Sequential Random Sampling Research Articles

A stereological study: Volume estimation in the cerebellum of Norduz sheep

In this research, it was aimed to investigate the cerebellum volume values of Norduz sheep raised within the borders of Gurpinar district of Van province. For this purpose, 6 male and 6 female Norduz sheep heads were selected as materials. The brains were dissected and kept in formaldehyde for a week. Cerebellums were separated from the brain hemispheriums. For better fixation, the cerebellums were kept in formaldehyde again for a week. Tissues obtained by sequential random sampling were included in tissue tracking. Then each tissue was embedded in paraffin. An average of 10-12 sections with a thickness of 5µm were obtained from the tissue cassettes obtained by a Rotary microtome (Leica RM, 2135, Nussloch Germany). Sections stained with hematoxylin and eosin were photographed with an x4 objective. From these photographs, total cerebellum, medulla and cortex volumes, as well as vermis volume, were calculated using the Shtereom I program using the Cavalieri Principle. The results were evaluated statistically with the Mann-Whitney U test. No statistical difference was detected in terms of male and female cerebellum volume values, Coefficient of Error (CE) and Noise calculations (p>0.05). However, in the evaluation between genders, it was determined that the only difference was seen in the medulla section of the hemispherium cerebelli sinister (p<0.05). Keywords: Cavalieri Principle; cerebellum; Norduz sheep; stereology; volume.

Association between Fat Intake, Dietary Fiber Intake, Physical Activity with Triglyceride Levels among Type 2 Diabetes Mellitus Patients at Grogol Health Center, Sukoharjo

Background: Hyperlipidemia is closely associated with dietary intake and physical activity. Excessive dietary fat intake, inadequate dietary fiber, and low physical activity will increase the risk of obesity and lipid profile disorder among type 2 diabetics. Objectives: This study aimed to identify the association between fat intake, dietary fiber intake, and physical activity with triglyceride levels among type 2 diabetics. Methods: A cross-sectional study was conducted using Sequential Random Sampling on 31 patients with type 2 diabetes with dyslipidemia from Grogol Community Health Center, Sukoharjo, in March 2023. The 3x24-hour food recall nonconsecutive days was used to collect data on fat and fiber intake, the International Physical Activity Questionnaire-Short Form (IPAQ-SF) was employed to obtain physical activity data, and the patient's medical record for the last month was utilized to obtain fasting blood sugar and triglyceride levels. The statistical test was carried out using the Spearman Rank correlation test. Results: Around 54.8% of subjects had excessive fat intake (60.90 g/day); 96.8% of subjects had severe deficit fiber intake (9.74 g/day); 51.6% of subjects had low physical activity (894.74 METs/minute/week). A statistically significant association exists between fat intake and level of triglyceride (p=0.005; r=0.493), but there was no significant association between dietary fiber intake and triglyceride levels (p=0.897; r=0.024), and there was no significant association between physical activity and level of triglyceride (p=0.394; r=-0.159). Conclusions: There is a significant association between fat intake and the level of triglyceride. As such, it is necessary to decrease intakes of saturated fat and trans fatty acids; replacing them with unsaturated fatty acids could be beneficial in lowering triglyceride levels.

The Analisis Faktor Risiko Leukosituria Pada Pasien Diabetes Di Desa Uteun Kot Kota Lhokseumawe

