Food Security and Insecurity Analysis in Jambi Province

This study analyzed food security and insecurity using FSVA (Food Security and Vulnerability Atlas) mapping approach. The FSVA map presents district distribution based on food security and insecurity indicators. Current issues on food security include a drop in production and productivity due to land conversion, low adoption of technology at the farmer level, price fluctuation and ineffective price management, inefficient commerce system, low quality and quantity of public food consumption, failure to implement Diverse, Nutritious, Balanced and Safe Food Consumption Pattern (B2SA). This study aims to determine the vulnerability level of each district and propose countermeasures to reduce its rate. The results of FSVA mapping show that the 139 districts in Jambi could be grouped into the following categories: vulnerable (4 districts), quite vulnerable (18), sufficiently resistant (34), resistant (61), and very resistant (22). No districts fall under very vulnerable categories. Based on the ratio of per capita normative consumption of cereal production, 36 districts (25.90%) are vulnerable to food. Based on the toddler stunting prevalence, 78 districts (56.12%) are vulnerable to food, while based on the indicators of life expectancy, 48 Districts (34.53%) are food vulnerable.

A Financial Incentive Mechanism for Truthful Reporting Assurance in Online Crowdsourcing Platforms

In today’s world, crowdsourcing is regarded as an effective strategy to deal with a high volume of small issues whose solutions can have their own complexities in systems. Moreover, requesters are currently providing hundreds of thousands of tasks in online job markets and workers need to perform these tasks to earn money. Thus far, various aspects of crowdsourcing including budget management, mechanism design for price management, forcing workers to behave truthfully in bidding prices, or maximized gains of crowdsourcing have been considered in different studies. One of the main existing challenges in crowdsourcing is how to ensure truthful reporting is provided by contributing workers. Since the amount of pay to workers is directly correlated with the number of tasks performed by them over a period of time, it can be predicted that strong incentives encourage them to carry out more tasks by giving untruthful answers (providing the first possible answer without examining it) in order to increase the amount of pay. However, crowdsourcing requesters need to obtain truthful reporting as an output of tasks assigned to workers. In this study, a mechanism was developed whose implementation in crowdsourcing could ensure truthful reporting by workers. The mechanism provided in this study was evaluated as more budget feasible and it was also fairer for requesters and workers due to its well-defined procedure.

Global oil risk price management in Iran and Russia

Oil is one of the most important sources of income for oil-exporting countries such as the Russian Federation and Iran, as well as the main raw material in the production process in oil-importing countries. Risks fluctuations in world oil prices can cause sovereign financial risks of instability in macroeconomic variables in both groups of oil exporting and importing countries. Negative shocks in world oil prices for countries such as Iran and Russia, whose economic structure is oriented towards oil and provides a significant part of the state budget through oil, could have significant consequences for the economies of these countries. Such fluctuations not only affect the economies of oil-importing countries, but are also one of the main causes of disruptions in the economies of oil-exporting countries. This study examines the government's management of risk fluctuations in world oil prices and its actions in Iran and Russia. The results of this study show that Iran and Russia, as sanctioned countries and oil exporters, have taken various measures to deal with these shocks, the most important of which is the creation of sovereign wealth funds in the two countries. In this article, the characteristics of national development funds in Iran and Russia are compared. The differences between Iran and Russia in risk management and the structure of these funds are shown.

Forecasting of Energy Demands for Smart Home Applications

The utilization of energy is on the rise in current trends due to increasing consumptions by households. Smart buildings, on the other hand, aim to optimize energy, and hence, the aim of the study is to forecast the cost of energy consumption in smart buildings by effectively addressing the minimal energy consumption. However, smart buildings are restricted, with limited power access and capacity associated with Heating, Ventilation and Air Conditioning (HVAC) units. It further suffers from low communication capability due to device limitations. In this paper, a balanced deep learning architecture is used to offer solutions to address these constraints. The deep learning algorithm considers three constraints, such as a multi-objective optimization problem and a fitness function, to resolve the price management problem and high-level energy consumption in HVAC systems. The study analyzes and optimizes the consumption of power in smart buildings by the HVAC systems in terms of power loss, price management and reactive power. Experiments are conducted over various scenarios to check the integrity of the system over various smart buildings and in high-rise buildings. The results are compared in terms of various HVAC devices on various metrics and communication protocols, where the proposed system is considered more effective than other methods. The results of the Li-Fi communication protocols show improved results compared to the other communication protocols.

Stock Price Management and Share Issuance: Evidence from Equity Warrants

We investigate whether firms manage stock prices in anticipation of share issuance. Warrant exercise results in share issuance and warrant expiration dates are fixed years in advance, which precludes market timing. We predict firms manage stock prices to prevent (induce) warrant exercise when exercise is dilutive (anti-dilutive) to existing shareholders. To test our prediction, we examine stock returns around warrant expiration dates. We find that the difference between out-of-the-money (OTM) and in-the-money (ITM) firms' return patterns (i.e., post-expiration minus pre-expiration returns) is positive, and OTM (ITM) firms' return pattern is positive (negative). Return patterns of three sets of pseudo warrant firms differ from patterns of warrant firms. Return patterns are stronger when more feasible price changes are required to affect warrant expiration status, and firm-issued news items is a mechanism for price management. Thus, our findings provide evidence that firms engage in stock price management in anticipation of share issuance.

Price management system in the field of forming the value of eco-friendly commercial products

The purpose of this study is to develop a methodology for justifying and accepting prices for supplied and purchased commercial products, based on an analysis of the functioning of price management at high-tech production enterprises at the micro-, meso- and micro-levels. A conceptual interpretation problem is presented - either to organize and implement a unified price representation, or to create a unique management toolkit for each scheme. It is considered how it is possible to localize specialized management: in the area under consideration - as price management for various organizational and institutional levels of management, including the case of corporate groupings, such as Russian high-tech holdings.

A Bayesian analysis of hop price fluctuations

This paper quantifies the correlation between U.S. season average prices for hops with U.S. hop stocks and U.S. hop hectarage. The Hop Equilibrium Ratio, a measure of the supply/demand relationship for U.S. hops, was introduced. Through the Bayesian inference method, the authors used these data to calculate the effect an incremental change to one metric had on the probability of directional changes of future U.S. season average prices (SAP). Between 2010 and 2020, the dominance of proprietary varieties created unprecedented cartel-like powers offering opportunities for supply- and price-management. Research results will enable more accurate forecasting and greater price stability in the hop industry.

Construction cost management strategy based on BIM technology and neural network model

The construction of construction projects is an important industry of national social and economic development, and price management control is an important part of construction projects, and has become an important factor for major construction companies in China to manage construction projects. At present, the internal construction price management is not the best, nor the most ideal. Few investments exceed the budget, mainly due to defects in effective construction price management, lack of advanced technology and lack of prospects for prepayment, which make it difficult to match the actual and expected results of construction project price management. The actual results are always unsatisfactory. In this paper, the engineering cost estimation model is studied, and the neural network comprehensive prediction model is established to improve the accuracy and application technology of the prediction model. By using the building of BIM technology and neural network model, and effectively using the price advantage of ICT, it is used in the construction industry, and the cost is strictly controlled, so as to bring huge profits to the enterprise and promote the development of the enterprise.