One of the methods widely used by researchers to analyze the risk of maintenance operations is Failure Modes and Effects Analysis (FMEA). However, the conventional approach of the FMEA faces serious drawbacks to rank equipment and failure modes. The purpose of this paper is to dynamically rank equipment in an Interval-Valued Intuitionistic Fuzzy environment to identify critical equipment, So that the main drawbacks of the conventional FMEA are eliminated. To this end, we present the Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW). In following, by improving the interval-valued intuitionistic fuzzy power weight Heronian aggregation (IVIFPWHA) operator and improving the approach of multi attributive border approximation area comparison (MABAC) method, these two improved methods by Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW) have been merged and a robust FMEA model has been proposed in which the main drawbacks of the conventional FMEA have been eliminated. In order to prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

Due to the lack of measurements in many regions, wave characteristics are estimated using different methods. Wave climate hindcasting/forecasting is mostly conducted by numerical models or empirical methods. Until now, different empirical methods have been developed for wave hindcasting. However, with the development of high speed processors, several sophisticated numerical models have been developed for wave prediction. These models are mostly phase-averaged spectral wave models developed in three generations. In the last two decades, third generation wave models have been used widely in academic and practical projects. In this regard, Port and Maritime Organization has produced his own model, PMO Dynamic. This model has been developed as a part of first three phases of Monitoring and Modeling of Study of Iranian Coasts project. PMO Dynamic package is a software available for engineering purposes. It has several modules that have been developed for different objectives. Wave model is the module which is used for the generation and transformation of wind waves in coastal areas. In this paper, in order to test the PMO Dynamic model capabilities, it has been applied for the prediction of wave parameters in Bushehr Bay and the results have been compared with MIKE21 SW model and measured data.

Background: In intertrochanteric fractures، dynamic hip screw (DHS) is the most frequently used tool، but several studies did not give good results for this device in reverse-oblique and transverse fractures. Current study aimed to compare fixation results of reverse-oblique intertrochanteric and short-segment subtrochanteric fractures using dynamic condylar screw (DCS) and DHS in patients referred to Alzahra and Kashani Hospitals in Isfahan, Iran.Methods: In a cross-sectional study، medical files of the patients referred to emergency units of the two hospitals who were diagnosed with intertrochanteric or subtrochanteric fractures and underwent DHS or DCS surgery more than 6 months before were assessed; they were invited for follow-up visit and examination. Written consent forms were taken from all the patients upon their entry; and they were examined in terms of complications including nonunion and failure of device and level of fracture improvement. These cases were evaluated by simple radiography ,too. Results obtained from examination of patients in addition to demographic information were recorded in the data collection form for each patient.Findings: Perfect union was observed in 14 (of 25) patients in DHS group and 21 (of 25) patients in DCS group (56% vs. 84%) six months after the surgery. Bone union was significantly better in DCS group (P=0.031). In addition, six months after the surgery, the devices used in 14 people in DHS group and 24 people in DCS group were fixed and the difference between the two groups was significant (P=0.001). 14 and 24 patients had total recovery in DHS and DCS groups، respectively (20% vs. 44%) with a significant difference (P=0.020).Conclusion: Considering obtained results, it can be concluded that using DCS is recommended over DHS due to severity of pain, bone union and fixation of the device.

