Effect of FES Cycling Training on Spasticity in Spinal Cord Injured Subjects

Training with Functional Electrical Stimulation (FES) has both physiological and psychological benefits for spinal cord injured subjects. Commonly used methods for quantification of spasticity have shown controversial reliability. In this study we propose a method for quick determination of spasticity in spinal cord injured subjects on a cycling and measurement system. 23 patients did training sessions on an instrumented mobile FES cycle three times a week over two months as part of their clinical rehabilitation program. Spasticity (MAS) and the legs resistance to the pedaling motion were assessed before and after the FES training and measurements were done on the subjects ability to pedal with our without motor assistance. Measurements with test persons with incomplete spastic paraplegia have shown that spasticity is decreased after a 30 min cycling training with functional electrical stimulation (FES).

Mass Casualty Acute Pepper Spray Inhalation Respiratory Effect Severity

Pepper spray use has gained momentum since 1992 and although the active ingredient is readily available, it is considered a weapon with restricted use in many regions, including The Bahamas. In light of controversy in the literature regarding the severity of presenting respiration complaints among individuals postacute exposure of pepper spray inhalation, this descriptive case series study was conducted to assess the respiratory status of persons evaluated during a mass casualty in The Bahamas. Parameters noted were patients- demographics and respiration severity determined via clinical examination findings, disposition and follow-up review of the 20 persons. Their most common complaint was difficulty breathing post exposure. Two required admission and stayed for

The Study on the Wireless Power Transfer System for Mobile Robots

A wireless power transfer system can attribute to the fields in robot, aviation and space in which lightening the weight of device and improving the movement play an important role. A wireless power transfer system was investigated to overcome the inconvenience of using power cable. Especially a wireless power transfer technology is important element for mobile robots. We proposed the wireless power transfer system of the half-bridge resonant converter with the frequency tracking and optimized power transfer control unit. And the possibility of the application and development system was verified through the experiment with LED loads.

Design Based Performance Prediction of Component Based Software Products

Component-Based software engineering provides an opportunity for better quality and increased productivity in software development by using reusable software components [10]. One of the most critical aspects of the quality of a software system is its performance. The systematic application of software performance engineering techniques throughout the development process can help to identify design alternatives that preserve desirable qualities such as extensibility and reusability while meeting performance objectives [1]. In the present scenario, software engineering methodologies strongly focus on the functionality of the system, while applying a “fix- it-later" approach to software performance aspects [3]. As a result, lengthy fine-tunings, expensive extra hard ware, or even redesigns are necessary for the system to meet the performance requirements. In this paper, we propose design based, implementation independent, performance prediction approach to reduce the overhead associated in the later phases while developing a performance guaranteed software product with the help of Unified Modeling Language (UML).

Analysis of the EEG Signal for a Practical Biometric System

This paper discusses the effectiveness of the EEG signal for human identification using four or less of channels of two different types of EEG recordings. Studies have shown that the EEG signal has biometric potential because signal varies from person to person and impossible to replicate and steal. Data were collected from 10 male subjects while resting with eyes open and eyes closed in 5 separate sessions conducted over a course of two weeks. Features were extracted using the wavelet packet decomposition and analyzed to obtain the feature vectors. Subsequently, the neural networks algorithm was used to classify the feature vectors. Results show that, whether or not the subjects- eyes were open are insignificant for a 4– channel biometrics system with a classification rate of 81%. However, for a 2–channel system, the P4 channel should not be included if data is acquired with the subjects- eyes open. It was observed that for 2– channel system using only the C3 and C4 channels, a classification rate of 71% was achieved.

Response Surface Modeling of Lactic Acid Extraction by Emulsion Liquid Membrane: Box-Behnken Experimental Design

Extraction of lactic acid by emulsion liquid membrane technology (ELM) using n-trioctyl amine (TOA) in n-heptane as carrier within the organic membrane along with sodium carbonate as acceptor phase was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined effect of five independent variables, vizlactic acid concentration in aqueous phase (cl), sodium carbonate concentration in stripping phase (cs), carrier concentration in membrane phase (ψ), treat ratio, and batch extraction time (τ)  with equal volume of organic and external aqueous phase on lactic acid extraction efficiency. The maximum lactic acid extraction efficiency (ηext) of 98.21%from aqueous phase in a batch reactor using ELM was found at the optimized values for test variables, cl, cs, ψ, and τ as 0.06 [M], 0.18 [M], 4.72 (%,v/v), 1.98 (v/v) and 13.36 min respectively. 

