The analysis of geochemical data in frequency domain, as indicated in this research study, can provide new exploratory information that may not be exposed in spatial domain. To identify Deep geochemical anomalies, sulfide zone and geochemical noises in Dalli Cu– Au porphyry deposit, a new approach based on coupling Fourier transform (FT) and principal component analysis (PCA) has been used. The relationship between frequency attributes of surface geochemical data and mineralizing depth has been discussed. To determine the exploratory features in different frequencies, high- and low-pass filters have been performed on frequency domain; PCA method has been employed on these frequency bands separately. The results of this study have identified the mineralizing elements and showed the relationship between high- and low-frequencies and depths of anomalies. The geochemical halos of mineral deposits at different depths affected frequency distribution of elements in the surface. The information obtained from geophysical studies and exploration drillings, such as, trenches and boreholes, confirm the results of FT–PCA method. This new approach is very effective tool to identify the promising anomalies and Deep mineralization without drilling.

Distributed Denial of Service (DDoS) attacks are among the primary concerns in internet security today. Machine learning can be exploited to detect such attacks. In this paper, a multi-layer perceptron model is proposed and implemented using Deep machine learning to distinguish between malicious and normal traffic based on their behavioral patterns. The proposed model is trained and tested using the CICDDoS2019 dataset. To remove irrelevant and redundant data from the dataset and increase learning accuracy, feature selection is used to select and extract the most effective features that allow us to detect these attacks. Moreover, we use the grid search algorithm to acquire optimum values of the model’s hyperparameters among the parameters’ space. In addition, the sensitivity of accuracy of the model to variations of an input parameter is analyzed. Finally, the effectiveness of the presented model is validated in comparison with some state-of-the-art works.

Identification of Deep ore deposits is one of important subjects in exploration field. Discrimination of dispersed mineralization zones and blind mineralization area is an important challenge in exploration of mineral deposits. Geochemical Zonality method and alteration models are traditional method that utilized for exploration of Deep ore deposits specially Cu porphyry and Au veiny deposits. In this study, the anomaly thresholds have been determined using the fractal method for calculating the Zonality indexes in Tanurcheh area and then 4 important Zonality indexes have been used. In addition to these traditional methods, suitable information in this field can be achieved using interpretation of geochemical data in frequency domain. The situation of Deep deposits and dispersed zones can be surveyed using interpretation of frequency anomaly in frequency coefficients of elements method. In this study, the potential of Deep mineralization in one part of Kashmar Au and Cu mineralization area has been surveyed by frequency coefficients of elements method and obtained results have been compared to Zonality method and information of Deep exploratory boreholes. The results of frequency coefficients method have properly been confirmed using the results of Deep drillings unlike Zonality method.

Many roads in forest areas are located along the steep hills. The cut and fill method is currently used for construction of these roads. Settlement or consolidation in not enough compacted soil or creep in down slope, can lead to subsidence and cracks in roads. General methods for solving settlement related problems such as reconstruction, retaining structure and … are expensive. Deep patch method is a low- cost method for increasing the stability of slopes. In this method, the upper parts of the subsided area are excavated and replaced with reinforcement materials such as Geo grid in accordance with compacted soil. In this paper, limit equilibrium method has been implemented for determining the safety factor of a planar slip surface in a slope. Furthermore, graphs for determining safety factor of reinforced soil slope with Geo synthetics have been proposed.

In traditional speech processing, feature extraction and classification were conducted as separate steps. The advent of Deep neural networks has enabled methods that simultaneously model the relationship between acoustic and phonetic characteristics of speech while classifying it directly from the raw waveform. The first convolutional layer in these networks acts as a filter bank. To enhance interpretability and reduce the number of parameters, researchers have explored the use of parametric filters, with the SincNet architecture being a notable advancement. In SincNet's initial convolutional layer, rectangular bandpass filters are learned instead of fully trainable filters. This approach allows for modeling with fewer parameters, thereby improving the network's convergence speed and accuracy. Analyzing the learned filter bank also provides valuable insights into the model's performance. The reduction in parameters, along with increased accuracy and interpretability, has led to the adoption of various parametric filters and Deep architectures across diverse speech processing applications. This paper introduces different types of parametric filters and discusses their integration into various Deep architectures. Additionally, it examines the specific applications in speech processing where these filters have proven effective.

