Values Of Independent Variables Research Articles

Analisis Penawaran Jagung di Jawa Tengah

<p>This research aims to analyze some factors that influence the corn supply in Central Java, and to analyze the corn supply elasticity in Central Java. The basic method used in this research is descriptive method. The location of this research stated with purposive, that is Central Java Province. And the data used in this research is secondary data.</p><p>The analysis results the value of adjusted determination coefficient that is 87,6% and F-test analysis results that F-count (18,632) is greater than F-table (3,79) means that all the independent variables used in this research, which are corn’s harvested area in the recent year, corn’s production in the previous year, corn’s price in the previous year, peanut’s price in the previous year, urea fertilizer’s price in the previous year and the average of rainfall along the plant time influence in the together to the corn supply in Central Java. The results of t-test shows that corn’s harvested area in the recent year, corn’s production in the previous year, corn’s price in the previous year and urea fertilizers price in the previous year variables are the significant influential independent variables to the corn supply in Central Java. While based on the partial regression coefficient value of the significant influential independent variables, it is found that the corn’s harvested area in the recent area year has the highest value (0,992), so this variable has the greatest influence to the corn supply in Central Java.</p><p>The corn supply elasticity in Central Java to the harvested area (0,948), corn’s production in the previous year (0,434), corn’ price in the previous year (0,709), urea fertilizer’s price in the previous year (0,161) in short-run is tend to be inelastic. While in long-run, corn’s supply is tend to be elastic to the corn’s harvested are (1,696) and corn’s price in the previous year (1,296). And corn supply is tend to be inelastic to the corn’s production in the previous year (0,777) and urea fertilizer’ price in the previous year (0,289).</p><p>The results of this research shows that the corn’s farmers in Central Java in planting corn take the decisions based on profit (profit oriented) and have high response of the changing of corn’s harvested area in Central Java.</p>

ANALISIS PENGARUH KEPEMILIKAN MANAJERIAL, PROPORSI DEWAN KOMISARIS INDEPENDEN, DAN KONSERVATISME AKUNTANSI TERHADAP KUALITAS LABA SERTA PENGARUHNYA TERHADAP NILAI PERUSAHAAN

This research aims to examine the effect beetween managerial ownership, proportion of independent commissioner, accounting conservatism towards earnings quality and firm value. In the first research model, managerial ownership, proportion of independent commisioner, accounting conservatism are the independent variables while earnings quality is the dependent variable. In the second research model, earnings quality is the independent variable and firm value is the dependent varible. Object of this research is manufacturing companies that are listed in Indonesian Stock Exchange (BEI) during 2014 to 2016. For the first research model there are 156 sampels and 273 sampels for the second research model. Hypotheses examination for the first research model using multiple linear regressions and for the second model using simpel linear regression with SPSS version 23.0. The result from the first research model shows managerial ownership and proportion of independent commissioner has no effect towards earnings quality, while accounting conservatism have an effect towards earnings quality. The result from the second research model shows that earnings quality has an effect towards firm value.

Improved multislope MUSCL reconstruction on unstructured grids for shallow water equations

SummaryIn shallow water flow and transport modeling, the monotonic upstream‐centered scheme for conservation laws (MUSCL) is widely used to extend the original Godunov scheme to second‐order accuracy. The most important step in MUSCL‐type schemes is MUSCL reconstruction, which calculate‐extrapolates the values of independent variables from the cell center to the edge. The monotonicity of the scheme is preserved with the help of slope limiters that prevent the occurrence of new extrema during reconstruction. On structured grids, the calculation of the slope is straightforward and usually based on a 2‐point stencil that uses the cell centers of the neighbor cell and the so‐called far‐neighbor cell of the edge under consideration. On unstructured grids, the correct choice for the upwind slope becomes nontrivial. In this work, 2 novel total variation diminishing schemes are developed based on different techniques for calculating the upwind slope and the downwind slope. An additional treatment that stabilizes the scheme is discussed. The proposed techniques are compared to 2 existing MUSCL reconstruction techniques, and a detailed discussion of the results is given. It is shown that the proposed MUSCL reconstruction schemes obtain more accurate results with less numerical diffusion and higher efficiency.

