فهرست مطالب مهدی تیموری

Low Back pain is one of the most common diseases that face adults with various physical, psychological, economic, and social problems. Due to the fact that patients experience various degrees of disability during this period, the present study was conducted to determine the quality of life and functional outcome in patients with lumbar disc herniation. This study was a descriptive-interventional study that was performed in 2022. One hundred twenty patients undergoing lumbar disc surgery were included in the study by census method. Patients were investigated before and, 3, 6, and 12 months after the operation using a 12-question short-form questionnaire to measure the quality of life, the Oswestry Functional Disability Questionnaire to measure the severity of the disability, the European Quality of Life Questionnaire to measure the health-related quality of life, and the DASS Questionnaire to measure depression, anxiety, and stress. The data were analyzed using SPSS software (version 22) and the significance level was less than 0.05. The quality of life in the physical dimension improved after 12 months (P<0.05). Oswestry disability index improved from severe to moderate disability and preoperative disability improved compared to 12 months after surgery (P<0.05). The EQ-5D index improved after 12 months and significantly differed from before surgery (P<0.05). There was a significant difference between stress before and 12 months after surgery (P<0.05). The results indicated that there was a significant relationship between Oswestry functional disability index and body mass index (P=0.002) and age (P=0.01), and depression with gender (P=0.003). The results showed that the quality of life, functional ability, and stress in patients undergoing lumbar disc surgery improved after 12 months.

Droughts have a set of negative environmental, social and economic effects in a region or country. Using a monthly index and its analysis that, in addition to precipitation values, takes into account the effect of evaporation on the numerical value of the index, is very useful in determining drought parameters. Different indices are also a combination of variables with different marginal distributions, and for this purpose, their statistical analysis is difficult. Therefore, in order to determine the structure of dependence between two or more random variables, copula functions can be used, the distribution of margins is separated from the modeling of the structure of dependence between variables.

In this study, RDI index was used to determine the severity and duration of drought in 6 stations of North Khorasan province between 1988-2018 and Copula functions were used to analyze the severiy and duration. 26 different Copula functions were investigated using different statistical values. Also, two methods of local optimization and Monte Carlo Markov chain simulation with Bayesian estimator were used to numerically estimate the posterior distribution of selected Copula parameters. In order to evaluate the fit of different copulas, the common criteria were used for measuring the fit of different copulas including mean squared error, Bayesian information criterion, Akaike information and Nash-Sutcliffe efficiency criterion.

In all stations, the values of correlation coefficient with Pearson and Kendall tests were positive and had the same trend. The results of the Kolmogorov-Smirnov test at a significance level of five percent for choosing the optimal distribution showed that the generalized Pareto distribution was selected for the intensity and duration of Bojnord station and the exponential distribution for other stations was selected as the appropriate fitted distribution. The optimal function for Bojnord, Maneh and Semelghan stations was Burr function, Jajarm and Shirvan stations, Joe function, Farouj station, Galambos function and Esfarayen station, BB1 function. The results of the local optimization method are highly consistent with the Markov chain Monte-Carlo method. For the 100-year return period, the drought severity at bojnord station is 6.8, at esfarayen station, drought severity is 7.8, at faruj station, drought severity is 7.5, at jajarm station, drought severity is 7.8, at the station in manesemelghan, the drought severity was 8 and in shirvan station, the drought intensity was 2.8.

Conclusion and Suggestions :

The current study shows the high capability of copula functions in solving two-variable problems and recommends the use of all possible functions in choosing marginal distributions and copula in solving problems. Also, the high correspondence between the two methods of local optimization and Markov chain Monte Carlo for estimating the parameters of the functions is probably due to the short statistical period used. Investigating the capabilities of these functions in solving multivariate problems, implementing other Monte Carlo Markov chain estimators, and using longer data to compare different optimization algorithms are suggested in future researches.

Distal radius fractures are among the most common fractures. They can happen at any age group, and there are several treatment options and several classification systems for these fractures. One of these classifications is that of Fernandez. In this study, we evaluated the results of treatment of distal radius fractures by bridging external fixator and percutaneous pinning. In a cross-sectional study, 72 patients with Fernandez type 3, 4 and 5 that underwent external fixation and percutaneous pinning for comminuted distal radius fractures were followed and assessed after 3 and 6 months. The 72 patients had mean age of 44.2 years. 55% were male. The most common cause of fractures was vehicle accidents. 4 cases of malunion, 4 radial nerve injuries, 2 fixator loosening and 6 cases of infection were encountered. External fixator supplemented by percutaneous pinning is an efficient technique for treatment of unstable distal radius fractures. It has low rate of complication and high rate of patient's satisfaction.

