Simple Regression Method Research Articles

Multi Objective Optimization of Friction Stir Welding Parameters for Joining of Two Dissimilar Thin Aluminum Sheets

The article presents multi objective optimization of parameters affecting weld quality in tailored friction stir butt welding of 2.0mm thin dissimilar sheets of AA5052-H32 and AA5754-H22 using Taguchi grey based approach. The L9 orthogonal array has been used to design the experiments, and the experiments have been conducted in a laboratory stage vertical milling machine by varying tool rotational speed, worktable translational speed, tool shoulder diameter and tool pin geometry. After welding, the weld strength and percentage elongations have been evaluated using uniaxial tensile test. Based on the experimental data, empirical relations among the parameters correspond to each output feature has been developed using simple regression method. Optimum levels of parameters have been identified using grey relation grade.

Hurdles for sports consumption? The determining factors of household sports expenditures

The purpose of this article is to explore the determining factors of household expenditures on sports participation. Due to a relatively large amount of zero-expenditures, simple regression methods are not suited. Because of methodological reasons, the two-step Heckman approach is used over the Tobit approach and the Double Hurdle approach. The participation decision (spend money or not) is influenced by sports participation of the parents, family income, education, sports club membership, and sports frequency. Determining factors of the intensity decision (amount of money that is spent on sports participation) are family income, sports participation of parents during their youth, sports club membership, sports frequency, age of youngest child, and household size. Moreover, the results indicate that a two-stage approach is needed because it gives a more in-depth insight in the household spending behavior. For example, higher educated households more often spend money on sports participation. However, this research demonstrates that once higher educated households have decided to spend money on sports participation, the amount of money spent does not differ from lower educated households.

PENGARUH PENDAPATAN ASLI DAERAH TERHADAP BELANJA MODAL PADA KABUPATEN DAN KOTA PROPINSI SULAWESI UTARA

Regional Original Income is the main source of income of the local region itself. Regional Original Income is expected to be able to support Expense of Capital, because the Regional Original Income will increase is expected to add more revenue from existing infrasturcture development. This research aimed to determine the effect of Regional Original Income for Expense of Capital. Variables used in this research Is the Regional Original Income and Expense of Capital. The research data in the form of quantitative data and a secondary data obtained from the Central Board of Statistic in North Sulawesi. In this research has used simple regression method assisted by classical assumption. This research showed that the Regional Original Income has no effect on Expense of Capital.

PENGARUH PENYELENGGARAAN HAJI TERHADAP PENINGKATAN AKTIVITAS EKONOMl DI WILAYAH PROPINSI DKI JAKARTA

This research analyzes some factors affecting economic activities in relation with the conduct of pilgrimage. Those factors are the pilgrimage cost, the amount of pilgrims, and the amount of pilgrimage officers. The objective of this research is to acquire the information of how each factor and all factors together affect the economic activities. This research also analyzes the effect of foods and drinks expenses, the effect of nonfoods and drinks expenses, and the effect of miscellaneous expenses on UMKM - Micro, Small, Medium enterprises' economic activities.
 This research is conducted in DKI Jakarta in 2007. The population of this research is the average economic activities in DKI Jakarta in 2007. There are 42 respondents (Banks), 157 respondents (travel agencies), and 50 respondents (UMKM - Micro, Small, Medium enterprises) which are taken as samples from the population using the purposive sampling method. The data is obtained by the researcher using questioners and secondary data which is taken from 1990-2007.
 The methodology used in this research is based on. the causal relationship model In testing the hypothesis of this research, the researcher uses the simple and multiple regression methods, and path analysis method. The significant rate a = 0,05 used in determining the interpretation of the statistic result. The data is processed using SPSS (Statistical Packages for the Social Sciences) version 12.00.
 The results of the analysis in the 1st equation -are (i) the effect of the pilgrimage cost on banks' revenues is quite strong, (ii) the effect of the pilgrimage cost on travel agencies' revenues is quite strong, (iii) the effect of the pilgrimage cost on UMKM - Micro, Small, Medium enterprises' revenues is weak.
 The results of the analysis in the 2nd equation are (i) the effect, of the amount of pilgrims on Banks' revenues is very weak, (ii) the effect of the amount of pilgrims on travel agencies' revenues is very weak, (iii) the effect of the amount of pilgrims on UMKM - Micro, Smal4 Medium enterprises' revenues is very weak.
 The results of the analysis in the 3rd equation are (i) the effect of the amount of pilgrimage officers on banks' revenues is very weak, (ii) the effect of the amount of pilgrimage officers on travel agencies' revenues is very weak, (iii) the effect of the amount officers on UMKM-Micro, Small Medium enterprises' revenues is very weak.
 
