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Effect of metal mask and pad design on solder printability was evaluated by DOE in this study. The process parameters were stencil thickness, squeegee angle, squeegee speed, mask separating speed, and pad angle of PCB. The main process parameters for printability were stencil thickness and squeegee angle. The response surface showed that maximum printability of 1005 chip was achieved at the stencil thickness of 0.12 mm while the maximum printability of 0603 and 0402 chip was obtained at the stencil thickness of 0.05 mm. The bonding strength of the MLCC chips was also directly related with the printability. [ABSTRACT FROM AUTHOR]

Inconel 600 has good properties like Resistance to High Temperature and corrosion. This paper is mainly focused on the investigation of cutting parameters on turning performance characteristics. Feed, Speed and Back Rake Angle were considered as machining parameters while Material Removal Rate and Surface Roughness were taken as performance characteristics. Experiments were based on design of experiments-Taguchi L9 orthogonal array. The results from the studies indicate that sequence of Cutting speed of 300 m/min, Feed rate of 0.05 mm/rev and Rake angle of -3° was found to achieve minimum surface roughness whereas highest Material removal rate was obtained with a sequence of Cutting speed of 300 m/min, Feed rate of 0.15 mm/rev and Rake angle of -7°. Results from Analysis of variance indicate that feed rate has maximum influence on both Ra and MRR with 42.78% and 73.02 % contribution respectively. [ABSTRACT FROM AUTHOR]

This paper presents an optimization of the Al2O3/distilled water-based nanofluid process parameters for enhancing its thermal conductivity. Nanoparticle volume concentration, nanoparticle size, sonication time, stirring time, and surfactant volume concentration are selected as optimization factors to obtain higher thermal conductivity. Eighteen different nanofluid samples having various preparation parameters are determined and prepared as per the Taguchi orthogonal array. Thermal conductivity was measured using the KD2 Pro thermal properties analyzer at a working temperature of 28 °C. To study the structure and crystallite size of alumina nanoparticles, we used X-ray diffraction. A scanning electron microscope is used to investigate the morphology and size of Al2O3 nanoparticles. To assess the effect of each parameter on thermal conductivity, the main effect plot for means and the signal-to-noise ratio are utilized. The statistical contribution percentage of each parameter on thermal conductivity is determined using an analysis of variance. The signal-to-noise ratio demonstrated that the nanoparticle concentration in a base fluid is the most affecting parameter, with a delta value of 0.715. Furthermore, with delta values of 0.461, 0.413, 0.272, and 0.177, the stirring time, sonication time, surfactant concentration, and nanoparticle size all play significant roles in nanofluid thermal conductivity. The outcome of the analysis of variance shows that the nanoparticle concentration in the base fluid has the most significant impact on the thermal conductivity of the nanofluid with a contribution of 36.64%, whereas initial stirring has a contribution of 26.82% and sonication time has a contribution of 19.76%, while surfactant concentration has an 8.83% contribution and nanoparticle size has a less significant contribution with a 4.06% contribution on the thermal conductivity of the nanofluid. The obtained results indicate that the thermal conductivity of the Al2O3/distilled water-based nanofluid increased by 7.146% compared to the base fluid, i.e., distilled water. The optimum thermal conductivity is obtained as 0.640732 W/m-K at optimum parameter settings of 0.3% of nanoparticle concentration, with a nanoparticle size of 50 nm, 40 minutes of sonication time, and 10 minutes of initial stirring time with 0.2% of surfactant concentration, A confirmation test with optimized parameters was finally carried out to ensure the method's confidence. [ABSTRACT FROM AUTHOR]

This paper reports the preparationand tribological investigation of Nylon 6 (N6) reinforced with graphite (Gr) mixtures. The experiment samples were ready in an Injection moulding machine, by fluctuating the weight extents of Gr particles mixed with N6. The significant three boundaries were considered to gauge the wear of the composite materials like burden (P), speed (N) and weight % of support (w) and similar three cycle boundaries are considered to foster the Numerical models. The mathematical models were created by the Design of Experiment. A symmetrical cluster L16 (45) and Analysis of Variance are applied to investigated the impact of interaction boundaries on the sliding wear conduct of these composites. [ABSTRACT FROM AUTHOR]

Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data. [ABSTRACT FROM AUTHOR]

