Are Farmers Surviving the Level of Seasonal Cultivation of Tomatoes in Ghana? A Tobit Regression Analysis

Tomato is an important vegetable in the cultivation and diet of Ghanaians. However, statistics have shown that domestic production of fresh tomato is on the decline. As an important traded commodity, the research wonders if the decline is due to lower farm land devoted to its cultivation.The paper therefore, seeks to identify factors that influence the seasonal farm size devoted to tomato cultivation. A total of 159 farmers in three regions in Ghana were purposively and randomly sampled and interviewed. Results from thetobitregression model suggests that approaching the dry season, farmers using any irrigation technology tend to allocate smaller proportion of farmland to tomato. It was also realised that as farmers acquire additional farmland for crop production, they are likely to reduce the level of tomato cultivation. This could mean that farmers are only surviving the cultivation of tomato as they are unlikely to increase its cultivation. Strategies that reduce the cost of irrigation especially in the drier seasons and enhance access is critical for increasing tomato production in Ghana. Training of farmers must target good storage and use of seeds from formal sources. Key words: Seasonal, Tomato, Cultivation, Tobit Model, Ghan

Performance and Constraints of Small Scale Enterprises in the Accra Metropolitan Area of Ghana

Small Scale Enterprises play a crucial role in the development of entrepreneurial capabilities and indigenous technology which generate employment. Promotion of such enterprises in developing economies like Ghana is of paramount importance as it brings about a great distribution of benefits. The study seeks to quantify the determinants of the factors influencing performance of small scale enterprises in Accra Metropolitan Area of Ghana. Kendall’s coefficient of concordance was used to test the agreement between the ranked constraints of the small scale enterprises in relation to performance. The study uses structured questionnaire to interview 150 small scale entrepreneurs in Accra Metropolitan Area (AMA). Data collected was analyzed using Statistical Package for Social Science (SPSS) and Econometric views (E-views). Results of the analysis indicate that age of entrepreneur is the most influential determinant of performance of small scale enterprises. The Kendall’s coefficient of concordance indicates that there is 91 percent agreement between the respondents in the ranking of the constraints in relation to performance. High cost of borrowing is the most important constraint faced by the small scale entrepreneurs. Based on the results, we recommend a flexible policy geared towards helping young entrepreneurs, as well as reducing the high interest charges on loans. Key words: Performance, Constraint, Small Scale Enterprise, Accra Metropolitan Area, Ghan

Estimating the frequency of trains approaching red signals: A case study for improving the understanding of SPAD risk

This paper describes a novel technique for estimating the frequency with which trains approach signals showing a red aspect. This knowledge is potentially important for understanding the likelihood of a signal being passed at danger (SPAD) at individual signals and also for normalisation of SPAD data, both locally and nationally, for trending and benchmarking. The industry currently uses estimates for the number of red aspect approaches based on driver surveys which are considered to have significant shortcomings. Data for this analysis is sourced from publicly available live feeds provided by Network Rail which give information on train movements and signal states. The development of the analysis model and supporting software are described and some sample results from case studies are presented. An initial study of seven signalling areas showed that approximately 3.3% of all signal approaches are to red signals. However, it also highlighted that there is a large variation in the red approach rates between signalling areas and between individual signals. SPAD risk assessment at individual signals may be significantly enhanced by the ability to estimate red approach rates for individual signals using the techniques described

The role of data visualization in Railway Big Data Risk Analysis

Big Data Risk Analysis (BDRA) is one of the possible alleys for the further development of risk models in the railway transport. Big Data techniques allow a great quantity of information to be handled from different types of sources (e.g. unstructured text, signaling and train data). The benefits of this approach may lie in improving the understanding of the risk factors involved in railways, detecting possible new threats or assessing the risk levels for rolling stock, rail infrastructure or railway operations. For the efficient use of BDRA, the conversion of huge amounts of data into a simple and effective display is particularly challenging. Especially because it is presented to various specific target audiences. This work reports a literature review of risk communication and visualization in order to find out its applicability to BDRA, and beyond the visual techniques, what human factors have to be considered in the understanding and risk perception of the infor-mation when safety analysts and decision-makers start basing their decisions on BDRA analyses. It was found that BDRA requires different visualization strategies than those that have normally been carried out in risk analysis up to now

Can Farmers Receive Their Expected Seasonal Tomato Price in Ghana? A Probit Regression Analysis

Tomato price is an important indicator for farmers to continue producing the crop in Ghana. There are sometimes alleged reports that farmers tend to commit suicide when they are unable to meet their expected tomato price and thereby unable to recover their cost of production. However, data available indicate that the domestic production of fresh tomato is on the decline. The paper therefore, assesses the factors that affect whether or not farmers can receive their expected tomato price. A multistaged sample survey of 215 farmers across three regions was subjected to the binomial probit model. Results indicate that for farmers to receive their expected price, they have to adapt to produce the crop in the drier seasons, where tomato shortage can be observed. Farmer education and experience are also important factors that are likely to help farmers receive their expected tomato price. The studytherefore recommends the promotion of strategies that are cost reducing especially in the dry season and also to improve access to critical production techniques

Multiresolution Information Mining for Pavement Crack Image Analysis

Empirical mode decomposition (EMD) is a multiresolution data analysis method recently developed to cater to the inherent nonstationarity in real-world signals. A two-dimensional (2D) extension of EMD is used in this paper as a pavement distress image analytical tool. The algorithm decomposes an image into a set of narrow band components (called bidimensional intrinsic mode function, or BIMF) that uniquely reflect the variations in the image. Although some components could have good image edge characteristics, others might hold fidelity to the shape and size of objects or trends in the image. Therefore, the complete spatial and frequency characteristic of a desired image feature might also be divided into the different components, indicating that all attributes of a desired feature might not be found in a single component. An optimal solution requires image mining from the different component resolutions to accurately extract those specific attributes without compromising certain spatial and frequency characteristics. Two major contributions to pavement image analysis are achieved. First, the paper explores pavement image denoising or enhancement by combining the EMD and a weighted reconstruction technique as a tool for background standardization of images acquired under different types of illumination effects. Second, using principal component pursuit (PCP), the authors reconstruct a composite image by selecting salient information from coarse and fine resolution BIMFs useful for accurate extraction of linear patterns in a pavement distress image. Compared with conventional image reconstruction or approximation techniques, the methodology used in this paper yields better results. DOI:10.1061/(ASCE)CP.1943-5487.0000178. (C) 2012 American Society of Civil Engineers