Volume 6, Issue 8, August 2018 Edition - GSJ Journal Publication


The research presents the comparative analysis on the mechanical properties of a Metal-Matrix Composite (MMC) reinforced with palm kernel/periwinkle shell ash for automobile applications. Four specimens consisting of Sample A (300g of aluminum), Sample B (295% of aluminium, and 5% of Silicon Carbide [SiC]), Sample C (290% of aluminium, 5% of Silicon Carbide and 5% of palm kernel [PKSA]) and (285% of aluminium, 5% of Silicon Carbide, 5% of palm kernel and 5% of periwinkle shell ash [PSA]) were produced using stir casting method and their mechanical properties (hardness, tensile strength, microstructure) were evaluated. Particle reinforced Al-MMC can be synthesized stir- casting method. Commercially solid aluminium (up to 99.1% purity) served as the matrix while Silicon carbide, palm kernel shell ash and periwinkle shell ash particle were used as the reinforcements. It involved the melting of the aluminium solid followed by adding the reinforced particles for different weight percent to the melt. The microstructural examinations revealed a uniform distribution of the reinforcements. From the analysis of results obtained, we found that the ultimate tensile strength of aluminum based metal matrix composite decreased as we added the weight fraction of SiC; increased as we added the weight fraction of PKSA and decreased as we added the weight fraction of PSA particles. The elastic modulus of aluminum based metal matrix composite decreased as we added the weight fraction of SiC, increased as we added the weight fraction of PKSA and decreased as we added the weight fraction of PSA particles. The hardness of aluminum based metal matrix composite increased as we added the weight fraction of SiC, and decreased as we added the weight fraction of PKSA and increase as you add the weight fraction of PSA particles. The ductility of aluminum based metal matrix composite decreased as we added the weight fraction of SiC, and increased as we added the weight fraction of PKSA and PSA. Conclusively, with the observations made on the mechanical properties of pure Aluminium metal reinforced with SiC, PKSA and PSA, SiC and PKSA have a better mechanical properties if used as reinforcement material in Aluminium metal matrix composite. Thus, this work has provided ways of converting commercial wastes, especially palm kernel shell and periwinkle shell which are posing environmental problems, to useful substances.

The Utilization of Chlorella sp. in Feed to Growth Performance of Gouramy (Osphronemus gouramy.Lac) Grower Phase []

This study aims to determine the optimal doses of of Chlorella sp. meal into the feed which results in a high growth rate in the gouramy grower phase. The study was conducted in January until March 2018 (40 days) at Production Hall of Gouramy and Nilem Stockpip (BPPSIGN) Singaparna-Tasikmalaya. This study used the Completely Random Design (CRD) method, consisting of four treatments and four replications, namely commercial feeding (control), Chlorella sp. 1%, 2% and 3%. Parameters observed were feed convertion ratio, absolute growth and water quality. The feed convertion ratio and absolute growth data were analysed using variance analysis (ANOVA), while the quality of water was analysed descriptively by comparing it to the water quality standard SNI 2006. The results showed the best treatment was achieved within the dose 3% Chlorella sp in feed, which result feed convertion ratio of 2,85, absolute growth 44,66 gram and water quality parameters between 25,95-27oC, pH between 6,15-6,54 and Dissolved Oxygen (DO ) between 5,16-5,96 mg/L.


This study aims to determine the effect of carrot starch in enhancing the color brightness and to figure the optimal concentration of carrot starch added to artificial feed to enhance the color brightness of swordtail fish. This research was conducted at Hatchery Building 4 Faculty of Fisheries and Marine Sciences of Padjadjaran University from May to June 2018. The research method used is a Completely Randomized Design experiment consisting of five treatments and three replications. The carrot starch addition treatment used 0%, 2.5%, 5%, 7.5%, and 10% of carrot starch based on the feed amount. The parameters observed is color value by using Toca Color Finder as the main data while increased weight and survival rate act as supporting data. The color observation data were analyzed using Kruskal-Wallis analysis, if there were significant differences, Z test would be performed. The weight gain was analyzed using Analysis Off Variance (ANOVA). F test was performed in order to figure the effect of treatment upon the parameters, if there is a significant difference then Duncan’s Multiple Range Test (DMRT) would be performed. The results concluded that the addition of 10% carrot starch is the best treatment, resulting in 6.78 color brightness value enhancement on the tail and 7 color brightness value enhancement of the swordtail fish head.