Nowadays, the creation of a spatial distribution map for assessing fire risk is widely recognized as a crucial management tool at various levels. This tool helps monitoring natural resource sustainability and the effective control of this environmental hazard. Through the integration of field operations, remote sensing data, geographic information system techniques, and diverse statistical methods, it becomes feasible to develop a dependable spatial prediction of fire hazard potential for different regions. In this research, nine factors were identified to be effective in fire risk modeling, including altitude, slope, aspect, distance from the road, NDVI, LST, TWI, and TPI. Fuzzy Analytic Hierarchy Process (FAHP) and Logistic Regression (LR) were employed to identify risk areas and determine the most significant factors influencing the occurrence and spread of fire. Historical fire areas were identified using Google Earth Engine and MODIS images. The initial results showed that both models assign the highest coefficients to NDVI, LST, and distance from the road. However, during the verification phase, the performance characteristic curve of both models was relatively similar (0.847 for FAHP method and 0.837 for LR method). Upon examining historical fire pixels, it was found that FAHP method correctly identified approximately 87% of the pixels belonging to classes with high and very high risk, whereas LR method only overlapped with 22% of these pixels. This suggests that FAHP method is better at identifying areas with a high risk potential compared to LR method. While it is important to acknowledge that the creation of risk prediction maps using various models cannot completely eliminate all fires, it can greatly diminish their frequency and help their management by offering effective solutions.

The present research aims to determine areas with flood susceptibility using CART, RF and BRT models. Twelve factors affecting flood susceptibility including altitude )DEM), slope, aspect, distance from stream, lithology, rainfall, land use, SPI, TPI, TWI, curvature and RSP were selected. Out of 82 flood points, 70 percent to 30 percent were randomly classified as training and validation data. Also, random forest method was used to determine the most important parameters. The ROC curve was also used to validation the model. According to the random forest model, DEM, distance from stream, rainfall, land use and RSP were the most important factors affecting the susceptibility and probability of floods, respectively. According to the ROC chart, the accuracy of the RF model as a superior model has been very good in both training )0.884) and validation )0.856). According to the final flood susceptibility map, 32.7 percent of the study area has a medium to high flood susceptibility. The results showed due to the high accuracy of the spatial distribution map of flood susceptibility can be promising for decision makers, local managers and policymakers to reduce flood damages.

The accurate estimation of the design Precipitation is one of the requirements for the construction of hydraulic structures, which is done by various methods of frequency analysis. Classical methods of fitting observational data use the assumption of constant parameters of distribution functions; while, many studies have been done on non-stationary data due to factors such as climate change. Therefore, this paper aims to use the functions of non-stationary parameters - if necessary - and compare them with the stationary assumption of the maximum daily precipitation data of the Atrak river basin. Mann-Kendall test and White test were used to check the non-stationary in the mean and variance of annual data. The Generalized extreme value distribution function was also fitted to the data time series. Among the 24 stations with long-term data, 5 stations with trends and 6 stations with variance non-stationary were detected. Evaluation criteria including Akaike (AIC), Bayesian (BIC), Root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE) coefficient was determined under stationary and non-stationary assumptions, for all stations. The results showed that in all stations with non-stationary, considering the mentioned conditions in the analytical calculations is a good choice. Also, the lower (5%), median (50%), and upper (95%) limit values with the return period of 100 years with both assumptions were determined and compared with the classical maximum likelihood method. The underestimation of the maximum likelihood method compared to the Bayesian method used by using Markov chain Monte Carlo (MCMC) in parameter estimation was observed. Also, Akaike criterion provided better results among the used evaluation criteria.

In this study, a modified version of standard precipitatıon index (SPI), namely Agriculture-SPI,or aSPI was used to assese the impacts of drought on rainifed wheat yield in North Khorasan province,northeast of Iran. In the aSPI index, the effective rainfall is used instead of precipitation. The USDA-SCS, method was used for effective rainfall calculation. Both indices were worked out , using 30-years (1989-2018) monthly rainfall and temperature data. Rainfed wheat yield data for the period of 2004 to 2018 were also retrived from local oranizations and standardized for comparisons in different SPI time windows of 1, 3, 4, 5, 6, 7, 8, 9 and 12 months .The obtained annual yields were correlated with SPI and aSPI values in selected timescales. The results showed that in Bojnord station, the rainfall druring November-May period, in Shirvan, Faruj and Esfarayen stations April-June, in Maneh-Semelgan station, November-December period and in Jajarm station, October-June period rainfall, are the most signifcant variables affteting the rainfed wheat according to drought indices used in study region.