Diabetes mellitus (DM) is a chronic disease that is still a problem in Indonesia. DM occurs when there is an increase in the level of glucose in the blood (hyperglycemia), in which the body cannot produce enough insulin or use insulin effectively. It is important for DM patients to comply with a series of examinations such as controlling blood sugar so that subjective complaints do not occur that lead to complications. DM patients are at risk for chronic macrovascular complications in the form of infections, ranging from simple to complex infections. This study aims to determine and analyze risk factors for leukocyturia in DM patients in Uteun Kot Village. The research designs used were a laboratory examination and a survey using a questionnaire with a cross-section approach. Laboratory examinations were carried out on the urine of patients with diabetes mellitus (DM) to determine the incidence of leukocyturia and blood sugar levels to determine the blood sugar values of DM patients. The number of samples used in this study was 85 samples that met the criteria determined by using the Slovin formula. sampling using the sequential random sampling method. The variables used in this study were leukocyturia as the dependent variable and gender, duration of illness, and blood sugar levels as independent variables. Leukocyturia laboratory examination by urinalysis and microscopic examinationThe data analysis method used univariate analysis and bivariate analysis. The results showed that 68.2% of DM patients in Uteun Kot Village had leukocyturia, 63.5% of DM patients had high KGDS, and 71.8% had suffered from DM for more than 5 years. The variable duration of suffering from DM has a significant relationship with leukocyturia, where respondents with long suffering from DM above 10 years have a positive probability of leukocyturia 3.72 times compared to those suffering from DM under 10 years. Similarly, DM patients with uncontrolled blood sugar levels have a positive probability of leukocyturia 2.51 times compared to DM patients with controlled blood sugar levels.

The Pengaruh Pendidikan Sebaya Terhadap Perilaku Pencegahan Demam Berdarah Dengue (DBD) Pada Santri Madrasah Aliyah Dayah Modern Ihyaaussunnah Kota Lhokseumawe

Diabetes mellitus as known as DM, is a serious chronic disease which happens due to pancreas unable to produce insulin enough, or when the body cannot use the insulin that it already produces effectively. Patients with the diagnosis of DM need long term treatment / therapy in order to reduce the complication accident. If the diabetes is not handled well, it causes complications which are threatening and endanger life. Acute complications are being significant contributors towards death, loss of costs, and bad life quality. This research study aims to know the determinants of life quality of patients with diabetes mellitus at Banda Sakti public center, Lhokseumawe city. This research using a non-experimental method with prospective approach and analyzed with descriptively correlation. This research study adapts a cross section design. Amount of samples are 98 individuals which are determined based on the Slovin formula. The sampling is using a sequential random sampling method. There are three variables involed in this study, which are the life quality of patients with DM as a dependent variable. And duration variables experiencing DM and blood sugar level as independent variables. The analysis data method is using a univariate and bivariate (chi-square test) analysis method. The analysis results show that patients with Diabetes Mellitus (DM) type 2 at Banda Sakti Public health center Lhokseumawe are dominated by female patients (58,2%), mostly suffering in the age group of 40-60 years old (70,4%). With a long period of time above 10 years (49%). Patients with diabetes mellitus at banda sakti public health center have rough blood sugar that is not under control (59,2%) and most patients have bad life quality equals to 56,1%. The duration of DM and blood sugar level is related to life quality of patience with DM type 2 at banda sakti public health center, Lhokseumawe.

Pareto-like sequential sampling heuristic for global optimisation

In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening of the prominent domains while the greediness of the algorithm increases over time (iterations). Unlike traditional metaheuristics, the proposed method has no direct mutation- or crossover-like operations. It depends solely on the sequential random sampling that can be used in diversification and intensification processes while keeping the information-flow between generations and the structural bias at a minimum. By using a simple topology, the algorithm avoids premature convergence by sampling new solutions every generation. A simple theoretical derivation revealed that the exploration of this approach is unbiased and the rate of the diversification is constant during the runtime. The trade-off balance between the diversification and the intensification is explained theoretically and experimentally. This proposed approach has been benchmarked against standard optimisation problems as well as a selected set of simple and complex engineering applications. We used 26 standard benchmarks with different properties that cover most of the optimisation problems’ nature, three traditional engineering problems, and one real complex engineering problem from the state-of-the-art literature. The algorithm performs well in finding global minima for nonconvex and multimodal functions, especially with high dimensional problems and it was found very competitive in comparison with the recent algorithmic proposals. Moreover, the algorithm outperforms and scales better than recent algorithms when it is benchmarked under a limited number of iterations for the composite CEC2017 problems. The design of this algorithm is kept simple so it can be easily coupled or hybridised with other search paradigms. The code of the algorithm is provided in C++14, Python3.7, and Octave (Matlab).