Career Development Plan is one of the most important developmental processes in a student’s university experience. Deciding on a career is a developmental process, marked by significant events and experiences. Employers want well-rounded students that enhance their in classroom education with key career-related experiences. Students should strive to fine tune their career goals carefully. So creating Career Development Plan is a major issue of student life. Career Development Plan is to provide an action plan for students to follow during his undergraduate years. That will help student’s acquire knowledge of him, career paths, and academic and career opportunities. Career decision-making is a process, and while activities are suggested over a four-year timeline student can set his own pace in pursuing career development and use the timeline accordingly.

Experimental Investigation of the Effect of Cutting Parameters on Cutting Temperature Using RSM and ANN in Turning AISI 1040 []

In the present research, experimental investigation is done to identify the impact of cutting parameters (feed rate, cutting speed and depth of cut) on the cutting temperature in turning of AISI 1040 by using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Response surface methodology (RSM) is used to design the experimental layout consisting of 16 datasets using Central Composite Design (CCD). Significance of the cutting parameters is determined utilizing statistical analysis of variance (ANOVA) which indicates that all the three cutting parameters have noteworthy impact on the cutting temperature. The 3D response graphs present cutting temperature is increased with the increase of feed rate, cutting speed and depth of cut. Desirability Function Analysis (DFA) is employed to decide optimal values of cutting parameters. It is suggested from DFA that minimum temperature is obtained at lower feed rate (0.100 mm/rev), lower cutting speed (62.172 m/min) and lower depth of cut (0.200 mm). Afterward, main effects plot is analyzed to show the variation of response with the three input variables and the result found from main effects plot is almost coherent to the results found from 3D plots and Desirability Function Analysis (DFA). The predicted results using ANN indicate good agreement between the predicted values and experimental values. The R² value for model θ is noticed to be 0.99081. The deviation between experimental values, RSM predicted values and ANN predicted values is very minimum which presents the efficacy of the proposed RSM and ANN model. But MAPE for RSM is 0.001336 and ANN is 0.006245 which evidently indicates that the prediction capabilities of RSM model are better as compared to the ANN models for this experiment.


The new dimension of collaboration, brought by collaborative platforms, induces a new management approach that must consider methods of observation and behaviour analysis as a means to optimize the productivity of organizations. From this point of view, although they have evolved a lot in recent years, especially with social networks, the contextualization of digital interaction traces within collaborative platforms remains a major topic for the performance of data operating systems. The work that we present in this paper is part of the projects of implementation of collaborative and learning management systems, collaborative work and services, in a IT Environment for Human Learning vision (IEHL), more precisely, on the intelligent architectures of the platforms aiming at a better or-ganization around the concept of unity of interaction which introduces a sort of contextualization of the collected digi-tal traces. The resolution of the problem of the personalization of IEHL is moreover essentially dependent on the ability to produce relevant and exploitable digital traces of the individual or collective activity of the users (learners in particular), who interact with an IEHL. In the present work, we are interested in the organization of collaborative tools and its impact on the performance of digital interaction traces analysis mechanisms. Our study is based on the results of observation and analysis of human interactions within collaborative platforms, in particular those developed within the framework of our projects.


The present study was conducted to determine the efficacy of cow urine as plant growth enhancer by treating methi plant with different concentrations of cow urine i.e. 1%, 2%, 3%, 4% & 5% and blank was maintained using tap water. By following this procedure protein & chlorophyll content was estimated. Among these concentrations 5% was showing higher protein & chlorophyll content. Along with this the cellulolytic activity of cow urine was also determined by observing clearance around the colony on CMC agar plate. The lipase activity of cow urine was estimated by performing lipase assay which is titrimetric analysis. Both showed positive results for cellulase & lipase activity.


Cardiovascular disease is a major cause of death with coronary artery or heart disease being the single most important cause of death worldwide. Oxidative stress and inflammation are cooperative events involved in the development of atherosclerosis which is the underline factor in coronary artery disease progression. This study was designed to investigate plasma lipid profile namely total cholesterol (TC), low density lipoprotein cholesterol (LDLc), high density lipoprotein cholesterol (HDLc) and triglycerides (TG), plasma antioxidants; namely Vitamin C and E, Catalase, Superoxide dismutase and Glutathione peroxidise in coronary artery diseased patients. Plasma malondialdehyde(MDA) was also determined in these patients. A total of 200 angiographically diagnosed coronary artery duseased patients of both sexes attending various teaching hospitals, medical centers and general hospitals across Southwestern Nigeria were screened for this study. Significant risk factors such as cigarette and diabetes were excluded from the study. They were matched with equal number of normal subjects. The result of the study shows a significant increase in the plasma level of both total cholesterol and LDL cholesterol in coronary artery diseased patients while the plasma level of high density lipoprotein cholesterol was significantly lowered in these patients when compared with the control subjects. Similarly the plasma level of MDA in these patients was significantly higher than the control subjects. The result also shows a significant decrease in the plasma level of the various antioxidants considered in these patients when compared with the control subjects.