 The results of the analysis in the 4th equation are (i) the effect of all three factors which are the pilgrimage cost, the amount of pilgrims, and the amount of pilgrimage officers simultaneously on banks' revenues is very strong, (ii) The effect of all three factors which are pilgrimage costs, the amount of pilgrims, and the amount of pilgrimage officers simultaneously on travel agencies' revenues is strong, (iii) The effect of all three factors which are pilgrimage costs, the amount of pilgrims, and the amount of pilgrimage officers simultaneously on UMKM-Micro, Small Medium enterprises' revenues is strong.
 The result of the analysis in the 5th equation is the effect of foods and drinks expenses on UMKM-Micro, Small Medium enterprises' revenues is weak. In the 6th equation, the effect of nonfoods and drinks expenses on UMKM-Micro, small Medium enterprises' revenues is weak. In the 7th equation, the effect of miscellaneous expenses on UMKM - Micro, Small Medium enterprises' revenues is quite strong. In the 8th equation, the effect of all three factors which are the effect of foods and drinks expenses, the effect of nonfoods and drinks expenses, and the effect of miscellaneous expenses simultaneously on UMKM-Micro, Small Medium enterprises' revenues is quite strong.
 The implication of the research results mentioned above is the factors in the conduct of pilgrimage do increase the economic activities (Banks, Travel Agencies, and UMKM - Micro, Smal4 Medium enterprises) in DKI Jakarta. Therefore, considering that matter, the General Director of the conduct of pilgrimage division of Department of Religion Republic of Indonesia should determine the pilgrimage cost which is affordable, increase the service, and provide a good information system which will result in a better conduct of the pilgrimage.
 Key word: The Costs of Hajj, Hajj Officer, Travel Agency, UMKM

Trends of temperature extremes in Saudi Arabia

ABSTRACTIn characterizing the patterns of climate change across Saudi Arabia, several extreme indices are calculated from station values daily maximum and minimum temperature data. The trend analyses are performed on 13 annual extreme indices for Saudi Arabia, using observations from 27 surface stations with high‐quality data for the period 1981–2010. RClimDex is used to calculate the indices, and simple regression methods are employed for the trend analysis. The analyses of extreme temperature indices detected a significant increase in the majority of the stations, which further indicates that the country has experienced a warming trend. The findings show that 92/89% of the stations displayed a significant increase in the annual occurrence of warm days/nights and 96/93% revealed a significant decrease for the occurrence of cool days/nights. Time‐series analysis has also shown an important feature of the climate change signal. When the dataset is divided into two sub‐periods, the analysis reveals a distinctive long‐term trend that clearly distinguishes the two periods. It was found that the temperature extremes (hot and cold) in Saudi Arabia have increased significantly with greater magnitude in the recent‐past (1996–2010) compared to the previous period (1981–1995). The most telling evidence for this is the heat‐ and cold‐waves, where indices of both have occurred more frequently in the second part of the two sub‐periods.

