With the increased scope of fires and the widespread destruction of the environment and densely populated urban areas in recent years, researchers have investigated the adoption of rapid and effective firefighting solutions, particularly those based on wireless sensor networks (WSNs). In fact, by evaluating various statistical data and developing a new model of sensors, equipment, and intelligent technologies in a fire sensor network, an effective step toward controlling frequent fires on a wide scale and reducing environmental damage can be taken. In the proposed model, the mobile sensors or firefighting robots based on a fuzzy Q-learning (FQL) algorithm and using two learning strategies in the sensor network, namely partial and perfect, could be used to  surround fire in firefighting operations. We also formulate a sensor mode selection strategy as an optimization problem to maximize the lifetime of the energy harvesting-enabled WSN. Furthermore, we determine optimal upper and lower bounds for the number of active sensors in the fire detection system, guaranteeing that the target detection and false alarm probabilities are achieved. Computer simulations show that using such a solution in the optimal selection of moving sensors and determining the moving trajectory in rapid firefighting is effective.

The rapid population growth and urban development have notably influenced the role of water distribution networks (WDNs) compared to the past. This issue encourages operators to adopt new smart tools to better system management. Such a smart system is expected to play an effective role in both crisis and normal services. For fire extinguishing services, a WDN needs to be well-equipped to supply the fire flow efficiently. In this sense, WDNs are required not only modern fire-fighting equipment but also a systematic program to satisfy the fire demand in the right place at the right time. This paper aims at introducing a pre-processing (not real-time) approach for smart pressure management using the regulation of control valves. The problem is formulated as a mathematical programing in which the reliability measure is maximized and the valve opening positions are decision variables. Using a self-adaptive Genetic Algorithm coupled with EPANET, the problem is solved. The proposed algorithm is applied to a case study from the literature and produces the optimum pattern for regulation of valves. Such results can be an appropriate guide for operators to practically maneuver valves in fire situation. The case study manifests that by applying the model the reliability of system can be increased up to 40. 7%.

This study aimed to extract effective spatial criteria in construction of forest fire fighting stations. In this study for extraction and prioritization of effective criteria, Delphi and AHP methods were used.To determine effective criteria, the opinions of experts and specialists in a Delphi approach were asked to clarify the influencing factors to allocation of land to forest fire fighting stations. In the first stage after sending and collecting questionnaires, mentioned criteria by experts were examined and using expert perspective the criteria that have less importance was omitted. Finally the following criteria were selected: Proximity to residential areas, Proximity to river, Proximity to post fires, Proximity to road, and Proximity to forest edge. Then with using Analytical Hierarchy Process (AHP), weight or relative importance of each selected factors were obtained. Based on results the highest important factor was the proximity to road with 0.25 weight among other factors. Then Proximity to river (0.23), Proximity to post fires (0.22), Proximity to forest edge (0.19) and Proximity to residential areas, were next in rank, respectively. Also pairwise comparisons of sub-criteria for each factor showed that areas close to roads, river and areas with a history of prior fires in forest regions and also areas close to residential areas have highest importance in allocating land to the forest fire fighting station.

Background: Job stress is one of the important social phenomenon’s in life and serious threat to the health workforce. Job Stress is caused when there is an imbalance between worker skills and job requirements. The purpose of this study was to Evaluation of effective factors on occupational stress in firefighting personnel.Methods: A cross-sectional and descriptive- analytical study was conducted in 50 man firefighters in sanandaj. After Basic data collection, national Institute of Mental Health job stress Questionnaire was used to assess job stress which consists of 3 sections interpersonal relationships, physical and environmental conditions and Job favorites. Collected data were analyzed by SPSS19.Findings: 86% of the studied personnel were married and 14% of them were single. Participants ‘ages category were 16% Less than 30 year, 52% between 30-40, 32% more than 40 year. Participants work experience category were 22% less than 5 years, 28% between 5-10, 30% between 10-15 and 20% had more than 15 years. Their mean job stress was 172.7 and was estimated high stress level and physical and environmental agent had the highest mean score of stress. Statistical analysis showed that job, work experience, and job satisfaction are significantly associated with job stress.Conclusion: It seems that firefighters were being at risk of job stress disorder and type of job and work experience is the main factors affecting it. Job stress can decrease job satisfaction.

Criminal and civil liability is personal according to the rules of the current legal system of our country and its transferability requires judicial procedures. However, according to the United States General Assembly Fire Department, if a claim is made for the purpose of saving the life / persons, the claimant will not be held directly liable by the injured party against the rescued person and the rescuer. This research has been done by analytical-descriptive method with the aim of investigating the applicability of this rule in the legal system of the country. It was concluded that at present, only under the jurisprudential rule of Ehsan and citing Article 167 of the Constitution, first a claim for damages was made against the rescuer, which is usually upheld, and then a secondary lawsuit was filed by the rescuer against the rescued, which was accepted by the judge. From the jurisprudential rules of harmlessness, benevolence, causation and loss depend. Therefore, the implementation of this rule in the Iranian legal system is facing problems. Therefore, for the strict implementation of this rule, it is necessary for the legislator, while adding an article or notes to the civil and criminal laws, to determine the aspects of liability due to urgency and having a positive motive, aspects of its transfer, and simple formalities.

As a result of rule of law ideal, judges are required to act in accordance with laws. The ideal is justified by some political values: political liberty, legal liberty, personal liberty and equality. Citizens are subject only to the law not to the arbitrary will or judgment of another who wields coercive government power. But in some cases law is indeterminate. In these cases there is an important question: how can the law command when the law books are silent or unclear or ambiguous? There are three theory in jurisprudence: legal positivism, legal pragmatism and legal interpretivism. I reject positivism and pragmatism and urge interpretivism. I believe that it provides a better account of our law.

Location finding is considered as an NP-Hard problem, in which the complexity and volume of computations due to larger numbers of demand points and service centers are exponentially increased. To overcome such complexities meta-heuristic algorithms are usually used. These methods usually produce answers close enough to the optimum solution in acceptable time. In this research three Meta heuristic algorithms of Tabu Search (TS),Genetic Algorithm (GA) and Simulated Annealing (SA) are used to optimize the location of fire fighting station and allocating urban blocks to them. The mentioned Meta heuristic methods are evaluated and compared with respect to time scale, the value of objective function, number of iteration and coverage of the study area. Different scenarios are developed, based on the number of iterations and the initial population for the genetic method. Similarly, different scenarios are developed for annealing method based on the number of repetitions of the same movements and temperature. The Tabu Search method has the maximum time of computation and minimum value of objective function, among the Meta heuristic methods. In addition, the sites selected by Tabu Search provide the best coverage in the area studied. In simulated annealing method, the solution ideas are produced when the number of iteration is larger than the size of the problem. The achieved results, in second scenario of simulated annealing method, have proved the correctness of this claim. It could be concluded that the simulated annealing method can be a suitable method when quick time results are required. When both quality of solutions and performance are to be considered, the genetic algorithm can be a proper choice. Finally, when there is no time limitation, the Tabu Search can generate the best results.