108 research outputs found
Bulletin on food price dynamics, inflation, and the food security situation in Sudan: January 2023
No full textInternational prices of food commodities continued to decrease in January 2023 especially for vegetable oils, sugar, dairy, and meat. Resulting in further sluggish overall price inflation in January 2023 of 83.6 compared to 87.3 percent in December 2022.
The national retail prices of food commodities in January 2023 increased slightly compared to December 2022.
Fluctuations in the exchange rate were associated with the change in local prices of imported commodities such as wheat and sugar.
Food prices in relatively unstable states were higher than the national average.
The monthly inflation rate of food and beverages decreased by 0.2 percent in January 2023 compared to December 2022 driven by the declining CPI for the vegetables and fruits.Non-PRIFPRI1; SSSP; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural EconomiesDevelopment Strategies and Governance (DSG); Transformation Strategie
Quarterly bulletin on food price dynamics, inflation, and the food security situation in Sudan: 2021Q1- 2022Q4
No full text- Average international prices of wheat, sorghum, rice, and sugar slightly increased in Q4 of 2022 compared to Q3. Import parity prices decreased during the same period because of the reduction in the freight cost to Port Sudan.
- Annual inflation2 decreased from three-digit inflation (260.6 percent) in 2022Q1 to 92.6 percent in 2022Q4.
- Quarterly changes in the price of non-volatile commodities (core inflation) 3 increased slightly in Q4 compared to Q3 of 2022 due to the increase in the housing rents, education, communication, and processed food prices.
- Retail prices of food commodities were relatively stable during the last two quarters of 2022 com pared to the previous quarters of 2021 and 2022.
- Nominal wholesale prices of grains in Khartoum State increased gradually from 2021Q2 to reach a peak in 2022Q3, before dropping in real and nominal terms in 2022Q4.
- Although the national average of causal labor daily wage was increasing over time nominally (2021Q2–2022Q4), it was decreasing in real terms in 2022Q4.
- Poorer urban and rural households (bottom 40 percent) were more affected by the changes in the prices of food and beverage commodities during 2022Q4 than richer households (top 60 percent).
- Blue Nile, Darfur, and Eastern regions have the highest food insecure population classified in crisis or emergency.Non-PR2 Promoting Healthy Diets and Nutrition for all; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; IFPRI1; SSSPDevelopment Strategies and Governance (DSG); Transformation Strategie
Bulletin on food price dynamics, inflation, and the food security situation in Sudan: January 2023 [in Arabic]
No full textNon-PRIFPRI1; SSSP; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural EconomiesDevelopment Strategies and Governance (DSG); Transformation Strategie
Quarterly bulletin on food price dynamics, inflation, and the food security situation in Sudan: 2021Q1- 2022Q4 [in Arabic]
No full textNon-PR2 Promoting Healthy Diets and Nutrition for all; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; IFPRI1; SSSPDevelopment Strategies and Governance (DSG); Transformation Strategie
Energy-Efficient Internet of Drones Path-Planning Study Using Meta-Heuristic Algorithms
No full textThe increasing popularity of unmanned aerial vehicles (UAVs), commonly known as drones, in various fields is primarily due to their agility, quick deployment, flexibility, and excellent mobility. Particularly, the Internet of Drones (IoD)-a networked UAV system-has gained broad-spectrum attention for its potential applications. However, threat-prone environments, characterized by obstacles, pose a challenge to the safety of drones. One of the key challenges in IoD formation is path planning, which involves determining optimal paths for all UAVs while avoiding obstacles and other constraints. Limited battery life is another challenge that limits the operation time of UAVs. To address these issues, drones require efficient collision avoidance and energy-efficient strategies for effective path planning. This study focuses on using meta-heuristic algorithms, recognized for their robust global optimization capabilities, to solve the UAV path-planning problem. We model the path-planning problem as an optimization problem that aims to minimize energy consumption while considering the threats posed by obstacles. Through extensive simulations, this research compares the effectiveness of particle swarm optimization (PSO), improved PSO (IPSO), comprehensively improved PSO (CIPSO), the artificial bee colony (ABC), and the genetic algorithm (GA) in optimizing the IoD's path planning in obstacle-dense environments. Different performance metrics have been considered, such as path optimality, energy consumption, straight line rate (SLR), and relative percentage deviation (RPD). Moreover, a nondeterministic test is applied, and a one-way ANOVA test is obtained to validate the results for different algorithms. Results indicate IPSO's superior performance in terms of IoD formation stability, convergence speed, and path length efficiency, albeit with a longer run time compared to PSO and ABC.The authors would like to acknowledge the support of the Computer Engineering Department at King Fahd University of Petroleum and Minerals for the support of this work
The economy-wide impact of Sudan’s ongoing conflict: Implications on economic activity, agrifood system and poverty
No full textThe armed conflict between the Sudanese Armed Forces (SAF) and Rapid Support Forces (RSF) in Sudan entered its sixth month since it erupted on April 15th, 2023, with no signs of ending soon. The war has caused severe humanitarian catastrophe, destroyed key infrastructure, and constrained trade and production activities. Moreover, it disrupted access to public utilities, financial services, and markets, hence, triggering considerable scarcity of goods and services. In this paper, we utilize a Social Accounting Matrix (SAM) Multiplier modeling framework to assess the economywide implications of these disruptions of economic activity, productive resources, and livelihoods. Results reveal that the economy would shrink to nearly half its size before the war, household incomes decline by more than 40 percent in urban and rural areas, and the number of poor people increase by 1.8 million if the war continues until the end of the year. The impact would have been two thirds less should the war have ended before July 2023 and would be one third less if it would end before October 2023. This study therefore calls for rapid interventions from all relevant parties to help reach an end to the fighting.Non-PRIFPRI1; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and GovernanceDevelopment Strategies and Governance (DSG); Transformation Strategie