Investigating Relationship between Intellectual Characteristics and Academic Achievement Motive among Educational Sciences Students

Objective of the present study was to investigate relationship between intellectual characteristics and academic achievement motivation of educational sciences students of Isfahan city. The variables studied in this research were: (1) capacity and ability of individual to exalt, (2) ability of high level experiment from self-awareness, (3) ability of investigation and strainness of experiments and activities, (4) ability to employ intellectual resources in life problem-solving, and (5) ability to do virtuous acts. Population of the study was all educational sciences students of Isfahan city in academic year of 211-12. 370 male and female students were selected through stratified random sampling technique. Tools used in the present study were Academic Achievement Motivation (AAM) and Intellectual Characteristics (IC) questionnaires developed by the investigator. Content validity and retest reliability procedures were used to measure validity and reliability of the tools, respectively. To analyze the data, simple regression, multiple regression, factor analysis and secretion coefficient methods were applied. The findings showed that there was not a significant relationship between capacity and ability for straining of the works. However, a significant relationship was found between intellectual characteristics and academic achievement motive. Also, the findings indicate that factors, namely, ability to employ intellectual resources in life problem-solving, and ability of investigation and strainness of experiments and activities had the most effect on motive.

Simple to complex modeling of breathing volume using a motion sensor

PurposeTo compare simple and complex modeling techniques to estimate categories of low, medium, and high ventilation (VE) from ActiGraph™ activity counts. MethodsVertical axis ActiGraph™ GT1M activity counts, oxygen consumption and VE were measured during treadmill walking and running, sports, household chores and labor-intensive employment activities. Categories of low (<19.3l/min), medium (19.3 to 35.4l/min) and high (>35.4l/min) VEs were derived from activity intensity classifications (light <2.9METs, moderate 3.0 to 5.9METs and vigorous >6.0METs). We examined the accuracy of two simple techniques (multiple regression and activity count cut-point analyses) and one complex (random forest technique) modeling technique in predicting VE from activity counts. ResultsPrediction accuracy of the complex random forest technique was marginally better than the simple multiple regression method. Both techniques accurately predicted VE categories almost 80% of the time. The multiple regression and random forest techniques were more accurate (85 to 88%) in predicting medium VE. Both techniques predicted the high VE (70 to 73%) with greater accuracy than low VE (57 to 60%). Actigraph™ cut-points for light, medium and high VEs were <1381, 1381 to 3660 and >3660cpm. ConclusionsThere were minor differences in prediction accuracy between the multiple regression and the random forest technique. This study provides methods to objectively estimate VE categories using activity monitors that can easily be deployed in the field. Objective estimates of VE should provide a better understanding of the dose–response relationship between internal exposure to pollutants and disease.

Estimation of Resilient Modulus of Unbound Granular Materials from Senegal (West Africa)

The resilient modulus (Mr) is an important parameter which describes the mechanical behavior of unbound granular materials. However, this parameter can be determined from physical properties. This paper presents the relationship between resilient modulus and physical properties of Quartzite from Bakel (GB), Basalt from Diack and Bargny and Bandia limestones. Simple and multiple regression method by stepwise are used to establish linear and nonlinear relations to predict the resilient modulus. The results showed no significant correlation for Basalt, a weak estimation of the modulus for GB and good prediction of resilient modulus for limestone. These results also showed that the model of Uzan is more suitable to predict the resilient modulus than NCHRP model and the resilient modulus is better predicted in nonlinear relationship.

Phenotype prediction from genome-wide association studies: application to smoking behaviors

BackgroundA great success of the genome wide association study enabled us to give more attention on the personal genome and clinical application such as diagnosis and disease risk prediction. However, previous prediction studies using known disease associated loci have not been successful (Area Under Curve 0.55 ~ 0.68 for type 2 diabetes and coronary heart disease). There are several reasons for poor predictability such as small number of known disease-associated loci, simple analysis not considering complexity in phenotype, and a limited number of features used for prediction.MethodsIn this research, we investigated the effect of feature selection and prediction algorithm on the performance of prediction method thoroughly. In particular, we considered the following feature selection and prediction methods: regression analysis, regularized regression analysis, linear discriminant analysis, non-linear support vector machine, and random forest. For these methods, we studied the effects of feature selection and the number of features on prediction. Our investigation was based on the analysis of 8,842 Korean individuals genotyped by Affymetrix SNP array 5.0, for predicting smoking behaviors.ResultsTo observe the effect of feature selection methods on prediction performance, selected features were used for prediction and area under the curve score was measured. For feature selection, the performances of support vector machine (SVM) and elastic-net (EN) showed better results than those of linear discriminant analysis (LDA), random forest (RF) and simple logistic regression (LR) methods. For prediction, SVM showed the best performance based on area under the curve score. With less than 100 SNPs, EN was the best prediction method while SVM was the best if over 400 SNPs were used for the prediction.ConclusionsBased on combination of feature selection and prediction methods, SVM showed the best performance in feature selection and prediction.

