Autographic rain-GAGE networks are designed to provide the density and distribution of stations so that characteristics of the rainfall events both in time and over the region concerned can be determined with sufficient precision. The conventional rain-GAGE network design is simple random sampling, correlation of functions, and regression techniques. All procedures in generalized and theoretical approaches require some knowledge for the spatial correlation of rainfall processes. In this regard Kriging method, may fully define this spatial correlation. Therefore, the location(s) of the additional rain-GAGE(s), in an existing network, can be optimized on the basis of the estimated variance. The intensityduration- frequency (IDF) curves from 64 autographic rain-GAGE stations in Iran were used in this study. One-hour (60 min) duration, ten-year recurrence 60 P10 , a key entry to IDF curves, was used to analyze the adequacy of the present autographic rain-GAGE network. The results showed that at least six more rain-GAGEs are needed for reducing the relative CV from the initial value of 100% to 40%. Three of them must be added in Isfahan, two in Kerman, and the last one in Sistan-Baluchestan provinces. Application of this procedure for the other entry of 60 P100 verified the adequacy of the new proposed network. However, the performance of these six additional rain-GAGEs needs to be evaluated over time, using their real IDF curves.

In this paper, we present some attacks on GAGE, InGAGE, and CiliPadi, which are candidates of the first round of the NIST-LWC competition. GAGE and InGAGE are lightweight sponge based hash function and Authenticated Encryption with Associated Data (AEAD), respectively, and support different sets of parameters. The length of hash, key, and tag are always 256, 128, and 128 bits, respectively. We show that the security bounds for some variants of its hash and AEAD are less than the designers’ claims. For example, the designers’ security claim of the preimage attack for a hash function when the rate is 128 bits, and the capacity is 256 bits, is 2256. However, we show that the security of preimage for this parameter set is 2128. Also, the designer claimed security of confidentiality for an AEAD, when the rate is 8 bits, and the capacity is 224 bits, is 2116. However, we show the security of confidentiality for it is 2112. We also investigate the structure of the permutation used in InGAGE and present an attack to recover the key for reduced rounds of a variant of InGAGE. In an instance of AEAD of InGAGE, when the rate is 8 bits and the capacity is 224 bits, we recover the key when the number of the composition of the main permutation with itself, i. e., r1, is less than 8. We also show that CiliPadi is vulnerable to the length extension attack by presenting concrete examples of forged messages.

Estimation of rainfall spatial distribution is an important step in water resources studies. Preliminary assessment of existing rain GAGE networks show that the spatial distribution of the GAGEs is not suitable as many are just located in populated areas. Optimization of rain GAGE locations can improve the accuracy of water balance studies. Several methods have been proposed for such tasks. Kriging is a geostatistical method which can estimate the variance error based on a pre-determined semivariogram with no reliance on historical record. One can therefore apply Kriging method to estimate the reduction in error variance due to any change in the network such as addition of a new GAGE or moving an existing GAGE. In this paper, the objective is to optimize GAGE locations based on error variance and topography of the region. This is done such that no extra cost is incurred; i.e. only omission or moving the stations is allowed. The results indicated that the number and the network structure is sufficient for estimation of rainfall distribution in dry months. However, in case of wet months and the annual rainfall, moving some of the stations is necessary. In all, 17 stations may be moved to reduce the average error by 10 percent. It must be noted that the error is quite high in extrapolation regions, as expected.

Final step of rail manufacturing is cold rolling straightening process and it has significant effects on mechanical properties, straightness, flatness and development of residual stresses. Measurement of residual stresses after straightening process is obligated by rail manufacturing standards. In the present investigation, an attempt has been made to evaluate residual stresses after straightening process by finite element method and strain GAGE sectioning technique. The straightening process has been simulated here using the FE package ABAQUS. All the input data were extracted from experimental tests according to rail manufacturing standard and homogenous and isotropic behavior of material were considered. Moreover, initial camber of the rail was measured after hot rolling and cooling process. Obtained results of numerical calculation has been validated by strain GAGE sectioning technique and compressive residual stresses in head and web and tension residual stress in foot of the rail has been observed. The roller arrangement used in this investigation could reduce the amount of residual stresses comparing with the previous results. Furthermore, straightness of the rail after straightening was satisfactory.

Cold working a hole decreases the tendency of fatigue crack near the hole to commence or grow. It is due to the creation of some compressive tangential residual stresses around the hole. Determination of the mentioned residual stresses with a non-destructive, simple and nonexpensive method is the key step in the design process of holed components. In this article, residual stresses have been determined by mounting some strain GAGEs around the hole and, in fact, surface strains during cold working process have been introduced as a feature for residual stress field. Delineating the numbers of needed strain GAGEs and also proper place for mounting them around the cold worked hole are the main objectives of this research. Results have good agreement with test result of cold working on specimens made of Al2024. According to the results, mounting two strain GAGEs at the same radius on the opposite side of hole edge, in which one is in radial and the other in tangential direction is necessary for determining the residual stress field. Also, strain GAGEs should be mounted in elastic zone. Mounting the GAGEs in plastic zone led to errors and unreliable results.

Introduction: An important variable in investigation of agility during puberty is the age of reaching peak high VELOCITY, which like other agility indicators is under the effect of different factors such as physical condition and type. The purpose of present research was to examine relationship between somatotype and peak high VELOCITY (PHV) among Iranian 7-10 years old boys.Methods: Participants were 313 7-10 year-old members of Basij talent identification centers in all Iran's provinces. Somatotype data were calculated using Heath-Cartr instruction and PHV was measured using Mirwald formula and were analyzed using Pearson correlation and multiple regressions.Results: Results of pearson correlation showed that PHV had a positive correlation with ectomorphy and negative correlation with endomrphy and mesomorphy. Total correlation between PHV and somatotype was 0.50 which explained 25% of PHV variance. Results of regression analysis showed ectomrphy and endomorphy were significant predictors of PHV but msomrphy was not a significant predictor of PHV.Conclusion: Endomorphy had a smaller part in predicting the PHV age, but mesomorphy was not a strong predictor, Moreover, ectomorphy following endomrophy had a strong predicting power. Studies in this area suggest that those who have greater ectomorphic characteristics are less agile and the physiologic requisites for their puberty develop later in their bodies. Therefore poor sport performance of ectomorphic children may result from their distance to PHV age so coaches and instructors should consider this measurement and somatotype.

Drought as a climatic phenomenon affected many different environmental issues and generally is associated with the decreasing in average precipitation. Evaluation and monitoring of the drought is a fundamental step in proper programming of water resources management. Regarding the recent conditions water scarcity in the Urmia Lake basin, assessment of the drought index in this region is inevitable. This study was conducted to evaluation of the SPI index in western parts of the Urmia Lake basin. Rainfall data were collected from 11 rain GAGE stations in Tabriz and Maragheh plains. The standardized precipitation index in time scales of 9, 12, 24 months used for studying the drought features and adaptive neuro-fuzzy inference system model was applied for prediction of drought. The results indicated that the most serious (-4. 07) drought was occurred in Bonab station at the 9 month time scale in October 1984. The longest drought periods were occurred in Heravi, Saiedabad, and Maragheh stations and the shortest drought periods were occurred in Zinjab, Tabriz, and Lighvan stations. The results of SPI prediction by ANFIS model indicated that the model desirably could predict the drought conditions in the study area. The highest value of the coefficient of the determination of ANFIS model was 0. 829 for Maragheh station at 24 months’ time scale and the lowest values of r2 was 0. 480 for Saiedabad station at 9 months’ time scale. Results also indicated that the capability of the ANFIS tend to be better at long time scales.