Indonesian Highway Capacity Guidance (IHCG) correction factor for signalized intersection

Indonesian Highway Capacity Guidance or IHCG is a manual developed in 2014 to accommodate traffic characteristics which are no longer appropriate to the preceding manual (Indonesian Highway Capacity Manual or IHCM, established in 1997). From a preliminary study, there are still some differences between theoretical analysis (using IHCG) with the actual conditions. This study aims to obtain IHCG correction factor based on a comparison between predicted performance parameter of a signalized intersection (using IHCG) and measured data, in order to optimize IHCG development. Intersection performance parameters analyzed are the number of queue vehicles (NQ1 and NQ2), and queue length (QL). The model of the correction factor was determined with regression analysis, using DS value as the independent variable, and NQ1, NQ2, or QL differences value as the dependent variables. Implementation of the proposed correction factor of queue length on nearby intersections resulted that the corrected guidance could produce more accurate queue length against measured one by 12% deviation.

Concentration of fruit juice aroma compound from model multicomponent solution and natural apple juice hydrolate: Optimization and modeling by design of experiment

AbstractThis study presents aroma compounds separation from a model multicomponent solution as well as natural apple juice hydrolate by pervaporation (PV). Response surface methodology (RSM) was used to determine the influence of the operating parameters on membrane separation performance. The experiments were planned in accordance with the Box–Behnken design for such three input variables as temperature, feed flow rate, and the concentration of aroma compounds in the feed. For the enrichment factor as the system response, the optimal values of independent variables amounted to respectively T = 60 °C, Q = 1.30 dm3/min, and C = 0.5 wt %. For these conditions, the enrichment factor was predicted to be 87.56. In the last step, PV of apple juice hydrolate was performed under optimal conditions as determined through RSM for a multicomponent system. Optimal conditions determined by RSM for the model solution allowed for getting satisfactory effectiveness of PV of real fruit juice hydrolate.Practical ApplicationsAroma compounds of natural origin have nowadays become a precious commodity, due to a growing awareness on the part of the customers who are concerned with the quality and origin of the goods they purchase. Manufacturers are on the lookout for new production techniques that can reduce energy, natural resources or reagents consumption. Pervaporation (PV) ranks among such techniques, thanks to mild process conditions, low energy consumption, modular apparatus, and high effectiveness as compared to the commonly applied thermic processes or extractions with solvents. The current study investigates mathematical modeling of PV in order to determine optimal process parameters for separation experiments of aroma compounds from multicomponent aqueous systems as well as apple juice hydrolate. So far, RSM coupled with Box–Behnken design has not been applied for PV optimization of aroma compounds from multicomponent aqueous solutions. Additionally, PV has not yet been applied in the concentration of apple juice hydrolate.

Prediction of Percent Change in Linear Regression by Correlated Variables

Multiple linear regression can be applied for predicting an individual value of dependent variable y by the given values of independent variables x. But it is not immediately clear how to estimate percent change in y due to changes in predictors, especially when those are correlated. This work considers several approaches to this problem, including its formulation via predictors adjusted by their correlation structure. Ordinary least squares regression is used, together with Shapley value regression and another model based on solving some system of differential equations. Numerical estimations performed for a real marketing research data demonstrate meaningful results. The considered techniques can be very useful in practical estimations of the percent change of dependent variable by the change in predictors.

A QSAR model of Olanzapine derivatives as potential inhibitors for 5-HT2A Receptor.

Schizophrenia is a complex, chronic mental disorder, affecting about 21 million people worldwide. It is characterized by symptoms, including distortions in thinking, perception, emotions, disorganized speech, sense of self and behavior. Recently, a numbers of marketed drugs for Schizophrenia are available against dopamine D2 and serotonin 5-HT2A receptors. Here, we docked Olanzapine derivatives (collected from literature) with 5-HT2A Receptor using the program AutoDock 4.2. The docked protein inhibitor complex structure was optimized using molecular dynamics simulation for 5ps with the CHARMM-22 force field using NAMD (NAnoscale Molecular Dynamics program) incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. A quantitative structure activity relationship (QSAR) model was built using energy-based descriptors as independent variable and pKi value as dependent variable of eleven known Olanzapine derivatives with 5-HT2A Receptor, yielding correlation coefficient r2 of 0.63861. The predictive performance of QSAR model was assessed using different crossvalidation procedures. Our results suggest that a ligand-receptor binding interaction for 5-HT2A receptor using a QSAR model is promising approach to design more potent 5-HT2A receptor inhibitors prior to their synthesis.

