اتوماتای سلولی نقاط کوانتومی (QCA) با بهره‌گیری از پیشرفت‌های فن‌آوری نانو، بسیاری از محدودیت‌هایی که نیمه‌رسانا اکسید فلزی مکمل (CMOS) با آن روبرو شده بود را برطرف کرده است. مشخصه‌های نامطلوب همانند جریان‌های نشتی زیاد، طراحی‌های CMOS را در ابعاد نانو محدود می‌سازد. ایده‌ی طراحی سیستم‌های چند ارزشی منطقی (MVL) به جای دودویی استاندارد، برای بسیاری از طراحان جذاب شده است. کاربرد MVL در طراحی مدارهای دیجیتال، مزایای بسیاری نسبت به روش‌های مرسوم دارد. فلیپ فلاپ D یک مدار ترتیبی عمده در هر ثباتی است. در این مقاله، یک فلاپ فلاپ D چهار ارزشی مبتنی بر اتوماتای سلولی نقاط کوانتومی چهارچهاری (QQCA) معرفی شده و ساختار مدل چهارچهاری پیشنهادی شرح داده شده است. همچنین ما با استفاده از فلیپ فلاپ D چهارچهاری ارائه شده، یک ثبات 4 کوبیتی پیشنهاد کرده‌ایم. هر دو مدار توسط QCASim (نسخه چهارچهاری)، شبیه‌سازی و ارزیابی شده‌اند. QCASim می‌تواند نتیجه‌ی شبیه‌سازی را در قالب شکل موج و جدول صحت نمایش دهد. کار ما با سایر آثار منتشر شده مورد مقایسه قرار گرفته است. نتایج شبیه‌سازی نشان می‌دهد که مدار پیشنهادی از نظر تاخیر و مصرف انرژی کارآمد است. تفاصيل المقالة

شبکه‌های مخابراتی، مسلماً یکی از سنگ بناهای جامعه اطلاعاتی مدرن و یکی از محرک‌های اصلی اقتصاد هستند و زمینه‌ای را فراهم می‌کنند که بسیاری از فعالیت‌های روزمره بر آن تکیه نماید. همچنین فناوری های جدید مانند اینترنت اشیا، هوش مصنوعی، خودروهای خودران، G۵ و ... به پتانسیل کامل خود نمی‌رسند مگر این که یک شبکه ارتباطی زیربنایی نیازهای آن‌ها را برآورده کند که برای زیرساخت و خدمات آن‌ها امنیت موضوعی بسیار حیاتی است. از سوی دیگر پیشرفت فناوری محاسبات کوانتومی در سال‌های اخیر و ساخت رایانه‌های کوانتومی با توان پردازش بسیار بالا و حل مسائل بسیار پیچیده با سرعتی بیشتر از رایانه‌های فعلی باعث شده که امنیت سایبری، امنیت رایانه‌ها و وسایل ارتباطی به یک مسئله حیاتی و مورد توجه دولت‌ها تبدیل گردد. با این ‌حال با پیشرفت فناوری کوانتومی می‌توان با استفاده از روش‌های کوانتومی برای توزیع کلیدها از این تهدیدات جلوگیری نمود، لذا رمزنگاری کوانتومی به‌عنوان جایگزین روش‌های کلاسیک در مقابل رایانه‌های کوانتومی و حملات سایبری در نظر گرفته شده است. توزیع کلید کوانتومی معروف‌ترین زیرشاخه رمزنگاری کوانتومی است که امروزه نمونه‌های تجاری آن نیز در بازار موجود است. استفاده از رمزنگاری کوانتومی در زیرساخت شبکه‌های کلاسیک کنونی منجر به برقراری امنیت بی‌قید و شرط در ارتباطات بلند برد گردیده که در این مقاله به آن پرداخته شده است. نقطه تمایز این مقاله ارائه مروری بر جدیدترین تحقیقات در زمینه پیاده‌سازی شبکه‌های توزیع کلید کوانتومی در فیبرنوری است. همچنین شبکه‌های توزیع کلید کوانتومی پیاده‌سازی شده در دنیا بررسی و مقایسه گردیده و رویکرد کشورهای مختلف در این زمینه را مورد مطالعه قرار می‌دهد. تفاصيل المقالة

The present study is to investigate and design the logic gates and half adder circuits by using multilayer neural network. The parallel function of the neural networks allows their application in designing high-speed circuits. DSP and FPGA can be used in implementation of these circuits, which reduces the area of the circuit. This study first considers logic gates, and since half adder circuits are the basic systems in computing, a half adder circuit is designed in this study. To design a full adder circuit, two half adders and an OR gate can be used. The results of this study are consistent with the results of gates designed with other technologies such as CMOS and TTL, except that neural networks use less power. The results of the simulations are consistent with the results of logic gates and half adder designed with CMOS and TTL technologies. Matlab 2017 has been used in this paper for simulation. تفاصيل المقالة

