and the secondary loss of preexisting trafficking routes. Our long-term goal is to reveal how plants have acquired their unique membrane trafficking systems during evolution. This will be achieved by comparative analyses using the model plant Arabidopsis thaliana and a liverwort model, Marchantia polymorpha. We also aim to elucidate the detailed molecular mechanisms and physiological functions of membrane trafficking in higher-ordered plant functions. In collaboration with other groups with expertise in artificial intelligence, we are also developing a framework to deliver new findings in the basic biology field.
Analysis of Clustering Algorithms in E-Commerce using WEKA

Data clustering is a process of putting similar dat a into groups. A clustering algorithm partitions a data se t into several groups such that the similarity within a gr oup is larger than among groups. Moreover, most of the dat a collected in many problems seem to have some inhere t properties that lend themselves to natural grouping s. Clustering algorithms are used extensively not only to organize and categorize data, but are also useful f or data compression and model construction. This paper reviews on types of clustering techniquesk-Means Clusteri ng, Hierarchical Clustering, DBScan clustering, Optics, EM Algorithm.
SuperKEKB入射器における RF電子銃用レーザーの高性能化 IMPROVEMENT OF THE LASER SYSTEM FOR RF-GUN AT SUPERKEKB INJECTOR

SuperKEKB project is aimed at the generation of electron beams with a charge of 5 nC and a normalized emittance of 10 μm at injector linac. According to these demands, an Ytterbium (Yb) laser system is selected for RF-gun. For realizing the laser system operating under 25 Hz with double pulses or 50 Hz under single pulse operation, Yb-doped fiber and Yb:YAG thin-disk hybrid laser system with a central wavelength of 259 nm and a pulse width of 20 ps is developed. 3.0 nC bunch charge has been gotten by use of current laser system. In order to achieve more stable and efficient electron beam, improvements has been being done. In this letter, some improvements are introduced for optimizing the laser system.
An adaptive low complexity and high performance BLAST detection algorithm

It is well known that MIMO channel capacity was greatly improved by used of BLAST code, but the existing methods still have the decoding complexity and precision problem. This paper analyzes the advantage and disadvantage of the present detection algorithms for the BLAST system. An adaptive BLAST decoding algorithm with lower decoding complexity is proposed. The simulations show that the adaptive detection can achieve the moderate tradeoff between complexity and performance.
Potential anomaly separation using genetically trained multi-level cellular neural networks

In this paper, multi-level genetic cellular neural networks (ML-GCNN) are applied to the geophysical problem of potential anomaly separation and satisfactory results are obtained, compared to classical deterministic approaches. ML-GCNN is a stochastic image processing technique which is based on template optimisation using neighbourhood relationships of the pixels. The residual anomaly separation used in location decisions is one of the main problems in geophysics. The method proposed here is used in evaluating the Dumluca iron ore region of Turkey.
Improvement of cloud and convective Parameterizations in Climate Forecast System Version 2 ( CFSv 2 ) : Indian Summer Monsoon perspective

Acknowledging the challenge of simulating the mean and intraseasonal variability of Indian Summer monsoon by a coupled climate model CFSv2 (originally adopted from NCEP, USA), a holistic and thorough approach through modifying physical processes namely the cloud and convection is being presented in this report. Considering the CFSv2 systematic biases arising due to inappropriate representation of sub-grid scale and grid scale cloud processes, attempts are being made here, to test a revised sub-grid scale convection scheme namely Revised Simplified Arakawa-Schubert scheme. This scheme is found to improve the dry bias over Indian land mass, wet bias over equatorial Indian ocean and also the diurnal rainfall variability over Indian region. However, it could not improve the cold tropospheric temperature bias in the CFSv2. Keeping this in mind, the state-of-the art approach of superparameterization is used and a superparameterized version of CFSv2 (SP-CFS) has been developed. Apart from improving the annual cycle, northward propagation and the proportion of synoptic (2-10 days) and Intraseasonal Oscillation (10-90 days), the SP-CFS is able to improve the temperature bias. In spite of the success of SP-CFS, the major challenge is the computational expense which prohibits such approach to be adopted in operational forecasting. Keeping this in mind, the CFSv2 grid scale cloud microphysics has been revised by using a prognostic scheme for six class hydrometeors (WSM6). The revised CFS (CFS-CR) with modified sub-grid scale convection (Revised SAS), modified cloud microphysics (WSM6) is found to simulate a much realistic mean global and monsoon climate. Further it also shows promising improvement in capturing the spatio-temporal distribution of clouds in association with Boreal summer Intraseasonal Oscillation. This report thus clearly brings out the role of robust cloud and convection processes in modulating the coupled model (CFSV2) mean and intraseasonal variability. The modified CFSv2 namely CFS-CR will be tested further to evaluate its hindcast skill in future.
Active Self-Tracking and Visualization of Subjective Experience using VAS and Time Spirals on a Smartwatch

