Background and Aim: Deep fakes or complex computer forgeries are one of the recent achievements of human society. This phenomenon allows people to create unrealistic videos, images and sounds with a variety of purposes and functions. Some of these functions are part of the social life of society. But many abuses are also conceivable. This raises challenges regarding the type of criminal response to it. Method: The present study was conducted by descriptive and analytical methods. Findings and Results: Human rights treaties set out the criteria that governments should consider in taking any action to protect human rights and freedoms. These criteria should also be considered for Deep fakes. However, the new construction technology as well as its various functions have made the exact boundaries between criminal and legal instances unclear. This study concludes that, firstly, in the Iranian legal system, there is no specific criminalization for such forgeries, and secondly, despite the fact that many of its examples are covered by some crimes, the Iranian penal system with The specific facts and requirements of this phenomenon are inconsistent.

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.

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.

Artificial intelligence (AI) is simulating human brain by computer systems. It combines computer science and datasets, to enable problem-solving and decision-making capabilities of the human mind. During the last decade, this technology has attracted lots of attention because it has been rapidly developed and applied to so many areas of human activities. It could respond to so many of daily questions efficiently, and also, perform tasks and duties that would require human intelligence, such as learning, reasoning, perception and problem-solving. AI technology can process large amount of data and these days is being used across different businesses and industries.  Some of the advantages of AI are: ability to analyze data accurately and rapidly, promoting efficiency and productivity, save time, advise in different activities, such as management, finance, banking, marketing, health, transportation, and security affairs. Of course AI has some disadvantages, such as: job displacements, ethical concerns about people privacy, biased programming, accelerated hacking, terrorism, destroying cyber security, misuse of personal data and biometric information.     In order to avoid the negative consequences of artificial intelligence, AI should be developed and used in an ethical manner. Different countries and global institutions should try to combine its scientific capacity with ethical norms and principles effectively.

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.

This article presents new methods and tools used in the field of text analysis to identify fake news in the media. The problem with the research is that, as a rule, to identify fakes, a training dataset is required, on which thematic fakes were tested. This is not always feasible and requires additional resources. To solve this problem, a comprehensive research methodology has been developed that covers most detection tools, even in the absence of an established database containing reliable and fake news. The study includes a combination of various algorithms combined into a single analytical structure, presented in the work in the form of pseudocode. The authors introduce the concept of an "emotional fake model" similar to individual emotions included in a broader emotional spectrum. The essence of the model is to evaluate fakes based on the structure of definitions of emotions formed in fakes, which differ from the original signals due to different weight coefficients. The innovation involves a two—stage identification of fakes - initially clusters of messages from the text corpus are identified, and then, based on text analysis tools, their linguistic features and emotional differences are revealed (based on a set of emotions POMS). In the context of creating fake news using neural networks, emotional coloring plays a crucial role, providing a permanent foundation that can serve as a cornerstone for identification.

Single Cell Peotein (SCP) refers to the dried microbial cells or total protein extracted from pure microbial cell culture which can be used as food supplement to humans or animals. The choice of substrates that are normally abundant and in proximity to the production plant has determined the design and strategy of SCP processes. The aim of this study was the optimization of SCP production in pilot plant scale. So the continuous cultivation of Methylobacteriuum sp (strain 69) was carried on Minimal salt medium (MSB) with methanol as sole canbone and energy source.In continuous fermentation in a Deep jet fermenter of 1000L capacity, with a workingvolume of 600 liters, production of 25 g/L of dryied biomass was observed and the cell yield based on substrate was 0.4 g/g. The stoichiometry for the conversion of methanol into cell biomass was. The total protein contenet of the product was uo to 74% and because of high content of essential amino acids it can be a suitable replacement for animal feed.