Power Ultrasound Application on Convective Drying of Banana (Musa paradisiaca), Mango (Mangifera indica L.) and Guava (Psidium guajava L.)

High moisture content in fruits generates post-harvest problems such as mechanical, biochemical, microbial and physical losses. Dehydration, which is based on the reduction of water activity of the fruit, is a common option for overcoming such losses. However, regular hot air drying could affect negatively the quality properties of the fruit due to the long residence time at high temperature. Power ultrasound (US) application during the convective drying has been used as a novel method able to enhance drying rate and, consequently, to decrease drying time. In the present study, a new approach was tested to evaluate the effect of US on the drying time, the final antioxidant activity (AA) and the total polyphenol content (TPC) of banana slices (BS), mango slices (MS) and guava slices (GS). There were also studied the drying kinetics with nine different models from which water effective diffusivities (Deff) (with or without shrinkage corrections) were calculated. Compared with the corresponding control tests, US assisted drying for fruit slices showed reductions in drying time between 16.23 and 30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS and GS respectively. Considering shrinkage effects, Deff calculated values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and 5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and GS samples respectively. Reductions of TPC and AA (as DPPH) were observed compared with the original content in fresh fruit data in all kinds of drying assays.

An Improved Scheduling Strategy in Cloud Using Trust Based Mechanism

Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.

Variation of Streamwise and Vertical Turbulence Intensity in a Smooth and Rough Bed Open Channel Flow

An experimental study with four different types of bed conditions was carried out to understand the effect of roughness in open channel flow at two different Reynolds numbers. The bed conditions include a smooth surface and three different roughness conditions, which were generated using sand grains with a median diameter of 2.46 mm. The three rough conditions include a surface with distributed roughness, a surface with continuously distributed roughness and a sand bed with a permeable interface. A commercial two-component fibre-optic LDA system was used to conduct the velocity measurements. The variables of interest include the mean velocity, turbulence intensity, correlation between the streamwise and the wall normal turbulence, Reynolds shear stress and velocity triple products. Quadrant decomposition was used to extract the magnitude of the Reynolds shear stress of the turbulent bursting events. The effect of roughness was evident throughout the flow depth. The results show that distributed roughness has the greatest roughness effect followed by the sand bed and the continuous roughness. Compared to the smooth bed, the streamwise turbulence intensity reduces but the vertical turbulence intensity increases at a location very close to the bed due to the introduction of roughness. Although the same sand grain is used to create the three different rough bed conditions, the difference in the turbulence intensity is an indication that the specific geometry of the roughness has an influence on turbulence structure.

Lean Thinking and E-Commerce as New Opportunities to Improve Partnership in Supply Chain of Construction Industries

Construction industry plays a vital role in the economy of the world. However, due to high uncertainty and variability in the industry, its performance is not as efficient in terms of quality, lead times, productivity and costs as of other industries. Moreover, there are continuous conflicts among the different actors in the construction supply chains in terms of profit sharing. Previous studies suggested partnership as an important approach to promote cooperation among the different actors in the construction supply chains and thereby it improves the overall performance. Construction practitioners tried to focus on partnership which can enhance the performance of construction supply chains but they are not fully aware of different approaches and techniques for improving partnership. In this research, a systematic review on partnership in relation to construction supply chains is carried out to understand different elements influencing the partnership. The research development of this domain is analyzed by reviewing selected articles published from 1996 to 2015. Based on the papers, three major elements influencing partnership in construction supply chains are identified: ‘Lean approach’, ‘Relationship building’ and ‘E-commerce applications’. This study analyses the contributions in the areas within each element and provides suggestions for future developments of partnership in construction supply chains.

