Cameroon, with her numerous resources, still depends on foreign aid while the rate of poverty remains high. Thus, even though historical evidence gives impetus to the impasse over role of developmental aid, from the top down approach through to development as a springboard raising states from the doldrums of poverty, it is still very difficult to draw a substantial relationship between developmental aid and poverty reduction. Against this backdrop of controversy, I find it apt to put Cameroon on a balance scale. Therefore, the purpose of this research is to critically assess the implications of developmental aid on poverty reduction and agro-rural development in Cameroon, using the RUMPI Area Development Project in the South West region of Cameroon as a case study. The study will situate and contextualize the top-down and bottom-up approaches to development within the basis of a Cameroonian perspective, using the Sachs-Easterly debate. The RUMPI Project was introduced with the objective of improving agriculture and empowering the rural woman; thereby fighting poverty within the South West region of Cameroon. Despite its criticism of the barriers to development created by corruption, political pressure and limited use of local and grass-root partnerships, the study, in assessing these failures also tries to outline vital ways in which the project can be improved upon.

The main goal of this study is to show promising future food market of Northeast Asia countries, including China, Japan, and South Korea. Drinks market, including soft and alcoholic drinks is selected to show global food companies new opportunities for next strategic movements. Market Attractiveness Matrix is developed based on BCG matrix as a main framework for this study. CDI (Category Development Index) is also used. It is found that Asia-pacific has fast-growing markets and it has strong potential for future investment. Northeast Asia countries (China, Japan, and South Korea) turned out to be ones of the most attractive regional markets. However, European drinks market is saturated even though its size is still big. This study suggests that Northeast Asian market be considered a market for the next strategic movement and investment.

No abstract

Existing studies in weakly supervised semantic segmentation (WSSS) have utilized class activation maps (CAMs) to localize the class objects. However, since a classification loss is insufficient for providing precise object regions, CAMs tend to be biased towards discriminative patterns (i.e., sparseness) and do not provide precise object boundary information (i.e., impreciseness). To resolve these limitations, we propose a novel framework (composed of MainNet and SupportNet.) that derives pixel-level selfsupervision from given image-level supervision. In our framework, with the help of the proposed Regional Contrastive Module (RCM) and Multi-scale Attentive Module (MAM), MainNet is trained by self-supervision from the SupportNet. The RCM extracts two forms of selfsupervision from SupportNet: (1) class region masks generated from the CAMs and (2) class-wise prototypes obtained from the features according to the class region masks. Then, every pixel-wise feature of the MainNet is trained by the prototype in a contrastive manner, sharpening the resulting CAMs. The MAM utilizes CAMs inferred at multiple scales from the SupportNet as self-supervision to guide the MainNet. Based on the dissimilarity between the multiscale CAMs from MainNet and SupportNet, CAMs from the MainNet are trained to expand to the less-discriminative regions. The proposed method shows state-of-the-art WSSS performance both on the train and validation sets on the PASCAL VOC 2012 dataset. For reproducibility, code will be available publicly soon.