Rehabilitation Robot in Primary Walking Pattern Training for SCI Patient at Home

Recently attention has been focused on incomplete spinal cord injuries (SCI) to the central spine caused by pressure on parts of the white matter conduction pathway, such as the pyramidal tract. In this paper, we focus on a training robot designed to assist with primary walking-pattern training. The target patient for this training robot is relearning the basic functions of the usual walking pattern; it is meant especially for those with incomplete-type SCI to the central spine, who are capable of standing by themselves but not of performing walking motions. From the perspective of human engineering, we monitored the operator’s actions to the robot and investigated the movement of joints of the lower extremities, the circumference of the lower extremities, and exercise intensity with the machine. The concept of the device was to provide mild training without any sudden changes in heart rate or blood pressure, which will be particularly useful for the elderly and disabled. The mechanism of the robot is modified to be simple and lightweight with the expectation that it will be used at home.

Estimation of the Mean of the Selected Population

Two normal populations with different means and same variance are considered, where the variance is known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the mehod of Monte-Carlo simulation and their performances are analysed with the help of graphs.

A Comparative Study of Image Segmentation Algorithms

In some applications, such as image recognition or compression, segmentation refers to the process of partitioning a digital image into multiple segments. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. Image segmentation is to classify or cluster an image into several parts (regions) according to the feature of image, for example, the pixel value or the frequency response. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image. Several image segmentation algorithms were proposed to segment an image before recognition or compression. Up to now, many image segmentation algorithms exist and be extensively applied in science and daily life. According to their segmentation method, we can approximately categorize them into region-based segmentation, data clustering, and edge-base segmentation. In this paper, we give a study of several popular image segmentation algorithms that are available.

Optimum Design of Steel Space Frames by Hybrid Teaching-Learning Based Optimization and Harmony Search Algorithms

This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teachinglearning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Extraction, Characterization and Application of Natural Dyes from the Fresh Rind of Index Colour 5 Mangosteen (Garcinia mangostana L.)

This study was to explore and utilize the fresh rind of mangosteen Index Colour 5 as an upcoming raw material for the production of natural dyes. Rind from the fresh mangosteen Index Colour 5 was utilized to extract the dyes. The established extracts were experimented on silk fabrics via three types of mordanting and dyeing procedures; pre-mordanting, simultaneous mordanting and post-mordanting. As a result, the applications of the freeze-drying methodology and mechanizable equipment have helped to produce excellent range of natural colours. Silk fabric treated simultaneously with mordanting and dyeing with extract dye Index Colour 5 produced a brilliant shade of the red colour and the colour from this index is also discovered sensitive to light and washing during the fastness tests. The preliminary evaluation and instrumentation analysis allowed us to examine whether the application of different mordanting and dyeing procedures with the same extract samples and concentrations affected the colours and shades of the fabric samples.

The Impact of Government Expenditure on Economic Growth: A Study of Asian Countries

Main purpose of this study is to identify the impact of government expenditure on economic growth in Asian Countries. Consequently, main objective is to analyze whether government expenditure causes economic growth in Asian countries vice versa and then scrutinizing long-run equilibrium relationship exists between them. The study completely based on secondary data. The methodology being quantitative that includes econometrical techniques of cointegration, panel fixed effects model and granger causality in the context of panel data of Asian countries; Singapore, Malaysia, Thailand, South Korea, Japan, China, Sri Lanka, India and Bhutan with 44 observations in each country, totaling to 396 observations from 1970 to 2013. The model used is the random effects panel OLS model. As with the above methodology, the study found the fascinating outcome. At first, empirical findings exhibit a momentous positive impact of government expenditure on Gross Domestic Production in Asian region. Secondly, government expenditure and economic growth indicate a long-run relationship in Asian countries. In conclusion, there is a unidirectional causality from economic growth to government expenditure and government expenditure to economic growth in Asian countries. Hence the study is validated that it is in line with the Keynesian theory and Wagner’s law as well. Consequently, it can be concluded that role of government would play a vital role in economic growth of Asian Countries. However; if government expenditure did not figure out with the economy’s needs it might be considerably inspiration the economy in a negative way so that society bears the costs.