The paper studies a mathematical model of an oscillator with viscoelastic damping, built on the basis of a differential equation containing a fractional derivative. By means of analysis of variance, a qualitative evaluation of this mathematical model is given and a confidence interval of the expected predicted value of the considered mathematical model is provided. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between the passion for entrepreneurship and corporate sustainability, considering that the desire for entrepreneurship is the fuel that entrepreneurs need to continue and achieve sustainability. This study aims to identify the nature of the relationship between entrepreneurial passion and corporate sustainability, an applied study in Asia Telecom. Passion is an important behavior, despite all the recent attention towards entrepreneurship passion, one particularly important question that has not been fully addressed What makes entrepreneurs passionate? The literature on the passion for entrepreneurship has almost universally focused on the passion towards "activities", as the current study aims to investigate a variety of activities related to the context of entrepreneurial passion (i.e. activities related to invention, establishment and development). As a result of the research, if the research sample consisted of (100) entrepreneurs, and a set of statistical methods were used for the Spss v.28 (Amos) program, standard deviations, arithmetic averages, correlations and variance analysis, and the study problem centered on the following essential question "What is the impact of the passion of entrepreneurship on the sustainability of companies," and the current study tried to verify the main hypothesis "there is a correlation between the passion for entrepreneurship and corporate sustainability. More about this source textSource text required for additional translation information. Design: Methodology: Approach The data was collected by designing a questionnaire distributed to (100) employees of the Asia Telecom Company. The hypotheses developed through the literature related to the research variables were tested. Results:The findings revealed a correlation and impact relationship between entrepreneurship passion and corporate sustainability, indicating the importance of entrepreneurship passion. The extent of its contribution to achieving success, discovering innovative opportunities, developing a new business intends to achieve corporate sustainability, and the method of effective performance in light of competition and unexpected environmental factors. Suppose it is based on three elements (Passion for invention, establishment, and passion for development and development). In that case, passion plays a critical role in creating new projects and their results, whichaligns with the sustainability requirements of a successful organization.Originality and value: This research develops and tests a model that explores the impact of entrepreneurship passion on corporate sustainability. [ABSTRACT FROM AUTHOR]

This paper dispenses a study on sustainability of TiN-TiCN-Al2O3−ZrCN coated tungsten carbide (WC) cutting inserts during dry condition turning of T6 tampered AA7075, through investigation of influence of cutting factors on tool flank wear (Fw), followed by their significance prediction on the desired output through analysis of variance (ANOVA) and prediction of mathematical model through regression analysis. Fw was optimized following signal to noise (S-N) ratio concept of Taguchi, and finally some confirmatory experiments were executed. Results revealed augmentation of Fw on enhancing spindle speed (N) and feed (f), but it reduced slightly on incrementing the cutting depth (d). N was the highest significant factor for Fw, taken after by f, whereas d was non-significant. The predicted model was significant, and possessed high determination coefficient. Optimization results revealed that the factorial combination N = 250 rpm, f = 0.05 mm.rev−1 and d = 0.2 mm was optimal for Fw, which was further validated through confirmatory experiments, resulting an improvement of S-N ratio by 7.1446 dB. [ABSTRACT FROM AUTHOR]

This paper dispenses influence of cutting factors on surface quality of AA7075 while turning with tungsten carbide (WC) tools coated with TiN-TiCN-Al2O3−ZrCN in dry cutting environment, followed by their significance prediction on the desired output through analysis of variance (ANOVA) and prediction of mathematical model through regression analysis. Average surface roughness (Ra) was optimized following signal to noise (S-N) ratio concept of Taguchi, and finally some confirmatory experiments were executed. Results revealed augmentation of Ra on enhancing spindle speed (N) or feed (f), but on incrementing the depth of cut (d), Ra reduced first, then increased and again reduced on further increase of d. The highest factor of significance for Ra was f, taken after by N. The predicted model was significant, and possessed high determination coefficient. Optimization results revealed that the factorial combination N = 250 rpm, f = 0.05 mm.rev−1 and d = 0.2 mm was optimal for Ra, which was further validated through confirmatory experiments. [ABSTRACT FROM AUTHOR]

Efficiency in the stock market is an essential component of the capital allocation system and is crucial in promoting economic growth. In recent years, there has been a growing number of publications focusing on the effect of Covid-19 on human norms. Although there are many studies on the impact of Covid-19 on human norms, the empirical implications of the Covid-19 pandemic on financial markets are still poorly understood. This paper adds to the literature by discussing the effects of a pandemic by studying the stock market efficiency before and after the first case of Covid-19 hit Malaysia. Several robust techniques are utilised to validate the efficient market hypothesis (EMH), namely Ljung-box, Hurst exponent, Chow-denning, and Variance ratio tests. Results indicate a strong influence of Covid-19 on the stock movement. The returns are efficient for the overall sample period. However inefficient after the global pandemic. The findings reported here suggest an increasing chance for market predictability in the Malaysian stock market during the global Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