The economy-wide impact of Sudan’s ongoing conflict: Implications on economic activity, agrifood system and poverty [in Arabic]
No full textNon-PRIFPRI1; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; SSSPDevelopment Strategies and Governance (DSG); Transformation Strategie
Integrated simulation framework for the impacts of large dams: Example of the GERD
No full textEfficient water resources management is essential for the sustainable development of nations, and large dams are an important tool for achieving this endeavor. Here, we present an integrated approach to simulating the impacts of large dams, integrating river systems infrastructure, hydrodynamic, and economywide models. We apply the framework to examine the biophysical, GDP, and distributional impacts of the Grand Ethiopian Renaissance Dam (GERD) on Sudan.Non-PRIFPRI1; SSSP; 1 Fostering Climate-Resilient and Sustainable Food SupplyNatural Resources and Resilience (NRR); Development Strategies and Governance (DSG); Transformation Strategie
Impact of the ongoing conflict on smallholder farmers in Sudan: Evidence from a nationwide survey
No full textThis study addresses the impact of the ongoing conflict in Sudan on smallholder farmers' intentions and challenges during the 2023 summer agricultural season. A nationally representative survey of 3,284 smallholder farmers was conducted. Due to the security hazards and connectivity challenges, we used a combination of three interview types, Interactive Voice Recording (IVR), Computer-Assisted-Tele phone-Interviews (CATI) and face-to-face (in-person) interviews. Key findings are that close to a third of the farmers were displaced from their farms’ locations and 40 percent were unable to prepare for plant ing season because of the conflict. Most of the farmers who did not prepare for the summer season at the time of the interview were not intending to plant later in the season. The key challenges that pre vented them from planting were the lack of finance to buy agricultural inputs (such as seeds and fertiliz ers) and/or to hire farm labor. This is compounded by bad weather conditions, poor quality of the local seed varieties, higher cost of improved seeds, and delayed rains (climate challenges). In addition, the ongoing conflict has had direct and indirect impacts that prevented many farmers from planting this season. It disrupted market functionality and reduced the availability of and/or raised the cost of agricul tural inputs and farm labor. The lack of finances has also seen farmers reduce the size of the area they planted this season compared to last year’s season. The compounding challenges of these reduced production are expected to be felt as soon as the harvest season begins. The implications suggest the need for rapid intervention to support farmers during the harvest and winter seasons to mitigate the im pact of the conflict on agricultural activities.Non-PRIFPRI1; 1 Fostering Climate-Resilient and Sustainable Food Supply; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; SSSPDevelopment Strategies and Governance (DSG); Transformation Strategie
Detect and Avoid for Autonomous Agents in Cluttered Environments
No full textAutonomous agents are the future of many services and industries such as delivery systems, surveillance and monitoring, and search and rescue missions. An important aspect in an autonomous agent is the navigation system it uses to traverse the environment. Not much emphasis has been paid in the past on autonomous agent navigation in cluttered environments. Cluttered and unknown environments such as forests and subaquatic environments need to have autonomous navigation systems developed just for them due to their uncertain and changing nature. Path planning algorithms are used for the navigation of an autonomous agent in an environment. The agent needs to reach a target location while avoiding the obstacles it detects along the path. Such a system is called a Detect and Avoid (DAA) system and there are different implementations for it of which some are explored in this thesis. The Artificial Potential Fields method or APF for short is a method for mobile agent navigation which is based on generating an attractive force on the agent from the target and a repulsive force from the obstacles. This leads to the agent reaching the target while avoiding the obstacles along the way. The Classical APF (CAPF) method works for structured environments well but not for cluttered environments. The CAPF method can be replaced with a modified version where the agent is surrounded by a set of points (called bacteria points) around its current location and the agent moves by selecting a bacteria point as a future location. This method is named the Bacteria APF (BAPF) method. This selection happens through combinatorial optimization based on the potential value of each bacteria point. In this thesis, we propose two distinct contributions to the BAPF method. The first one being the use of an adaptive parameter in the repulsive cost function which is determined through a brute-force search. The second addition is a branching cost function that changes the value of the repulsive potential based on predefined perimeters around each obstacle. We show through simulations on densely and lightly cluttered environments that this Improved BAPF (IBAPF) method significantly improves the performance of the system in terms of the convergence to the target by almost 200% and reduced the time it takes to converge by around 25% as well as maintain the safety of the navigation route by keeping the average distance from obstacles around the same value.Airborne Data Collection on Resilient System ArchitecturesElectrical Engineering | Signals and System
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