 Pulley is a synovial tissue that attaches the flexor tendons to the dorsal portions of the fibro-osseous tunnel near the tendon attachment. Pulley type A with ring structure is one of the most important pulleys in fingers. Two-stage reconstruction by silicon is the common treatment in damaged tendon which has long recovery time and the tendency of the repaired tendon to adhere to the fibrous-bone tunnel around it. Accordingly, the one-stage reconstruction by synthetic pulley is a promising approach to resolve the mentioned problems.
 

 In the present research, the polyurethane (PU) nanofiber scaffolds have been designed for synthetic pulley applications, and their mechanical and structural properties have been evaluated.

 The structural properties of nanofiber scaffolds show similar properties to protein and polysaccharide fibers in the extracellular matrix (ECM). The Fourier transform infrared spectroscopy (FTIR) results confirmed the functional groups of PU without any unwanted reactions. The amount of stress (3.19 ± 0.54) and Young's modulus (1.20 ± 0.39) in PU nanofiber scaffolds show similar mechanical properties to natural pulley.

 The obtained results showed that the PU nanofibers scaffolds can be proposed as a suitable candidate for fabrication of synthetic pulley in flexor tendon injuries.

To determine and zonation of flood prone hazardous area and prioritization the sub-basins in terms of flood potential can have great contributions in promising watershed management. The present research aims to prioritize flood and sedimentation potential in the sub-basins of the Bonekooh watershed using TOPSIS, SAW, ELECTRE and VIKOR methods.

In this present study, we used area estimation indices, drainage density, gravel coefficient, basin average height, basin average slope, curve number, sediment yield, cover percentage, sediment delivery ratio, runoff height and concentration time as an important indicators affecting water permeability, runoff production and, consequently, the potential for flooding and sedimentation. Then, using the Analytic Hierarchy Process (AHP) method, the weight of each index is met. Following the formation of decision matrix with 18 options (sub-basins) and 11 criteria (evaluation index), Technique for order Preference by Similarity to ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Elimination Et Choice Translation Reality (ELECTRE) and Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) techniques were used to prioritize sub-basins. Borda and Copland methods were used to combine the rank of proposed techniques. The residual sum of squares (RSS) method was used to determine the closest method to the final result. Also, in order to validate the models, we estimated the percentage change and the intensity of the changes.

The results showed that the highest runoff height index (0.18) and the gravel coefficient had the lowest weight (0.028), according to experts. Prioritization results showed that in SAW, TOPSIS and VIKOR methods, sub-zones 9, 4, and 2 ranked first to third priorities respectively and are in a more critical situation, but in the ELECTRE approach sub-basins 9, 4, 2 and 7, respectively, have the first to third priorities. Considering the results of the combined ranking of the proposed techniques, sub-basins 9, 4 and 2 are in first to third priority, respectively, and have a more critical situation than the rest of the sub-basins. Also, zones with flood and sedimentation potential in the area showed that 32% of the area in high and very high risk. The results of the sum squared error showed that the VIKOR method had the least error and the ELECTRE method had the most error than the final ranking. Also, the TOPSIS and VIKOR methods with the lowest percentage of change (59.72%) were ranked first and the ELECTRE method with the highest percentage change (65.27%) is the last rank. The lowest intensity was also observed in the VIKOR method (4.59) and the highest intensity variation was observed in ELECTRE method (5.61).

Therefore, it can be said that multi-criteria decision-making techniques are a practical and appropriate approach for better decision-making based on mathematical sciences and optimization. Therefore, these types of low-cost and fast-track research can be prioritized to protect watersheds.

In the present research, changes in sediment regime in two statistical periods of "natural flow" and "modified / debris flow" were evaluated. In order to determine the significant difference between two mentioned periods (1966-1992) and (1993-2015), the significance test was used. In order to determine the most suitable method of Sediment Rating Curve and correction coefficients, the results of simple linear, bilinear, midline rating curve methods as well as the mentioned rating curves with correction coefficients including correction coefficients of FAO, MVUE, QMLE and Smearing methods were evaluated. The results showed that since 1993, with the onset of large floods, the sediment discharge regime with a high intensity and increasing trend is out of normal and in the period 2011 to 2015, the highest rate of sediment transfer in the form of debris flow has occurred. Among the methods, the one-line curve method and the smearing correction factor for the natural sediment regime period (1966-1992) and the two-line curve method and the smearing correction coefficient for the modified sediment regime / debris flow period (1993-2015) are more accurate in estimating sediment flow. On the other hand, the one-line curve method without taking into account the correction coefficients have a higher low estimation error and among the mentioned correction coefficients, the FAO coefficient has a very high overestimation error. In the batch middle method, sediment estimation at high discharges is improved by reducing the effect of low points.