Thai Perception on Litecoin Value

This research analyzes factors affecting the success of Litecoin Value within Thailand and develops a guideline for selfreliance for effective business implementation. Samples in this study included 119 people through surveys. The results revealed four main factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Litecoin within the community. 4) A great majority didn't know what Litecoin was. The guideline for self-reliance planning consisted of 4 aspects: 1) Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into every day usage. Local communities need to develop awareness of the usefulness of Litecoin and share the value of Litecoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Litecoin within their departments. 3) Further research should be pursued on how Litecoin Value can improve business and tourism within Thailand. 4) Local communities should focus on developing Litecoin awareness by encouraging street vendors to accept Litecoin as another form of payment for services rendered.

Nonlinear and Chaotic Motions for a Shock Absorbing Structure Supported by Nonlinear Springs with Hysteresis Using Fast FEA

This paper describes dynamic analysis using proposed fast finite element method for a shock absorbing structure including a sponge. The structure is supported by nonlinear concentrated springs. The restoring force of the spring has cubic nonlinearity and linear hysteresis damping. To calculate damping properties for the structures including elastic body and porous body, displacement vectors as common unknown variable are solved under coupled condition. Under small amplitude, we apply asymptotic method to complex eigenvalue problem of this system to obtain modal parameters. And then expressions of modal loss factor are derived approximately. This approach was proposed by one of the authors previously. We call this method as Modal Strain and Kinetic Energy Method (MSKE method). Further, using the modal loss factors, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. This transformation yields computation efficiency. As a numerical example of a shock absorbing structures, we adopt double skins with a sponge. The double skins are supported by nonlinear concentrated springs. We clarify influences of amplitude of the input force on nonlinear and chaotic responses.

Using Different Aspects of the Signings for Appearance-based Sign Language Recognition

Sign language is used by the deaf and hard of hearing people for communication. Automatic sign language recognition is a challenging research area since sign language often is the only way of communication for the deaf people. Sign language includes different components of visual actions made by the signer using the hands, the face, and the torso, to convey his/her meaning. To use different aspects of signs, we combine the different groups of features which have been extracted from the image frames recorded directly by a stationary camera. We combine the features in two levels by employing three techniques. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, or by concatenating feature groups over time and using LDA to choose the most discriminant elements. At the model level, a late fusion of differently trained models can be carried out by a log-linear model combination. In this paper, we investigate these three combination techniques in an automatic sign language recognition system and show that the recognition rate can be significantly improved.

Microalgal Lipid Production by Microalgae Chlorella sp. KKU-S2

The objective of this work is to produce heterotrophic microalgal lipid in flask-batch fermentation. Chlorella sp. KKU-S2 supported maximum values of 0.374 g/L/d, 0.478 g lipid/g cells, and 0.112 g/L/d for volumetric lipid production rate, and specific yield of lipid, and specific rate of lipid production, respectively when culture was performed on BG-11 medium supplemented with 50g/L glucose. Among the carbon sources tested, maximum cell yield coefficient (YX/S, g/L), maximum specific yield of lipid (YP/X, g lipid/g cells) and volumetric lipid production rate (QP, g/L/d) were found of 0.728, 0.237, and 0.619, respectively, using sugarcane molasses as carbon source. The main components of fatty acid from extracted lipid were palmitic acid, stearic acid, oleic acid and linoleic acid which similar to vegetable oils and suitable for biodiesel production.

Hand Gesture Recognition Based on Combined Features Extraction

Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Our system is based on three main stages; automatic segmentation and preprocessing of the hand regions, feature extraction and classification. In automatic segmentation and preprocessing stage, color and 3D depth map are used to detect hands where the hand trajectory will take place in further step using Mean-shift algorithm and Kalman filter. In the feature extraction stage, 3D combined features of location, orientation and velocity with respected to Cartesian systems are used. And then, k-means clustering is employed for HMMs codeword. The final stage so-called classification, Baum- Welch algorithm is used to do a full train for HMMs parameters. The gesture of alphabets and numbers is recognized using Left-Right Banded model in conjunction with Viterbi algorithm. Experimental results demonstrate that, our system can successfully recognize hand gestures with 98.33% recognition rate.