Effect of Foreign Direct Investment (FDI) on the Economic Development of India

In the recent times, there is a growing importance for Foreign Direct Investment (FDI). FDI is playing a vital role in filling investment gaps in various key sectors of the developing countries. Policy makers of many emerging countries have recognized the need for change in their policy frameworks to give a boost to foreign investment. In the present study, influence of FDI on economic development of India has been studied by employing simple OLS Regression and Autoregressive Integrated Moving Average (ARIMA) method. The study covers a period from 1st June, 1997 to 31st March, 2011. Index of Industrial production is used as a proxy of economic development. Monthly data of Foreign Direct Investment (FDI) and Index of Industrial Production (IIP) were collected from various issues of Reserve Bank's Hand Book of Statistics. Pearson's Correlation Coefficient results show strong association between FDI and IIP. Results of Ordinary Least-Squares Regression points out the significant influence of foreign investment on economic development of the country. Results of ARIMA also confirm that FDI has a significant impact on the economic development of the country.

Measuring the Income Inequality in Nigeria: the Lorenz Curve and Gini Co-efficient Approach

In recent years, especially since the mid 1990s, there have been debates and commentaries exploring the concept, types, sizes and economic implications of income inequalities. This study carried out a quantitative measure of the size and the core determinant of income inequality in Nigeria. The study used standard traditional measurement approach: the Lorenz Curve and Gini Co-efficient to determine the size of income inequality and ordinary least square simple regression method to analyze the basic determinant of income inequality in Nigeria. The Gini co-efficient of Nigeria lies between 46 and 60 percent. From the result obtained, we discovered that there is a disturbing income inequality in Nigeria. The regression result shows that 1 percent increase in the literacy rate increase the Gini coefficient by 3 percent meaning that there is higher disparity in the income distribution in Nigeria with increase in literacy rate. The findings of the study support the need for the government to formulate policies targeting at improving the welfare of the poor and those that provide employment and improve the lot of low-paid workers.

Surveillance of community outbreaks of respiratory tract infections based on house-call visits in the metropolitan area of Athens, Greece.

BackgroundThe traditional Serfling-type approach for influenza-like illness surveillance requires long historical time-series. We retrospectively evaluated the use of recent, short, historical time-series for recognizing the onset of community outbreaks of respiratory tract infections (RTIs).MethodsThe data used referred to the proportion of diagnoses for upper or lower RTIs to total diagnoses for house-call visits, performed by a private network of medical specialists (SOS Doctors) in the metropolitan area of Athens, Greece, between January 01, 2000 and October 12, 2008. The reference standard classification of the observations was obtained by generating epidemic thresholds after analyzing the full 9-year period. We evaluated two different alert generating methods [simple regression and cumulative sum (CUSUM), respectively], under a range of input parameters, using data for the previous running 4–6 week period. These methods were applied if the previous weeks contained non-aberrant observations.ResultsWe found that the CUSUM model with a specific set of parameters performed marginally better than simple regression for both groups. The best results (sensitivity, specificity) for simple regression and CUSUM models for upper RTIs were (1.00, 0.82) and (0.94, 0.93) respectively. Corresponding results for lower RTIs were (1.00, 0.80) and (0.93, 0.91) respectively.ConclusionsShort-term data for house-call visits can be used rather reliably to identify respiratory tract outbreaks in the community using simple regression and CUSUM methods. Such surveillance models could be particularly useful when a large historical database is either unavailable or inaccurate and, thus, traditional methods are not optimal.