This paper presents the phytochemical and antioxidant activities of single bulb garlic (Allium sativum) callus. The addition of sucrose by in vitro method can affect the secondary metabolites content of the callus. The experiment was designed to investigate the potential antioxidant activities of single bulb garlic callus with sucrose addition (30, 60, 90, and 120 g). The antioxidant activity was assessed using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) method; callus wet weight was analyzed using analysis of variance (ANOVA) followed by a Tukey test. The best callus, with an addition of 90 gL−1 of sucrose into Murashige Skoog medium with a callus wet weight of 5.29 g, produced a yellowish-white callus color and crumb texture. Phytochemical analysis revealed that the callus of a single bulb of garlic contained secondary metabolic chemicals such as phenolics, alkaloids, saponins, and triterpenoids. The treatment with 90 gL−1 of sucrose had the highest total phenolic content and antioxidant activity, with a TPC of 31.41 0.162 mg GAE/g and an IC50 of 33.78 g mL−1. Single bulb garlic callus has the potential to be developed into an antioxidant agent. [ABSTRACT FROM AUTHOR]

This paper first builds an agile manufacturing model involving external agility evaluation and internal enabling technology. Based on the model and international manufacturing strategy survey data, factor analysis and analysis of variance are used to compare the agility of manufacturing companies in China and the United States. It is found that China's agility is better than that of the United States in recent years, but the gap is not big. Then use regression analysis and analysis of variance to compare the application of various enabling technologies in the two countries, and explore the causes of the differences in agility between the two countries. The key lies in the in-depth application of specific technologies and the organization and coordination of the upstream and downstream of the supply chain in China. Finally, based on the above analysis, reasonable suggestions for improving the agility of Chinese manufacturing companies are put forward. [ABSTRACT FROM AUTHOR]

Joints of two dissimilar grades of aluminum are the requirement of the hour in several lightweight military assemblies. The Paper aims to seek the best probable combination of the factors involved in producing the quality joints of treated (AA6061) and treated (AA5083) aluminum alloy by the FSW process. The current study uses a hybrid Taguchi-PCA - Grey Relational Analysis (GRA) to perform friction joining of two unlike materials (AA5083 & AA6061). The principal component approach and grey relational technique were applied to evaluate the output properties such as tensile strength and % elongation. Tensile strength and % elongation testing values were used to predict the quality of the welded connection. The main input parameters include rotational speed, welding speed, and axial force. Analysis of variance (ANOVA) is used to obtain the significant contribution of parameters. The confirmation run establishes and validates the optimal levels of the process parameters. The results produced by using the optimized level of parameters lay in the range of 95% confidence in ideal settings with lesser variations. [ABSTRACT FROM AUTHOR]

A control flow error in a directed graph is a sequence of nodes (interpreted as a run through the graph) which is not a valid path in the graph. In this paper we study the detection of control flow errors and propose a configurable reference algorithm for the detection. With this algorithm we prove properties about which deviations are detected, depending on the choice of the nodes where to perform the check. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a new method we call “Tridiagonal Folded Kernel Enhanced Multivariance Products Representation (TFKEMPR)”, which involves both Tridiagonal Kernel Enhanced Multivariance Products Representation (TKEMPR) and Tridiagonal Folmat Enhanced Multivariance Products Representation (TFEMPR) as its very specific circumstances. [ABSTRACT FROM AUTHOR]

In this paper, the concept of Time Reversal Beamforming (TRBF) is put forward which forms a theoretical framework unifying the physical TR process and the signal processing method. Four TRBF systems are raised and their evolution illustrates that TRBF can be made more practical for target detection in real environments. The availability of these TRBF systems is shown by simulation and experiment. [ABSTRACT FROM AUTHOR]

This paper studies at developing an empirical relation to forecast the porosity and micro-hardness, by means of High Velocity Oxy Fuel (HVOF) method, of WC-10Co coatings. For determining the coating performance, process parameters such as LPG fuel flow rate, oxygen flow rate, spray distance, flow rate of carrier gas and feed rate of the coating powder play a significant role. Five-elements, Five-level Central Composite Rotatable Design (CCD) was employed in this analysis to reduce the number of experiments by covering all possible combinations of the process variables. A Mathematical model was established to assess the porosity and microhardness of the coatings including HVOF process parameters and the appropriateness of the model was examined using Variance of Analysis. The optimization of HVOF parameters using RSM, as well as the correlation of spray variables with properties of the coating, enables the recognition of the framework of the characteristics to attain the preferred consistency of WC-10Co coatings. [ABSTRACT FROM AUTHOR]