Simulation of Activity Stream inside Energy Social Business Environment using Assemblage Theory and Simplicial Complex Tool

Social, mobility and information aggregation inside business environment need to converge to reach the next step of collaboration to enhance interaction and innovation. The following article is based on the “Assemblage" concept seen as a framework to formalize new user interfaces and applications. The area of research is the Energy Social Business Environment, especially the Energy Smart Grids, which are considered as functional and technical foundations of the revolution of the Energy Sector of tomorrow. The assemblages are modelized by means of mereology and simplicial complexes. Its objective is to offer new central attention and decision-making tools to end-users.

N. A. Nazarbayev and Peculiar Features of Ethnic Language Processes in Kazakhstan

The report focuses on such an important indicator of the nature and direction of development of ethnic and cultural processes in the Republic of Kazakhstan, as ethno linguistic situation. It is shown that, in essence, on the one hand, expresses the degree of the actual propagation and the level of use of the languages of the various ethnic communities. On the other hand, reflects the important patterns, trends and prospects of ethno-cultural and ethnodemographic processes in the Republic. It is important to note that the ethno linguistic situation in different regions of Kazakhstan, due to its more dynamic and much more difficult to demonstrate a much greater variety of options when compared with the ethnic situation in the country. For the two major ethnic groups of the republic – Kazakh and Russian language ethno differentiating retains its value, while for the other ethnic groups observed decline in the importance of this indicator. As you know, the language of international communication in the country is Russian. As the censuses of population, the Russian language in many areas of Northern, Central and Eastern Kazakhstan becomes a means of ethno linguistic development for most of the non-Russian population. This is most clearly illustrated by the Germans, and the Slavic ethnic groups. In this case, the Russian language is not just a means of international communication for a number of ethnic groups, and ethnic groups, it becomes a factor of ethnic self-expression. The value of the Kazakh language as their mother tongue for the other groups of the population is small. More clearly it can be traced only to the Turkic-speaking population of the republic – Uzbeks, Uighurs, Tatars, Turks, etc. The state Kazakh language is a means of international communication in the Western and Southern Kazakhstan, with a predominance of the Kazakh population. The report shows that the most important factor in the development of ethno-linguistic and ethno-cultural processes is bilingualism. Comparative analysis of materials census shows, first, on the increase of the proportion of bilingual population among Kazakhs and Russian, and second, to reduce the proportion of bilingual population of other ethnic groups living in Kazakhstan, and third, a higher proportion bilingual population among residents than rural residents, regardless of their ethnicity. Bilingualism is mainly of a "national Kazakh", "national Russian" or "Kazakh-national" or "Russian-national" character. The President N.A. Nazarbayev said that the Kazakh language is the most important factor in the consolidation of the people of Kazakhstan. He therefore called on government and other state and local representative bodies fully develop the state language, to create all the necessary organizational, material and technical conditions for free and open learning the state language by all citizens of the Republic of Kazakhstan.

Approximation of Sturm-Liouville Problems by Exponentially Weighted Legendre-Gauss Tau Method

We construct an exponentially weighted Legendre- Gauss Tau method for solving differential equations with oscillatory solutions. The proposed method is applied to Sturm-Liouville problems. Numerical examples illustrating the efficiency and the high accuracy of our results are presented.

Slovenian Text-to-Speech Synthesis for Speech User Interfaces

The paper presents the design concept of a unitselection text-to-speech synthesis system for the Slovenian language. Due to its modular and upgradable architecture, the system can be used in a variety of speech user interface applications, ranging from server carrier-grade voice portal applications, desktop user interfaces to specialized embedded devices. Since memory and processing power requirements are important factors for a possible implementation in embedded devices, lexica and speech corpora need to be reduced. We describe a simple and efficient implementation of a greedy subset selection algorithm that extracts a compact subset of high coverage text sentences. The experiment on a reference text corpus showed that the subset selection algorithm produced a compact sentence subset with a small redundancy. The adequacy of the spoken output was evaluated by several subjective tests as they are recommended by the International Telecommunication Union ITU.