Measurement-driven sequential random sample consensus GM-PHD filter for ballistic target tracking

In this paper, a new filter named measurement-driven sequential random sample consensus Gaussian mixture probability hypothesis density (MD-S-RANSAC-GM-PHD) filter is proposed for estimating the trajectory of a ballistic target during its coast phase. Unlike the traditional multiple-target tracking (MTT) algorithms that require data association, the proposed method involves modelling the respective collections of targets and measurements as random finite sets (RFS) and applying the PHD recursion to propagate the posterior intensity in time. To generate the new birth target intensity adaptively, a measurement-driven birth intensity estimation algorithm is developed. Since the measurement set used for birth intensity estimation may contain a large amount of clutter, a measurement set pre-processing method based on density-based spatial clustering and sequential random sample consensus (S-RANSAC) algorithm is proposed to eliminate the interference of clutter on generating new target birth intensity. Specifically, the proposed filter extends the standard GM-PHD filter by distinguishing between the persistent and the newborn target, and the extended Kalman filter (EKF) implementation of our proposed filter for ballistic target tracking is also derived. Simulation results illustrate the advantages of our proposed filter in tracking ballistic missile.

First quantitative assessment of growth, sugar accumulation and malate breakdown in a single ripening berry

Background: Most approaches to grape physiology accept that the berry and the future harvest should display identical developmental features, which obviously requires synchronised fruits.Aims: Rejecting this assumption compels to revisit the kinetic and metabolic bases of berry ripening.Methods and Results: Two to three thousand berries were individually analysed for sugar, malate and weight. The huge heterogeneity in sugar and malic acid concentrations among fruits was mostly explained by time lags in the onset of sugar storage, which proved nearly as long as the second growth phase. Individual berries from different cultivars displayed similar kinetics following the normalisation of their maximal volume. Phloem sucrose unloading started at its maximum speed at softening, but growth resumed one week later. Four hexoses accumulated per malic acid, which was oxidised during the first two weeks of ripening, and then malate breakdown stopped without affecting sugar accumulation. Sugar and water accumulation were simultaneously arrested four weeks after softening, at 0.9 M hexose, at which point sugar concentration continued through water losses.Conclusions: The accepted sequential random sampling methods representative of average fruit and future wine compositions have led to a scrambled vision of grape developmental biology, presenting serious kinetic and composition biases. Single berry composition provides first quantitative evidence for the induction of a dominant H+/sucrose exchange on the tonoplast, which is first electro-neutralised by malate breakdown, then by ATP demanding H+ recirculation, in line with functional and molecular studies.Significance of the Study: The kinetics of single berry ripening are presented for the first time. A more reliable and reproducible model of berry growth, sugar import and malate breakdown is shown here, which have definitively been improved from a quantitative point of view. It illustrates that the temporal structure of a berry population may largely contribute to future wine quality, in addition to metabolic plasticity, thereby providing another target for the impact of GxE interaction. In this respect, addressing the structure of berry cohorts may provide a new approach regarding the developmental biology/terroir nexus.

Testing methods and statistical models of genomic prediction for quantitative disease resistance to Phytophthora sojae in soybean [Glycine max (L.) Merr] germplasm collections.