Mould designers have been struggling for the improvement of the cooling system performance, despite the fact that the cooling system complexity is physically limited by the fabrication capability of the conventional tooling methods. However, the growth of Solid Free Form Technology (SFF) allow the mould designer to develop more than just a regular conformal cooling channel. Numerous researchers demonstrate that conformal cooling channel was tremendously given significant result in the improvement of productivity and quality in the plastic injection moulding process. This paper presents the research work that applies the passive enhancement method in square shape cooling channel to enhance the efficiency of cooling performance by adding the sub groove to the cooling channel itself. Previous design that uses square shape cooling channel was improved by adding various numbers of sub groove to meet the best sub groove design that able reduced the cooling time. The effect of sub groove design on cooling time was investigated by Autodesk Modlflow Insight software. The simulation results showed that the various sub groove designs give different values to ejection time. The Design 7 showed the lowest value of ejection time with 24.3% increment. The addition of sub groove significantly increased a coolant velocity and a rate of heat transfer from molten plastic to coolant. [ABSTRACT FROM AUTHOR]

Coupled analysis of heat and moisture transport in complicated structural elements or in whole structures deserves a special attention because after space discretization, large number of degrees of freedom are needed. This paper describes possible solution of such problems based on domain decomposition methods executed on parallel computers. The Schur complement method is used with respect to nonsymmetric systems of algebraic equations. The method described is an alternative to other methods, e.g. two or more scale homogenization. [ABSTRACT FROM AUTHOR]

The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problem in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimizing proble3ms. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension. [ABSTRACT FROM AUTHOR]

In this paper, the aim was to introduce uninitiated readers extensive research on an incomplete Latin square design and pitfalls in methodology for solving the incomplete Latin square design. The incomplete Latin square design commonly leads to difficulties in the analysis of variance (ANOVA). Accordingly, several techniques were discussed by a number of researchers. It should be noted that the values of sums of squares in the ANOVA table by means of a missing-plot approach without adjusting the bias and an exact approach with a general regression significance test are not identical. This paper suggests to readers that the Latin square design of any order consisting of missing values should be analyzed by means of the exact approach or the missing-plot technique with adjusting the bias. A comprehensive review of the literature provided the gap for further research. It was a lack of definite formula for the ANOVA table with the exact approach for the cases of the incomplete Latin square design. It is thus of interest to provide the ready-made formula of the sums of squares by means of the exact approach in order to reduce the calculation process. [ABSTRACT FROM AUTHOR]

The 2.5D finite/infinite element approach for simulating the ground vibrations by surface or underground moving trains will be briefly summarized in this paper. By assuming the soils to be uniform along the direction of the railway, only a two-dimensional profile of the soil perpendicular to the railway need be considered in the modeling. Besides the two in-plane degrees of freedom (DOFs) per node conventionally used for plane strain elements, an extra DOF is introduced to account for the out-of-plane wave transmission. The profile of the half-space is divided into a near field and a semi-infinite far field. The near field containing the train loads and irregular structures is simulated by the finite elements, while the far field covering the soils with infinite boundary by the infinite elements, by which due account is taken of the radiation effects for the moving loads. Enhanced by the automated mesh expansion procedure proposed previously by the writers, the far field impedances for all the lower frequencies are generated repetitively from the mesh created for the highest frequency considered. Finally, incorporated with a proposed load generation mechanism that takes the rail irregularity and dynamic properties of trains into account, an illustrative case study was performed. This paper investigates the vibration isolation effect of the elastic foundation that separates the concrete slab track from the underlying soil or tunnel structure. In addition, the advantage of the 2.5D approach was clearly demonstrated in that the three-dimensional wave propagation effect can be virtually captured using a two-dimensional finite/infinite element mesh. Compared with the conventional 3D approach, the present approach appears to be simple, efficient and generally accurate. [ABSTRACT FROM AUTHOR]

Neuroblastoma is the most common solid tumor in children under 5 years of age. In this paper analysis of variance (ANOVA) is used to determine the prognostic significance of Imaging Defined Risk Factors (IDRF) for the time of relapse or death. IDRFs include a list of 20 conditions, separated across bodily compartments of tumor origin, with a slight overlap of some entities, when said entities are in transitional zones between two major compartments. They include vascular encasement by tumor, encasement of vital organs, infiltration of adjacent tissues. Each IDRF has to fulfil certain imaging criteria to be deemed as present in a given patient with neuroblastoma. The data are obtained from 42 patients – 16 boys and 26 girls, who have been admitted to the University Hospital “Saint Marina”, Varna, Bulgaria in the period 2000-2017. Time to event is calculated as the time from study entry to first event or date of last contact. [ABSTRACT FROM AUTHOR]