Hip hemiarthroplasty is a common method in treating femoral neck fractures in patients older than 70 years old. Depending on the severity of bone destruction, and bone stock, two methods either cemented or non-cement bipolar prosthesis may be used.

In a prospective study, 60 patients with femoral neck fractures who were referred to the university hospitals of Isfahan, Iran, were divided into two treatment groups.: 30 patients were treated with cemented bipolar method and 30 with non-cement bipolar hip arthroplasty surgery. In a 6-month follow-up, the surgical outcomes were assessed using the VAS pain scale, SF36 general health instrument score, and Harris hip score (HHS).

The pain scale (VAS), SF36 and Harris scores showed non- significant differences in the two groups: pain=3.63 out of 10 in 3 months and 2.6 out of 10 in 6 months; SF36= 69 and 86 in 3 and 6 months ,respectively; HHS=78 in both in 3 and 6 month in the cemented group .In non-cemented group the pain scores were 3.91and 3.12 in 3 and 6 months; SF36=67 and 83, and HHS=82 in 3 and 6 months respectively..

It seems that the two methods of cemented and non-cemented bipolar hemiarthroplasty ,in elderly hip fractures, would have similar pain, quality of life, and hip function in short term follow-ups.

GSM cellular standard is still widely used worldwide. In this standard, A5 ciphering algorithms are employed for protecting user data. A5/1 and A5/3 are two variants of A5 ciphering algorithms that are proven to be very powerful. Most known attacks on these ciphering algorithms assume some known plaintext data. In this paper, for the first time, a method of plaintext prediction is proposed for SDCCH logical channel. Four possible downlink SDCCH packets, which are RR, UA, SABM, and UI Fill frames, are considered. The matrices of the occurrence positions and probabilities of these packets are learned by observing the network traffic. Four matrices are considered corresponding to four different types of sessions. Experiments on a real-world network show that we can correctly predict on average 2.94 plaintexts for each session. Moreover, the average position of the first correct plaintext in all predicted plaintexts is equal to 1.24. So, the required time for cipher cracking is around 25% more than the time required by an ideal plaintext prediction system

The GSM cellular standard is still widely used worldwide. In this standard, the A5 ciphering algorithms are employed for protecting user data. A5/1 and A5/3 are two variants of A5 ciphering algorithms that are proven to be very powerful. Most known attacks on these ciphering algorithms assume some known plaintext data. In this paper, for the first time, a method of plaintext prediction is proposed for the SACCH logical channel. The sequence of downlink SACCH messages is modeled by a first-order Markov chain. Experiments on a real-world network show a 99% success rate. Moreover, the average position of correct plaintext in all predicted plaintexts is equal to 3.21. So, the speed of cipher cracking is around one-third of the speed of an ideal plaintext prediction system.

The purpose of this research is to determine the groundwater potential of areas and to prioritize the factors affecting it using the maximum entropy method and the new height above the nearest drainage index. In the present study, 14 effective indicators have been used for groundwater potential including topographic, geological, climatic, hydrological and land use factors as well as a new height above the nearest drainage index (HAND). First, the factors were divided into two parts including of topographic and other factors such as geology, climate, hydrology and land use, and groundwater potential map was prepared based on them. Then, with the integration of the indices, the final groundwater potential map was prepared. Of the 2547 springs, using the Mahalanobis distance method, 60% of the data was classified as test data and 40% as validation data. The results showed that according to topographic indices, other factors and the combination of all indicators, 38.5, 27.4 and 34.7 percent of the area have groundwater potential, respectively. Also based on Jackknife Diagram, the altitude, land use, slope, relative slope, HAND index and lithology were the most important factors influencing groundwater potential. The area under curvature (AUC) based on ROC diagram indicates accuracy of 83, 83 and 85% (very good) at the training stage and 82, 81 and 84% (very good) in the validation step based on topographic indicators, other factors and the integration of all indicators. Given that the HAND index has been an effective factor of groundwater, it has a crucial role in identifying areas with groundwater potential.

The transverse dike has many applications for River bank erodibility stabilization and consolidation. Water flow pattern, erosion and sedimentation around the transverse dike are dependent of various factors, Such as transverse dike type, geometry sections, sediment transport capacity and etc. In This study With regard to the significance role of the flow velocity and shear stress forces on river bank erosion, two-dimensional numerical modeling as CCHE2D was performed to Numerical Simulation of the Transverse Dike and Islands effect over Water Flow Pattern in Natural Meandering of the Tajan River (in the north of Sarakhs and downstream of Noruzababd village- Razavi Khorasan Province, Iran).

