نشریه مهندسی برق
سال پنجاه و چهارم شماره 1 (پیاپی 107، بهار 1403)

Various methods have been presented to evaluate trust management between users in social networks. Individual and subjective diagnosis is less considered in the evaluation of trust and often a general and general model is presented for all users. trust evaluation without considering the personal and mental characteristics of users is not effective. in the proposed method of this research, users' characteristics are calculated and their importance is determined using fuzzy rough set theory. users' characteristics are combined and aggregated by considering their importance and using Dempster Shafer theory of evidence. the sets of trust and distrust values and ambiguity are evaluated to determine the degree of trust. the final values are used to make a trust decision and create a secure connection. the level of user trust in the entire network is determined by all users. the comprehensive performance of the proposed method and RTARS, ABC, DSL-STM and AUTOMATA algorithms have been compared in four evaluation indices and in 10 independent implementations. the obtained results show the improvement of the trust decision and the creation of safe communication in social networks. the proposed algorithm has been able to correctly decide the trust of users in social networks with 92.54% accuracy. the experimental results show that the proposed method is able to infer trust more accurately than the previous methods.

In this paper, the structure of a plasmonic waveguide nanofilter based on monolayer MoS2 ring resonator is proposed and investigated. The structure performance is for a part of terahertz frequencies. Due to the low absorption and reflection of monolayer MoS2, considerable wave transmission and as a result, transparency, is provided. Filtering response caused by the proposed waveguide filter is resulted by the resonator which makes possible the coupling of the input and output nanoribbon waveguides. The structure operation has been simulated using the numerical method of finite difference time domain. The values of coupling efficiency, bandwidth at half of maximum, and quality factor, in operating wavelength of 1255 μm are respectively 0.78, 162 μm, and 7.7. The operating wavelength complies with the second resonance mode of the resonator. Also, the sensitivity of various structural indices in respect to manufacturing telorance is investigated. The proposed structure can have exnetsive application as a transparent electrode in photonic integrated circuits.

In this paper, an adaptive controller for damping inter-area oscillations based on power system stabilizer and global signals is proposed. In order to investigate the nature of inter-area oscillations, a generalized SMIB model is introduced and the mechanism of inter-area oscillations is analyzed. In order to design the proposed adaptive controller, by using dynamic data gathered from the wide area measuring system, a new index is introduced to identify effective generators in damping the inter-area oscillations. Also, in order to design the adaptive controller, after determining effective generators, the stabilizer parameters are adjusted using intelligent methods. The proposed method for selecting effective stabilizers and selecting global signals is implemented on two different systems including the two-area power system consists of six synchronous generators and a practical nation IRAN power grid. Results indicate the ability of the proposed adaptive scheme to damp inter-area oscillation.

In computing circuits, the unexpected interruption of the voltage source causes the loss of data and redoing the calculations, which reduces the speed of calculations and increases the power consumption. Consequently, today, the design of computing circuits using non-volatile elements has received much attention. In these circuits, it is easier and less expensive to implement the power-gating technique, which plays an important role in reducing leakage power. In the non-volatile circuits that have been proposed so far, a separate back-up module is used, which saves the state of the D-flip-flops on the chip at specific time intervals. However, the use of a separate backup module ultimately leads to an increase in the total power consumption, the occupied area, and a decrease in the calculation speed. In addition, the backup module requires external control signals, which increases the complexity of the system. To solve these problems, in this paper, a new non-volatile flip-flop with simultaneous data backup capability is proposed, which uses NCFET ferroelectric transistor to fundamentally advance the non-volatile computing paradigm. The proposed flip-flop for backup and recovery operation has energy at fJ level and delay at ps level.

The Stack Overflow website is one of the most popular communities used by millions of programmers. If we consider a question and its corresponding answers as a knowledge unit on the Stack Overflow website, then there are different semantic relationships between two knowledge units, which include duplicate, direct, and indirect relationships with the proposed question. Recognizing different categories of semantic relationship between knowledge units in Stack Overflow can significantly improve the effectiveness and efficiency of information search. In this study, a hybrid approach based on deep learning methods and traditional similarity criteria is presented to detect the relationship between questions. In particular, two deep network architectures are presented, the first architecture consists of a long short-term memory network as well as a cosine similarity calculation layer. The second architecture is an extension of the first architecture by adding an attention mechanism. The proposed approach was evaluated on a dataset of Java programming language contining 40000 questions. The obtained results show that in terms of F1, Recall and Precision, the proposed model performs better than the existing models. Specifically, the model proposed in this article has a 17.3% improvement in terms of F1 measure compared to the best current model. Also, the results of the experiments show that using the pre-trained word embedding model significantly improves the performance of the presented models.

