Journal of Electrical and Computer Engineering Innovations
Volume:10 Issue: 1, Winter-Spring 2022

In an energy harvesting cognitive radio network, both energy efficiency and spectrum efficiency can be improved, simultaneously. In this paper, we consider an energy harvesting-based multi-antenna cognitive radio network to execute cooperative spectrum sensing, data transmission and RF energy harvesting by secondary transmitter from PU’ signal and the ambient noise, simultaneously. In his paper, two novel models called Joint Power allocation and Energy Harvesting by Time switching and Antennas splitting (JPEHTA) and Joint Power allocation and Continuous Energy Harvesting (JPCEH) are proposed. We formulate the joint optimization problems of the sensing time, detection threshold, energy harvesting time, number of cooperative antennas for sensing and energy harvesting as well as power allocation for each antenna in both proposed models. The aim is for enhancing both the spectral and the energy efficiencies under constraints on the probabilities of global detection and false alarm, energy harvesting and transmission power budget. Then, the considered multi-variable problem is solved by using two convex-based iterative proposed algorithms having less computational complexity compared to baseline approaches to achieve the optimal parameters and goals of the problem. The results present insights about the impact of the sensing time, detection threshold, power allocation and the number of antennas on the energy and spectrum efficiencies of cognitive radio network with an energy harvesting capability. Simulation results shown that the proposed schemes outperform the structures that have not optimized all the parameters considered in this paper, jointly or schemes in which single-antenna SU are participated in spectrum sensing, energy harvesting and data transmitting.

In recent years, linear generators have been broadly utilized to harness wave motion energy. There are various types of linear generators with different magnetic and geometric structures. Among these generators, linear permanent magnet synchronous generator provides a higher energy density than other generators. Due to the simplicity of the structure and the low cost of producing a flat double-sided structure, this type of structure is investigated in this paper. The purpose of the paper can be divided into two main categories: first, modeling of the flat double-sided linear permanent magnet synchronous generator by using magnetic equivalent circuit (MEC) method and second, deriving the generator electrical equations which are used in analysis and design process. The behavior of the linear permanent magnet synchronous generator is studied and the induced voltages are calculated. The no-load and loaded conditions of the generator with different loads are investigated and the voltage and the current of the load are obtained. In order to confirm the results, finite element method (FEM) is employed. The designed linear generator is simulated by FEM. Comparing the results obtained by MEC and FEM show good agreements between two methods, validating the presented modelling method.

Applications and systems software that are running constantly become obsolete due to the accumulation of error conditions or the depletion of resources like physical memory or performance degradation. In this regard, software rejuvenation has been proposed to deal with such a phenomenon and prevent software failure in the future. This paper proposes a multiple objective of software rejuvenation models with several policies. The purpose is to identify the right rejuvenation policy in practical situations. We model software system with four policies using the Markov process. These policies are: (a) Software system without rejuvenation; (b) Software system with partial rejuvenation; (c) Software system with partial and full rejuvenation; and (d) Software system with four different types of rejuvenation. In the models and each policy, we consider assigning the level of performance on which the availability and operating costs are calculated. To evaluate the models with the four policies, many numerical experiments were performed. For each policy, we evaluated and compared three objectives, namely performance, availability and operating costs. The experimental results states that for Software System with the policy of four different type of rejuvenation has about 18 and 16 percent improvement in performance and availability, respectively, compared with those other policies. Moreover, the operating cost of the software system with partial rejuvenation policy is lower and more efficient than other policies. According to the calculated objectives and the results of the policies, it can be concluded that in systems with lower operational costs, the most appropriate policy is the software system with four different types of rejuvenation because this policy bring the maximum possible value for the performance and availability.