Absence of ultrasound inflammation in patients presenting with arthralgia rules out the development of arthritis

BackgroundTo decrease the burden of disease of rheumatoid arthritis (RA), patients at risk for RA need to be identified as early as possible, preferably when no clinically apparent synovitis can be detected. Up to now, it has been fairly difficult to identify those patients with arthralgia who develop inflammatory arthritis (IA), but recent studies using ultrasound (US) suggest that earlier detection is possible. We aimed to identify patients with arthralgia developing IA within 1 year using US to detect subclinical synovitis at first consultation.MethodsIn a multi-centre cohort study, we followed patients with arthralgia with at least two painful joints of the hands, feet or shoulders without clinical synovitis over 1 year. Symptom duration was < 1 year, and symptoms were not explained by other conditions. At baseline and at 6 and 12 months, data were collected for physical examinations, laboratory values and diagnoses. At baseline, we examined 26 joints ultrasonographically (bilateral metacarpophalangeal joints 2–5, proximal interphalangeal joints 2–5, wrist and metatarsophalangeal joints 2–5). Scoring was done semi-quantitatively on greyscale (GS; 0–3) and power Doppler (PD; 0–3) images. US synovitis was defined as GS ≥ 2 and/or PD ≥ 1. IA was defined as clinical soft tissue swelling. Sensitivity and specificity were used to assess the diagnostic value of US for the development of IA. Univariate logistic regression was used to analyse the association between independent variables and the incidence of IA. For multivariate logistic regression, the strongest variables (p < 0.157) were selected. Missing values for independent variables were imputed.ResultsA total of 196 patients were included, and 159 completed 12 months of follow-up. Thirty-one (16%) patients developed IA, of whom 59% showed US synovitis at baseline. The sensitivity and specificity of US synovitis were 59% and 68%, respectively. If no joints were positive on US, negative predictive value was 89%. In the multivariate logistic regression, age (OR 1.1), the presence of morning stiffness for > 30 minutes (OR 3.3) and PD signal (OR 3.4) were associated with incident IA.ConclusionsThe presence of PD signal, morning stiffness for > 30 minutes and age at baseline were independently associated with the development of IA. Regarding the value of US in the diagnostic workup of patients with early arthralgia at risk for IA, US did perform well in ruling out IA in patients who did not have US synovitis.

Development and characterization of soluble fiber enriched noodles via fortification with partially hydrolyzed guar gum

Partially hydrolyzed guar gum was prepared via enzymatic hydrolysis of native guar gum. Partially hydrolyzed guar gum (PHGG) thus obtained after enzymatic hydrolysis contained 80.04% soluble dietary fiber and 83.1% total dietary fiber. In present study, the effect of process variables such as PHGG level (1–5%), water level (30–40%) and mixing time (2–6 min) on response variables i.e. cooking yield, cooking loss and overall acceptability of noodles were studied using response surface methodology. The second order model obtained for cooking yield, cooking loss and overall acceptability of noodles revealed coefficient of determination of 0.9796, 0.9446 and 0.7787, respectively. The optimum values for independent variables i.e. PHGG level, water level and mixing time were 2.23, 32.03% and 2.81 min, respectively. Results showed that noodles with reduced cooking yield, increased cooking loss and improved sensory and textural characteristics were prepared with fortification of 2.23% partially hydrolyzed guar gum as soluble fibre.

Multiplicative Models For Continuous Dependent Variables: Estimation on Unlogged versus Logged Form

