Introduction: Urban green space is one of the land uses whose distribution and dispersion throughout cities is of paramount importance and constitutes an inextricable part of city structure. Thus, city green space is a sort of urban land use covering manmade vegetation and boasting both social and ecological output. City parks should be geographically distributed in ways that are easily accessible. Moreover, along with the rapid growth of urbanization and constructions in recent decades, the appearance of the city of Mashhad, the second metropolis in Iran, has changed in such way that a dire dearth is noticeable in terms of the land use of city parks.

The purpose of this study is to determine the impact and prioritization of participation management variables in schools. The present statistical population is comprised of principals in the schools of Mazandaran province, out of which 24 experts were studied by purposeful sampling. In this paper, NETWORK ANALYSIS and dimensional ANALYSIS TECHNIQUEs are used to evaluate the variables and their relationships. Dematel is a suitable method to evaluate and analyze data in estimating the system's internal relationships. In this study, a paired comparison questionnaire was used. After analyzing the data on the components of the management of the partnerships, the decision-making criterion is given first priority and the communication criterion is given second priority. Leadership, structure, and control criteria were ranked third, fourth, and fifth, respectively. It should be noted that the structure component has the most interaction in the system of contributions. That is, this component has the most impact in terms of impact and impact. Knowledge-led managers can obtain effective decisions and provide educational systems.

Well designed monitoring NETWORKs are essential for the effective management of groundwater resources but the costs of monitoring well installations and sampling can prove prohibitive. Principal Component ANALYSIS (PCA) is one of the data reduction TECHNIQUEs used to extract the important components that explain the variance of a system. In this paper, the PCA was used to identify the effective wells and remove the less important ones. For this purpose, 160 wells were constructed in the Salman Farsi agro-industry, which was measured twice in a month during 10 months. In this TECHNIQUE, variation factors called principle components are identified with considering data structures. Using the PCA, the relative importance of each well was calculated for groundwater depth estimation. In the present study, the acceptable threshold was taken to be 0. 8, according to which the number of wells in determining groundwater depth was reduced to 33 wells. By identifying important wells, important points for sampling are identified, and groundwater depth monitoring is performed only in these wells. As a result, it can save a great deal of time and cost of studies.

The rapid growth of the Halal market and its many unknown opportunities has attracted the attention of economic actors and global marketers. Understanding the consumers’ mental image from the Halal brand helps them understand their behavior and facilitates the functioning of the Halal market for companies and businesses. This research aimed to study the consumers' mental image from the Halal brand. The present research had an applied orientation, a survey strategy, and exploratory-descriptive purpose. By using the neural NETWORK TECHNIQUE and MATLAB software, the data collected through interviews with 48 experts and managers of marketing, sales and research and development who were familiar with the Halal brand were studied. The samples were selected by using purposive non-random sampling method. The number of samples was determined to reach theoretical saturation by the snowball method. The results indicated that the Iranian consumers’ mental image of Halal brand included the following characteristics: the responsibility of the producer, the profitability of the products, the quality of the products, building loyalty in the customer, making mental peace for the customer, and product differentiation.