In this paper, we describe a smartwatch-based system that enables self-tracking and registration of subjective experience (such as pain) using a VAS-like scale, as well as allowing the acquired data to be visualized directly on the smartwatch. The data visualization is tailor-made for the round smartwatch form factor using an interactive time spiral. Our proof-of-concept prototype implementation is described along with a case study where the application has been used to self-track back pain as the phenomenon of interest. It is found that the smartwatch allows momentary self-registration when the phenomenon occurs and that the spiral structure of the data visualization facilitate identifying recurring patterns in the data.
Synthetic Sensor of Landsat 7 ETM + Imagery to Compare and Evaluate Pan-sharpening Methods

Several studies and applications are present in literature to compare pan-sharpening methods: the greater part of them is based on indexes that relate radiometric characteristics of derived images to the correspondent original ones. Among others correlation index, RMSE (Root Mean Square Error), UIQI (Universal Image Quality Index) and RASE (Relative Average Spectral Error) are used, but evaluation is limited if there aren’t other multispectral images with higher geometric resolution to which compare the pan-sharpened results. In this paper Landsat 7 ETM+ artificial sensor was introduced to permit more reliable comparison and evaluation of pan-sharpening methods. Data concerning Campania region (Italy) were used: firstly Landsat 7 ETM+ panchromatic image and multispectral ones with acquisition bands within that of pan were processed to conduct their digital numbers to radiance values; then synthetic sensor was considered and geometric resolutions degraded by reducing original pixel dimensions 15 m × 15 m and 30 m × 30 m respectively to 30 m × 30 m and 60 m × 60 m. In other terms, new images were derived as equivalent products to those that should have been obtained by sensor with lower geometric resolutions but same acquisition bands of Landsat 7 ETM+ (panchromatic and multispectral). Pan-sharpening methods were applied to derived images and products compared with original data so to obtain a credible evaluation of performances of the implemented approaches. Copyright © 2014 IFSA Publishing, S. L.
Design & Development of Regenerative Braking System at Rear Axle

In this work, a new methodology with external generator is developed for regenerative braking system. Experimental test setup is developed to verify the feasibility of new methodology. Results are verified using Matlab Simulink simulation. About 10 to 12% of battery energy can be regenerated and stored into battery which shows 10 to 12% increase in Electric vehicles mileage.
Identification of Lactobacillus Species Isolated From Traditional Dairy Products Using RAPD-PCR

Background: Probiotics are non-pathogenic useful microorganisms having positive effects on the host health. The aim of the present study was to discriminate Lactobacillus species extracted from traditional dairy products. Methods: This study was conducted on 26 specimens collected from traditional dairy products in Bukan. Lactobacillus species were separated and purified employing biochemical tests. Then, the intra/inter-species diversity was investigated using RAPD-PCR (random amplified polymorphic DNA-polymerase chain reaction) technique. Results: Polymorphism information content (PIC) value varied between 15.9% and 34.4% with a maximum value of 34.4% associated with primer 1254. The mean of and Marker index (MI) for the 6 primers was 4.52, in which the maximum and minimum values belonged to the primers 1254 and OPA-02, respectively. The isolates were categorized into 4 main clusters according to Jaccard similarity coefficient using UPGMA (unweighted pair group method with arithmetic means) clustering method. Principle coordinates analysis (PCoA) demonstrated that the first and second components explained 30.59% and 22.48% of variances, i.e. 53.07% of variances in total. The results of RAPD marker indicated that the intra-species diversity was greater than inter-species diversity. The intra-group variance explained 94% of the all variance, while inter-group variance explained only 6% of the all variance. Moreover, the results of analysis of molecular variance (AMOVA) indicated that the highest level of discrimination occurred at the 16 groups cut-off point with a similar coefficient of 0.56. Conclusions: From the results of the present study, it can be concluded that traditional dairy products are enriched sources of probiotic bacteria which can ensure the health of general population and enhance their immunoe systems. Moreover, RAPD-PCR is an appropriate method for detection and calssification of lactobassiluses.
Optimal speckle reduction in multi-look polarimetric SAR image