Genomic prediction of quantitative resistance toward Phytophthora sojae indicated that genomic selection may increase breeding efficiency. Statistical model and marker set had minimal effect on genomic prediction with > 1000 markers. Quantitative disease resistance (QDR) toward Phytophthora sojae in soybean is a complex trait controlled by many small-effect loci throughout the genome. Along with the technical and rate-limiting challenges of phenotyping resistance to a root pathogen, the trait complexity can limit breeding efficiency. However, the application of genomic prediction to traits with complex genetic architecture, such as QDR toward P. sojae, is likely to improve breeding efficiency. We provide a novel example of genomic prediction by measuring QDR to P. sojae in two diverse panels of more than 450 plant introductions (PIs) that had previously been genotyped with the SoySNP50K chip. This research was completed in a collection of diverse germplasm and contributes to both an initial assessment of genomic prediction performance and characterization of the soybean germplasm collection. We tested six statistical models used for genomic prediction including Bayesian Ridge Regression; Bayesian LASSO; Bayes A, B, C; and reproducing kernel Hilbert spaces. We also tested how the number and distribution of SNPs included in genomic prediction altered predictive ability by varying the number of markers from less than 50 to more than 34,000 SNPs, including SNPs based on sequential sampling, random sampling, or selections from association analyses. Predictive ability was relatively independent of statistical model and marker distribution, with a diminishing return when more than 1000 SNPs were included in genomic prediction. This work estimated relative efficiency per breeding cycle between 0.57 and 0.83, which may improve the genetic gain for P. sojae QDR in soybean breeding programs.

Project Design and Sustainability of Dairy Goat Projects for Livelihood Improvement in Kenya

The debate around sustainability of development projects is intriguing, emerging as a contemporary development paradigm. Nevertheless, empirical literature insinuates that sustainability of development projects is seldom realized. Perhaps because the sustainability drivers are not well articulated at the project design stage making sustainability uncertain. This paper calls for a decisive paradigm shift in dairy goat project designs for sustainability. The paper is based on a study conducted in Tharaka Nithi County, Kenya, to investigate the influence of project design factors on the sustainability of dairy goat projects. Design factors considered for this study are the Project Beneficiary Selection Process, Community Capacity, Institutional Linkages and Project Infrastructure. The study was anchored on the structural-functional theory, diffusion of innovations theory and collective action theory. The sample size was 196 respondents sampled using sequential and stratified random sampling. Purposive sampling was used to sample 13 key informants. Further, six focus group discussions each with 8 participants were conducted. Questionnaires, interview guide and FGD guide were used respectively to collect data. Descriptive statistics were computed for all variables and frequencies, percentages, arithmetic mean and standard deviation. Pearson’s Product Moment Correlation (r), simple regression, multiple regression and stepwise regression (R squared), F-tests were used to test hypotheses. Hypothesis (H0) that the combined project design factors have no significant influence on the sustainability of dairy goat projects was tested. Results; r = 0.389 implying a positive slope between project design and sustainability. R- Squared = 0.152, that 15.2% of the variation in sustainability was explained by variation in project infrastructure, community capacity, project beneficiary selection process, and institutional linkages. ANOVA indicated the model was statistically significant at (F (1,183) = 8.176) and the p-value = 0.000≤0.05, shows that there exists a positive correlation and the slope of the population regression line is not zero. therefore, H0 was rejected. The study concludes that combined project design factors are critical and important in enhancing project sustainability and recommends that dairy goat project design should incorporate authentic project beneficiary selection Process, their capacities developed and the project linked to supportive institutions as well as promoting the requisite infrastructure. The study found a gap in literature on the social economic contribution of dairy goats to the community livelihoods, as a measure of sustainability and recommends further study on this area.

Real-time location estimation for indoor navigation using a visual-inertial sensor