In regression analysis with a continuous and positive dependent variable, a multiplicative relationship between the unlogged dependent variable and the independent variables is often specified. It can then be estimated on its unlogged or logged form. The two procedures may yield major differences in estimates, even opposite signs. The reason is that estimation on the unlogged form yields coefficients for the relative arithmetic mean of the unlogged dependent variable, whereas estimation on the logged form gives coefficients for the relative geometric mean for the unlogged dependent variable (or for absolute differences in the arithmetic mean of the logged dependent variable). Estimated coefficients from the two forms may therefore vary widely, because of their different foci, relative arithmetic versus relative geometric means. The first goal of this article is to explain why major divergencies in coefficients can occur. Although well understood in the statistical literature, this is not widely understood in sociological research, and it is hence of significant practical interest. The second goal is to derive conditions under which divergencies will not occur, where estimation on the logged form will give unbiased estimators for relative arithmetic means. First, it derives the necessary and sufficient conditions for when estimation on the logged form will give unbiased estimators for the parameters for the relative arithmetic mean. This requires not only that there is arithmetic mean independence of the unlogged error term but that there is also geometric mean independence. Second, it shows that statistical independence of the error terms on regressors implies that there is both arithmetic and geometric mean independence for the error terms, and it is hence a sufficient condition for absence of bias. Third, it shows that although statistical independence is a sufficient condition, it is not a necessary one for lack of bias. Fourth, it demonstrates that homoskedasticity of error terms is neither a necessary nor a sufficient condition for absence of bias. Fifth, it shows that in the semi-logarithmic specification, for a logged error term with the same qualitative distributional shape at each value of independent variables (e.g., normal), arithmetic mean independence, but heteroskedasticity, estimation on the logged form will give biased estimators for the parameters for the arithmetic mean (whereas with homoskedasticity, and for this case thus statistical independence, estimators are unbiased, from the second result above).

Carboxymethyl cellulose production from sugarcane bagasse with steam explosion pulping: Experimental, modeling, and optimization

The sugarcane bagasse was used for producing carboxymethyl cellulose (CMC) and obtaining high-molecular-mass hemicellulose as co-product. To this end, the steam explosion process was employed. It was found that the optimum operating conditions are the temperature of 187.15°C, NaOH/bagasse ratio of 39% (w/w), and retention time (RT) of 10min. Next, the obtained cellulose in the optimized condition was extracted and purified, and it was subsequently converted to CMC according to Williamson etherification technique. This paper also employed response surface methodology (RSM) to model effective factors against a degree of substitution (DS). Based on it, the optimum values of independent variables are the NaOH concentration of 28.4%, MCA mass of 1.14gram, temperature of 57.85°C, and reaction time of 4.01h which the CMC had the DS of 1.085, the yield of 181.302%, purity of 71.6%, and crystallinity of 30.1% with low viscosity. Samples comparatively studied by FT-IR, TGA and XRD.

Pengaruh Kualitas Produk dan Religiusitas Terhadap Keputusan Nasabah dalam Memilih Asuransi Syariah di PT. Prudential Life Anssurance Cabang Kota Gorontalo

This study aims to determine the Effect of Product Quality and Religiosity on customer decisionsin choosing Islamic insurance at PT.Prudential Life Anssurance Branch of Gorontalo City, with asample size of 177 respondents using random sampling method. This study uses multiple regressionanalysis tool on primary data found that the factor of Product Quality have positive andsignificant influence to customer decision to choose sharia insurance and religiosity have positiveand significant influence to customer decision to choose sharia insurance.The result of hypothesis test simultaneously (Test F) from both independent variables withFhitung equal to 80,111 in area of Ho rejected. This means that simultaneously factor of productquality and religiosity have a positive and significant influence to the decision of customers tochoose sharia insurance in PT. Prudential Life Ansurance Branch of Gorontalo City.Determination coefficient value of both independent variables obtained results of 0.479, it meansthat the Effect of Product Quality and Religiosity on customer decisions in choosing shariainsurance in PT.Prudential Life Anssurance Branch of Gorontalo City of 47.9% and the rest of52.1% influenced by other variables Which were not included in this study. Other variables may bepresent in marketing mix such as: promotion, people, place, process, and physical evidence.

Environmental arsenic exposure and risk of diabetes type 2 in Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand: unmatched and matched case-control studies.

BackgroundThere are inconsistent findings on associations between low-to-moderate level of arsenic in water and diabetes risk from previous epidemiological reports. In Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand, a low level of arsenic exposure among population was observed and increased diabetes mellitus (DM) rate was identified.ObjectivesWe aimed to investigate the association between determinants (including low-level water arsenic exposure) of DM type 2 risk among residents of three villages of Ron Phibun subdistrict, Nakhon Si Thammarat Province.Materials and methodsSecondary data from two previous community based-studies, conducted in 2000 and 2008, were utilized. Data on independent variables relating to arsenic exposure and sociodemographic characteristics were taken from questionnaires and worksheets for health-risk screening. Water samples collected during household visit were sent for analysis of arsenic level at certified laboratories. Diabetes cases (N=185) were those who had been diagnosed with DM type 2. Two groups of controls, one unmatched to cases (n=200) and one pair matched on age and gender (n=200), were selected for analysis as unmatched and matched case–control studies, respectively. A multiple imputation technique was used to impute missing values of independent variables. Multivariable logistic regression models, with independent variables for arsenic exposure and sociodemographic characteristics, were constructed. The unmatched and matched data sets were analyzed using unconditional and conditional logistic analyses, respectively.ResultsOlder age, body mass index (BMI), having a history of illness in siblings and parents, and drinking were associated with increased DM type 2 risk. We found no convincing association between DM type 2 risk and water arsenic concentration in either study.ConclusionWe did not observe meaningful association between diabetes risk and the low-to-moderate arsenic levels observed in this study. Further research is needed to confirm this finding in the study area and elsewhere in Thailand.