How to reconfigure a logic gate for a variety of functions is an interesting topic. In this paper, a different method of designing logic gates are proposed. Initially, due to the training ability of the multilayer perceptron neural network, it was used to create a new type of logic and full adder gates. In this method, the perceptron network was trained and then tested. This network was 100% accurate to determine outputs based on inputs. The results of comparison showed that the multilayer perceptron network had higher velocity and less delay in most cases, and used a smaller number of neurons, which will reduce the loss of power. Meanwhile, implementation of these gates will require less space through the multi-layer perceptron network. This method is prioritized in terms of the number of neurons and the level of implementation, and the speed of the detection of output compared to the other design. It also occupies less hardware space and is less complicated. تفاصيل المقالة

In this paper, a new method for extending and relaxing the noise-coupling (NC) technique is proposed to enhance the noise-shaping order without adding the number of integrators. The noise-shaping order of the introduced ∑∆ modulator whit applying a second-order noise-coupling technique is enhanced and its performance with optimizing the noise transfer function (NTF) zeros is improved. Also, by removing the analog adder at feedforward path and transferring it to a new feedback branch before the last integrator and adding second-order NC path can be decreased the input voltage swing to the quantizer. Thus, by improving the modulator resolution, power consumption can be reduced. Mathematical analyses and behavioural simulation results confirm the effectiveness of the new NC method. To examine its performance, a 2nd-order single loop ΣΔ modulator was designed. The new noise-coupling method is used to achieve the three-order noise shaping to increase the resolution with low complexity and low-power. The results show an outstanding improvement in signal-to-noise and distortion ratio (SNDR) compared to the conventional structure. تفاصيل المقالة

In junctionless nanowire transistors, drain-channel-source doping is of the same type and level. Therefore, fabricating junctionless transistors is less complicated than inversion mode transistors. However, the reduced ratio of on current to off-state current (ION/IOFF) in junctionless nanowire transistors has made their operation difficult due to the high impurity scattering in the channel. The larger ION / IOFF ratio indicates an increase in transistor switching speed. In this study, the use of gate oxide engineering is proposed to increase of ION / IOFF ratio. The proposed oxide thickness is 1.5nm, which is a buffer layer with K = 5.7 and a thickness of 0.5nm, and the oxide with a high permittivity factor with K = 29 and a thickness of 1nm. The proposed structure is called GAA-JL-FET-with-oxide buffer layer. In GAA-JL-FET-with-oxide buffer layer, the ION / IOFF ratio has been improved by about 106 and 102 times compared to the structure with K = 3.9 and K = 7.5, respectively. Due to the high switching speed, the GAA-JL-FET-with-oxide buffer layer is applied to design the multiple-valued logic (MVL) interconnection network in the voltage mode for the first time using the mixed-mode tool in Silvaco software. The results reveal improving subthreshold parameters of the simulated device significantly enhance the average power, max delay and power delay product (PDP) of the proposed interconnection networks. تفاصيل المقالة

In this paper, we present a novel algorithm for VANET using cloud computing. We accomplish processing, routing and traffic control in a centralized and parallel way by adding one or more server to the network. Each car or node is considered a Client, in such a manner that routing, traffic control, getting information from client and data processing and storing are performed by one or more server in different bases. The procedure is about each client that receives its situation by GPS system and sends it online to the concerned server via GPRS networks. In order to perform routing and displaying data, each client sends a request to server. All processes and operations will be executable by the software which is inside the server. Finally, we propose an algorithm to work in server and make decision on route selection on the basis of three priorities of traffic, safety and shortest route. This algorithm is represented for the first time. The results indicate that by using this method VANET network is improved. By using this algorithm, we can communicate generally, not regionally, and improvement of processing and accurate statistics is achieved. In fact, the processing in the server is Fuzzy. It means that these priorities are Fuzzy. تفاصيل المقالة

With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of data mining is very important, this paper proposes four faster classification algorithms in comparison with each other. In this paper, A Multi-Layer perceptron (MLP) Network is trained with Imperialist Competitive Algorithm (ICA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and Invasive Weed Optimization (IWO) separately. The classifications are done on Wisconsin Breast Cancer (WBC) data base. At the end, to illustrate the speed and accuracy of these classifiers, they are compared with each other and two other types of Genetic algorithm classifiers (GA). تفاصيل المقالة