The Hemispherical Resonator Gyroscope (HRG) has been a valuable choice for the aerospace industry due to its low noise, good performance, and long lifetime. Its main part consists of a hemispherical shell resonator (HSR). Recently, with the idea of using MEMS technology and using materials such as Pyrex in the construction of HSR, a significant reduction in the size, weight, and power consumption of this gyroscope along with the special gyroscopic characteristics of HRG, Today, the Micro-HRG has been introduced as a sensor in the strategic class. Micro-HSR can be implemented in three ways: micromachining, blowtorching, and glass blowing. In this paper, after a brief introduction and comparison of possible approaches to make an HSR, the glass blowing method is selected and the sub-processes of this method are introduced and the results of its implementation are presented. The proposed sensor is made by performing the glass blowing method, with a radius of 1.536 mm, a middle base radius of 252 µm, and a shell height of 355 µm. Also, the most important fabrication parameters for achieving the desired geometrical shell were as follows: The appropriate initial thickness of Pyrex is 200 µm and the depth of the cavity under the silicon layer is 532 µm. The bonding process to create a stable connection between Si and Pyrex must be performed at a voltage of 800 V at a temperature of 550 °C for the 30s. And the blowing process with a heating rate of 4 °C/s and a cooling rate of 9.5 °C/s has been evaluated as a suitable thermal profile. By optimally controlling the temperature process in the blowing sub-process, the crystallization phenomenon is prevented, which will lead to the improvement of the HSR quality factor. Achieving the technology of making this hemispherical glass shell in sub-millimeter dimensions, which plays the role of the resonator in an HRG, due to the superior features of this gyroscope such as low noise, good performance, and long lifetime and its application in strategic industries, like navigation and smart weapons, it is of particular importance.

Thermal problem is one of the main challenges in 3D on-chip networks. Inappropriate traffic distribution, poor heat dissipation, cooling restriction for layers away from the chip heatsink are the main reasons for this problem. This paper proposes a new intelligent routing algorithm called (Int-TAR) to solve these problems. Int-TAR applies a routing for managing the heat in 3D on-chip networks dynamically. The main idea behind Int-TAR is to save the past states of the system and, according to these states, predict the future behavior of the network and perform routing dynamically. It is done by the threshold of routers dynamically based on the current status of the routers. The simulation results show that Int-TAR decreases the temperature of the network by 13% and improves performance efficiently. The proposed idea shows the better benchmark for the thermal problem in 3D on-chip network. Also, the higher memory for storing the past state of the network can make accurate and the further performance for the network.

The Ant-Miner algorithm works based on Ant Colony Optimization as a tool for data analysis , and is used to explore classified laws from a set of data. In the current study, two new methods have been proposed for the purpose of optimizing this algorithm. The first method adopted logical negation operation on the records of the produced laws, while the second employed a new Pheromone Update strategy called “Generalized exacerbation of quality conflict”. The two proposed methods were executed in Visual studio C#.Net , and 8 public datasets were applied in the test. Each one of these datasets was executed 10 times both in an independent way and combined with others, and the average results were recorded. In this study, we have proposed two approaches for the earlier method. Using the first method in the construction of rule records, idioms that include the rules can be made in the form of . Compared to the idioms of the early algorithm, these idioms are more compatible while constructing rules with high coverage. The advantage of this generalization is the reduction of the produced rules, which results in greater understandability of the output. During the process of pheromone update in the ordinary ACO algorithms, the amount of the sprayed pheromone is a function of the quality of rules. The objective of the second method is to strengthen the conflict between not-found, weak, good, and superior solutions. This method is a new strategy of pheromone update where ants with high-quality solutions are motivated through increasing the amount of pheromone sprayed on the trail that they have found; conversely, the ants that find weaker solutions are punished through eliminating pheromone from their trails. The optimization of the initial algorithm using the two proposed methods produces a smaller number of rules, but increases the number of construction diagrams and prevents the production of low-quality rules. The results of tests performed on the dataset indicated the enhancement of algorithm efficiency in idioms of fewer tests, increased prediction accuracy of laws, and improved comprehensibility of the produced laws using the proposed methods.

Louvain is a time-consuming community detection algorithm especially in large-scale networks. Using Graphic Processing Unit (GPU) in order to calculate modularity sigma, which is a major processing section in Louvain algorithm, can reduce algorithm execution time and make it practical for large-scale networks. The proposed algorithm Dynamic CUDA Louvain Method (DCLM) blocks hardware threads dynamically on cores inside GPU. By considering the properties of GPU, this algorithm allocates the maximal number of processing cores to each Stream Multi-Processor (SM) as number of threads in a block.  If the number of nodes in the graph is smaller than all physical cores on GPU, number of threads per block Is equal to the ratio number of graph nodes over the number of SMs. The implementation results demonstrated that the proposed algorithm is able to decrease the run time by 15% in comparison with the best past method in the large-scale graph. We have introduced DCLM algorithm based on GPU that accelerates Louvain community detection algorithm. Dynamic allocation of threads to each block has a significant effect on the reduction of algorithm execution time. However, incrementing the number of threads per block alone does not result to acceleration the speed of calculations.