Diagnosing the type of cancer, which is called the subtype, is very important in determining the treatment process. This paper focuses on the diagnose of the four subtypes of the brain cancer. Disease subtype diagnosis can be modeled as a classification problem. Due to the significant progress made in bioinformatics in extracting genetic information from the human body, recently this information is widely used in the representing of patients in machine learning. In this paper, three types of genetic information including mRNA, miRNA and DNA methylation are used.It should be noted that combining different information sources in the form of multimodal data instead of using a single information source increases the accuracy of information classification. To extract more desirable features from the original genetic data, auto-encoder has been used so that the features extracted from auto-encoder are concatenated to the original genetic data.Random forest has performed well as a classifier in classifying patients based on genetic information. By extending deep methods in neural networks and their good performance, a version of deep random forest with layered structure has been proposed. The deep random forest has the advantage that has a limited number of parameters and lower computational complexity in addition to the optimal performance in information classification. In this paper, deep random forest is used to determine the subtype of a special type of brain cancer. The experiment results show the desired performance of the proposed method.

This article proposes a paper-based microfluidic chip that can non-invasively measure glucose with optical detection technique using NIR. This paper chip is disposable, portable, low-cost, lightweight, and suitable for point-of-care and cost-effective tests. This paper chip is fabricated with a kind of photoresist that is used in the publishing industry called UV curable resin. This method is chip, simple, and suitable for mass production. This paper chip is used for measuring glucose non-invasively and an interface sensor is designed with an NIR technique that can measure glucose concentration between 60 to 500 mg/dl with voltage range of 630 to 730 mV.

In the fifth generation of mobile networks (5G), managing the high traffic volume of applications and the needs of active objects in this network requires a strong, isolated, and secure platform. This is achieved by using the new concept of network slicing. DBNS (a distributed approach based on blockchain) is a method of allocating resources in terms of network slices. Unfortunately, this method faces a security issue caused by the non-observance of data transparency. A smart As a result of the allocation of resources between providers, this article utilizes the smart contract feature of the blockchain to create data transparency, as well as a secure communication platform, in the context of network slicing and among different service providers (SPs), creating a service and even reducing the delay imposed on the network. In this paper, we present a smart DBNS approach that uses smart contracts and blockchains to make interactions between SPs more secure and smart. The simulation results of the proposed method show that on average, the service delivery delay is reduced by 18% and 5%, respectively, in the two parts of the uRLLC and mMTC networks, and it promotes a new approach in the integration of these two technologies.

The important features of LED (Light Emited Diode) drivers are low current ripple on the output side, high power factor on the ac side and to extent possible avoid using electrolytic capacitors In order to solve this problem, in this paper, an integrated non-isolated LED driver consisting of three stages is proposed, which is composed of three dc-dc converters. The proposed integrated driver has only one active power switch. Therefore, the volume and complexity of the structure is reduced. Additionally, the main characteristics of the proposed driver are high power factor, low current flicker in the output and eliminating need for electrolytic capacitor. Then to show the performance of the driver based on the duty cycle variation, the proposed driver has been analyzed step by step. Semiconductors voltage stress and voltage ripple of capacitors have been calculated, and in order to simultaneously control the output current and the input power factor, a linear controller has been designed and used. The simulation and the experimental results have been presented to validate the feasibility and versatility the proposed LED driver. In the provided results, the ripple of the output current and the harmonic of the input current are within the acceptable range according to the standards, and additionally without using electrolytic capacitor, the desired output current and high input power factor have been obtained.

Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance rate.

A High-gain, fully balanced preamplifier is presented. The proposed structure advantages flipped voltage follower scheme to achieve a compact current conveyor with very low input impedance. The presented current conveyor then is used as a core element to realize a high-gain, gm-enhanced trans-conductance amplifier. The presented amplifier is suitable for application as a preamplifier. The high gain of amplifier makes it very suitable to be configured in a feedback form to deliver a high-precision predefined or programmable amplification gain. The proposed structure draws a very low power of 150nW from a 0.6V supply voltage. The Spectre Post-layout simulations with TSMC 180nm CMOS technology have been performed. The proposed amplifier exhibits an open-loop DC gain of 141.5dB and 3-dB frequency bandwidth of 2.4kHz at 60dB closed-loop configuration. The load capacitance is set to be 5pF. The proposed structure also delivers high CMRR and PSRR values of 148.3dB and 153.7dB, respectively.

We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio networks (CRNs) based on simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect channel state information (CSI) on the CBS-PU link.