Effect of Atmospheric Turbulence on Hybrid FSO/RF Link Availability under Qatar Harsh Climate

Although there has been a growing interest in the hybrid free-space optical link and radio frequency FSO/RF communication system, the current literature is limited to results obtained in moderate or cold environment. In this paper, using a soft switching approach, we investigate the effect of weather inhomogeneities on the strength of turbulence hence the channel refractive index under Qatar harsh environment and their influence on the hybrid FSO/RF availability. In this approach, either FSO/RF or simultaneous or none of them can be active. Based on soft switching approach and a finite state Markov Chain (FSMC) process, we model the channel fading for the two links and derive a mathematical expression for the outage probability of the hybrid system. Then, we evaluate the behavior of the hybrid FSO/RF under hazy and harsh weather. Results show that the FSO/RF soft switching renders the system outage probability less than that of each link individually. A soft switching algorithm is being implemented on FPGAs using Raptor code interfaced to the two terminals of a 1Gbps/100 Mbps FSO/RF hybrid system, the first being implemented in the region. Experimental results are compared to the above simulation results.

Chemical Composition of Essential Oil and in vitro Antibacterial and Anticancer Activity of the Hydroalcolic Extract from Coronilla varia

The aims of study were investigation on chemical composition essential oil and the effect of extract of Coronilla varia on antimicrobial and cytotoxicity activity. The essential oils of Coronilla varia is obtained by hydrodistillation and analyzed by (GC/MS) for determining their chemical composition and identification of their components. Antibacterial activity of plant extract was determined by disc diffusion method and anticancer activity measured by MTT assay. The major components in essential oil were Caryophyllene Oxide (60.19%), Alphacadinol (4.13%) and Homoadantaneca Robexylic Acid (3.31%). The extracts from Coronilla varia had interesting activity against Proteus mirabilis in the concentration of 700 μg/disc and did not show any activity against Staphylococus aureus, Bacillus subtillis, Klebsiella pneumonia and Entrobacter cloacae. The positive control, Ampicillin, Chloramphenicol and Cenphalothin had shown zone of inhibition resistant all bacteria. The ethanol extract of Corohilla varia inhibited on MCF7 cell lines. IC50 0.6(mg/ml) was the optimum concentration of extract from Coronilla varia inhibition of cell line growth. The MCF7 cancer cell line and Proteus mirabilis were more sensitive to Coronilla varia ethanol extract.

Nonlinear Absorption and Scattering in Wide Band Gap Silver Sulfide Nanoparticles Colloid and Their Effects on the Optical Limiting

In this paper, we study the optical nonlinearities of Silver sulfide (Ag2S) nanostructures dispersed in the Dimethyl sulfoxide (DMSO) under exposure to 532 nm, 15 nanosecond (ns) pulsed laser irradiation. Ultraviolet–visible absorption spectrometry (UV-Vis), X-ray diffraction (XRD), and transmission electron microscopy (TEM) are used to characterize the obtained nanocrystal samples. The band gap energy of colloid is determined by analyzing the UV–Vis absorption spectra of the Ag2S NPs using the band theory of semiconductors. Z-scan technique is used to characterize the optical nonlinear properties of the Ag2S nanoparticles (NPs). Large enhancement of two photon absorption effect is observed with increase in concentration of the Ag2S nanoparticles using open Zscan measurements in the ns laser regime. The values of the nonlinear absorption coefficients are determined based on the local nonlinear responses including two photon absorption. The observed aperture dependence of the Ag2S NP limiting performance indicates that the nonlinear scattering plays an important role in the limiting action of the sample. The concentration dependence of the optical liming is also investigated. Our results demonstrate that the optical limiting threshold decreases with increasing the silver sulfide NPs in DMSO.

Prediction of Writer Using Tamil Handwritten Document Image Based on Pooled Features

Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.

Auto-Calibration and Optimization of Large-Scale Water Resources Systems

Water resource systems modeling has constantly been a challenge through history for human beings. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

The Study of the Desulfurization Process of Oil and Oil Products of “Zhanazhol” Oil Field Using the Approaches of Green Chemistry

In this paper we studied sono catalytic oxidative desulfurization of oil and diesel fraction from “Zhanazhol” oil deposits. We have established that the combined effect of the ultrasonic field and oxidant (ozone-air mixture) in the presence of the catalyst on the oil is potentially very effective method of desulfurization of oil and oil products. This method allows increasing the degree of desulfurization of oil by 62%.