In the first step of this study, a large topographic scale map was prepared with scale 1: 2000. And in three sections of the surveyed sections, the flow parameters were measured. Using topographic data obtained from field surveys and then the geometry model and the computational mesh (grid) with different dimension and also field measurements of flow characteristics such as velocity and depth, the two-dimensional hydrodynamic model was run. Simulated data were compared with observed ones in order to assess the velocity horizontal profile gradients, the distribution of shear stress and the flow depth condition in curved parts of the river channel and around the transverse dike and islands.Furthermore, two statistical criteria (RMSE and MAPE) were used to evaluate the performance of the model.

The results indicated that the simulated values are in good agreement with the field measurements. In the study area, water flow pattern around the transverse dike and islands is dependent of hydraulic conditions and at various discharges has different impact on the flow pattern. due to transverse dike and islands, cross-sections reduce, reason increasing the depth, speed and shear stress, sediment transport capacity and bed load.

The results of this study show that for Observation discharge (47 m3/s) and discharge with a return period of less than 25 years, transverse dike have local effects on the deviation of the flow, and they cannot lead to the diversion of floods with a return period of less than 25 years to the eastern banks. Because the high density of vegetation and high roughness on the east coast, prevents the distribution of flow to the two natural canals. Key words: Transverse Dike (Epi), Island, CCHE2D, Meandering, Tajan riverKey words: Transverse Dike (Epi), Island, CCHE2D, Meandering, Tajan river

It is very complex and difficult to fully understand the relationships in watersheds due to the heterogeneity and non-linear nature of hydrological and erosive behaviors. Therefore, the evaluation of watersheds requires a modeling process. After introducing the features of the eWater Source software as a management modeling environment for watersheds, two rainfall-runoff models of the GR4J and the IHACRES were compared to simulate the runoff of the Chel-Chay Watershed in the eWater Source environment. Chel-Chay Watershed, with an area of 256 square kilometers is located in Province of Golestan. In order to simulate the rainfall -runoff, the position of the watershed, sub-watersheds, stations, watershed outlet, operational units (based on land use map) and the watershed waterway network was simulated using the digital height model (DEM) in the Source environment. The GR4J and the IHACRES models were used. In this rainfall -runoff models, the continuous time series data were considered in the daily time steps. The time series of the daily precipitation of the years (2001 to 2010), and the daily evaporation and transpiration (during the same period) were used to implement the models. The models were implemented in the eWater Source environment. The discharge data for the period (2001-2010) were used to calibrate the models. The accuracy of the flow simulation based on the Nash-Sutcliffe criterion for the GR4J and the IHACRES models in the calibration period (2001-2010) were 0.79 and 0.73, and in the validation period (2011-2015) were 0.76 and 0.68, respectively. Therefore, it may be concluded that these models performed well in the simulation. The evaluation of results indicates that the GR4J model performs better than the IHACRES model for simulating the daily flow. Due to the high capabilities of the eWater Source software, this environment is recommended as a management model for the discharge of watersheds.

With the increase in population, the importance of groundwater resources as one of the most important sources of drinking water in the arid regions becomes apparent. In this research, in order to determine the areas with groundwater potential in the city of Torbate Jam and prioritizing the effective factors, hierarchical analysis methods and maximum entropy method using MaxEnt model and the factors of distance from fault and fault density, lithology, slope, slope direction, distance from the waterway and drainage density, elevation, land use, slope curvature, topographic humidity index and topographic position indicator was used. Also, for assessing these two methods, the Receiver Operating Characteristic (ROC) was used. From 220 sources, 30% were randomly assigned as validation data and 70% were categorized as test data in maximum entropy method. Results showed that 29.6% of the watershed had high groundwater potential according to the maximum entropy method. Based on Jack-Knife Diagram, DEM, slope, distance from fault and lithology were the most important factors affecting groundwater potential, respectively. The Area Under the Curve (AUC) in the maximum entropy method indicated a precision of 91% (excellent) at the training period and 80% (very good) in the validation period to determine areas with potential for groundwater. Based on AHP method, 34.4% of the area has groundwater potential, and the slope layers, lithology, elevation and distance from the faults were the most important factors, respectively and accuracy of this method was 73%. The results showed that applying AHP and maximum entropy methods, while saving time and cost, have a good ability to predict the potential of groundwater and the maximum entropy method has more superiority than the hierarchical analysis method.