Due to the increased sensitive loads, improving power quality in distribution grids by custom power tools is one of the important fields of electrical engineering. This paper proposes a new kind of three-phase three-wire dynamic voltage restorer (without including storage sources or DC link) and also its control method.

The proposed structure includes an AC/AC converter, low-pass filters at the input and output sides, and three-phase injection transformers. The control system is based on the combination of feedback and feedforward control that its advantages are high speed, good response quality, and very simple implementation. To overcome the harmonics raised from AC/AC converter switching on the main line, a SOGI-PLL has been used. Also, SOGI-PLL operates independently on each phase so that the asymmetric voltage variations can be identified.

The proposed control method is capable to compensate the power quality problems such as voltage sag, swell, and harmonics in balanced and unbalanced conditions. The detailed modelling and design of the proposed controller are verified through computer simulations and experimental results under different operating conditions. Simulation and experimental results show that the proposed control strategy can compensate the power quality events as close as possible to the desired values under different operation modes.

In this paper, a three-phase three-wire dynamic voltage restorer (DVR) was assessed using direct AC/AC converters without a supply source and DC link. A control system based on combined feedback and feedforward control (CFBFFC) and SOGI-PLL has been proposed for the DVR. The simulation results on a three-phase 20kV system as well as the experimental results obtained from a single-phase 220V system verified the performance of the DVR and the control system. It was shown that this structure can compensate for 0.5pu voltage sag, above 1pu voltage swell, and all kinds of harmonic faults.

In order to compensate the nonlinearity, several linearization approaches such as feedback, feed-forward, and predistortion have been proposed. Among these linearization methods, the analog predistortion (APD) method is very suitable for the power amplifier and TWTA linearization, because it has a good compromise between complexity, linearity improvement and bandwidth. On the other hand, analog predistortion circuit can be added to existing amplifiers as a separate circuit. Many of the reported linearizer circuits are capable of linearizing power amplifiers with high gain and phase variations. However, these circuits are complex and bulky due to the use of distortion producer, phase shifter, adjustable attenuator, combiner/divider, and control unit. The objective of this paper is increasing the dynamic range of the predistorter by a simple proposed circuit. Hence, linearization capability of the linearizer is boosted. A new analog predistortion linearizer based on a coupler and a Schottky diode is presented. The proposed structure satisfies linearization requirements of the solid-state power amplifiers (SSPAs) and traveling wave tube amplifiers (TWTAs). Using a parallel combination of two Schottky diodes along with transmission line in port 2 and 3 of the coupler, the dynamic range of reflection coefficient of each port is increased compared to using a single diode in each branch. By increasing the range of reflection signal, the linearization capability has been increased to linearize power amplifiers and TWTAs. The AM/AM and AM/PM of the linearizer is controlled by changing the bias voltage of power supply. The simulation results show that about 30° phase shift and 5 dB gain expansion can be compensated for power amplifiers and TWTAs. Because of utilizing two diodes, the linearization capability of the new linearizer is augmented compared to the conventional linearizer. A novel analog predistortion circuit based on the hybrid coupler and Schottky diodes is presented. The suggested topology increases the dynamic range of reflected power from each port. Using the proposed idea, AM/AM and AM/PM characteristics are expanded such that this characteristic can linearize the power amplifier with high linearity.

Reliable data transmission and congestion control are considered as the transport layer primary functions in Wireless Sensor Networks (WSNs). WSNs are a specific category of wireless ad-hoc networks where their performance is highly affected by their characteristics and limitations. These limitations necessitate an effective data transport control in WSNs which considers quality of service (QoS), energy efficiency, and congestion control.

Congestion affects normal data transmission and ends in packet loss. Furthermore, wireless channels introduce packet loss because of high bit-error rate which wastes energy and affects reliability. The major problems regarding transport protocols in WSNs are congestion and reliability where the latter is classified and reviewed in the current paper.

In this paper, reliable data transport protocols are classified as the traffic direction, the parameter the reliability focuses on, and loss detection, notification, and recovery. Traffic direction-based reliable data transport protocols can be upstream, downstream or bidirectional, however, the parameter-based ones can be packet-based, event-based or destination-based, the loss detection and notification-based ones can be ACK-based, NACK-based, ACK and NACK-based or SACK-based, and the loss recovery-based reliable data transport protocols can be E-2-E or H-by-H. Thereafter, a comprehensive review of different reliable data transport protocols in wireless sensor networks is presented. Also, different performance metrics are used to compare these schemes.