A Model to Approximate Lake Temperature from Gridded Daily Air Temperature Records and Its Application in Risk Assessment for the Establishment of Fish Diseases in the UK

Ambient water temperature is a key factor controlling the distribution and impact of disease in fish populations, and optimum temperature ranges have been characterised for the establishment of a number important aquatic diseases exotic to the UK. This study presents a simple regression method to approximate daily average surface water temperature in lakes of 0.5-15 ha in size across the UK using 5 km(2) gridded daily average air temperatures provided by the UK Meteorological Office. A Geographic information system (GIS) is used to present thematic maps of relative risk scores established for each grid cell based on the mean number of days per year that water temperature satisfied optimal criteria for the establishment of two economically important pathogens of cyprinid fish (koi herpesvirus (KHV) and spring viraemia of carp virus (SVCV)) and the distribution and density of fish populations susceptible to these viruses. High-density susceptible populations broadly overlap the areas where the temperature profiles are optimal for KHV (central and south-east England); however, few fish populations occur in areas where temperature profiles are most likely to result in the establishment of spring viremia of carp (SVC) (namely northern England and Scotland). The highest grid-cell risk scores for KHV and SVC were 7 and 6, respectively, out of a maximum score of 14. The proportion of grid cells containing susceptible populations with risk scores of 5 or more was 37% and 5% for KHV and SVC, respectively. This work demonstrates a risk-based approach to inform surveillance for exotic pathogens in aquatic animal health management, allowing efficient use of resources directed towards higher risk animals and geographic areas for early disease detection. The methodology could be used to examine the change in distribution of high-risk areas for both exotic and endemic fish diseases under different climate change scenarios.

Correlation between neuropsychological tests and hypoperfusion in MCI patients: anatomical labeling using xjView and Talairach Daemon Software

Statistical analysis of brain perfusion SPECT images has shown mild to severe abnormalities, consistent with cortical dysfunctions in the brain. Recently, functional brain imaging such as fMRI, PET and SPECT is increasingly used for diagnosis of MCI. In this study, we calculate the correlation with perfusion of brain SPECT and neuropsychological test scores of patients by SPM analysis to evaluate the relationship with cerebral hypoperfusion and cognitive dysfunction in MCI patients. Anatomical labeling was performed automatically using the Talairach Daemon (TD) and xjView. Ninety-three patients (mean age 67.2 ± 7.42 years; 59 women and 34 men) with MCI were selected and examined by the comprehensive neuropsychological test. Tc-99m-HMPAO brain SPECT images were acquired on the patients using a two-head gamma camera. We analyzed the brain image of MCI patients by SPM8 software, and observed the anatomical correlated region, between the neuropsychological tests and cerebral hypoperfusion. The SPM8 tool provided correlation between neuropsychological score and brain perfusion by simple regression method. The neuropsychological test included attention, language function, visuospatial function, memory, frontal executive function, depression score and general cognitive function. Percentage of voxels with correlated area to the whole brain was calculated and the values by Rey complex figure test (CFT) copy score, MMSE score, Seoul verbal learning test (SVLT) immediate recall score and Rey CFT delayed recall score were 15.3, 12.33, 10.59 and 8.45 %, respectively. Rey CFT copy score was correlated with perfusion in the left middle temporal gyrus (BA 21), right inferior frontal gyrus (BA 45), right lingual gyrus, left lingual gyrus (BA 18), right postcentral gyrus (BA 40), right cingulate gyrus (BA 31) and left thalamus (pulvinar) with p < 0.01 FDR. The correlation related to MMSE included left parahippocampal gyrus, right fusiform gyrus and right middle frontal gyrus (BA 46). SVLT immediate recall score was correlated with left superior temporal gyrus and Rey CFT delayed recall score was correlated with left inferior frontal gyrus (BA 47), right inferior frontal gyrus, and left lentiform nucleus. Visuospatial and general cognitive dysfunctions in the patients with MCI were most correlated with cerebral hypoperfusion. Rey CFT copy and MMSE scores were more strongly correlated with blood perfusion of the brain than with other neuropsychological test scores. xjView was a useful tool to find out the anatomical name of the selected voxel or clusters and to display the cluster's anatomical information and list all cluster information and could be used instead of TD Client.