Underground water is one of the most important water resources that plays an important role in providing water for agricultural and drinking activities in arid and semi-arid regions (Usamah and Ahmad, 2018, Wu et al., 2019, Kumar et al., 2019). Awareness of the quality of water resources is one of the most important requirements in managing, planning, and developing, protecting, and controlling water resources. Using multivariate statistical techniques helps researchers identify the most important factors affecting the quality of water systems and is a valuable tool for water resources management (Pasandidehfard et al., 2019). On the other hand, geostatistical methods are also capable of zoning water quality at the watershed level and can play an important role in completing the assessment of water quality (Ahmadi et al., 2019). The aim of this study is to evaluate the quality of groundwater used for drinking and farming in Hable-Rood Basin, analyze and interpret the quality of these resources using ArcGIS, and perform statistical tests to determine the role of land use and geology formations in water quality.

To do this research, 132 water sources including wells, springs, and Qanats were used during the statistical period of 2008-2018. The watershed can be divided into fifteen main categories in terms of geology. Hable-Rood watershed has 11 main land uses, which has the largest area of the watershed for pasture and the smallest area of the dams. The main components were analyzed (factor analysis) to understand the most important parameters affecting the water quality. This method weighs the components and expresses a special value for each of them (Finkler et al., 2016). Factor analysis has three stages of producing a correlation matrix from all variables (Pearson correlation method), extracting the main factors, and interpreting the results. Duncan's test was also
used to check the significance level of parameters among land uses and the type of formations. Geostatistical methods were used for zoning water quality for drinking and farming purposes in the GIS. The spatial relationship of a random variable in the geostatistics was determined by the semivariogram (software GS +). The root mean square error (RMSE) method was used to assess the geostatistical methods and select the best method. It should be noted that the Schoeller diagram and Wilcox diagram were used for the drinking water zoning and agricultural water quality zoning, respectively.

The results showed that the Cl, EC, TDS, Na, Ca, TH, and SO4 vary significantly in different land uses. The highest average was related to industrial areas within the watershed due to the release of industrial materials and the spread and diffusion of groundwater pollution. Also, the parameters of Cl, EC, TDS, TH, and SO4 differed significantly in varied formations. The trend of water quality changes shows the water quality impact of land use, and water quality has decreased sharply in the industrial area, low-yielding land, saline lands, agriculture, and residential areas. The EC parameter showed the highest correlation with TDS at 5% significance level, which is due to a high correlation with the effect of increasing EC on TDS. The pH parameter did not correlate with the other parameters. The factor analysis on the basis of water quality characteristics showed that 88.16% of the water quality variations among land uses were controlled by a single factor (TDS with a weight of 0.99). The factor analysis on the basis of water quality characteristics showed that 91.59% of water quality changes in the formations were determined by two factors (the first and the second factors with weight loads of 0.95 and 0.95 belonged to the TDS and EC parameters, respectively), and the variance percentages of each of factors 1 and 2 were 77.29 and 14.3%, respectively.

In this research, the effects of geology and land use on groundwater quality were evaluated using multivariate statistical methods and geostatistical methods in ArcGIS. It was determined that some of the groundwater quality parameters were affected by land use and some of the other parameters were under the influence of the geology in the watershed. In general, however, it can be stated that in the first priority, the land use factor and human activities, and in the second priority, the geological factor affecting groundwater quality have the most significant effects. In the formation part of the geology, the dissolution of calcareous and dolomite formations, the chemical processes of salt dissolution, and evaporative formations are the main factors controlling
groundwater chemistry in the region. Based on the results, multivariate statistical techniques and geostatistical methods have the ability to recognize factors affecting groundwater quality and the zoning of water quality for different uses and are, therefore, suggested for similar research.

Groundwater is the most important and vital natural resource in arid and semi-arid regions. The purpose of the study is to determine the potential of groundwater in different areas of the watershed and prioritize the factors affecting it. Fourteen indices were used which affect groundwater potential namely slope, elevation, slope aspect, topographic curvature, distance from any stream, drainage density, distance from a fault, fault density, topography humidity index, lithology, land use, relative slope position, topographic position, and topographic hardness. Moreover, from the 145 springs, 30% were randomly classified as the validation data and 70% were categorized as the test data. The maximum entropy method and the MaxEnt model was used to prioritize the effective factors and zonation of groundwater potential using the ArcGIS in the Piranshahr Watershed. Further, the ROC model was used to evaluate the developed model. The results indicated that 33.6% of the watershed had groundwater potential, which is located mostly in its center. Based on the jackknife</em> chart, humidity, topography, DEM, lithology (sandstone and shale), topographic hardness, topographic position and slope were the most important factors influencing the groundwater potential. The area under the curve shows an accuracy of 93% (excellent) at the training stage and 81% (very good) at the validation stage for the determination of the watershed groundwater potential. The results of this research may be used to manage the groundwater resources of the Piranshahr Watershed, especially with regards to imminent population growth.