Wireless sensor networks(WSN) have unique properties that distinguished them from other wireless networks and have special challenges. Not-chargeable, not-changeable and limited power supplies of sensor nodes is the most important challenge of this networks, and if the power supply of node expired, a part of data maybe lost. Because of the importance of covers in wireless sensors, in this work we have presented approaches that in their designs nodes are in special and different areas so that the hole of environment be covered and for saving power consumption, in each active period only one node is active and others are in inactive. For implementing the task cycle and avoiding from over-load of one node, the active node which have the task of sensing and maintaining the cover of area, in the next period, another node will replace it. It seems that by zoning the environment and cycle of tasks, the overall cover of wireless network improves. تفاصيل المقالة

Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optimization uses a similar mechanism to solve the optimization problem. Usually the main difficulties of evolutionary algorithm for solving the optimization problem are: early convergence, loss of population diversity, and placing in a local minimum .Therefore, it needs the way that preserves the variation and tries to avoid trapping in local minimum. In this paper by combining ant colony algorithm and mutation hybrid algorithms that leads to the better solution for optimization of FPGA (Field Programmable Gate Array) placement problem is made. They are different types of swarm intelligence algorithm. After designing the algorithm, its parameters tuning have been done by solving several problems, and then the proposed methods have been compared with the other approaches. The results show that in most problems, the proposed hybrid method is able to obtain better solutions and makes fewer errors. تفاصيل المقالة

In vehicular ad hoc networks there is the ability to communicate between vehicles. This Communication which is wireless should be rapid and reliable. These networks have unique characteristic. This communication among vehicles has many advantages in safety and comfort applications. Since, the roads are always encountered to accidents and risks, using optimized tools could be useful in these situations. In this study, AODV and ADV routing algorithms has been compared through their performance metrics in a city scenario, include delay, network loss, collision and throughput were investigated through NCTUns 6.0. تفاصيل المقالة

Routing in ad-hoc networks, specifically intelligent-based ones, is a highly interested research topic in recent years. Most of them are simulation-based study. Large percentages have not even mentioned some of the fundamental parameters. This strictly reduces their validity and reliability. On the other hand, there is not a comprehensive framework to classify routing algorithms in wireless sensor networks yet. In this paper, we present a novel comprehensive taxonomy for routing algorithms along with a complete experimental evaluation framework. It makes the ability to put each routing algorithm in its place. It also provides a complete view of the algorithm behavior. At the end, a proper framework is introduced to express essential simulation parameters too. This can lead to improve the quality of scientific practices in the simulation studies. تفاصيل المقالة

Nowadays Network-on-Chips is used instead of System-on-Chips for better performance. This paper presents a new algorithm to find a shorter path, and shows that genetic algorithm is a potential technique for solving routing problem for mesh topology in on-chip-network. تفاصيل المقالة

Wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. Routing attacks on the networks, where a malicious node from sending data to the base station is perceived. In this article, a method that can be used to transfer the data securely to prevent attacks is suggested. The selection based on optimal path by routing using genetic algorithm uses. The proposed optimal paths to transmit data perceived to have chosen and ensures reliable data transmission. تفاصيل المقالة

In this paper, an Adaptive-Network-based Fuzzy Inference System (ANFIS) is used for forecasting of natural gas consumption. It is clear that natural gas consumption prediction for future, surly can help Statesmen to decide more certain. There are many variables which effect on gas consumption but two variables that named Gross Domestic Product (GDP) and population, are selected as two input variables. The input variables data and output variable (gas consumption) data are collected in years 1993 till 2012. Pre-process is done on the primary data to obtain better results then finally our outputs are post-processed. In this paper, many fuzzy models are applied and the results and error of every model are investigated. All ANFIS outputs are compared with real output by considering Mean Absolute Percentage Error (MAPE). The best model, which has the lowest MAPE, is chosen for forecasting gas consumption. In this paper, the values of gas consumption are forecasted from 2013 to 2020 تفاصيل المقالة

In this paper, by means of fuzzy approaches, an accurate method is introduced for edging of color photographs. The difference between our method with other similar methods is the use of a morphological operation to think or thick the obtained edges. In this proposed method, a 3×3 window is dragged on the photo. For each block, 12 point sets will be defined, each including two non-overlapping point sets. Then, a fuzzy membership function will be designed for each point sets according to data of contrast. At last, the range of membership contrast degree for the points of second point sets will be assessed. A comparison of membership degree of second point sets with a pre-defined threshold indicates whether central point of window is bordered or non-bordered. The method was performed on some reference images and the results were compared with common edging methods. The results show that proposed method has a high capability to edge photographs تفاصيل المقالة