Hubungan Disiplin Kerja dan Motivasi Kerja dengan Efektivitas Kerja Pegawai PT. Aqua Golden Mississipi Cicurug Sukabumi

&#x0D; Aqua Golden Mississippi Cicurug Sukabumi is one of the company engaged in the provision of bottled water in Indonesia, which lead employees to work productively and can carry out their duties properly. Problem often encountered leader PT. Aqua Golden Mississippi is how to find the best way to be taken in order to mobilize and increase the effectiveness of employees in order to consciously and responsibly carry out the task as well as possible, because every employee has a need and desire different that leaders must know and understand the needs and wishes of the members.&#x0D; &#x0D; Based on the background of the problem, then that becomes the central issue in&#x0D; this study is how much influence the work of discipline and motivation to work against the&#x0D; effectiveness of employees, from the data above the authors try to identify the problem as follows: How does the discipline of work, how&#x0D; to discipline the working relationship with the effectiveness of employees, how the work&#x0D; motivation of employees, how the relationship with the effectiveness of work motivation, how the effectiveness of employees, and how&#x0D; relationships work discipline and motivation of employees working with the effectiveness of&#x0D; employees in PT. Aqua Golden Mississippi&#x0D; Cicurug Sukabumi&#x0D; Research used in this research is descriptive method. Method is a descriptive study to determine the value of independent variables. In this study the descriptive method used to see an overview of each independent variable. While the unit is the unit of analysis&#x0D; &#x0D; that will be used to explain or describe the characteristics of a larger set of objects again.&#x0D; The results of assessment of the&#x0D; relationship of work discipline and motivation to work with employee work effectiveness can be summarized as follows:&#x0D; 1) Employee labor relations discipline&#x0D; (X1) with employee work effectiveness (Y)&#x0D; is shown by a correlation value of r X 1 with Y = 0.816, means a relationship (X1) and (Y) very strong, and its influence + (positive).&#x0D; 2) Labor relations employee motivation (X2) with employee work effectiveness (Y) is shown by the value of X2 with Y correlation of r = 0.890, means a relationship (X2) and (Y) very strong, and its influence + (positive).&#x0D; 3) Relationship of labor discipline (X1)&#x0D; and employee motivation (X2) together with employee work effectiveness (Y) is&#x0D; shown by the multiple correlation, which&#x0D; shows the value of r = 0.949, and the magnitude of the relationship of labor discipline and the effectiveness of employee work motivation employees working at 90.1% (R square = 0.901), this statement has meaning relations (X1) and (X2) and (Y) has a very strong positive relationship.&#x0D; &#x0D; Keywords: Employment Relations, Work Motivation Discipline, Employee Work Effectiveness

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

Factors associated with cholera in Kenya, 2008-2013.

IntroductionKenya experienced widespread cholera outbreaks in 1997-1999 and 2007-2010. The re-emergence of cholera in Kenya in 2015 indicates that cholera remains a public health threat. Understanding past outbreaks is important for preventing future outbreaks. This study investigated the relationship between cholera occurrence in Kenya and various environmental and demographic factors related to water, sanitation, socio-economic status, education, urbanization and availability of health facilities during the time period 2008-2013.MethodsThe primary outcome analyzed was the number of cholera cases at the district level, obtained from the Kenya Ministry of Health's national cholera surveillance records. Values of independent variables were obtained from the 2009 Kenya Population and Housing Census and other national surveys. The data were analyzed using a zero-inflated negative binomial regression model.ResultsMultivariate analysis indicated that the risk of cholera was associated with open defecation, use of unimproved water sources, poverty headcount ratio and the number of health facilities per 100,000 population (p < 0.05). No statistically significant association was found between cholera occurrence and education, percentage of population living in urban areas or population density.ConclusionThe Sustainable Development Goals and Kenya's blueprint for development, Kenya Vision 2030, call for access to sanitation facilities and clean water for all by 2030. Kenya has made important economic strides in recent years but continues to be affected by diseases like cholera that are associated with low socio-economic status. Further expansion of access to sanitation facilities and clean water is necessary for preventing cholera in Kenya.

