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The large amount of data generated by internet of things (IOT) has high impact values, the mining algorithms with IOT used to get the meaningful information that has been hidden in the data. In this paper a system designed to review the data in the knowledge view, technique view and application view, including clustering, classification, time series, association, outlier analysis and the application used in mining algorithm are surveyed. As more and more devices connected to internet of things, large volume of data should be analysed. At last architecture has been suggested for big data mining system.

Agribusiness has a major role to play in the transformation of the agricultural sector in Africa. With the demand for high-value food products increasing across the world, there is an opportunity for an increase in income/employment through the production and export of these goods. To capture the benefits of this trend and capitalize on this opportunity for long-term agricultural growth, there is a need to increase the competitiveness of agribusiness in Africa. Further, along with competitiveness, increasing agricultural productivity and food security are other major challenges in African agricultural development. In this paper, we compare the competitiveness of African countries and develop typologies with their food security and agricultural productivity status. The typologies reveal various stylized facts on competitiveness of agribusiness to help nations prioritize issues for agricultural development and growth. Additionally, we also present policy implications for increasing agribusiness competitiveness status of countries in Africa.

In sub-Saharan Africa, agribusiness has a major role to play in the transformation of the agricultural sector. The demand for high-value food products is increasing, creating an opportunity for the production and export of these goods. To capture the benefits of this trend and capitalize on this for long-term agricultural growth, the capacity for agribusiness must be strengthened at all levels. To effectively build the necessary capacities, the skills built by agribusiness education and training must correspond to the needs of the agribusiness sector. This article examines what capacities are needed for agribusiness development and management in sub-Saharan Africa at the individual, organization, and policy process levels. By reviewing the current agribusiness education offerings, this article identifies capacity gaps that must be filled for agribusiness development and wider agricultural transformation.

Power quality is one of major concerns in the present era. It has become important, especially, with the introduction of sophisticated devices, whose performance is very sensitive to the quality of power supply. To improve the power quality, custom power devices are used. The device considered in this work is DVR. This work presents a control strategy for a DVR to improve the stability in wind farms based on SCIG. The DVR controller is designed to work under unbalanced conditions, which allows overcoming most faults in the power grid. The proposed strategy is capable of balancing voltages at wind farm terminals obtaining several advantages. Firstly, negative-sequence currents are eliminated; thus, overheating, loss of performance, and decreasing of generator useful life are avoided. Secondly, by nullifying negative sequence voltages, 2ω pulsation in the mechanical torque is prevented, reducing high stress in the turbine mechanical system, especially in the gearbox. The power system, DVR converter, and controller were implemented in the Sim power Systems blockset of SIMULINK/MATLAB®.

Drought stress is the major constraint to rice (Oryza sativaL.) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help develop rice cultivars suitable for rainfed regions through molecular marker assisted breeding. Quantitative trait loci (QTLs) linked to plant water stress indicators, phenology and production traits under irrigated and drought stress conditions were mapped by means of a doubled‐haploid (DH) population of 154 rice lines from the cross CT9993‐5‐10‐1‐M/IR62266‐42‐6‐2. The DH lines were subjected to water stress before anthesis in three field experiments at two locations. The DH lines showed significant variation for plant water stress indicators, phenology, plant biomass, yield and yield components under irrigated control and water stress. A total of 47 QTLs were identified for various plant water stress indicators, phenology, and production traits under control and water stress conditions in the field, which individually explained 5 to 59% of the phenotype variation. A region was identified on chromosome 4 that harbored major QTLs for plant height, grain yield, and number of grains per panicle under drought stress. By comparing the coincidence of QTLs with specific traits, we also genetically dissected the nature of association of root traits and capacity for osmotic adjustment with rice production under drought. Root traits had positive correlations with yield and yield components under drought stress. This study demonstrated that the region RG939‐RG476‐RG214 on chromosome 4 identified for root‐related drought resistance component QTLs also had pleiotropic effects on yield traits under stress. Consistent QTLs for drought resistance traits and yield under stress were detected and might be useful for marker‐assisted selection for rainfed rice improvement.

Osmotic adjustmen(OA)is a major component of drought resistance. Four different methods for measuring OA in plants are in general use, but there is no information on the comparative performance of these methods. Two similar experiments were designed to evaluate the four methods for measuring OA in diverse indicaand japonicacultivars of rice (Oryza sativaL.) subjected to a drying cycle in large pots in the greenhouse. The four methods were:(i) derivation of OA from regressions of leaf relative water content (RWC) on leaf osmotic potential(OP);(ii) estimation of OA from OP of stressed plants calculated to rehydrated state; (iii) estimation of OA from OP of stressed plants that have been rehydrated; and( iv) estimation (from data used in Metho 1) of OA capacity by the sustained RWC at given OP of −3.5 MPa. Method 1 was a priori considered as the best estimate. Under relatively mild atmospherci conditions and a slow development of water deficit (first experiment), mean OA over cultivars was 0.89, 0.51, and 0.72MPa by Methods 1, 2, and 3, respectively. Mean RWC at −3.5 MPa was 6 9.3%. Significant(P≤ 0.05) variation in OA among cultivars was observed by all methods, up to a four‐fold difference in OA among cultivars (0.35≤1.51 MPa) by Method 1. Simple correlation for OA across 12 cultivars with Method 1 was significantly higher for Method 3(r= 0.76; P= 0.04) and Method 4 (r= 0.87; P< 0.01) than for Method 2(r= 0.54; P0.07). OA by Method 4 was better correlated with Method 3(r0.80;P< 0.01)than with Method 2(r= 0.67;P= 0.02).The coefficient of variation (CV) as a measure of error was greater for Method 1 (47%)and Method 2 (31%)than for Method 3 (21%) or 4 (24%). Both Methods 2 and 3 were less demanding on labor and plant materials than Methods 1 and 4. The results support the use of Method 3 (the “rehydration method”) as a faster and an economical replacement for Method 1.

This article uses a case study from Malawi to demonstrate the use of a Food Security and Nutrition Monitoring (FSNM) system for managing and mitigating the effects of drought. The implementation of FSNM during the drought emergency is presented, along with a description of the process of information generation and the use of results in emergency interventions. Presenting the lessons learned from the Malawi experience for the benefit of future drought-management and disaster-prevention efforts in other sub-Saharan African countries, the article concludes that a decentralized system of data collection, processing, and analysis is more likely to be successful in planning interventions for food security and nutritional improvements during periods of drought.

Lack of sufficient analytical capacity in most of the developing countries in sub-Saharan Africa has been frequently suggested as a major factor in determining the appropriateness of food and nutrition policy interventions. This paper documents an approach implemented in Malawi for the past seven years to develop multidisciplinary capacity to analyse food and nutrition policies and programmes. A conceptual framework for identifying the areas of capacity-strengthening in food and nutrition planning and policy analysis is developed. Generalizable lessons from the Malawi experience are presented. Various issues that relate to enhancing the efficiency of capacity-strengthening programmes in sub-Saharan Africa are addressed. It is argued that continuous dialogue between food and nutrition researchers and policy decision makers and between the trainers in academic institutions and donor agencies is fundamental for achieving the goals of improved capacity for food and nutrition policy analysis.