Background and aims: Hazard identification is a critical factor to ensure safe design and operation of systems in the process industries. Process industries are one of the most complex systems, with a variety of equipment, control systems, and executive procedures. In these industries, the use of hazardous materials as raw materials or products is quite common. Interactions between technical components, human factors, and organizational and managerial issues can lead to defects and accidents. Therefore, ensuring safety in the process industries can be a very complicated task. The process industries had led to many accidents with very severe consequences. For example, the explosion and fire of the Piper Alpha oil platform with 167 people killed in 1988, the explosion and fire at Esso gas in Longford, with 2 deaths in Australia in 1988, the explosion of the BP refinery with the death of 15 people in Texas in the year 2005 and Deepwater Horizon in 2010 could be mentioned. In order to prevent the occurrence of accidents or reduce the likelihood of occurrence and the severity of the consequences, various TECHNIQUEs have been developed to identify the hazards. However, due to the complexity of the unique conditions of process industries and resource constraints, always the most appropriate TECHNIQUE for identifying hazards should be used. Hazard identification and risk assessment are the implications of system safety since the mid-twentieth century, with the emergence of an action-oriented approach to safety. Since then, several methods have been developed to identify the hazard and evaluate risk in various manufacturing processes. Various generations of these TECHNIQUEs have been presented and each one is trying to provide the best formula or mental patterns to assessors to identify the hazards. Typically, the choice of hazard identification method is based on the frequency of application of that method in a particular industry and the degree of its acceptance among the experts in that industry. But sometimes the situation is not clear and the decision is somewhat difficult. In this situation, experts face a multi-criteria decision-making problem. Multi-criteria decision-making methods are used in situations where there are many alternatives and criteria. Selecting an inappropriate method to identify the hazards in the process industry could lead to a large number of hazards and waste of resources. Therefore, the aim of this study is to identify effective criteria in selecting the most appropriate method for identifying hazards in process industries and determining the most appropriate method in this industry. Methods: In this study, to select the most appropriate methods for identifying hazards in process industries, Preliminary Hazard ANALYSIS (PHA), Hazard and Operability Study (HAZOP), Subsystem Hazard ANALYSIS (SSHA), System Hazard ANALYSIS (SHA), Operability & Support Hazard ANALYSIS (O&SHA), Fault Tree ANALYSIS (FTA), Energy Trace and Barrier ANALYSIS (ETBA), Software Hazard ANALYSIS (SWHA), Failure Mode & Effects ANALYSIS (FMEA), Management Oversights & Risk Tree (MORT), Chang ANALYSIS (CA), and Job Safety ANALYSIS (JSA) TECHNIQUEs were used. Also, in order to assess the hazard identification methods, ‘ the cost of implementation of the TECHNIQUE, user-friendly features, flexibility, implementation time of the TECHNIQUE, the human resources required to perform safety ANALYSIS, the possibility of using the TECHNIQUE in the most phases of the system life cycle, history of using TECHNIQUE in similar industries, TECHNIQUE’ s logic, experience of ANALYSIS team, reliability and depth of the ANALYSIS of the TECHNIQUE, dependence on information and data, and equipment needed to implement the TECHNIQUE’ criteria were used based on the opinions of the research team. In order to select important criteria from a set of criteria, a panel of experts with a work experience of at least 5 years comprised of 9 PhDs in occupational health, 3 PhDs in chemistry, 1 specialist in risk management, 6 MScs in HSE and 1 PhD in environment were used. Expert’ s opinions about the importance of each of the criteria were gathered through a questionnaire composed of the five "Very good, good, moderate, weak and very weak" spectrum. Finally, using one sample t-test in SPSS 16 software was used to determine the important criteria according to the expert’ s opinion. In order to determine and select the most appropriate method for identifying hazards in the process industry, according to experts’ comments based on the existence of an internal relationship between the evaluation criteria of the methods, ANP TECHNIQUE was used. Initially, in order to obtain the weights of each criterion, internal relations and alternatives, a panel of experts with a work experience of at least 5 years, consisting of 5 PhDs in occupational health, 1 risk management specialist, 2 PhDs in chemistry and 2 MScs in HSE were selected. In the following, the number of paired comparisons in each questionnaire was calculated to determine the weight and importance of the factors. The way of completing the paired comparison questionnaire was to first explain to each of the experts the parameters of the questionnaire and how to complete the paired comparison using the 9-way suggested range by saaty. It should be noted that each of the experts completed the questionnaires alone. The weight vector of each of the criteria and alternatives was calculated by pair comparisons for each expert. Since a panel of experts has been used in this study for the sake of completeness, the geometric meaning was taken from all of the matrices drawn from the experts. Inconsistency ratio by 0. 1 bases for pairwise comparison Matrices was calculated. Subsequently, the formation of the inverted supermatrix, the calculation of the superharmonic matrix and the calculation of the supermatrix Mandar distribution were performed. In this study, Super Decision software version 2. 6. 0 was used to determine the weight of criteria and alternatives by ANP method. Results: The statistical ANALYSIS of one sample T-test was based on the opinions of 20 experts in order to determine the important criteria for participating in the proposed ANP model structure at 95% confidence level, 6 of the 12 criteria were selected. These criteria were ‘ experience of ANALYSIS team, reliability, and depth of the ANALYSIS of the TECHNIQUE, dependence on information and data, history of using the TECHNIQUE in similar industries, flexibility, and the possibility of using the TECHNIQUE in the most phases of the system life cycle’ . Criteria obtained from the last stage were pairwise comparison by the experts' opinions. The inconsistency ratio was 0. 058. The results showed that the reliability and the depth of the ANALYSIS of the TECHNIQUE criterion with a normalized weight of 0. 21 has the highest weight and is in the first priority. In the following, based on the obtained weights, ‘ the possibility of using the TECHNIQUE in the most phases of the system life cycle (0. 206), flexibility (0. 201), dependence on information and data (0. 106), experience of ANALYSIS team (0. 189), and history of using TECHNIQUE in similar industries (0. 088)’ criteria were prioritized, respectively. In this study, based on expert panel comments, there was an internal relationship between reliability and depth of the ANALYSIS of the TECHNIQUE, flexibility, and dependence on information and data criteria. The supermatrix represents the relationships between the components of the NETWORK, through which the final weight of the alternatives can be achieved according to the importance of criteria and their internal relations. Accordingly, the normalized weight and the importance of the alternatives (hazard identification methods) were obtained. Based on the results, the HAZOP (0. 1396), FMEA (0. 1385), ETBA (0. 1197), FTA (0. 0984), PHA (0. 0875), SHA (0. 0806), CA (0. 0769), O&SHA (0. 0735), SWHA (0. 0574), MORT (0. 0495), SSHA (0. 0395) and JSA (0. 0389) were the most preferred TECHNIQUEs in order to identify hazards in process industries. Conclusion: One of the biggest problems in the process industries is the selection of the most appropriate method for identifying hazards and risk scenarios, why so determining the correct control measures is conditional on complete identification of the risk scenarios. In general, the purpose of this study was to explain a structured method for selecting a risk identification method in the industry so that experts and analysts take into account the criteria affecting the application of a method and the degree of importance of each criterion in choosing the appropriate TECHNIQUE for their purpose. In this regard, the process industries have been selected as a high-risk industry, which has been significantly developed in Iran. In this industry, a specific method for identifying hazards called HAZOP has been presented, and the results of this study showed that this TECHNIQUE is at the top of possible choices. However, other TECHNIQUEs such as FMEA are also applicable to these industries. Accordingly, the HAZOP, FMEA, FTA, PHA, SHA, CA, O&SHA, SWHA, MORT, SSHA, and JSA methods were identified as the most preferred TECHNIQUEs for identifying hazards in the process industries by experts. Also, the implementation of this study showed that in other industries that have not been provided with a specific method, a systematic selection of hazard identification methods is possible. The results of this study showed that, despite the various criteria for selecting a risk identification method, some of the criteria are more important and their significance and the internal relationship could be estimated using multi-criteria decision-making TECHNIQUEs such as ANP. One of the limitations of this study is extracting hazard identification TECHNIQUEs and evaluation criteria from one source. Another limitation of this study is the use of exact numbers scale in the process of weighing the criteria and alternatives based on verbal expressions. Therefore, it is suggested that the proposed ANP model be solved under fuzzy conditions in future studies in order to eliminate the probabilistic ambiguity and possible uncertainty in verbal expressions.