PCA is a statistical approach that analysis a data table in which observations are describes by several inter correlated quantitative dependent variables. It uses mathematical principals to transform number of possibly correlated variable into a smaller number of variable called principal component. One of compute intensive application of PCA is face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set. The weights are found out after selecting a set of most relevant eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring minimum Euclidean distance. Some of the modules such as Covariance Module, Jacobi Module, Eigenface Module required more time for execution. These modules will be made parallel with the help of parallel programming models such as OpenMP and MPI and performance & evaluation will be made between sequential and parallel implementation.


Real-time PCR has been used to quantify the gene expression of selected genes to compare among different isolated cancer stem cells. These genes were detected are linked with the reproduction, cell apoptosis and chemotherapy. These genes used as markers to investigate cancer stem cells and as target therapy. In addition, to identify the expression pathways of some genes which related with BCSCs that identified to contribute to tumourgenesis as well as drugs resistance. The expression of these genes will be used to isolate BCSCs from tumour samples or breast cell lines which based on CD44+/CD24-/low, which considers as a crucial marker or ALDH+ phenotypes. Because this isolation will help to analyse the molecular mechanisms which present by self-renewed and differentiation of cells. There is evidence proposed that the isolation of BCSCs will allow the discovery of target therapy and this will remove the mass tumour and breast cancer by using these genes which will up-regulate or down-regulated as it was conducted by several papers. In addition, to clarify the expression of selected genes markers in the isolated BCSCs and the tumourgenicity that is a phenomenon degenerated by a subpopulation of the tumour cell which known as cancer stem cells. In this investigation that aimed to isolate BCSCs from the bulk of breast cancer cell. This extraction of breast cancer stem cells was identified by using sphere formation assay. The total RNA was extracted from the isolated breast cancer stem cell in order to detect the expression of novel markers such as;(ALDH3A1) Aldehyde dehydrogenase 3family member A1, the main cancer stem markers CD44,CD133 and finally tumour necrosis factor receptor super family 9(TNFRSF9) by run Real-Time PCR.In this part of our project, we will look at different genes and their expression profiles that are related to the same cells. These isolated stem cells could be tested to quantify the expression profiles of selected genes CD44, CD133, ALDH3A1 and TNFRSF9 as crucial biomarkers.We investigate cancer stem cells by molecular analysis that includes detection and clarification of the down and up-regulated genes between the strengthened cancer stem cells (spheroid), single and parental cells. Therefore, this isolation allows us to identify the bulk cells to select more specific target therapy.

Isolate and identified cancer stem cells by using MCF7 human breast cancer cell line, using mammospheres formation in two different methods []

Cancer represents one of the most significant challenges facing biological and clinical research. A higher understanding of the theory and mechanism of cancer will allow scientists to develop an active target therapy of cancer diseases. It has been suggested in several studies that a tumour that has been derived from many cells that have the ability to rapidly reproduce many more new cells and increase the tumour. Cancer stem cells are one of these types of cells which have been isolated in different parts of the body such as in the breast, prostate and colon. Breast cancer stem cells (BCSCs) have been shown in several studies to comprise of small parts of cancer cells which lead to an increase the prognosis of breast cancer. This type of tumour cells able to develop tumour generation. The focus of this research will be in breast cancer (BC) which still the main issue of public concerns. As a result of many studies which show that BC remains the popular cancers among women in the world. In China, for example, more than million cases each year. In spite of all the concentration to discover a new, fast diagnosis method and treatment, BC still forms the second causes of death among women in the world. The majority of cancers incidence are belonged to uncontrolled on the rapid growing of the cells.In this project, MCF7 human breast cancer cell line used to isolate cancer stem cells by using mammospheres formation in two different methods.The main target of this work was to isolate cancer stem cells from human breast cancer cell lines and compare with the parental cells, single and cancer stem cells which we have identified by using spheres formation assay.


Mobile banking has become abstract concept this upcoming economy, it facing critical challenges in today’s world and more often it got impacted by HR recent trends Digital HR and GIG economy. The study contains a questionnaire based primary study. In which a questionnaire is developed and checked through convergent validity and face validity. Later results discussed in detail. Challenges to Mobile banking, Mobile banking serves, digital HR and Gig economy have a significant positive relationship with individual performance. IT shows individual performance while using mobile banking do have a huge scope. This paper is the first effort to come up with the effect of Recent HR trends, Challenges and Services to Individual performance using mobile banking.