Application of artificial neural networks in modeling and optimization of biofuels production

Artificial neural networks, the artificial intelligence systems that imitate functions of biological neurons, have been widely used in different areas due to their variety and ability to conform to specificities of different applications. When it comes to application of artificial neural networks in bioprocess modeling, their task usually represents prediction or forecasting the values of dependent variables (outputs) based on given values of independent variables (inputs). Although bioprocess model is the 'black box' and remains unknown, which could represent the obstacle in bioprocess analysis, neural networks have shown better ability in prediction of bioprocess results comparing to other modeling methods, such as RSM (Response Surface Methodology) and mathematical modeling. Obtained model could be further used for bioprocess optimization, commonly performed using genetic algorithms. This study provides the review of the main characteristics and applications of artificial neural networks in modeling and optimization of biofuels (bioethanol, biogas and biohydrogen) production.

Knowledge-based Comparable Predicted Values in Regression Analysis

Regression analysis has a major role in predicting values of a dependent variable by using values of independent variables. The estimate of predicted values is obtained as projected values in a linear subspace spanned by vectors of independent variables. However, if the data set has been observed simultaneously from multiple different data sources, then we must create different linear subspaces to estimate the different predicted values corresponding to the different data sources. Then, we cannot compare the different predicted values, since the linear subspaces are different. In order to solve this problem, we propose a method to obtain comparable predicted values obtained from different data sources by utilizing a fuzzy clustering result and an orthogonal projector which projects two different vectors corresponded with the two different dependent variables to the same intersection of the two different linear subspaces. From this, since the different predicted values from different data sources can be obtained in the common space, we can compare the different predicted values.

Demand forecasting for manufacturing under Z-Information

Achieving profitability of the manufacturing sector in today’s business environment is directly related to accurate forecasting of demand products to satisfy the market. It is very important for business manager to plan resources, employees, production capacity etc. Demand forecasting provides a sense of directions that helps managers to make better decisions in many aspects of business. Prediction of demand almost is performed in face of uncertainty. Unfortunately, in existing studies demand prediction is considered on base of deterministic relationship between values of demand and independent variables as price and other input parameters. In some studies these relationship is extended to statistical and fuzzy information. Unfortunately, in these works reliability of information is not taken into consideration that leads to loss of information in obtained results. In this paper we investigate the problem of demand forecasting for manufacturing under information with partial reliability, namely Z–environment. Forecasting model is based on new approach – Z regression model.

Factors Affecting Patient Safety Programme in Government Hospitals of Sri Lanka

The objective of this study is to assess the factors that affect the patient safety programme in government hospitals of Sri Lanka. Method: A hospital based cross sectional descriptive study was conducted at the selected line ministry hospitals as they have established Quality Management Units. The study population was the administrative and clinical staff at these hospitals who had been employed at the hospital for at least 6 months and they should be working on a permanent basis. A self-administered questionnaire was used to collect the data collection. It contains two parts. First part deals with the perception on patient safety programme. It consists patient safety programme as dependent variable and five independent variables (organizational safety culture, leadership, communication, team structure and work environment) with 45 questions. The second part comprised six questions on socio-economic characteristics. Results: 327 members participated in his study. Out of that, 242(74%) were female, 74(22.6%) were male and 11(3.4%) didn’t mention the gender. Leadership has the highest mean value of independent variables and work environment has the second highest mean. Patient safety programme shows highest correlation with team structure (0.255), and lowest with work environment (0.200). Organizational safety culture has the correlation of 0.253 with patient safety programme which is an important factor next to team structure. Communication has the correlation of 0.231 and leadership has the value of 0.221, and both have significant correlation with patient safety programme. Conclusion: All assessed independent variables such as team structure, organizational safety culture, leadership, communication and work environment significantly affect the patient safety programme. Team structure and organizational safety culture have the highest correlation with patient safety programme.