Aims The use of intrauterine devices (IUDs) has been one of the most effective, the safest and cost-effective methods for preventing pregnancy, for a long time. However, some complications have been reported for IUDs. The complications may be reduced by using a specific TECHNIQUE for placement of IUD. The objective of this study was to introduce the rotating withdrawal TECHNIQUE for the first time, which was investigated to reduce the complications of IUD insertion. Materials & Methods This historical cohort study was conducted on 1199 females who referred to Sarem Medical Center for IUD insertion from 1984 to 1995. After primary examinations, IUD was inserted by rotating withdrawal TECHNIQUE. The subjects were followed up for 2 years. Findings Displacement was observed just in 20 cases (1. 67%). All of them were seen in the first month after placement. For these cases, IUD insertion was done again. After the second replacement, displacement was observed in 4 cases (0. 035%) after one month. Therefore, it was recommended to them to use another preventive method. There was no pregnancy or displacement in the other cases during 2 years. Conclusion The rotating withdrawal TECHNIQUE can minimize the pregnancy rate when IUD is used. In addition to the type and quality of IUD, insertion method of IUD can increase its effectiveness.

In this paper, a new method for extending and relaxing the noise-coupling (NC) TECHNIQUE is proposed to enhance the noise-shaping order without adding the number of integrators. The noise-shaping order of the introduced ∑∆ modulator whit applying a second-order noise-coupling TECHNIQUE is enhanced and its performance with optimizing the noise transfer function (NTF) zeros is improved. Also, by removing the analog adder at feedforward path and transferring it to a new feedback branch before the last integrator and adding second-order NC path can be decreased the input voltage swing to the quantizer. Thus, by improving the modulator resolution, power consumption can be reduced. Mathematical analyses and behavioural simulation results confirm the effectiveness of the new NC method. To examine its performance, a 2nd-order single loop ΣΔ modulator was designed. The new noise-coupling method is used to achieve the three-order noise shaping to increase the resolution with low complexity and low-power. The results show an outstanding improvement in signal-to-noise and distortion ratio (SNDR) compared to the conventional structure.

In today’s world, the global nature of business and advances in information and communication technology, forced organizations to use emerging technologies to maintain themselves competitive. In recent years, electronic business (e-learning) has been adopted by many organizations. Thereby companies can improve their operational efficiency, profitability and competitive position. This research tried by using burst detection algorithm in scientometrics, to examine all keywords, titles, premier authors, universities, countries as well as co-authors NETWORK in the field of e-business. Hence, all relevant articles in the Web of Science database - as a reference for this study- during 1980 to 2015 have been investigated. In this regard, 4697 articles extracted and burst detection algorithm was used to analyze.

In this study, Neural NETWORK TECHNIQUE is used to predict advance time using inflow rate, n coefficient, slope, length of furrow, infiltration curve number, initial soil moisture and bulk density by ANN and PCA TECHNIQUE. Field measurements on furrows of different length and slopes in Mashhad, Dezful, Orumia, Birjand and Karaj having various soil Textures were used in this study. In the Training phase 144 advance time measured data were initially used and then 96 other field measurements were used for cross validation (48) and evaluation (48) phase. The enter parameters determined by using the sensitivity ANALYSIS NETWORK and Principle Component ANALYSIS (PCA) TECHNIQUE The obtained results showed Neural NETWORK TECHNIQUE is well capable of estimating advance Time with high accuracy. The best results (R2= 0. 995) obtained from models that used of Principle Component ANALYSIS as enter parameters. The models that used of initial soils moisture content (R2= 0. 848) have higher accuracy in comparison to models that used of infiltration curve number (R2= 0. 417) and Coefficient of Manning formula (R2= 0. 492).