Search results for: Mezajoug Kenfack Laurette Blandine
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5

Search results for: Mezajoug Kenfack Laurette Blandine

5 Evaluation of the Nutritional Potential of a Developed Spice Formulation for nah poh (An Emulsion-Based Gravy): Physicochemical and Techno-Functional Characterisations

Authors: Djiazet Stève, Mezajoug Kenfack Laurette Blandine, Ravi Pullakhandam, Bethala L. A. Prabhavathi Devi, Tchiegang Clergé, Prathapkumar Halady Shetty

Abstract:

The nutritional potential of a developed spice formulation for nah poh was evaluated. It was found that when spices were used for the formulation for nah poh, the concentration of some nutrients is diluted while that of some of them increases. The proportion of unsaturated fats was estimated to be 76.2% of the total fat content while the chemical score varied between 31 to 39%. The contents of some essential minerals of nutritional interest in mg are as follows for 100g of spice: 2372.474 ± 0.007 for potassium, 16.447 ± 0.010 for iron, 4.772 ± 0.005 for zinc, 0.537 ± 0.001 for cupper, 0.138 ± 0.005 for selenium, and 112.954 ± 0.003 for manganese. This study shows that the consumption of these spices in the form of formulation significantly contributes to meet the mineral requirements of the populations whose food habits regularly require these spices.

Keywords: spice formulation, characterisation, nutritional potential, nah poh, techno functional properties

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4 Fairness in Recommendations Ranking: From Pairwise Approach to Listwise Approach

Authors: Patik Joslin Kenfack, Polyakov Vladimir Mikhailovich

Abstract:

Machine Learning (ML) systems are trained using human generated data that could be biased by implicitly containing racist, sexist, or discriminating data. ML models learn those biases or even amplify them. Recent research in work on has begun to consider issues of fairness. The concept of fairness is extended to recommendation. A recommender system will be considered fair if it doesn’t under rank items of protected group (gender, race, demographic...). Several metrics for evaluating fairness concerns in recommendation systems have been proposed, which take pairs of items as ‘instances’ in fairness evaluation. It doesn’t take in account the fact that the fairness should be evaluated across a list of items. The paper explores a probabilistic approach that generalize pairwise metric by using a list k (listwise) of items as ‘instances’ in fairness evaluation, parametrized by k. We also explore new regularization method based on this metric to improve fairness ranking during model training.

Keywords: Fairness, Recommender System, Ranking, Listwise Approach

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3 Modelling a Distribution Network with a Hybrid Solar-Hydro Power Plant in Rural Cameroon

Authors: Contimi Kenfack Mouafo, Sebastian Klick

Abstract:

In the rural and remote areas of Cameroon, access to electricity is very limited since most of the population is not connected to the main utility grid. Throughout the country, efforts are underway to not only expand the utility grid to these regions but also to provide reliable off-grid access to electricity. The Cameroonian company Solahydrowatt is currently working on the design and planning of one of the first hybrid solar-hydropower plants of Cameroon in Fotetsa, in the western region of the country, to provide the population with reliable access to electricity. This paper models and proposes a design for the low-voltage network with a hybrid solar-hydropower plant in Fotetsa. The modelling takes into consideration the voltage compliance of the distribution network, the maximum load of operating equipment, and most importantly, the ability for the network to operate as an off-grid system. The resulting modelled distribution network does not only comply with the Cameroonian voltage deviation standard, but it is also capable of being operated as a stand-alone network independent of the main utility grid.

Keywords: Cameroon, rural electrification, hybrid solar-hydro, off-grid electricity supply, network simulation

Procedia PDF Downloads 99
2 Realising the Socio-Economic Rights of Refugees Under Human Rights Law: A Case Study of South Africa

Authors: Taguekou Kenfack Alexie

Abstract:

For a long time, refugee protection has constituted one of the main concerns of the international community as a whole and for the South African government in particular.The focus of this paper is on the challenges refugees face in accessing their rights in South Africa. In particular, it analyses the legal framework for the protection of the socio economic rights of refugees under international law, regional and domestic law and the extent to which the rights have been realized. The main hypothesis of the study centered on the fact that the social protection of refugees in South Africa is in conformity with international standards. To test this hypothesis, the qualitative research method was applied. Refugee related legal instruments were analyzed as well as academic publications, organizational reports and internet sources. The data analyzed revealed that there has been enormous progress in meeting international standards in the areas of education, emergency relief and assistance, protection of women and refugee children. The results also indicated that much remain to be desired in such areas as nutrition, shelter, health care, freedom of movement and very importantly, employment and social security. The paper also seeks to address the obstacles which prevent the proper treatment of refugees and to make recommendations as how the South African government can better regulate the treatment of refugees living in its territory.Recommendations include the amendment of the legal instruments that provide the normative framework for protection and improvement of protection policies to reflect the changing dynamics.

Keywords: international community, refugee, socioeconomic rights, social protection

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1 A Modular Solution for Large-Scale Critical Industrial Scheduling Problems with Coupling of Other Optimization Problems

Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

Abstract:

Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

Procedia PDF Downloads 155