Backgrounds: Regarding the prevalence of injuries to flexor tendon in Zone II and its known side effects after routine repair, and also with respect to the possible diameter increase of repaired region after repairing with modified Kessler core suture followed by epitenon peripheral suture which in turn could cause problems in tendon motion in Zone II. This study has been developed to determine the efficacy of Deep peripheral first suture technique (D.P.F.S.) in patients referring to 15 Khordad Hospital during the academic years of 1996 till 1998. Materials and methods: This clinical trial of semi-experimental type has been carried out on 50 patients suffering from tendon rupture of 70 digits in Zone [I. Patients were followed for 6 months. Strickland classification has been used for result analysis. Results: Among 50 patients with mean age of 30, 70% were male and the remaining 30% were female. Left hand was hurt in 70% of the cases and right hand in 30%. Third finger was the most common site of injury. Rupturing of both superficial and Deep tendons was reported in 72% of the cases. Injury to the digital nerve was seen in 34% of the patients. Conclusion: Regarding the satisfactory results obtained in our study, Deep peripheral first suture technique (D.P.F.S.) revealed to be a successful method in primary flexor tendon repair in Zone n. In the meanwhile, another clinical trial to compare this technique with other successful routine methods is strongly recommended.

Plastic hinge properties play a crucial role in predicting the nonlinear response of structural elements. The plastic hinge region of reinforced concrete normal beams has been previously studied experimentally and analytically. The main objective of this research is to evaluate the behavior of the plastic hinge region of reinforced concrete Deep beams and its comparison with normal beams through finite element simulation. To do so, ten beams contain six Deep beams, and four normal beams, under concentrated and uniformly distributed loading, are investigated. Lengths in the plastic hinge region involving curvature localization, rebar yielding, and concrete crushing zones are studied. The results indicate that the curvature localization zone is not suitable for the prediction of plastic hinge length in reinforced concrete Deep beams. Based on the results it can be stated that in simply supported normal beams the concrete crushing zone is focused on the middle span, but in simply supported Deep beams by creating a compression strut between loading place and support, the concrete crushing zone spreads along the compression trajectory. The rebar yielding zone of simply supported beams increases as the loading type is changed from the concentrated load at the middle to the uniformly distributed load.

The Damanghor gold mineralization occurrence is located in north of Bardaskan, Khorasan Razavi Province, and Taknar zone. The geology of the area consists of Precambrian green sericite schist and metarhyolite, intruded by diabase. mineralization in this area is in vein form with N50E stribe and 70NW dip and hosted by schist and metarhyolite with 300 meters length and 2 to 35 meters width. Disseminated and veinlet mineralization includes primary minerals of pyrite and chalcopyrite and secondary minerals such as covelit, malachite, azureite, hematite, goethite and limonite with quartz, sericite, and lesser clay minerals. Silicic-sericitic alteration is the most important alteration zone associated with mineralization. Based on rock samples taken from explorative trenches, gold anomalies range from 0. 3 to 12. 5 ppm, silver up to 30 ppm, copper up to 860 ppm, and zinc about 9252 ppm. Based on the evidence of host rock, the type and extent of alteration, structural control, shape and type of mineralization and primary minerals and geochemical anomalies, the occurrence of Damanghor gold mineralization is epithermal with intermediate sulfidation state that is related to hydrothremal derived from Cenozoic magmatic activities.

Detection of dispersed and blind mineral deposits is an important aim in the mineral exploration. Detailed exploratory operations such as drilled boreholes which are performed for exploration of mineral deposits in the depth caused high cost and risk. In this research, a new scenario based on spectral analysis of geochemical data has been utilized for prediction of mineralized zones in the depth without any additional cost. The variations of mineralized elements from the surface to the depth are predicted and delineated by using this approach based on surface geochemical data. This proposed approach is the state-of the-art application of two-dimensional Fourier transformation (2DFT) for geochemical image processing. This approach which is named frequency coefficient method (FCM) has been defined based on the behavior of elements in the frequency domain. In this study, the FCM shows two Pb and Zn mineralized zones at the surface and moderate depth and a non-mineralized zone at the profound depth in Chichakloo Pb–, Zn mineralization. Finally, the results of FCM have been validated and confirmed by the results of drilled boreholes and geophysical surveys.