Effects of Practice on the Wechsler Adult Intelligence Scale-IV Across 3- and 6-Month Intervals

A total of 54 participants (age M = 20.9; education M = 14.9; initial Full Scale IQ M = 111.6) were administered the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) at baseline and again either 3 or 6 months later. Scores on the Full Scale IQ, Verbal Comprehension, Working Memory, Perceptual Reasoning, Processing Speed, and General Ability Indices improved approximately 7, 5, 4, 5, 9, and 6 points, respectively, and increases were similar regardless of whether the re-examination occurred over 3- or 6-month intervals. Reliable change indices (RCI) were computed using the simple difference and bivariate regression methods, providing estimated base rates of change across time. The regression method provided more accurate estimates of reliable change than did the simple difference between baseline and follow-up scores. These findings suggest that prior exposure to the WAIS-IV results in significant score increments. These gains reflect practice effects instead of genuine intellectual changes, which may lead to errors in clinical judgment.

Determining the Occurrence of Freshwater in the Aquifers of the Deltaic Formation, Niger Delta Nigeria

The study attempted to determine the occurrence of freshwater in the aquifers of the Deltaic Formation, Niger Delta Nigeria using Lithologic Logs, Electrical Resistivity and Borehole Parameter (Depth) as input data. The Geographical Information System technique that permit diverse geospatial analyses, modelling and data manipulation and Simple Regression Method that permits the assessment of relationship between two variables were adopted in this study. While the Lithologic Logs were adopted to delineate aquifers and aquitards, the Electrical Resistivity was employed to determine the occurrence of freshwater in the aquifers of the study area. The modelled Geological Sequence revealed that the geology of the study area is very complex and consists mostly of unconsolidated sedimentary materials from top soil to the deep horizon. Hence, all the aquifers have very high storage capacity. It was revealed that the nature of resistivity does significantly increases with depth, which indicates lower level of salinity with increasing depth of hole. The study established positive relationship between depth of hole and aquifer resistivity in 80% of the sampled locations indicating the occurrence of freshwater in deep aquifers of the study area. The study identified three distinct aquifers (shallow, intermediate and deep) within the Deltaic Formation. The study also emphasized the occurrence of near surface overlying aquitards in the eastern part of the study area, indicating that shallow aquifers of the eastern part are less vulnerable to near surface contamination. Finally, the study concluded that, in most cases, groundwater quality increases as the depth of well increases within the study area. Finally, this study demonstrated the capabilities of Geographic Information System in spatially referenced visualization of hydrogeological characteristics of complex geology.

A chi‐square‐based heuristic statistical procedure for approximating bid price in a competitive marketplace: a case study

Purpose – The purpose of this paper is to propose a chi‐square‐based heuristic statistical procedure that considers the most recent bid prices of self and competitors in proposing an optimum winning bid price. The use of simple regression method to predict the adjusted optimum bid price is also considered.Design/methodology/approach – In order to achieve this objective, the proposed approach uses past bid prices of the case company and its competitors. A heuristic chi‐square statistical procedure is then developed to obtain the expected bid prices. The absolute difference between the prices is obtained and the same is adjusted to get the optimal bid price for the forthcoming bid.Findings – It is demonstrated that the proposed heuristic chi‐square‐based approach is superior to that of the regression method, which is otherwise in practice in the case company, since the latter still gets support from the former. Further, the paper throws light on how a familiar statistical method could be conveniently but ef...

Pengaruh Pengungkapan Corporate Social Responsibility (CSR) Pada Nilai Perusahaan

This study aims to determine the influence of the level of CSR disclosure in annual report to corporate values that proxies with Economic Value Added (EVA) and Market Value Added (MVA). The objects of this study are companies that were included in Kompas 100 Edition of the second review in 2010.The chosen model of this research is simple regression which can be defined as a model that used the normal probability plot for data normality test, DurbinWatson test for autocorrelation, graph plots to test heteroscedasticity, and saw the value of tolerance and VIF for multicollinearity test. Hypothesis is analyzed using simple regression method The results showed that the level of CSR disclosure contained in the annual report has a significant influence on the EVA. The same results were also found on the MVA, where the level of CSR disclosure contained in the annual report has a significant influence on the MVA.&#x0D; Key words: Corporate Social Responsibility, Economic Value Added, Market Value Added