PurposeThe purpose of this study is to use visual and inertial sensors to achieve real-time location. How to provide an accurate location has become a popular research topic in the field of indoor navigation. Although the complementarity of vision and inertia has been widely applied in indoor navigation, many problems remain, such as inertial sensor deviation calibration, unsynchronized visual and inertial data acquisition and large amount of stored data.Design/methodology/approachFirst, this study demonstrates that the vanishing point (VP) evaluation function improves the precision of extraction, and the nearest ground corner point (NGCP) of the adjacent frame is estimated by pre-integrating the inertial sensor. The Sequential Similarity Detection Algorithm (SSDA) and Random Sample Consensus (RANSAC) algorithms are adopted to accurately match the adjacent NGCP in the estimated region of interest. Second, the model of visual pose is established by using the parameters of the camera itself, VP and NGCP. The model of inertial pose is established by pre-integrating. Third, location is calculated by fusing the model of vision and inertia.FindingsIn this paper, a novel method is proposed to fuse visual and inertial sensor to locate indoor environment. The authors describe the building of an embedded hardware platform to the best of their knowledge and compare the result with a mature method and POSAV310.Originality/valueThis paper proposes a VP evaluation function that is used to extract the most advantages in the intersection of a plurality of parallel lines. To improve the extraction speed of adjacent frame, the authors first proposed fusing the NGCP of the current frame and the calibrated pre-integration to estimate the NGCP of the next frame. The visual pose model was established using extinction VP and NGCP, calibration of inertial sensor. This theory offers the linear processing equation of gyroscope and accelerometer by the model of visual and inertial pose.

The Differences of Salivary and Urine Acetone Levels in Diabetes Mellitus Patients

Ketone objects (acetone, beta-hydroxybutyric, acetoacetic acid) are compounds produced by the body from the breakdown of fatty acids (lipolysis) on the pathway of lipid metabolism. Synthesis of ketones can be caused by insulin hormone disorders such as those experienced by people with diabetes mellitus (DM). Such conditions trigger an increase in lipolysis in adipose tissue which results in the release of free fatty acids as a substrate for the process of ketogenesis in the liver. Acetone as a product of ketogenesis will enter the kidney to be excreted with urine, and if the amount is excessive, then some will accumulate into the saliva. The purpose of this research was to determine differences in salivary and urine acetone levels in DM patients. The type of research is analytic with the cross-sectional approach. Samples were taken using a sequential random sampling technique as many as 18 DM patients, both men and women aged 40-65 years old. The data collection technique was by conducting a direct examination of salivary and urine acetone which measured using spectrophotometric methods. The results showed an average salivary acetone level of 18.9 mg/L, while the mean level of urine acetone was 555.6 mg/L. Mann-Whitney statistical test showed a significance value of 0.000 (P <0.05), so it was concluded that there were significant differences between salivary acetone levels and urine acetone levels. Urine samples with smaller acetone concentrations are able to give positive results, while salivary samples will show positive results when acetone levels in urine are very high.

Statistical analysis of the sensitivity of bubble sample size during saturated nucleate boiling based on experimental data

This study aims to investigate the sensitivity of bubble sample size during the saturated nucleate boiling of ethane. Experiments were conducted on a horizontal flat surface, under pressures of 0.15, 0.2, and 0.3 MPa with heat fluxes varying from 14.27 kW m−2 to 81.22 kW m−2. Mathematical tools like statistical analysis were used for the standardized study on boiling. Sequential analysis and random sampling were conducted to investigate the sensitivity of bubble sample size. The trend in which parameters changed with sample size was observed. The relative deviation (ε) was within ±10%, ±5%, and ±2% for sample sizes of 40, 95, and 215, respectively. The analytical results could provide reference to establish uniform standards in the boiling field. In addition, common statistical analysis was performed to examine the data distribution characteristics of bubble departure diameters. The Gauss function was evaluated as the best fitted probability distribution function. Data distribution changed with heat flux and pressure. The experimental results have a direct and substantial contribution to the boiling area.

Strategic Planning, External Environment and Performance of County Governments in Kenya

The purpose of the study was to determine the effect of effect of strategic planning on organizational performance of Nairobi County. Descriptive research design was adopted in this study which targeted a total of 246 employees of Nairobi County government of whom 23 were top level managers, 61 middle level managers and 162 low level managers. Data was collected using structured questionnaire administered through drop and pick from a sample of 80 employees who were selected using stratified and sequential random sampling methods. Correlation and linear regression analysis were used to analyze the data. Regression results revealed that there was a positive and significant relationship between strategic planning and performance of the county government. Regression results further revealed that external environment has a positive and significant effect on performance of county government. In addition, external environment moderate the relationship between strategic planning and performance of county government. The study recommends that strategic formulation should be a top priority activity at every county government. County government should also employ top-bottom communication during the strategic plan implementation process. In addition, the county government should ensure they have enough competent staff to implement strategic initiatives. Adequate financial resources should also be allocated towards strategy control in their county. Performance indicators and targets should also be clearly defined and communicated within the county. In addition, employees of the county should comply with the county by laws. The county government should therefore do proper environmental scanning so as to improve their performance. The county government should also comply with the parliamentary Acts formulated from the Kenya’s 2010 constitution.