In Mobile Cloud Architecture (MCA) empowers constrained resources mobile devices to execute the complex application with collaborative way. The offloading system is a process in which mobile application can be divided into local execution and cloud execution in order to minimize energy consumption of mobile CPU. However, existing offloading systems do not consider data transfer communication energy while performing mobile offloading system. They have just focused on mobile CPU energy consumption. In this paper, we are investigating the energy consumption mobile CPU and communication energy collaboratively while performing mobile offloading for complex applications. To cope up with the above problem, we have proposed Energy Efficient Task Scheduler (EETS) algorithm, which aim is to determine optimal task execution in offloading system in order to minimize mobile CPU and communication energy. Simulation results show that EETS outperforms as compared to baseline approaches.

Impact of Firm Specific Factors on Profitability of Firms in Food Sector []

The aim of this study is to examine the impact of firm specific and macroeconomic factors on profitability of food sec- tor in Pakistan. This study explores the impact of firm specific factors on profitability of companies listed in food sector of Karachi stock market in the presence of food inflation by employing multivariate regression analysis in common ef- fect setting for the period of 2012-2018. The firm specific factors include debt to equity, tangibility, growth and size and macroeconomic factor include food inflation. Findings of study reveal the presence of significant negative relation- ship between size and profitability. However, tangibility, growth of the firm and food inflation are found insignifi- cantly positively related to profitability. Similarly, an insignificant negative relationship is observed between debt to equity ratio of firm and its profitability. Empirical results provide evidence that the profitability of food sector is shaped by firm specific factors and not macroeconomic variables. One important limitation of study is that it only considers one macroeconomic factor i.e. food inflation. In future studies more macroeconomic factors will be explored to examine their impact on profitability of food sector firms. However, this study still provides significant insight about dynamics of profitability in food sector and helps in making optimal decisions of resource allocation in food sector of Pakistani equity market.


The research is aimed at exploring Foreign Direct Investment and its impact on economic growth of Nigeria. The study covers 31-year period between 1985-2016. Simple ordinary least-square regression model is used to measure the effects and relationships between the independent variable and the dependent variable using E-views 9.0. Foreign Direct Investment (FDI) serve as the independent variable while economic growth as the dependent variable. GDP, exchange rate, inflation rate, unemployment rate, total savings and interest rate were used as proxies for economic growth. Data on FDI, GDP, exchange rate, unemployment rate, savings and interest rate were retrieved from the CBN Annual Statistical Bulletin, World bank Report and National Bureau of Statistics. The stationarity property of a time series data can be examined by conducting unit root test in order to ascertain the stationarity or otherwise of the series variables (Akinola,2016). Augmented Dickey-Fuller (ADF) test due to Dickey and Fuller (1979, 1981), and the Phillip-Perron (PP) due to Phillips (1987) and Phillips and Perron (1988) were used to ensure the stationarity of the time series data i.e dependent and independent variable. The finding showed that there is a strong and positive relationship between FDI and economic growth in Nigeria. The government of Nigeria must put all hands-on desk, formulating policies and necessary reforms to ensure that foreign direct investments are attracted to benefit the populace at large. It also recommended that Institutionalized corruption both in private and public sectors must be fought, if the nation must attract FDI, we must change our ways of doing things.

Energy and Wave-function correction for a quantum system after a small perturbation []

This study mainly focused on calculating the energy and the wave function of a new quantum system after the original quantum state is perturbed by a small perturbation or Hamiltonian. Perturbation theory method was adopted for calculationg the first and the second order of Energy and wave function correction for the new quantum state for both degenerate and non-degenerate quantum states.Finally, the new quantum system is represented by a new wave function and energy after asmall perturbation.

Cloud Computing Simulation Using CloudSim Toolkits []

Cloud simulation aims to power the next generation data centers and enables application service providers to lease data center capabilities for deploying applications depending on user QoS (Quality of Service) requirements. Cloud Simulation applications have different composition, configuration, and deployment requirements. Quantifying the performance of resource allocation policies and application scheduling algorithms at finer details in Cloud computing environments for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is a challenging problem to tackle. in this paper we propose CloudSimulation:an extensible simulation toolkit that enables modeling and simulation of various Cloud Simulation environments. The CloudSim toolkit supports modelling and creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs. It also allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications between user and hosts due to cloudlet.