Presents a method, called the multi-look polarimetric whitening filtering (MPWF), to reduce speckle in multi-look polarimetric SAR image by processing elements of the complex covariance matrix into pixel intensity that minimizes the image speckle. By considering a multiplicative speckle model, the solution of the MPWF is proved to be the maximum likelihood (ML) estimation of the scalar texture parameter. The performance of the MPWF for detection of targets in clutter is also analyzed. Experimental results with NASA/JPL L-band 4-look polarimetric SAR data demonstrate the effectiveness of the presented method. Compared with the span and.
Randomized global optimization for robust pose estimation of multiple targets in image sequences

The problem of determining the position and pose of multiple targets in an image sequence can be treated as a mathematical optimization problem. Therefore we show a technique based on randomized black-box optimization to detect multiple targets with similar appearance in bird’s-eye view image sequences. An easy to adapt cost-map and parameter-constraints are used to design a fitness-function evaluated for each target separately. Especially for crowded targets in limited space like in livestock-environments this approach is able to demonstrate its strengths. The detection performance is evaluated on two hand-labeled data-sets of piglets, recorded for behaviour studies. Detection rates above 90% at runtimes of 220ms per processed frame prove the potential of the proposed technique.
Patterns of rats and treeshrews in bornean rainforest inferred from marK-recaPture data

Movement and space-use patterns influence animal population dynamics and interactions with the environment in various ways. In this study, we estimated movement patterns of six rat (Muridae) and four treeshrew (Tupaiidae) species from Borneo based on mark-recapture data in three unlogged and three logged rainforest sites. The treeshrews Tupaia gracilis, T. longipes, and T. tana moved longer straight-line distances than any of the observed rats, with the largest movement distances recorded for T. longipes. The largest mean movement distance for rats was observed for the giant rat leopoldamys sabanus, while the shortest movements were recorded for the rats Maxomys whiteheadi and Sundamys muelleri. Generally, rats showed a higher frequency of short movements than treeshrews, suggesting that rats are more restricted in their ranging patterns compared with the more exploratory movements of treeshrews. Mixed effects modeling suggests a significant impact of forest type on movement patterns of l. sabanus, and marginal impacts on the movements of N. cremoriventer and T. longipes. Significant sexand age-specific effects were detected for l. sabanus, N. cremoriventer, M. surifer, M. whiteheadi, S. muelleri, T. longipes, and T. gracilis. Interacting effects such as forest age and type on movements of l. sabanus, as well as the relatively weak effect of forest type in mixed-effects analysis for T. tana, in contrast to univariate analysis, indicate that various factors appear to simultaneously influence movements. While trapping data allow a first insight into how species of rats and treeshrews differ in using the rainforest environment, more detailed and specific investigations are needed to understand space-use patterns. Accepted 26 November 2008.
Expression of the a v b 6 Integrin Promotes Migration and Invasion in Squamous Carcinoma Cells

*Department of Oral Pathology, Eastman Dental Institute, University College London, U.K.; 2Department of Orthodontics, Eastman Dental Institute, University College London, U.K.; 3Department of Dermatology, Stanford University Medical Center, Palo Alto, California, U.S.A. ; §Lung Biology Center, UCSF, San Francisco, California, U.S.A. ; ¶Richard Dimbleby/ICRF Department of Cancer Research, Kings College, St. Thomas' Hospital, London, U.K.
Use Rodents as an Indicator of Environmental Pollution

Human is one of the biggest factors that cause pollution in the environment at the local or global level. At the local level, the impact of man is confined to the small environment surrounding it. On the global level, the effect of human pollution of the atmosphere resulting in global climate change. Therefore, rodents can be used as a biological indicator to assess the damage caused to the environment as a result of exposure to pollution factors that cause imbalance in the environment and affected by humans, plants and animals.
Gaming to Make Sense of Risks : Toward a Thicker Description of Game-Based Training

In the past decades we have seen an increased interest in the use of games beyond entertainment. Although a few successes are known and valuable insights are provided on the use of games for impact, the field is in dire need of comprehensive and rigorous studies. To fill this gap in the area of game-based training, in this chapter the study and results of a unique game called Levee Patroller are discussed. In this game, players will need to make sense of levee risks. The study’s objectives were to design and implement an innovative game-based training intervention that would allow to gather empirical evidence as well as a substantiated understanding of how participants experienced the training and played the game. A mixed methods research design was employed using questionnaires, tests, and game data, among others. With the results a “thicker description” was retrieved from which it became clear that games can be a potentially powerful tool to enable players to make sense of phenomena, but that the full potential has not been reached. Future research should continue to employ mixed methods research designs to capture the complexity inherent in playing games and to bring game research to another next level.