The crucial task in the prevention of ductile fracture is the availability of a tool for the prediction of such defect occurrence. The technical literature presents a wide investigation on this topic and many contributions have been given by many authors following different approaches. The main class of approaches regards the development of fracture criteria: generally, such criteria are expressed by determining a critical value of a damage function which depends on stress and strain paths: ductile fracture is assumed to occur when such critical value is reached during the analysed process. There is a relevant drawback related to the utilization of ductile fracture criteria; in fact each criterion usually has good performances in the prediction of fracture for particular stress - strain paths, i.e. it works very well for certain processes but may provide no good results for other processes. On the other hand, the approaches based on damage mechanics formulation are very effective from a theoretical point of view but they are very complex and their proper calibration is quite difficult. In this paper, two different approaches are investigated to predict fracture occurrence in cold forming operations. The final aim of the proposed method is the achievement of a tool which has a general reliability i.e. it is able to predict fracture for different forming processes. The proposed approach represents a step forward within a research project focused on the utilization of innovative predictive tools for ductile fracture. The paper presents a comparison between an artificial neural network design procedure and an approach based on statistical tools; both the approaches were aimed to predict fracture occurrence/absence basing on a set of stress and strain paths data. The proposed approach is based on the utilization of experimental data available, for a given material, on fracture occurrence in different processes. More in detail, the approach consists in the analysis of experimental tests in which fracture occurs followed by the numerical simulations of such processes in order to track the stress-strain paths in the workpiece region where fracture is expected. Such data are utilized to build up a proper data set which was utilized both to train an artificial neural network and to perform a statistical analysis aimed to predict fracture occurrence. The developed statistical tool is properly designed and optimized and is able to recognize the fracture occurrence. The reliability and predictive capability of the statistical method were compared with the ones obtained from an artificial neural network developed to predict fracture occurrence. Moreover, the approach is validated also in forming processes characterized by a complex fracture mechanics. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

Numerical simulation becomes essential in manufacturing large part by incremental forging processes. It is a splendid tool allowing to show physical phenomena however behind the scenes, an expensive bill should be paid, that is the computational time. That is why many techniques are developed to decrease the computational time of numerical simulation. Multi-Grid method is a numerical procedure that permits to reduce computational time of numerical calculation by performing the resolution of the system of equations on several mesh of decreasing size which allows to smooth faster the low frequency of the solution as well as its high frequency. In this paper a Multi-Grid method is applied to cogging process in the software Forge 3. The study is carried out using increasing number of degrees of freedom. The results shows that calculation time is divide by two for a mesh of 39,000 nodes. The method is promising especially if coupled with Multi-Mesh method. [ABSTRACT FROM AUTHOR]

In this paper a new non-parametric independence test is presented. García and González-López (2014) [1] introduced the LIS test for the hypothesis of independence between two continuous random variables, the test proposed in this work is a generalization of the LIS test. The new test does not require the assumption of continuity for the random variables, it test is applied to two datasets and also compared with the Pearson's Chi-squared test. [ABSTRACT FROM AUTHOR]

nnovation in the construction sector has the capacity to drive productivity and performance in the industry. However, the track record for investment in research and development (R&D) has been relatively unimpressive. The study was aimed at examining the barriers and enablers of R&D among construction firms. Using a research survey design of a questionnaire instrument, data was collected from construction firms in Lagos State. A purposive sampling technique was used in selecting construction firms within the study area. A total of 122 construction firms were surveyed. The study used statistical tools of compare mean score, principal component analysis (PCA) and analysis of variance (ANOVA) test. The study showed that the major barriers to R&D in construction firms were mainly lack of research funding, inadequate research facilities and low level of R&D at the national level. These barriers were further categorized as internal/government factors, construction market factors, and industry characteristics' factors. The major solutions to increase R&D in construction firms are exemption of import duties on industrial equipment for R&D, financial support from government & investors, and increase in information and communication usage in the industry. The study recommended the need to increase R&D at the national level with intensive policy making that engenders commitment in finance and actions that engineer R&D in all sectors of Nigeria's economy. [ABSTRACT FROM AUTHOR]

Studies of mangrove species's reflectance characteristic are important in order to have a deep understanding of mangrove vegetation. In this paper, the significant wavelengths which can be used to separate the six mangrove species at Matang Mangrove Forest Reserve (MMFR), Perak were examined. The investigated mangrove species comprise of Rhizophora apiculata, Acrostichum aurem, Acrostichum speciosum, Acanthus ilicifolius, Ceriops tagal and Sonneratia ovata. In-situ spectral reflectance data of six mangrove species's leaf were obtained using ASD FieldSpec3 spectroradiometer and were statistically tested using SPSS program. First, wavelengths which exhibited significant differences (P value<0.05) among the mean reflectance of six mangrove species were identified using a series of one way ANOVA. Second, the identified wavelengths were further analyzed using canonical stepwise discriminant analysis and 26 significant wavelengths were obtained which can be utilized to distinguish among the six mangrove species. In conclusion, each mangrove species in MMFR have it own unique reflectance properties and these characteristic enable the mangrove species can be discriminated among each other under proper analysis and data extraction. [ABSTRACT FROM AUTHOR]