Optimization of Control Parameters for EWR in Injection Flushing Type of EDM on Stainless Steel 304 Workpiece

The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece using copper tools are being optimized according to its individual machining characteristic i.e. Electrode Wear Ratio (EWR). Higher EWR would give bad dimensional precision for the EDM machined workpiece because of high electrode wear. Hence, the quality characteristic for EWR is set to lower-the-better to achieve the optimum dimensional precision for the machined workpiece. Taguchi method has been used for the construction, layout and analysis of the experiment for EWR machining characteristic. The use of Taguchi method in the experiment saves a lot of time and cost of preparing and machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that negative polarity machining parameter setting will decreases EWR.

Development of Quasi-Two-Dimensional Nb2O5 for Functional Electrodes of Advanced Electrochemical Systems

In recent times there has been a growing interest in the development of quasi-two-dimensional niobium pentoxide (Nb2O5) as a semiconductor for the potential electronic applications such as capacitors, filtration, dye-sensitised solar cells and gas sensing platforms. Therefore once the purpose is established, Nb2O5 can be prepared in a number of nano- and sub-micron-structural morphologies that include rods, wires, belts and tubes. In this study films of Nb2O5 were prepared on gold plated silicon substrate using spin-coating technique and subsequently by mechanical exfoliation. The reason this method was employed was to achieve layers of less than 15nm in thickness. The sintering temperature of the specimen was 800oC. The morphology and structural characteristics of the films were analyzed by Atomic Force Microscopy (AFM), Raman Spectroscopy, X-ray Photoelectron Spectroscopy (XPS).

Scaling up Detection Rates and Reducing False Positives in Intrusion Detection using NBTree

In this paper, we present a new learning algorithm for anomaly based network intrusion detection using improved self adaptive naïve Bayesian tree (NBTree), which induces a hybrid of decision tree and naïve Bayesian classifier. The proposed approach scales up the balance detections for different attack types and keeps the false positives at acceptable level in intrusion detection. In complex and dynamic large intrusion detection dataset, the detection accuracy of naïve Bayesian classifier does not scale up as well as decision tree. It has been successfully tested in other problem domains that naïve Bayesian tree improves the classification rates in large dataset. In naïve Bayesian tree nodes contain and split as regular decision-trees, but the leaves contain naïve Bayesian classifiers. The experimental results on KDD99 benchmark network intrusion detection dataset demonstrate that this new approach scales up the detection rates for different attack types and reduces false positives in network intrusion detection.

Prediction of Soil Hydraulic Conductivity from Particle-Size Distribution

Hydraulic conductivity is one parameter important for predicting the movement of water and contaminants dissolved in the water through the soil. The hydraulic conductivity is measured on soil samples in the lab and sometimes tests carried out in the field. The hydraulic conductivity has been related to soil particle diameter by a number of investigators. In this study, 25 set of soil samples with sand texture. The results show approximately success in predicting hydraulic conductivity from particle diameters data. The following relationship obtained from multiple linear regressions on data (R2 = 0.52): Where d10, d50 and d60, are the soil particle diameter (mm) that 10%, 50% and 60% of all soil particles are finer (smaller) by weight and Ks, saturated hydraulic conductivity is expressed in m/day. The results of regression analysis showed that d10 play a more significant role with respect to Ks, saturated hydraulic conductivity (m/day), and has been named as the effective parameter in Ks calculation.

Regional Convergence in per Capita Personal Income in the US and Canada

This study examines regional convergence in per capita personal income in the US and Canada. We find that the disparity in real per capita income levels across US states (Canadian provinces) has declined, but income levels are not identical. Income levels become more aligned once costs of living are accounted for in relative per capita income series. US states (Canadian provinces) converge at an annual rate of between 1.3% and 2.04% (between 2.15% and 2.37%). A pattern of σ and β-convergence in per capita personal income across regions evident over the entire sample period, is reversed over 1979-1989 (1976-1990) period. The reversal may be due to sectoral or region-specific shocks that have highly persistent effects. The latter explanation might be true for half of the US and most of Canada.