Estimation of Parameters of Skew Log Laplace Distribution

SYNOPTIC ABSTRACTIn this article, the maximum likelihood estimators (MLEs) of the shape parameters of Skew log Laplace distribution (SLLD) are derived when the scale parameter is known. In the case of a fixed sample size, it is observed that they are not always defined. Hence, modified MLEs are suggested. It is shown that unbiased estimators do not exist. A modified sampling scheme based on sequential random sampling is suggested so that MLEs and unbiased estimators are defined. The finite sample and asymptotic properties of the aforementioned estimators are studied, and the estimators are compared on the basis of generalized variance.

Skill based training of accredited social health activists: training effectiveness assessment using training and programme evaluation model

Background: Accredited Social Health Activists (ASHAs) are gross root health workers introduced under NRHM; for delivery of health services in rural areas. Training them for capacity building and functioning was a big challenge which has been tackled through skill based training. The study has been done to evaluate training effectiveness using managerial approach (Kirkpatrick’s model) and find out the gaps and suggest measures to improve ASHAs knowledge and skills. Methods: A cross sectional study on 580 ASHAs selected by sequential random sampling at training centres of Indore and Dewas districts. Sample size reduced to 10% of original for qualitative assessment. Interview of subjects and inspection of records was done using questionnaires/Performa. Paired, unpaired t test, Mcnemar test were applied with p<0.05for statistical significance. Results: Significant improvement in knowledge was found and the mean knowledge score got almost doubled after training (from 8.68 to 15.27 in a 30 point score, paired t test p<0.0001). 80% of ASHAs learnt the skills of hand washing, recording temperature and applying eye ointment and 50-60% learnt skill of weighing newborn, preventing baby from cold. Conclusion: Training was helpful in improving knowledge, skills and activities done by ASHAs. But still very few ASHAs were able to score passing marks and competent in all skills essential for new born care.

Sequential time interleaved random equivalent sampling for repetitive signal.

Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.

Prescripción de Actividad Física en Atención Primaria, Valoración de factores que influyen en la adherencia al tratamiento y posibles mejoras

Con este trabajo pretendemos comprobar si existe abandono de los programas de actividad física y analizar algunas variables, las más frecuentemente referidas por los pacientes, para identificar cuáles de ellas pueden ser los motivos principales de la escasa adherencia al tratamiento de actividad física en atención primaria.Metodología: Estudio longitudinal prospectivo desde enero de 2015 hasta noviembre de 2015 con muestreo secuencial no aleatorio en ZBS de Níjar, de 133 pacientes con prescripción de ejercicio físico, mediante un programa de ejercicios adaptado a su patología, sin criterios de exclusión. Se realiza entrevista de valoración de fisioterapia para recogida de datos y la evaluación de si existen las siguientes variables: un problema laboral que le impida realizar actividad por horario, problema de transporte o desconocimiento del idioma, así como otras que consideramos importantes como si tiene prescripción de electroterapia, tipo de patología por la que es derivado y procedencia de la derivación.Resultados: Analizaremos contraste de independencia con tablas cruzadas usando Spss 22. Obtenemos un elevado porcentaje de abandono del tratamiento y relación significativa entre el abandono del programa de ejercicios y el desconocimiento del idioma. p 0.02, mostrándose que es más probable abandonar el tratamiento si se desconoce el idioma.