The aim of this paper is to extend the theory of F-tests with random sample sizes to situations when missing observations may occur. We consider the one-way ANOVA with fixed effects. This approach is illustrated through an application to patients affected by melanoma skin cancer, from three different states of Brazil. [ABSTRACT FROM AUTHOR]

This is research was conducted in a company engaged in the field of plastic resin processing, as the main raw material for packing rice and fertilizer. The problem is formulated to this work is the influence of temperature and noise levels to the activities of the operator at the work station of smoothed woven plastic sacks. The purpose of this study was to obtain an overview of the effects of temperature and noise level on the work of the operator at the work station smoothed woven plastic sacks on this manufacturing with ANOVA method as hypothesis testing. The result from this research that shown temperature factor in this company has a significant influence on the work of operator. This study suggests for deeper research on the temperature in this company so that the operator comfortable in working. [ABSTRACT FROM AUTHOR]

Best subsets regression is an effective approach to distinguish models that can attain objectives with as few predictors as would be prudent. Subset models might really estimate the regression coefficients and predict future responses with smaller variance than the full model using all predictors. The inquiry of how to pick subset size X depends on the bias and variance. There are various method to pick subset size X. Regularly pick the smallest model that minimizes an estimate of the expected prediction error. Since data are regularly small, so Repeated K-fold cross-validation method is the most broadly utilized method to estimate prediction error and select model. The data is reshuffled and re-stratified before each round. However, the "one-standard-error" rule of Repeated K-fold cross-validation method always picks the most stingy model. The objective of this research is to modify the existing cross-validation method to avoid overfitting and underfitting model, a modified cross-validation method is proposed. This paper compares existing cross-validation and modified cross-validation. Our results reasoned that the modified cross-validation method is better at submodel selection and evaluation than other methods. [ABSTRACT FROM AUTHOR]

Electrical Discharge Machining (EDM) is a non-conventional machining process, which is popular to make dies and moulds in manufacturing industry. This paper presents the machining work of powder mixed EDM on HcHcr D2 tool steel, which produces better results than conventional process. MMC electrodes are widely used in the industry therefore attempt has been made to see the effect of Al SiC composite in PMEDM. Nickel and chromium powders were used as additives in dielectric fluid. Pulse on time, current, voltage and duty cycle of EDM were chosen as design variables to see the effect on response factors in terms of Material Removal Rate (MRR) and Tool Wear Rate (TWR). Full factorial design and ANOVA has been used to plan and analyse the experiment. The most important variables affecting selected response measures are identified and effects of additive variations have been observed. Result shows the positive influence of the Nickel and Chromium powders for the improvement of material removal rate and tool were rate. The parametric optimization's results from this study will be useful for EDM industry to select appropriate design parameters and levels. [ABSTRACT FROM AUTHOR]

In the classical design of experiment, a randomized complete block design (RCBD) is a helpful experimental design because this design uses a small number of experimental units. The randomized complete block design is comprised of two factors, i.e., one nuisance factor and one potential factor. In many real experiments, some data may be missing or unrecorded. The instant formulae were not provided for an analysis of variance in this case. This paper took into account the RCBD with a treatments and b blocks. In this contribution, the RCBD with an unrecorded value was analyzed by means ofthe exact scheme with the general linear model. Due to no ready-made formula in the past, this research paper provided the mathematical formulae for the fitted parameters and the overall regression sum of squares (ORSS) for the full model of experimental data. [ABSTRACT FROM AUTHOR]

This paper deals with the estimability of variance components, in mixed models, when the dimension of the commutative algebra, spanned by all possible variance-covariance matrices, is greater than the number of linearly independent unknown variance components. As example we present an application to a random three-factor crossed-model. [ABSTRACT FROM AUTHOR]

The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria. [ABSTRACT FROM AUTHOR]

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia. [ABSTRACT FROM AUTHOR]

In this study we first give short extract from our forthcoming paper for Newton-Padé approximations for univariate next, we generalize main lemmas for the case of multivariate functions. [ABSTRACT FROM AUTHOR]

In this paper, we discuss control variate methods for Asian option pricing under exponential jump diffusion model for the underlying asset prices. Numerical results show that the new control variate XNCV is much more efficient than the classical control variate XCCV when used in pricing Asian options. For example, the variance reduction ratios by XCCV are no more than 120 whereas those by XNCV vary from 15797 to 49171 on average over sample sizes 1024, 2048, 4096, 8192, 16384 and 32768. [ABSTRACT FROM AUTHOR]

