Mohsen Babaei, Afshin Shariat-Mohaymany, Nariman Nikoo and Ahmad-Reza Ghaffari
One of the problems in post-earthquake disaster management in developing countries, such as Iran, is the prediction of the residual network available for disaster relief…
Abstract
Purpose
One of the problems in post-earthquake disaster management in developing countries, such as Iran, is the prediction of the residual network available for disaster relief operations. Therefore, it is important to use methods that are executable in such countries given the limited amount of accurate data. The purpose of this paper is to present a multi-objective model that seeks to determine the set of roads of a transportation network that should preserve its role in carrying out disaster relief operations (i.e. known as “emergency road network” (ERN)) in the aftermath of earthquakes.
Design/methodology/approach
In this paper, the total travel time of emergency trips, the total length of network and the provision of coverage to the emergency demand/supply points have been incorporated as three important metrics of ERN into a multi-objective mixed integer linear programming model. The proposed model has been solved by adopting the e-constraint method.
Findings
The results of applying the model to Tehran’s highway network indicated that the least possible length for the emergency transportation network is about half the total length of its major roads (freeways and major arterials).
Practical implications
Gathering detailed data about origin-destination pair of emergency trips and network characteristics have a direct effect on designing a suitable emergency network in pre-disaster phase.
Originality/value
To become solvable in a reasonable time, especially in large-scale cases, the problem has been modeled based on a decomposing technique. The model has been solved successfully for the emergency roads of Tehran within about 10 min of CPU time.
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Mohsen Pakdaman, Sara Geravandi, Ali Hejazi, Mobin Salehi and Mahboobeh Davoodifar
Currently, the health system is a treatment-oriented system focused on service providers. In this system, the main focus is on the health market, with little attention on insured…
Abstract
Purpose
Currently, the health system is a treatment-oriented system focused on service providers. In this system, the main focus is on the health market, with little attention on insured. One way to get out of existing conditions is to empower the insured in order to involve them actively in maintaining and improving health. The paper aims to discuss these issues.
Design/methodology/approach
This qualitative study was done using the content analysis method. Based on the purposive sampling method and theoretical saturation criterion, 24 individuals including 12 health insurance experts and 12 insured participated in the study in 2018. The semi-structured interview method was used to collect data. Data were analyzed using MAXQDA10 software.
Findings
Having analyzed the interviews, 750 codes were obtained. These codes were categorized into two categories of “insurance experts” and “insured” and ten subcategories of “informing and educating, cost reduction, intersectional activities, expectations from the insured, services package, access to services, inability to pay costs, participation, and expectations from the insurance organization.”
Originality/value
This qualitative study was conducted to assess and determine the effective strategies for empowering the insured under health insurance. The results of this study are helpful to the health insurance organizations and health decision makers to detect the effective ways to develop the quality of insurance services, improve the status of insured, and increase access to health care goods and services.
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Hadi Shams Esfandabadi, Mohsen Ghamary Asl, Zahra Shams Esfandabadi, Sneha Gautam and Meisam Ranjbari
This research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.
Abstract
Purpose
This research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.
Design/methodology/approach
A three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.
Findings
Rice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCImin and VCImin are found to be the most proper indices to predict rice yield.
Practical implications
The results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.
Originality/value
This study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.
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Mohsen Karimi, Mohammad Pichan, Adib Abrishamifar and Mehdi Fazeli
This paper aims to propose a novel integrated control method (ICM) for high-power-density non-inverting interleaved buck-boost DC-DC converter. To achieve high power conversion by…
Abstract
Purpose
This paper aims to propose a novel integrated control method (ICM) for high-power-density non-inverting interleaved buck-boost DC-DC converter. To achieve high power conversion by conventional single phase DC-DC converter, inductor value must be increased. This converter is not suitable for industrial and high-power applications as large inductor value will increase the inductor current ripple. Thus, two-phase non-inverting interleaved buck-boost DC-DC converter is proposed.
Design/methodology/approach
The proposed ICM approach is based on the theory of integrated dynamic modeling of continuous conduction mode (CCM), discontinuous conduction mode and synchronizing parallel operation mode. In addition, it involves the output voltage controller with inner current loop (inductor current controller) to make a fair balancing between two stages. To ensure fast transient performance, proposed digital ICM is implemented based on a TMS320F28335 digital signal microprocessor.
Findings
The results verify the effectiveness of the proposed ICM algorithm to achieve high voltage regulating (under 0.01 per cent), very low inductor current ripple (for boost is 1.96 per cent, for buck is 1.1) and fair input current balance between two stages (unbalancing current less than 0.5A).
Originality/value
The proposed new ICM design procedure is developed satisfactorily to ensure fast transient response even under high load variation and the solving R right-half-plane HP zeros of the CCM. In addition, the proposed method can equally divide the input current of stages and stable different parallel operation modes with large input voltage variations.