In this paper, reliable data transport protocols in WSNs are classified, reviewed and compared using different performance metrics. Finally, the current work attempts to provide specific directives to design and develop novel reliable data transport protocols in wireless sensor networks.

Robot manipulator with flexible-joints is very complex nonlinear system whose control is one of the most challenging issues in the control word. Therefore, the design of voltage-based controller in addition, using of order reduction methods can reduce the complexity of the control law in such systems. This paper proposes a voltage controller for flexible-joint robot manipulators based on singular perturbation method. The presented control approach has all three advantages of the singular perturbation method for model order reduction, the proper structure of Port-Hamiltonian systems, and voltage control strategy (VCS). In this approach, the robot manipulator model is divided into three sub-systems, slow, medium and fast sub-systems. Each of the sub-systems is controlled using separate controller. In addition, the stability of these sub-systems and ultimately the whole system are proved. Unlike other related works, in this work the tracking error system is considered from the beginning, and by singular perturbation method, a controller is designed to stabilize the tracking system. Moreover, in the suggested voltage-based controller unlike torque control strategy, the electrical model of actuators is used. The main advantages of proposed approach are simple structure, using only velocity of motors, the position of the joints as a control signal and considering the electrical model of the actuators. So, practical implementation of this controller will be with much less effort, compared to the methods like feedback linearization or other controllers in related works. Moreover, using the Lyapunov-based method, the ultimate bounded stability of the closed loop system is proved. Then, some simulations are provided for tracking, regulation, robustness and response speed purposes. Since, the controllers for every sub-system are designed separately, also, the control signal parameters such as joints position, motors velocity, and motors current can be simply measured, therefore, the structure of designed controller is very simple and practically implementable. As the simulation results confirm, the performance of this controller is appropriate, even when external disturbances are present or the frequency of reference signal increases. At last, by comparison and analysis of the simulation results between the presented approach and a related work, the suitable tracking performance of the suggested controller is shown.

Substitution-box (S-Box) is one of the essential components creating confusion and nonlinear properties in cryptography. To strengthen a cipher against various attacks, including side channel attacks, these boxes need to have numerous security properties. In this paper, a novel S-Box construction method is introduced aimed at improving the resistance of S-Boxes against power analysis attacks. In the preprocessing phase of this approach, a suitable initial S-Box with some basic security properties was generated by adopting a fast algorithm. Then, in the main stage, using the initial S-Box, we generate new S-Boxes which not only have the properties of the initial S-Box but also have significantly improved under another set of security properties. To do this, new S-Boxes were generated using a genetic algorithm on a particular subset of the linear combination set of coordinate functions of the initial S-Box. The performed experiments demonstrated that the values of all security properties of these new S-Boxes, especially the measures of transparency order, signal-to-noise ratio, confusion coefficient, bijection property, fixed point, and opposite fixed points, have been substantially improved. For example, our experiments indicate that 70, 220, 2071, 43, and 406 S-Boxes are found better than the initial S-Box, respectively, in the dimensions of 4×4 through 8×8 In this paper, a new S-Box construction method is introduced where the properties related to side channel attacks are improved, without destroying other security features. Besides, some results obtained from generated S-Boxes in the dimensions of 4×4 through 8×8 demonstrated that the generated S-Boxes are not only improved relative to the initial S-Box, but also in certain cases, considerably better than some well-known S-Boxes.

Today, replacing gasoline-powered vehicles with electric vehicles (EVs) and connecting them to an electric power source have made the optimal usage of energy-saving resources. Therefore, wireless Power Transfer (WPT) outstands as an alternative technology to improve the user perception about the charging process of the EVs. Superconducting coils (SCs) with high-temperature have an applied feature in decreasing losses of wireless power transmission (WPT). The Magnetic force has effects of overall deformation modes between two current carrier superconducting coils, i.e. axial extension, torsion, and bending. Coil misalignment is a fundamental problem and its impact on wireless power transmission efficiency is very complex. The analysis of a magnetic force which is presented in this paper are beneficially for the design and application of the WPT systems. Here, a fast analytical solution is presented to obtain the magnetic force between the transmitter and receiver helical superconducting coils in different positions. In this paper, a new method applied to solve the numerically magnetic force solutions in different superconducting coils mismatch states for WPT. Finally, for improvement of efficiency, the WPT system has been designed on the basis of mutual inductance changes which receiving helical coil was moved inside the transmitting helical coil. Hence, the magnetic force calculation of movable YBCO superconducting helical coils inside each other is presented. These models have been compared with the FEM. Results show that the presented equations are reliable as well. According to the comparing the analysis and FEM data, the obtained results indicated the errors with less than 0.0064%. Also, results show an excellent agreement with respect to the finite element method. In this paper, the numerical solutions of magnetic force in different superconducting coils mismatch states were solved by a new method. The magnetic force analysis basics introduced in this paper are useful to develop and apply for wireless power transmission system. The simulation results show that only by applying some constraints, the efficiency of the transmitted wireless power will be optimized. Then, analytical models have been presented which make it possible to calculate the axial force which was exerted between two axially Helical magnetized and two thin coils in air. Also, the analytical stiffness calculation applied between these distributions of magnetic source has been presented. These models have been compared with the FEM to show an appropriate consistency.