Correlated regions of cerebral blood flow with clinical parameters in Parkinson’s disease; comparison using ‘Anatomy’ and ‘Talairach Daemon’ software

We assign the anatomical names of functional activation regions in the brain, based on the probabilistic cyto-architectonic atlas by Anatomy 1.7 from an analysis of correlations between regional cerebral blood flow (rCBF) and clinical parameters of the non-demented Parkinson's disease (PD) patients by SPM8. We evaluated Anatomy 1.7 of SPM toolbox compared to 'Talairach Daemon' (TD) Client 2.4.2 software. One hundred and thirty-six patients (mean age 60.0 ± 9.09 years; 73 women and 63 men) with non-demented PD were selected. Tc-99m-HMPAO brain single-photon emission computed tomography (SPECT) scans were performed on the patients using a two-head gamma-camera. We analyzed the brain image of PD patients by SPM8 and found the anatomical names of correlated regions of rCBF perfusion with the clinical parameters using TD Client 2.4.2 and Anatomy 1.7. The SPM8 provided a correlation coefficient between clinical parameters and cerebral hypoperfusion by a simple regression method. To the clinical parameters were added age, duration of disease, education period, Hoehn and Yahr (H&Y) stage and Korean mini-mental state examination (K-MMSE) score. Age was correlated with cerebral perfusion in the Brodmann area (BA) 6 and BA 3b assigned by Anatomy 1.7 and BA 6 and pyramis in gray matter by TD Client 2.4.2 with p < 0.001 uncorrected. Also, assigned significant correlated regions were found in the left and right lobules VI (Hem) with duration of disease, in left and right lobules VIIa crus I (Hem) with education, in left insula (Ig2), left and right lobules VI (Hem) with H&Y, and in BA 4a and 6 with K-MMSE score with p < 0.05 uncorrected by Anatomy 1.7, respectively. Most areas of correlation were overlapped by two different anatomical labeling methods, but some correlation areas were found with different names. Age was the most significantly correlated clinical parameter with rCBF. TD Client found the exact anatomical name by the peak intensity position of the cluster while Anatomy 1.7 of SPM8 toolbox, using the cyto-architectonic probability maps, assigned the anatomical name by percentage value of the probability.

A simple method for mapping bathymetry over turbid coastal waters from MODIS data: possibilities and limitations

Timely mapping of underwater topography over turbid coastal waters is very important to navigation. Such a task is ideally accomplished through moderate- resolution imaging spectroradiometer (MODIS) satellite data that have a temporal resolution measured in hours. In this article we propose a simple regression method for retrieving bathymetry from MODIS bands. It only requires concurrently collected total suspended solids and water depth samples at limited spots, without considering the downward attenuation coefficient, surface reflectance or bottom reflectance. Regression analysis of the observed spot depth (D) against individual bands and their transformation enables an empirical model to be established. The model in which band 3 (M 3) is the exploratory variable is the most accurate, with an r value (correlation coefficient) of only 0.654. Correction of this model by the concentration level of suspended solids using bands 2 (M 2) and 5 (M 5) improves the prediction accuracy from 3.26 to 1.52 m, or from 39% to 24%. The best model takes the form of D = –7.833 + 0.0326M 3 / (M 2 M 5) (r = 0.815, n = 3318). Application of this model to the MODIS imagery led to the generation of a bathymetric map over the 15 000 km2 study area. Assessed against four profiles, the retrieved bathymetry has a mean absolute accuracy of around 2 m or a relative inaccuracy of 10% to 18%. The remotely sensed bathymetry contains many minor relief features absent from its in situ-surveyed counterpart. It is concluded that this proposed simple method can produce reasonably accurate results without the need to consider atmospheric effects or bottom reflectance over the range of 5–20 m. However, it may not work so well in clear oceanic Case I waters.