This paper studies the one-dimensional wave propagation in an elastic medium with spatially non-uniform quadratic nonlinearity. Two problems are solved analytically. One is for a time-harmonic wave propagating in a half-space where the displacement is prescribed on the surface of the half-space. It is found that spatial non-uniformity of the material nonlinearity causes backscattering of the second order harmonic, which when combined with the forward propagating waves generates a standing wave in steady-state wave motion. The second problem solved is the reflection from and transmission through a layer of finite thickness embedded in an otherwise linearly elastic medium of infinite extent, where it is assumed that the layer has a spatially non-uniform quadratic nonlinearity. The results show that the transmission coefficient for the second order harmonic is proportional to the spatial average of the nonlinearity across the thickness of the layer, independent of the spatial distribution of the nonlinearity. On the other hand, the coefficient of reflection is proportional to a weighted average of the nonlinearity across the layer thickness. The weight function in this weighted average is related to the propagating phase, thus making the coefficient of reflection dependent on the spatial distribution of the nonlinearity. Finally, the paper concludes with some discussions on how to use the reflected and transmitted second harmonic waves to evaluate the variance and autocorrelation length of nonlinear parameter β when the nonlinearity distribution in the layer is a stochastic process. [ABSTRACT FROM AUTHOR]

In this paper we revisit the quantitative formulation of the Heisenberg uncertainty principle. The primary version of this principle establishes the impossibility of refined simultaneous measurement of position x and momentum u for a (1-dimensional) quantum particle in terms of variances: <|x|2><|u|2>>=1/4. Since this inequality applies provided each variance exists, some authors proposed entropic versions of this principle as an alternative (employing Shannon's or Rényi's entropies). As another alternative, we consider moments-based formulations and show that inequalities involving moments of orders other than 2 can be found. Our procedure is based on the Rényi entropic versions of the Heisenberg relation together with the search for the maximal entropy under statistical moments' constraints (<|x|a> and <|u|b>). Our result improves a relation proposed very recently by Dehesa et al.. [1] where the same approach was used but starting with the Shannon version of the entropic uncertainty relation. Furthermore, we show that when a =b, the best bound we can find with our approach coincides with that of Ref. [1] and, in addition, for a = b = 2 the variance-based Heisenberg relation is recovered. Finally, we illustrate our results in the cases of d-dimensional hydrogenic systems. [ABSTRACT FROM AUTHOR]

This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Micro metal injection molding (μMIM) which is a variant of MIM process is a promising method towards near net-shape of metallic micro components of complex geometry. In this paper, μMIM is applied to produce 316L stainless steel micro components. Due to highly stringent characteristic of μMIM properties, the study has been emphasized on optimization of process parameter where Taguchi method associated with Grey Relational Analysis (GRA) will be implemented as it represents novel approach towards investigation of multiple performance characteristics. Basic idea of GRA is to find a grey relational grade (GRG) which can be used for the optimization conversion from multi objectives case which are density and strength to a single objective case. After considering the form 'the larger the better', results show that the injection time(D) is the most significant followed by injection pressure(A), holding time(E), mold temperature(C) and injection temperature(B). Analysis of variance (ANOVA) is also employed to strengthen the significant of each parameter involved in this study. [ABSTRACT FROM AUTHOR]

Taguchi method of L27 (313) orthogonal array is used in this paper as a tool in optimization of Metal injection molding (MIM) parameters for the highest green strength. Parameters optimized are the injection pressure, injection temperature, powder loading, mold temperature, holding pressure and injection speed. Besides those, interaction of the injection pressure, injection temperature and powder loading were studied. The metal powder of Ti-6Al-4V is mixed with binder 60wt% of palm stearin and 40wt% of polyethylene successfully injected at optimum parameter condition: 350 bar of injection pressure, 140° C of injection temperature, 65vol% of powder loading, 50° C of mold temperature, 600 bar of holding pressure, and 10 ccm/s of the injection rate. Analysis of variance (ANOVA) for the best signal to noise ratio (S/N) presents the contribution of the parameters to the quality characteristic (green strength). Results show that the mold temperature has highest significant percentage (27.59%) followed by powder loading (15.44%) and injection pressure (12.30%). Nevertheless, the analysis of variance does not show any contribution from interaction. [ABSTRACT FROM AUTHOR]

The water entry problem is considered as a classic problem which has a research history of more than 70 years, the water-entry process for projectiles with different nose will be significant for related application and experimental design. In this paper, a series of numerical simulations were conducted to study the water-entry behaviors of cylindrical, hemispherical and conical projectiles using the coupled Lagrange-Euler technology in the non-linear finite element code AUTODYN-2D. The detailed cavity expansion process and the cavity characteristics of three projectiles in the early stages of water-entry were obtained. The effects of the projectile nose shape and the projectile velocity on the cavity shapes were studied. Simultaneously, the laws of velocity attenuations for three projectiles were also proposed in this study. The results show that cylindrical projectile has the minimum ratio of the cavity length to the cavity half thickness among the three projectiles when they have identical impact velocities and the smoothed nose shape of projectiles can help reduce the water resistance, thus slowing down the velocity attenuations. [ABSTRACT FROM AUTHOR]