Vision-based approach towards lane line detection and vehicle localization

Localization of the vehicle with respect to road lanes plays a critical role in the advances of making the vehicle fully autonomous. Vision based road lane line detection provides a feasible and low cost solution as the vehicle pose can be derived from the detection. While good progress has been made, the road lane line detection has remained an open one, given challenging road appearances with shadows, varying lighting conditions, worn-out lane lines etc. In this paper, we propose a more robust vision-based approach with respect to these challenges. The approach incorporates four key steps. Lane line pixels are first pooled with a ridge detector. An effective noise filtering mechanism will next remove noise pixels to a large extent. A modified version of sequential RANdom Sample Consensus) is then adopted in a model fitting procedure to ensure each lane line in the image is captured correctly. Finally, if lane lines on both sides of the road exist, a parallelism reinforcement technique is imposed to improve the model accuracy. The results obtained show that the proposed approach is able to detect the lane lines accurately and at a high success rate compared to current approaches. The model derived from the lane line detection is capable of generating precise and consistent vehicle localization information with respect to road lane lines, including road geometry, vehicle position and orientation.

Effect of land use change and slope position on soil organic carbon in Kitabi Watershed Rwanda

Soil organic carbon (SOC) is widely used as a proxy for soil health and soil fertility. Land use change(LUC) has been implicated as one of the factors leading to the loss of SOC and increased release of green house gases (GHGs) to the atmosphere hence contributing to global climate change (GCC). Rwanda is a mountainous country and has faced a challenge of land use inter-conversions between forests, perennial crops and annual crops over the years. The impact of LUC on SOC stocks is poorly documented. The aim of this study was to investigate the effect of LUC and slope positions on SOC stocks in Kitabi watershed. Lands at TM-5 images of 2008 and 1986 were used to make a land use change map using Maximum Likelihood Classification (MLC) algorithm in Erdas. Slope positions were derived from the DEM using Topographic Position Index (TPI) tool and the output raster was overlaid with the LUC map to identify sample strata. Soil samples were obtained using stratified top sequential random sampling from annual crops, community tea and factory tea. A total of 134 soil samples were taken from the three LU categories along each of the three slope positions: upslope, middle slope and down slope. Soil sampling was done at two depths 0-20 cm and 20-50 cm in each land use category using a soil auger. To make a composite soil mixture, five samples were taken from 10 m x 10 m plots in each land use category.SOC laboratory analysis was done using Loss on ignition (LOI). One-Way ANOVA and Games Howell tests were used to analyze the data. Results indicate that LU types significantly affect SOC stocks (p &lt; 0.001) while slope position does not (p =.491). The interaction of LU and slope position has no significant effect on SOC stocks across the three land use types (p = .061). Good management practices in community tea and soil erosion control measures in annual crops are recommended.

A rapid appraisal of training issues of ASHAs (Accredited Social Health Activist) in Madhya Pradesh

Background: ASHA (Accredited Social Health Activist) acts as a ‘bridge’ between the rural people and health service outlets and play a central role, in achieving national health and population policy goals. Their effectiveness largely depends on the training and support from health system and the community. Training is the backbone of capacity building and functioning of ASHAs. Material and methods: cross sectional study done in Indore and Dewas districts of Madhya Pradesh in year 2013.Facility survey of training centre, observation of training micro plan and its implementation and trainees feedback (satisfaction) regarding training using structured Performa was done. Feedback from 270 ASHA from Indore and 310 ASHAs from Dewas selected by sequential random sampling was recorded. For statistical analysis Mann whitney U test was applied and p value less than 0.05 was considered significant. Observations: one of the training centre lack basic facilities like separate dormitories, mess, dining hall, adequate number of toilets. Delay in the running of session was seen and ASHAs come late at the training centre on first day. Feedback revealed that 70 % of the participants were satisfied with objectives, 94% of agreed with course material adequacy and utility and 74% agreed with their teaching efficiency. But only 65% were satisfied with the overall facilities at the training centres. Conclusion: there were deficiencies in the facilities for proper conduction of training which can be improved for better outcome of the training and functioning of ASHAs.