Majlesi Journal of Telecommunication Devices
Volume:8 Issue: 3, Sep 2019

In this research, the design and survey of the satellite (Kensett) has been addressed. The main mission is to study the atmosphere and eventually land on the air bag, and new designs and ideas were designed. The motivation for this design is to be native and affordable in comparison with foreign ones.

In the course of the amazing growth of science and technology over the last half-century, using technology in designing new methods of teaching movement skills has improved the performance of champions and led to setting new records. The present study aims to produce and assess the photo finish devices and compare the results to those of the manual measurements in the track and field tests. In order to do so, the photo finish device was designed and constructed as a portal. Afterward, the results of athletes’ performances in a track and field test were recorded simultaneously by both a photo finish device and a handheld stopwatch. Dependent T-test was used so as to compare the results of both measurement methods. Results showed, that there is a statistically significant relationship between the average of obtained records from time measurement via photo finish devices and handheld stopwatch (t= -11/99, P= 0.0001).

Many complex natural and social structures can be considered as networks. Internet sites, social networks, organizational communications, family connections, electronic mails, phone calls, and financial transactions are just a few examples of these networks. Nowadays, network analysis is one of the most popular and widely used research branches in the world. One of the most commonly used topics in network analysis is the identification of organizations in the network. In this research, we present the detection of communities in static social networks using the genetic algorithm and its improvement with the label propagation algorithm known as Genetic Algorithm- Label Propagation. The genetic algorithm explores the search space well and converges to the best answer. This algorithm is scalable and our results show that our proposed algorithm performs faster and better than other algorithms.

Content-based image retrieval (CBIR) system plays an important role in retrieving desired images from a large database of images. These programs in all areas, including hospitals, regulatory applications (surveillance), architecture, journalism and many other items found in the role. In initial research text-based image retrieval was performed, but with the advent of great challenges in text-based retrieval (eg spelling errors), content-based image retrieval has been introduced by researchers, which is by far the most effective method for image retrieval. Content-based image retrieval system uses features such as color, shape and texture. To extract the tissue properties local binary patterns and edge filtering methods are of particular popularity among researchers. A review of the methods presented so far shows that despite the quality of the descriptors and categories and retrieval methods, none of these methods can meet the needs and challenges of the present, so to improve the accuracy of image retrieval, in this study, a method introduced. To extract feature from the images, five color histogram descriptors, color moment, edge histogram, gradient oriented histogram and MRELBP were used. To classify the attributes extracted by the descriptors, three categories of support vector machine and k nearest neighbour and random forest are used. In the method, the features extracted by the five descriptors are combined and after classifying and identifying the test image class, using the Kmeans cluster, the closest images to the test image are retrieved from the identified class. Experimental results method on three databases Corel 4k, Wang and Corel 5k show We have accomplished the highest precision rate of 86% using proposed CBIR system.

Optimal utilization of frequency spectrum in wireless networks particularly in device to device communication is of significant importance owing to the growing demand. Traditional methods to optimal spectrum utilization of spectrum are not sufficiently efficient and result in loss of spectrum. Recently, application of Cognetive radio is suggested to solve this problem. Cognetive radio is a smart wireless system which is aware of the spectral traffic condition of its environment in an instantaneous way and through these spectral conditions, changes the power of transmitter and the type of modulation and it adapts to the environment. The main purpose of this paper is to investigate the problem of spectral sharing. Today, communication systems suffer from main problems including limited bandwidth, download speed increase, rate increase and saving in transmitted power. To solve such problems, new methods based on machine learning in spectrum sharing are necessary to overcome such challenges. In this work, using cellular learner automata, a method is proposed for simultaneous assigning of spectrum and resource. The aim of each pair of transmission is to transmit in an appropriate channel and power level so that it can maximize its compensation in cellular learner automata. In these scenarios, compensation is taken as the difference between operational (collective) and consumed power. The cost of the consumed power is the signal to interference noise ration. Proposed method is simulated on a LTE-A network as well as an NS2. Proposed algorithm is of rapid convergence and semi-optimal efficiency in low repetitions.

In the present paper, the effect of an integrated planning of renewable energy resources, electrical and thermal storage, electric vehicles charger strategy, and various side demand response programs on electrical and thermal load supplying cost of a residential area was investigated. In this regard, a mathematical model was presented for an optimal integrated planning of renewable energy resources, heating equipment of buildings, thermal and electrical storages, electrical vehicles with respect to demand side management. The proposed model for optimal planning has been formulated as a mixed integer linear programing model. In this model, operational constraints of distribution network were considered. In order to evaluate the performance of the proposed model, its efficiency on electrical and thermal resources of a residential area with certain number of buildings was analyzed. The simulation obtained results revealed that using thermal and electrical storages and side demand response programs as well as the presence of a high number of electric vehicles can be followed by many merits when it is controlled by an energy management system. The outmost advantage is power absorption in low-load hours and releasing it in peak hours. This advantage causes decreasing load peak for electricity network and subsequently, decreasing the cost of supplying a residential area’s electricity. It is useful for both residents and operator. As found, it can be generally stated that an optimal and integrated planning of energy resources with respect to side demand management significantly decrease energy supply costs. According to simulation results, an integrated planning of all energy resources of a residential area can decrease consumption power in peak hours, energy supply cost as well as the need of buying it from a distribution network. This is in favor of both consumers and distributor company.