The emergence of ultra-sharp carbon nanotube (CNT) tips provides a new approach to minimize the distortion of the measured linewidth profile caused by interaction with the finite probe tip size. However, the inevitable tilt angle resulting from attaching the nanotube to an ordinary probe causes a significant probe-related distortion on one sidewall of the linewidth sample. In order to obtain accurate images at both sidewalls, the sample is measured twice. After the first measurement which provides an accurate image on one sidewall, the sample is rotated 180° to measure the other sidewall. The two images are stitched together as a composite image in which both sidewall images are minimally distorted. To accurately stitch the two images, their position difference caused by the 180° rotation must be eliminated. In this paper, the template matching method is adopted after the primary image processing that includes surface leveling and rotation. At the optimum matching position, these two images are stitched as a composite image, in which the average linewidth and the standard deviation are calculated. [ABSTRACT FROM AUTHOR]

This paper is focused on the determination of mechanics characteristics for tubular materials, using tube bulge process. A comparative study is made between two different models: theoretical model and finite element analysis. The theoretical model is completely developed, based first on a geometrical analysis of the tube profile during bulging, which is assumed to strain in arc of circles. Strain and stress analysis complete the theoretical model, which allows to evaluate tube thickness and state of stress, at any point of the free bulge region. Free bulging of a 304L stainless steel is simulated using Ls-Dyna 970. To validate FE simulations approach, a comparison between theoretical and finite elements models is led on several parameters such as: thickness variation at the free bulge region pole with bulge height, tube thickness variation with z axial coordinate, and von Mises stress variation with plastic strain. Finally, the influence of geometrical parameters deviations on flow stress curve is observed using analytical model: deviations of the tube outer diameter, its initial thickness and the bulge height measurement are taken into account to obtain a resulting error on plastic strain and von Mises stress. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

When constructing non-parametric models from noisy data, it is useful to have information regarding the statistical properties of the noise distribution. In many cases, such information is not explicitly available, and must be estimated directly from the data. Under the hypothesis of additive noise, algorithms for estimating the variance of the noise distribution have appeared in the literature. In this paper we present a novel algorithm for estimating the noise variance under a multiplicative hypothesis. © 2005 American Institute of Physics [ABSTRACT FROM AUTHOR]

Computational science and engineering methods have allowed a major change in the way products and processes are designed, as validated virtual models -- capable to simulate physical, chemical and bio changes occurring during production processes - can be realized and used in place of real prototypes and performing experiments, often time and money consuming. Among such techniques, Optimal Shape Design (OSD) (Mohammadi & Pironneau, 2004) represents an interesting approach. While most classical numerical simulations consider fixed geometrical configurations, in OSD a certain number of geometrical degrees of freedom is considered as a part of the unknowns: this implies that the geometry is not completely defined, but part of it is allowed to move dynamically in order to minimize or maximize the objective function. The applications of optimal shape design (OSD) are uncountable. For systems governed by partial differential equations, they range from structure mechanics to electromagnetism and fluid mechanics or to a combination of the three. This paper presents one of possible applications of OSD, particularly how extrusion bell shape, for past production, can be designed by applying a multivariate constrained shape optimization. [ABSTRACT FROM AUTHOR]

Injection moulding is well known for its manufacturing process especially in producing plastic products. To measure the final product quality, there are lots of precautions to be taken into such as parameters setting at the initial stage of the process. Sometimes, if these parameters were set up wrongly, defects may be occurred and one of the well-known defects in the injection moulding process is a shrinkage. To overcome this problem, a maximisation at the precaution stage by making an optimal adjustment on the parameter setting need to be done and this paper focuses on analysing the shrinkage by optimising the parameter at thick plate part with the help of Response Surface Methodology (RSM) and ANOVA analysis. From the previous study, the outstanding parameter gained from the optimisation method in minimising the shrinkage at the moulded part was packing pressure. Therefore, with the reference from the previous literature, packing pressure was selected as the parameter setting for this study with other three parameters which are melt temperature, cooling time and mould temperature. The analysis of the process was obtained from the simulation by Autodesk Moldflow Insight (AMI) software and the material used for moulded part was Acrylonitrile Butadiene Styrene (ABS). The analysis and result were obtained and it found that the shrinkage can be minimised and the significant parameters were found as packing pressure, mould temperature and melt temperature. [ABSTRACT FROM AUTHOR]

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model. [ABSTRACT FROM AUTHOR]