Financial Inclusion from the Perspective of Social Innovation: The Case of Colombia

Financial inclusion has become a crucially important factor in debates on economic inequality posing challenges to the financial systems of countries around the world. Nowadays governments and banks are concerned about creating products that allow access to wide sectors of the population. The creation of banking products by the financial sector for people with low incomes tends to lead to improvements in the quality of life of vulnerable parts of the population. In countries with notable social and economic inequalities, financial inclusion is a key aspect for equitable economic growth. This study is based on the case of Colombia, which is a country with a strong record of economic growth over the past decade. Nevertheless, corruption, unemployment, and poverty contribute to uncertainty regarding the country’s future growth prospects. This study wants to explain the situation of financial exclusion and financial inclusion with respect to the Colombian case. Financial inclusion is going to be studied from the perspective of social innovation.

Molecular Dynamics Simulation for Buckling Analysis at Nanocomposite Beams

In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long- (10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Subarray Based Multiuser Massive MIMO Design Adopting Large Transmit and Receive Arrays

This paper describes a subarray based low computational design method of multiuser massive multiple input multiple output (MIMO) system. In our previous works, use of large array is assumed only in transmitter, but this study considers the case both of transmitter and receiver sides are equipped with large array antennas. For this aim, receive arrays are also divided into several subarrays, and the former proposed method is modified for the synthesis of a large array from subarrays in both ends. Through computer simulations, it is verified that the performance of the proposed method is degraded compared with the original approach, but it can achieve the improvement in the aspect of complexity, namely, significant reduction of the computational load to the practical level.

A Methodology for Automatic Diversification of Document Categories

Recently, numerous documents including large volumes of unstructured data and text have been created because of the rapid increase in the use of social media and the Internet. Usually, these documents are categorized for the convenience of users. Because the accuracy of manual categorization is not guaranteed, and such categorization requires a large amount of time and incurs huge costs. Many studies on automatic categorization have been conducted to help mitigate the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorize complex documents with multiple topics because they work on the assumption that individual documents can be categorized into single categories only. Therefore, to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, the learning process employed in these studies involves training using a multi-categorized document set. These methods therefore cannot be applied to the multi-categorization of most documents unless multi-categorized training sets using traditional multi-categorization algorithms are provided. To overcome this limitation, in this study, we review our novel methodology for extending the category of a single-categorized document to multiple categorizes, and then introduce a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Teachers’ Perceptions of Their Principals’ Interpersonal Emotionally Intelligent Behaviours Affecting Their Job Satisfaction

For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Investigating the Nail Walls Performance in Jointed Rock Medium

Evaluation of the excavation-induced ground movements is an important design aspect of support systems in urban areas. Geological and geotechnical conditions of an excavation area have significant effects on excavation-induced ground movements and the related damage. This paper is aimed at studying the performance of excavation walls supported by nails in jointed rock medium. The performance of nailed walls is investigated based on evaluating the excavation-induced ground movements. For this purpose, a set of calibrated 2D finite element models are developed by taking into account the nail-rock-structure interactions, the anisotropic properties of jointed rock, and the staged construction process. The results of this paper highlight effects of different parameters such as joint inclinations, anisotropy of rocks and nail inclinations on deformation parameters of excavation wall supported by nails.

Numerical Simulation of Thermo-Fluid Behavior in Wavy Microchannel Used in Microelectronic Devices

The hydrodynamic and thermal behaviors of fluid flow in wavy microchannel are investigated numerically. Effects of Reynolds number on the hydrodynamics and thermal behaviors are investigated. Three cases of Reynolds number (580, 1244, and 1910) are adopted in this study. It is found that the separation zone begin appears when Reynolds number is greater than 1910 at the endsection of the wave. Also it is found that dimensionless maximum velocity at the mid-section of the wave decreases and becomes as a turbulent behavior as Reynolds numbers increases. The maximum temperature at the center line at the mid-section of the wave increases as Reynolds number increases until it reaches the turbulent behavior when Reynolds number is equal or greater than 1244, while this behavior will be achieved at very high velocities at the end section of the wave.

