This project presents a novel approach and a new dataset for the problem of driver drowsiness and distraction detection. Lack of an available and accurate eye dataset strongly feels in the area of eye closure detection. Therefore, a new comprehensive dataset is proposed, and a study on driver distraction of the road is provided to supply safety for the drivers. An artificial network is also designed in such a way that two goals of real-time application, including high accuracy and fastness, are considered simultaneously. The main purposes of this project are as follows: Estimation of driver head direction for distraction detection, introduce a new comprehensive dataset to detect eye closure, and also, presentation of three networks in which one of them is a Fully Designed Neural Network (FD-NN) and others use transfer learning with VGG16 and VGG19 with extra designed layers (TL-VGG). The experimental results show the high accuracy and low computational complexity of the estimations and the ability of the proposed networks on drowsiness detection.

The rapid growth of IT applications and providing more services on computer networks comes with security threats with malicious and business targets. One method to deal with network traffic analysis complexities is to analyze a summary of network data that is extracted from network connections. Netflow is a defacto standard for generating network flow data introduced by Cisco and integrated into Cisco switches and routers which produce flow records about underlying network traffic. In this paper, we use machine learning techniques to analyze Netflow data and classifying connections pertain to network attacks and do respective prevention measures after the classification. Machine learning algorithms including Naïve Bayes, SVM, and NBTree has been used to model different attacks based on network flow data. In the evaluation phase, KDDcup99 dataset used and related features to Netflow data are selected (7 features), and then, classification has been done with both original KDDcup99 features (41 features) and our selected Netflow features. Average classification accuracy for different 22 attack classes and one benign class shows that using just seven Netflow related features does not affect the accuracy obviously while the computation overhead is obviously decreased. Average detection accuracy for our selected features in different algorithms is 97% whereas, for the best case (i.e, SVM) with 41 features, the average accuracy is 99% which is not so much better than our less complex Netflow based method.

Computational circuits, including full adders, are used as an important base for the design and implementation of many applications such as adaptive filters, modulators, and fuzzy logic controllers. Having an optimal design with the aim of increasing the speed and reducing the power consumption can be the reason for the progress of industries and also improve the military power of the country. This article provides a new implementation for a 1-Bit Full-Adder Cell with 10 CMOS transistors. This design presents a higher speed and lowers power consumption compared to other standard 1-bit full adder cells. Eliminating an inverter from the critical path accounts for its high speed while reducing the number and magnitude of the cell capacitances, in addition to eliminating the short circuit power component, account for its low power consumption. The simulation results show the advantages of the proposed design. In this paper, 0.18 μm technology, temp = 27 °C, a 1.8 V power supply, and TT corner are used. The software used in this article is Cadence IC Design, which will show the proposed circuit will save 9% of energy consumption.

Signal attenuation is one of the most important problems in wireless communication systems. The message conveyed by the transmitted waveform will not be recovered correctly if this attenuation is such that the SNR in the receiver is less than a specific threshold. Channel fading which results from receiving many non-coherent reflected versions of transmitted signal in the receiver, is one of the sources of this signal degradation. Fading may result in severe changes in the strength of the received signal in short time intervals. Diversity techniques are the most powerful tools to combat degrading effects of wireless fading, by using two or more independent communication channels. Diversity techniques are mainly designed for digital communications, therefore employing them in analog systems such as FM radios is a challenging issue. In this study, spatial diversity in receiver is proposed in order to making the current VHF wireless systems smart against channel fading. Based on this idea, three different applicable methods have been proposed for traditional analog FM repeating systems which can be implemented with little changes in the current hardware system. Simulation results show the improvement in reliability and performance of the systems using these methods.

Designing an oscillator with appropriate parameters can have a significant impact on the final performance of a telecommunications system. Here, a voltage-controlled oscillator is intended for the X-band, which uses an active amplifier. An elliptical filter is used here as a frequency stabilizer. This article uses the NESG2030M04 transistor. The specific idea in this case is to optimize the transition filter as the stabilizing element of the frequency in selecting the best frequency of the desired frequency. The oscillator designed with inactive phase noise filter is obtained at  -145 dBc / Hz at 1 MHz offset frequency.  However, in order to improve the critical parameter of phase noise in the oscillator, active activation technique and elliptical filter have been used. After applying this method in the oscillating phase noise equal to -154 dBc / Hz at an offset frequency of 1 MHz.

Organizations need innovation to survive. The Internet of Things can bring innovation to the organization by making changes to managers' decisions on a variety of issues, as new decisions often lead to the use of new technologies, so this decision Managers can create new ways for their organization and company. The main issue in this research is what changes the Internet of Things makes in the field of innovation in organizations. This is implemented in a technology-based organization (municipality or police). Because such organizations are one of the large organizations that have recently connected many of their services to Internet applications, and therefore the study of the use of the Internet of Things in the process of innovation in such organizations can be useful and usable data. Offer. The data in this study were analyzed using Smart PLS software. Also, in the data analysis, descriptive statistical methods and appropriate inferential statistics were used using Excel for descriptive statistics of SPSS software version 24 to test the hypothesis. According to the results of this study, the use of the Internet of Things on corporate orientation or material innovation (innovation in the use of new technologies in the company), as well as intangible innovation (innovation in the use of human capital, knowledge of people), in a technology-based organization, it has a positive and significant effect.

Recently, the use of information and communication technology have very important role in smartening cities and the police. With the development of the internet of things and the smart city, the ability to easily access high-reliability communications and provide a platform for fast coverage and connectivity is becoming a vital need for the next generation of wireless telecommunications systems. UAVs play an important role in providing timely and necessary wireless communication services for public safety applications, smart city, smart police and to recover services immediately after disasters. Collaboration between UAVs and communications infrastructure is able to support public safety requirements such as immediate analysis, immediate monitoring and advanced decision-making to help smart cities meet their public safety needs. Therefore, the deployment of UAV-based wireless communications can save individuals and ecosystems in an efficient way by helping public safety organizations deal with threats and disaster management. In this paper, the types of UAVs and their characteristics have been investigated, then, the benefits of their use for public safety and smart police applications are outlined. In the following, the various applications of UAVs in different aspects of smart cities, smart police, military and disaster management and next-generation cellular telecommunication networks have been discussed. The benefits, limitations, telecommunication and security challenges of these systems have also been addressed.