A greater community of researchers widely studies fog computing as it reduces the massive data flow to the existing cloud-connected network and performs better for real-time systems that expect a quick response. As the fog layer plays a significant role in a fog-cloud system, all of the devices participating in fog computing must be balanced with appropriate load to upstretched the system performance. The proposed method is founded on a tree-based dynamic resources arrangement mechanism that refreshes the fog clusters created using Fuzzy C Mean (FCM) to increase the speed of resource allocation. With the help of Fuzzy rule-based load calculation and intra-cluster job allocation, the load inside the group is maintained. The system also has the facility of inter-cluster job forwarding, which works on demand. A novel load balancing strategy, Real-Time Flexi Forwarded Cluster Refreshing System (RTFRS) is proposed by which all the tasks can be handled efficiently within the fog cloud system. The proposed system is designed so that overall complexity is not upraised and becomes suitable for fog computing architecture with low processing capacity by maintaining the quality of service. Experimental results show that the proposed model outperforms standard methods and algorithms used in fog computing concerning average turnaround time, average waiting time, resource utilization, average failure rate, and the load on the gateway.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method based on dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method based on dynamic programming for the stabilizing design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Introduction Climate change is the greatest threat to humanity, because it is the main factor in increasing the frequency and severity of atmospheric events such as droughts, floods, heat waves, etc. that are experienced today. Climate change can cause a wide range of environmental problems, including severe drought and water scarcity, crop loss, and increased socioeconomic consequences. One way to identify climate change is to evaluate climate and temperature indicators. Based on statistical tests and time series of occurrence of these parameters in the long run, the status of change and its trend can be identified. Given the importance of the impact of climate change on all sectors, the study of the consequences of these changes requires the study of all sectors and effective factors with a systemic approach. One of the concerns of human society is the changes that have caused climate change due to global warming. In this regard, given the importance of climate change on all sectors, the study of the consequences of these changes requires the study of all sectors and factors with a systemic approach. Considering the importance of climate change and its effects, this study seeks to answer the following questions by considering important climatic parameters and vulnerable urban dimensions (economic, social, political, environmental): 1-The trend of climate change changes (Temperature and rainfall, humidity, wind speed) what is it like in Ahvaz? 2-What is the causal relationship between the causes of climate change and vulnerable sectors in the city of Ahvaz? 3-What are the effects and consequences of climate change on the city of Ahvaz? Materials & Methods The research methodology is based on statistical tests and qualitative modeling with a systemic approach. The present study analyzes the trend of changes in climatic parameters including temperature, precipitation, relative humidity, and wind speed for a period of 30 years (1991-2020) in Ahvaz using the statistical Mann-Kendall Test was examined. Then, using the science of system dynamics, the causal relationships between variables and structural modeling of the consequences of climate change in Vensim software are investigated. The main stage of using the system dynamics approach is to try to understand and identify the feedback loops of the system under study, for which purpose diagrams of causal loops are drawn. In this study, inputs are the factors that shape climate change are factors that affect the city system. System outputs will be the consequences of climate change. Results & Discussion Based on the results of the analysis of the trend of climatic parameters, the city of Ahvaz in the study period has faced an increase in temperature, increase in relative humidity, decrease in wind speed, and decrease in rainfall. During the 30-year trend (1991-2020), the average rainfall has been (226) mm, each year (1. 32) mm, has decreased and followed a downward trend. The average temperature has been (25. 38) degrees Celsius, it has increased every year (by 0. 051) degrees, which shows an increasing trend over 30 years. Based on the results, the average relative humidity was (41. 1), which increased every year (0. 007). Also, according to the results, the average wind speed is (2. 65 m/s) and has decreased by about (0. 018) every year. Therefore, the wind speed shows a decreasing trend over 30 years. Given that climate change refers to the spatial-temporal changes in the long-term average of climatic elements, the results of this study clearly showed that climatic parameters (temperature, relative humidity, precipitation, wind speed) in the study area have undergone fundamental changes. The consequences of climate change on all economic, social, political, and environmental aspects were evaluated. The results of qualitative modeling and causal relationship showed that climate change in Ahwaz has a direct impact on different sectors of water resources, agricultural production, and energy consumption. Variables of (reduction of water reserves upstream, extreme heat waves) are the most important leverage points of the model. Different outcomes have complex interactions with each other in such a way that they affect different economic, social, environmental, and political dimensions and ultimately intensify each other's effects on reducing the quality of life and increasing climate migration. Conclusion As a result, climate change has consequences such as increasing unemployment, reducing the quality of life, reducing urban resilience, and ultimately increasing climate migration in the city of Ahvaz, and the urban environment is not equipped to adapt to climate change.