Physical-Mechanical Characteristics of Monocrystalline Si1-xGex (x≤0,02) Solid Solutions

Si-Ge solid solutions (bulk poly- and mono-crystalline samples, thin films) are characterized by high perspectives for application in semiconductor devices, in particular, optoelectronics and microelectronics. From this point of view, complex studying of structural state of the defects and structural-sensitive physical properties of Si-Ge solid solutions depending on the contents of Si and Ge components is very important. Present work deals with the investigations of microstructure, microhardness, internal friction and shear modulus of Si1-xGex(x≤0,02) bulk monocrystals conducted at room temperature. Si-Ge bulk crystals were obtained by Czochralski method in [111] crystallographic direction. Investigated monocrystalline Si-Ge samples are characterized by p-type conductivity and carriers’ concentration 5.1014-1.1015cm-3. Microhardness was studied on Dynamic Ultra Micro hardness Tester DUH-201S with Berkovich indenter. Investigate samples are characterized with 0,5x0,5x(10-15)mm3 sizes, oriented along [111] direction at torsion oscillations ≈1Hz, multistage changing of internal friction and shear modulus has been revealed in an interval of strain amplitude of 10-5-5.10-3. Critical values of strain amplitude have been determined at which hysteretic changes of inelastic characteristics and microplasticity are observed. The critical strain amplitude and elasticity limit values are also determined. Dynamic mechanical characteristics decreasing trend is shown with increasing Ge content in Si-Ge solid solutions. Observed changes are discussed from the point of view of interaction of various dislocations with point defects and their complexes in a real structure of Si-Ge solid solutions.

Microbiological Profile of UTI along with Their Antibiotic Sensitivity Pattern with Special Reference to Nitrofurantoin

Urinary Tract Infections are considered as one of the most common bacterial infections with an estimated annual global incidence of 150 million. Antimicrobial drug resistance is one of the major threats due to wide spread usage of uncontrolled antibiotics. In this study, a total number of 9149 urine samples were collected from R.H Patiala and processed in the Department of Microbiology G. M. C Patiala (January 2013 to December 2013). Urine samples were inoculated on MacConkey’s and blood agar plates and incubated at 370C for 24 hrs. The organisms were identified by colony characters, Gram’s staining, and biochemical reactions. Antimicrobial susceptibility of the isolates was determined against various antimicrobial agents (Hi – Media Mumbai India) by Kirby Bauer DISK diffusion method on Muller Hinton agar plates. Maximum patients were in the age group of 21-30 yrs followed by 31-40 yrs. Males (34%) are less prone to urinary tract infections than females (66%). Culture was positive in 25% of the samples. Escherichia coli was the most common isolate 60.3% followed by Klebsiella pneumoniae 13.5%, Proteus spp. 9% and Staphylococcus aureus 7.6%. Most of the urinary isolates were sensitive to, carbepenems, Aztreonam, Amikacin, and Piperacillin + Tazobactum. All the isolates showed a good sensitivity towards Nitrofurantoin (82%). ESBL production was found to be 70.6% in Escherichia coli and 29.4% in Klebsiella pneumonia. Susceptibility of ESBL producers to Imipenem, Nitrofurantoin and Amikacin were found to be 100%, 76%, and 75% respectively. Uropathogens are increasingly showing resistance to many antibiotics making empiric management of outpatient UTIs challenging. Ampicillin, Cotrimoxazole and Ciprofloxacin should not be used in empiric treatment. Nitrofurantoin could be used in lower urinary tract infection. Knowledge of uropathogens and their antimicrobial susceptibility pattern in a geographical region will help in appropriate and judicious antibiotic usage in a health care setup.

Methods of Geodesic Distance in Two-Dimensional Face Recognition

In this paper, we present a comparative study of three methods of 2D face recognition system such as: Iso-Geodesic Curves (IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram (GIH). These approaches are based on computing of geodesic distance between points of facial surface and between facial curves. In this study we represented the image at gray level as a 2D surface in a 3D space, with the third coordinate proportional to the intensity values of pixels. In the classifying step, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). The images used in our experiments are from two wellknown databases of face images ORL and YaleB. ORL data base was used to evaluate the performance of methods under conditions where the pose and sample size are varied, and the database YaleB was used to examine the performance of the systems when the facial expressions and lighting are varied.