Visual attention is a high order cognitive process of human brain which defines where a human observer attends. Dynamic computational visual attention models are modeled on the behavior of the human brain and can predict what areas a human will pay attention to when viewing a scene such as a video. However, several types of computational models have been proposed to provide a better understanding of saliency maps in static and dynamic environments, most of these models are used for specific scenes. In this paper, we propose a model that can generate saliency maps in a variety of dynamic environments with complex scenes. We used a deep learner as a mediating network to combine basic saliency maps with appropriate weighting. Each of these basic saliency maps covers an important feature of human visual attention, and ultimately the final saliency map is very similar to human visual behavior. The proposed model is run on two datasets and the generated saliency maps are evaluated by different criteria such as ROC, CC, NSS, SIM and KLdiv. The results show that the proposed model has a good performance compared to other similar models. The proposed model consists of three main parts, including basic saliency maps, gating network, and combinator. This model was implemented on the ETMD dataset and the resulting saliency maps (visual attention areas) were compared with some other models in this field by evaluation criteria and their results were evaluated. The results obtained from the proposed model are acceptable and based on the accepted evaluation criteria in this area, it performs better than similar models.

Determining effective factors in cloud computing adoption on employees of Noor credit institution in South Khorasan province, Iran, is the purpose of the present study. A practical oriented method is applied regarding the research objective and a descriptive-survey method is used for collecting field data. Employees of Noor credit institution of South Khorasan province (50 people) are selected as the research sample. Accurate questionnaires are analyzed. Two researcher-made questionnaires are conducted as research tools. These questionnaires consist of effective factors in cloud computing adoption (12 factors including 47 items) and cloud computing adoption intention (3 items). The reliability of the research is evaluated using Cronbach's alpha coefficient which is obtained α=0.54% for the questionnaire of effective factors in cloud computing adoption and has various values for the questionnaire of the cloud computing adoption intention. Also, the descriptive statistics approach is used to define variables, and confirmatory factor analysis and path analysis are applied in the inferential section. Structural equation modeling using Smart-PLS software is used to determine the effective factors in cloud computing adoption All 12 determined factors in cloud computing adoption are considered as dependent variables and cloud computing adoption intention is considered as an independent variable. 12 effective factors in cloud computing adoption on Noor credit institution of South Khorasan in Iran are determined and examined. It can be concluded that all factors (except the support of the top manager) have a positive and significant effect on cloud computing adoption intention, nonetheless, the value of statistic t for path analysis of the support of the top manager on cloud computing adoption intention is less than 1.96. This shows that the support of the top manager does not have a significant effect on cloud computing adoption intention.

The principal aim of this paper is to show an independent vector control of two five-phase Linear Induction Motors (LIMs) that are supplied from a single VSI. The LIMs are running at the same speed but with different load conditions. This concept can be especially beneficial in long trains with distributed power. To achieve excellent control characteristics and to reduce the undesirable tension forces between the train mechanical couplers, Fuzzy Logic Controllers (FLCs) have been utilized. As a result, the fault occurrence of the train control systems decreases, and the system reliability increases. The results prove the electrical independence in control of a five-phase two-LIM drive supplied with a single VSI. Furthermore, in the presence of the train mechanical couplers and connections, the application of FLC offers excellent control characteristics and reduces the undesirable tension forces. Furthermore, to obtain a more worthwhile validation of the theoretical results, an experimental set up has been constructed and results have also been presented. According to the results, the undesirable tension forces imposed on train couplers are reduced. Consequently, it leads to higher system efficiency, lower deterioration of the train couplers and connections, greater system reliability, and higher passenger safety and comfort.