‎The class of α-stable distributions incorporates both heavy tails and skewness and so are the most widely used class of distributions in several fields of study which incorporates both the skewness and heavy tails‎. ‎Unfortunately‎, ‎there is no closed-form expression for the density function of almost all of the members of this class‎, ‎and so finding the maximum likelihood estimator for the parameters of this distribution is a challenging problem‎. ‎In this paper‎, ‎in order to tackle this issue‎, ‎we propose some type of EM algorithm‎. ‎The performance of the proposed EM algorithm is demonstrated via simulation and analyzing three sets of real data‎.

One of the major challenges in electronic and cyber warfare is to achieve maximum information from the intercepted signals of a communications network. To this aim, the first step is reverse engineering of the physical and data transmission layers in order to obtain the transmitted packets. In the next step, service layer should be identified. In this step, the exact meaning of each packet along with the communications state machine should be identified. By completing these tasks, the information content exchanged through the network would be available. In this paper, a comprehensive scheme is proposed for identification of the service layer. With the intention of proving proficiency of the proposed scheme, usability of this scheme for identification of nine different standards, including GSM, LTE, HSDPA, DVB-S2, FLEX,

The main objective of this research is to prioritize the factors affecting the occurrence of landslide and its susceptibility zoning in Lorestan province using the maximum entropy and MaxEnt models. To do this research, 11 factors affecting the occurrence of landslide including height, slope, aspect, surface curvature, distance from the stream, fault and road, lithology, land use, rainfall, and topographic humidity index have been used. In this research, 30, 40, 50, 60 and 70 percent of landslides were evaluated for validation to determine the sensitivity and accuracy of the model. For evaluation of the model, the relative recognition function curve (ROC) was used. From the total of 176 landslides, 70% of the data was used as the test data and 30% as the validation data using Mahalanobis distance method and the accuracy of the model in the testing and validation stages based on the curve level was reduced. The results showed that 35.5% of the province of Lorestan has a landslide sensitivity. Based on jackknife diagram, rainfall, distance from road, lithology and land use layers were the most important factors influencing the sensitivity of landslide. The AUC level based on the relative function recognition curve indicated a 90% accuracy (excellent) of the maximum entropy method at the training stage and 83% (very good) at the validation stage to determine the landslide susceptibility. The results of this study will be suitable for provincial administrators and managers in order to land planning and reduce the damage caused by landslide occurrence. Mass movements, including landslide, is one of the most important issues in natural hazards, because its occurrence can cause many human and economic losses, especially in mountainous areas (Symeonakis et al., 2016). Regarding the destructive effects of landslides on natural resources, as well as human habitats and erosion of significant volumes of valuable soils, the identification of susceptible areas and zoning of potential occurrence or landslide susceptibility is vital and very important (Zhang et al., 2019). In recent years, the use of GIS and remote sensing along with machine learning methods has created a new step in the zoning of landslide occurrences. Lorestan province is a vulnerable area to landslide hazard due to the mountainous and wetness conditions. Therefore, the main objective of this research was to prioritize the factors affecting the occurrence of landslide and its susceptibility zoning in Lorestan province using the maximum entropy and MaxEnt model.

Lorestan province with an area of 2829612 hectares is one of the major provinces in the west of the country. To do this research, 11 factors affecting the occurrence of landslide including altitude, slope, aspect, surface curvature, distance from the stream, fault, and road, lithology, land use, rainfall, and topographic humidity index have been used. The required maps were prepared using GIS and RS techniques. In this research, 30, 40, 50, 60 and 70 percent of landslides` division were evaluated for validation to determine the sensitivity and accuracy of the model. For evaluation of the model, the relative recognition function curve (ROC) was used. Using Mahalanobis distance method, from the total of 176 landslides, 70% of the data was used as the test data and 30% were utilized as the validation data for having the best classification. The difference of the current research with other similar studies was that in this study, use was made of Mahalanobis distance method for classification of validation data and training instead of random classification. The Mahalanobis distance helps to classify data richness and prevents random selection of points for validation. Maximum entropy method (MaxEnt model) is one of the methods of machine learning and one of the main advantages of MaxEnt model is the ability of this model to identify the most important variables and sensitivity analysis of variables using Jackknife method, which has been investigated in the current study.

