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A rough set theory model utilising fuzzy sets was developed to investigate artificial reef placement based on fish ecosystem components. The model incorporates consumption estimates and presumed foraging behavior to provide a rule-based approach to determine how far apart artificial reefs must be placed to eliminate density-dependent competition for prey resources. Simulation of the ecosystem parameters and potential reef distances as triangularly defined fuzzy sets generates input into the rules. Then, based upon the strength of belief in a rule, the artificial reef placement location can be accepted or rejected as being conducive to consumption at the reef and foraging behaviour of the species. Ease of utilisation of the model is highlighted by spreadsheet application to a red snapper (Lutjanus campechanus) ecosystem in Gulf of Mexico waters off the coastal shelf of Alabama. Implications exist for similar applications to other ecosystems and different fish species. Further applications are relevant beyond fish management when viewed as a general managerial decision-making process involving fuzzy sets and simulation.

Reference management software (RMS) is the most important aspect that is essential for all levels of researchers. They are established as research tools to help scholars in organising their work, improving workflows, and ultimately saving time. Choosing an appropriate RMS for managing records and utilising the bibliographic citation has been a challenge among researchers. They always seek for the features of an appropriate RMS prior to making an investment to buy the software. In this paper, a fuzzy logic approach is adopted for assessing the features of RMS from the researchers’ perspectives. Accordingly, a web-based survey was conducted and data collected from the researchers who had experience with different types of RMS. Then, we analyse the effects of RMS features on researcher perception in selecting an appropriate reference management program and find the importance level of those features. This study provides a toolset for RMS developers to identify the importance level of RMS features and accordingly consider these important features in developing the next generation of citation management software.

The development of customised healthcare systems is becoming an important issue in the healthcare industry due to the rapid increase in the number of chronically ill patients. These systems aim to deliver effective care to patients having chronic diseases through customised services. However, knowledge bases need also to be customised since systems are confronted with huge amount of personalised and imprecise medical knowledge. Therefore, we propose in this paper a new system to customise medical knowledge according to progressive disease phases and pathological cases. A rule management process first customises rules according to the specificities of every disease phase, and then matches a private knowledge base with each enrolled patient. This base contains only the patient’s customised knowledge. After reasoning, another customisation process is carried out by the component, Result Manager, which ensures the validation of the system outcomes by the pathological case experts, before being recommended. This will better ensure the recommendation of the generated results to the non-professional users. In addition, Result Manager offers fuzzy semantic queries to the experts. In conclusion, our new decision support system makes medical aid decisions not only addressed to physicians, but also to chronically ill patients and persons regarded as caregivers.

The Underwater Acoustic Sensor Network (UASN) plays a dynamic role in various application extents like surveillance, military, terrestrial networks and industrial application. In UASN, each Underwater Sensor Node (USN) is deployed in many places. The multiple paths are always used for transmitting data from USN to the Sink Node (SN). Each sensor constitutes a set of small devices and a small battery. If data is received from multiple nodes at the same time then, there is a chance for a collision and also it will bring down network lifetime. In recent years, only a few research works are done in fuzzy based routing in UASN. For increasing the network’s lifetime, there is always a need for an optimum routing path in UASN with improved parameters related to propagation delay, energy and throughput. The present paper proposes the Fuzzy Logic Depth based Energy-Aware Routing (FLDEAR) path in UASN. A static USN was utilized in the proposed system. Each USN is assigned a Priority Number (PN) by the SN. The PN is used for avoiding collision in the proposed model. The simulation is conducted employing Aqua-Sim (AS) which is based on Network Simulator-2(NS2). The simulation results illustrate that this system outperforms the existing routing protocol such as protocols of Energy Efficient Cooperative Opportunistic Routing (EECOR), Fuzzy Depth Based Routing (FDBR) and Depth Based Routing (DBR) in terms of improved parameters related to energy, propagation delay and throughput. Finally, the lifetime of UASN is improved by 70–80% by the implementation of the proposed FLDEAR protocol.