Poincaré Plot for Heart Rate Variability

Heart is the most important part in the body of living organisms. It affects and is affected by any factor in the body. Therefore, it is a good detector for all conditions in the body. Heart signal is a non-stationary signal; thus, it is utmost important to study the variability of heart signal. The Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and has become important dependent measure in psychophysiology and behavioral medicine. The standards of measurements, physiological interpretation and clinical use for HRV that are most often used were described in many researcher papers, however, remain complex issues are fraught with pitfalls. This paper presents one of the nonlinear techniques to analyze HRV. It discusses many points like, what Poincaré plot is and how Poincaré plot works; also, Poincaré plot's merits especially in HRV. Besides, it discusses the limitation of Poincaré cause of standard deviation SD1, SD2 and how to overcome this limitation by using complex correlation measure (CCM). The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared toSD1 and SD2.

Fundamental Natural Frequency of Chromite Composite Floor System

This paper aims to determine Fundamental Natural Frequency (FNF) of a structural composite floor system known as Chromite. To achieve this purpose, FNFs of studied panels are determined by development of Finite Element Models (FEMs) in ABAQUS program. American Institute of Steel Construction (AISC) code in Steel Design Guide Series 11 presents a fundamental formula to calculate FNF of a steel framed floor system. This formula has been used to verify results of the FEMs. The variability in the FNF of the studied system under various parameters such as dimensions of floor, boundary conditions, rigidity of main and secondary beams around the floor, thickness of concrete slab, height of composite joists, distance between composite joists, thickness of top and bottom flanges of the open web steel joists, and adding tie beam perpendicular on the composite joists, is determined. The results show that changing in dimensions of the system, its boundary conditions, rigidity of main beam, and also adding tie beam, significant changes the FNF of the system up to 452.9%, 50.8%, - 52.2%, %52.6%, respectively. In addition, increasing thickness of concrete slab increases the FNF of the system up to 10.8%. Furthermore, the results demonstrate that variation in rigidity of secondary beam, height of composite joist, and distance between composite joists, and thickness of top and bottom flanges of open web steel joists insignificant changes the FNF of the studied system up to -0.02%, -3%, -6.1%, and 0.96%, respectively. Finally, the results of this study help designer predict occurrence of resonance, comfortableness, and design criteria of the studied system.

Application of Vortex Induced Vibration Energy Generation Technologies to the Offshore Oil and Gas Platform: The Feasibility Study

Ocean current is always available around the surrounding of SHELL Sabah Water Platform and data are collected every 10 minutes, 24 hours a day, for a period of 365 days. Due to low current speed, conventional hydrokinetic power generation is not feasible, thus leading to the study of low current enabled vortex induced vibration power generation application. In this case, the design of a vortex induced vibration application is studied to obtain an optimum design for the VIV oscillator. Power output is then determined to study the feasibility of the VIV application in low current condition.

Mobile Collaboration Learning Technique on Students in Developing Nations

New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Five research questions and hypotheses were formulated, and tested at 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following submissions was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and training should be organized to train teachers on the use of this technique, schools and government should consistently align curriculum standard to trends of technological dictates and formulate policies and procedures towards responsible use of MCLT.

The Impact of Demographic Profile on Strategic HRM Practices and Its Challenges Faced by HR Managers in IT Firm, India: An Empirical Study

The authors conducted a study for the sample size of 75 HR managers from an Indian IT company through systematic sampling method. This study identifies that the female employees are facing lesser conflict than the male employees against their managers within the organization. There is a positive correlation between gender and conflict management with the superior towards the work. There is a significant variance between age and response towards appraisal system, succession planning and employee engagement. The education qualification plays a major role in determining the compensation factor for the employees working in the organization. The study determines the impact of demographic profile on strategic HRM practices and its challenges faced by HR managers in IT firm, India.

Predictive Models for Compressive Strength of High Performance Fly Ash Cement Concrete for Pavements

The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% @ 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes that have been designed, three were conventional concretes for three grades under discussion and fifteen were HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days, and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave-One-Out Validation (LOOV) methods.