The results showed that 35.5% of the province of Lorestan had landslide susceptibility. Based on Jackknife diagram, rainfall, distance from road, lithology and land use were, respectively, the most important factors influencing the susceptibility of landslide. The AUC level, based on the relative function recognition curve, indicated 90% accuracy (excellent) of the maximum entropy method at the training stage and 83% (very good) at the validation stage to determine the susceptibility of landslide occurrence.

Discussion and conclusion

Landslide is considered as one of the most dangerous natural disasters in the world. In this study, taking into account the affective environmental and human factors, and using the maximum entropy method, the map of landslide susceptibility of Lorestan province was prepared. The results showed that factors such as rainfall, distance from the road, lithology, land use, distance from the fault and slope were the most important factors influencing landslide susceptibility with the participation of over 60%, regarding which, land use management and road construction principles need human activity interventions. The drawn ROC curve showed that the accuracy of the model in the estimation of landslide susceptibility regions both in the stage of the test and in the validation stage was excellent and very good, which meant the excellent performance of the model. According to the obtained results, it can be said that MaxEnt model had a high ability to determine areas with landslide susceptibility and due to the speed and accuracy of the model,it is suggested that in similar researches, especially in developing countries, due to the lack of facilities and financial resources, as well as the time consuming of identifying areas with landslide susceptibility, it can be used. In addition to natural factors, some human factors such as road construction, play an important role in the occurrence of landslide, which requires avoiding ecosystem change as a disaster risk factor to reduce relative risks. The results of this research can be applicable to the decision making and management of provincial lands as well as urban planning, and they can have a significant role in preventing and reducing the damage caused by landslide.

Runoff estimation is a fundamental activity in water resource management, and plays an important role in the best usage of a hydrologic system. Runoff estimation is usually based on different hydrological models. Calculation of intensity and duration of precipitation is not efficient in the most regions of the globe for determining general properties of precipitation because these calculations are based on pointed data of ground observation, whereas precipitation is a spatial phenomenon. The aim of this paper is simulating monthly runoff of Kalam Basin based on satellite data of precipitation using SWAT model. In order to running SWAT, precipitation data of TRMM and GPCP, temperature, relative humidity, wind speed and solar radiation is used for the period of 1998 to 2012 for study area. Also, soil and land use maps and DEM are converted to the model format for study area. Period 2001 to 2009 is used for calibration and 2010 to 2012 for validation of the model. Nash Sutcliffe Efficiency Index and Weighting Coefficient was 0.41, 0.44, 0.32 and 0.37 for TRMM and GPCP respectively for calibration and 0.52, 0.71, 0.10 and 0.19 for validation. The results indicated that SWAT achieved a reasonable fit after calibration by using TRMM and not reasonable using GPCP data the model.

Eutrophication is a natural process which can be increased by human interferences and finally lead to water quality degradation and reservoir aging, and always is one of the challenging problems of reservoir across the world. Since determining of the trophic status of the reservoir is a complex and intriguing process, this study used fuzzy synthetic evaluation method with entropy weighting technique to determine eutrophication level in the Shirin-darreh dam reservoir in the North Khorasan province for a one year period of time. To this end, fuzzified data of main variable including chlorophyll-a concentration, total phosphorous, saturation oxygen and total nitrogen were used to determine membership function and the Shannon entropy technique was used for weighting index variables. Finally, results of this approach was compared with the results of equal weighting technique and Carlson method. The results showed that from December to March the reservoir was in oligotrophic status, during November in mesotrophic status and during other months it experienced an eutrophic condition. Considering the capability of this approach to express the degree of certainty and intensity at different levels and months, it was observed that July, August and September have the highest eutrophication level with most degree of certainty. Also, this approach has reasonable and realistic results in comparing with Carlson method and equal weighting fuzzy technique.

In this paper we focus on two topics. Firstly, we propose $U$-statistics for the Weibull distribution parameters. The consistency and asymptotically normality of the introduced $U$-statistics are proved theoretically and by simulations. Several of methods have been proposed for estimating the parameters of Weibull distribution in the literature. These methods include: the generalized least square type 1, the generalized least square type 2, the $L$-moments, the Logarithmic moments, the maximum likelihood estimation, the method of moments, the percentile method, the weighted least square, and weighted maximum likelihood estimation. Secondly, due to lack of a comprehensive comparison between the Weibull distribution parameters estimators, a comprehensive comparison study is made between our proposed $U$-statistics and above nine estimators. In our knowledge, this work is the most comprehensive comparison study for the estimators for the Weibull distribution. Based on simulations, it turns out that different estimators may appeal for different range of the parameters. So, practitioners are allowed to chose the best estimator that is suggested by the goodness-of-fit criteria.