Autism is the most well-known disease that occurs in any age people. There is an increasing concern in appealing machine learning techniques to diagnose these incurable conditions. But, the poor quality of most datasets contains the production of efficient models for the forecast of autism. The lack of suitable pre-processing methods outlines inaccurate and unstable results. For diagnosing the disease, the techniques handled to improve the classification performance yielded better results, and other computerized technologies were applied. An effective and high performance model was introduced to address pre-processing problems such as missing values and outliers. Several based classifiers applied on a well-known autism data set in the classification stage. Among many alternatives, we remarked that combine replacement with the mean and improvement selection with Random Forest and Decision Tree technologies provide our obtained highest results. The best-obtained accuracy, precision, recall, and F-Measure values of the MVO-Autism suggested model were the same, and equal 100% outperforms their counterparts. The obtained results reveal that the suggested model can increase classification performance in terms of evaluation metrics. The results are evidence that the MVO-Autism model outperforms its counterparts. The reason is that this model overcomes both problems.

Switches play an important role in controlling the signal flow in telecommunication systems. The traveling wave switch structure is introduced based on active transmission lines. By applying the gate voltage (Vg), the transfer of signal through the drain transmission line is controlled. By increasing operating frequency, lumped model is unreliable and semi and fully distributed modeling should be applied for the analysis of these elements. Traveling wave switches can be analyzed based on the lossy transmission line model, in linear and non-linear modes in the time and frequency domains. The study of transient behavior and time domain response of switch is very important. Switching and transient from on to off state and vice versa affect the performance of telecommunication systems.In the proposed method, the switch is modeled as the lossy transmission line that the primary elements of this model change with time based on the control voltage applied to the gate and are considered as variable with time. The structure is discretized in the space and time domains with ∆z and ∆t steps. The Finite-difference time-domain (FDTD) method is utilized to study the transient response of switches. By using the leap-frog algorithm, the new voltages and currents of the transmission line are calculated based on the values of adjacent spatial and temporal steps. The transient response of the switch is analyzed in transition from off to on states and vice versa, for the 800µm switch at 60GHz, based on the parameters of the passive transmission line and nonlinear Curtice2 FET model. For transient analysis of the structure, the time-variant lossy transmission line model was used that its elements changed based on the applied control voltage. The results of FDTD method were investigated with the transient analysis of commercial software that show good agreement with each other and validated the proposed method.

Distributed generation (DG) sources are modeled using an ideal DC voltage source connected to the microgrid via voltage source converters (VSCs). Model predictive control presents a distinct method for energy processing.  In this method, the electric power converter is considered a power amplifier with a discrete and nonlinear structure. Therefore, unlike linear control methods, the discrete and nonlinear nature of the converter is considered in this method. In this paper, the distributed model predictive controller was selected from among different methods of load allocation among DG sources due to its more advantages compared to the linear quadratic regulator (LQR) controller. It has been Proposed that we could obtain better results in predictive control, utilizing similarity transform in the state matrix and its modification. In this research, all the simulations have been performed in the MATLABSimpower environment of MATLAB software. Moreover, to demonstrate the superior performance of the model predictive controller compared to the LQR controller, both performance modes of the microgrid, namely the grid-connected and islanding modes, have been considered.

Images and videos play significant roles in our lives. Moreover, there are considerable improvements in computer data collection systems; therefore, anyone is able to acquire much many images or videos, whereas he/she cannot process them manually. Images and videos became attractive since depicting and digital processing of these kinds of data became possible. Since indeterminacy surrounded the world, including images and videos of that; imprecision is needed to interpret this world.

Neutosophic logic, which is from philosophy and is also included of logic, set theory and probability/statistics, is able to depict this imprecision. As a result, advanced image processing can be defined by translation of image processing into neutrosophic domain. In this paper, first of all, a general introduction about image/video processing (segmentation, noise reduction and image retrieval) and uncertainty is stated. Then, definitions of fuzzy sets, intuitionistic fuzzy sets and neutrosophic sets are expressed. In the following, applications of neutrosophic domain in image and video processing such as segmentation, noise reduction and image retrieval are introduced.

Although, neutrosophic is used for image restoration and segmentation; input images are usually medical images or gray level natural images. The remarkable point is that there are few researches that focuse on image restoration or segmentation using neutrosophic and consider color images. Therefore, color image restoration and segmentation in neutrosophic environment is novel to be done.

Neutrosophic usage in image retrieval brings out an improvement in average recall and precision measure compared to earlier methods. Considering different textures and shapes can extend usages of neutrosophic space in image retrieval applications.