Theoretical Appraisal of Satisfactory Decisions: Uncertainty, Evolutionary Ideas and Beliefs, and Satisfactory Time Use

Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.

Bioconversion of Oranges Wastes for Pectinase Production Using Aspergillus niger under Solid State Fermentation

The influence of cultivation factors such as content of ammonium sulfate, glucose and water in the culture medium and particle size of dry orange waste, on their bioconversion for pectinase production was studied using complete factorial design. A polygalacturonase (PG) was isolated using ion exchange chromatography under gradient elution 0-0,5 m/l NaCl (column equilibrate with acetate buffer pH 4,5), subsequently by sephadex G75 column chromatography was applied and the molecular weight was obtained about 51,28 KDa. Purified PG enzyme exhibits a pH and temperature optima of activity at 5 and 35°C respectively. Treatment of apple juice by purified enzyme extract yielded a clear juice, which was competitive with juice yielded by pure Sigma Aldrich Aspergillus niger enzyme.

Morphemic Analysis Awareness: A Boon or Bane on ESL Students’ Vocabulary Learning Strategy

This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.

Comprehensive Assessment of Energy Efficiency within the Production Process

The importance of energy efficiency within the production processes increases steadily. For a comprehensive assessment of energy efficiency within the production process, unfortunately no tools exist or have been developed yet. Therefore the Institute for Factory Automation and Production Systems at the Friedrich-Alexander-University Erlangen-Nuremberg has developed two methods with the goal of achieving transparency and a quantitative assessment of energy efficiency namely EEV (Energy Efficiency Value) and EPE (Energetic Process Efficiency). This paper describes the basics and state-of-the-art as well as the developed approaches.

The Impact of Bank Consolidation on the Performance of SMES in Nigeria

This paper seeks to assess the implications of bank consolidation on the performance of small and medium scale enterprises in the Nigerian economy. Multiple linear regression technique and correlation matrix test were employed to measure the extent to which small and medium scale enterprises asset size, survival and access to credit were influenced. The result showed that bank deposit (BD) and bank credit (L or BC) impacted on asset size and survival of small and medium scale enterprises. None of the variables had significant impact on SMEs access to credit. There is a shift of focus by commercial banks away from small and medium scale enterprises (small customers), which is evidenced by the significant negative influence of bank credit to both the survival and asset size of small and medium enterprises. While micro finance banks work hard at providing funds to small and medium scale entrepreneurs, their capacity to meet the needs of these entrepreneurs is constrained. CBN should make policies that will boost micro finance bank’s capital and also monitor closely the management of the banks to ensure prudent financing of small and medium scale investments.

The Effectiveness of Metaphor Therapy on Depression among Female Students

The present study aimed to determine the effectiveness of Metaphor therapy on depression among female students. The sample included 60 female students with depression symptoms selected by simple sampling and randomly divided into two equal groups (experimental and control groups). Beck Depression Inventory was used to measure the variables. This was an experimental study with a pre-test/post-test design with control group. Eight metaphor therapy sessions were held for the experimental group. A post-test was administered to both groups. Data were analyzed using multivariate analysis of covariance (MANCOVA). Results showed that the Metaphor therapy decreased depression in the experimental group compared to the control group.

Profit and Nonprofit Sports Clubs: Financial and Organizational Comparison in Poland

The paper identifies the features of Polish sports clubs in the particular organizational forms: profit and nonprofit. Identification and description of these features is carried out in terms of financial efficiency of the given organizational form. Under the terms of the efficiency the research allows you to specify the advantages of particular organizational sports club form and the following limitations. Paper considers features of sports clubs in range of Polish conditions as legal regulations. The sources of the functioning efficiency of sports clubs may lie in the organizational forms in which they operate. Each of the available forms can be considered either a for-profit or nonprofit enterprise. Depending on this classification there are different capabilities of increasing organizational and financial efficiency of a given sports club. Authors start with general classification and difference between for-profit and non-profit sport clubs. Next identifies specific financial and organizational conditions of both organizational form and then show examples of mixed activity forms and their efficiency effect.

Modeling Aeration of Sharp Crested Weirs by Using Support Vector Machines

The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free overfall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, Support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, Support vector machine (Polynomial and rbf) models and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free overfall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.