Sharif Digital Repository

This paper is concerned with the tele-operation of autonomous vehicles over analog Additive White Gaussian Noise (AWGN) channel, which is subject to transmission noise and power constraint. The nonlinear dynamic of autonomous vehicles is described by the unicycle model and is cascaded with a bandpass filter acting as encoder. Using the describing function method, the nonlinear dynamic of autonomous vehicles is represented by an approximate linear system. Then, the available results for linear control over analog AWGN channel are extended to account for linear continuous time systems with non-real valued and multiple real valued eigenvalues and for tracking a non-zero reference signal.... 

Background: It is important to improve verbal Working Memory (WM) in reading disability, as it is a key factor in learning. There are commercial verbal WM training programs, which have some short-term effects only on the verbal WM capacity, not reading. However, because of some weaknesses in current verbal WM training programs, researchers suggested designing and developing newly structured programs that particularly target educational functions such as reading skills. In the current double-blind randomized clinical trial study, we designed a new Verbal Working Memory-Balance (VWM-B) program which was carried out using a portable robotic device. The short-term effects of the VWM-B program,... 

In this paper, we first propose a new continuous action-set learning automaton and theoretically study its convergence properties and show that it converges to the optimal action. Then we give an adaptive and autonomous call admission algorithm for cellular mobile networks, which uses the proposed learning automaton to minimize the blocking probability of the new calls subject to the constraint on the dropping probability of the handoff calls. The simulation results show that the performance of the proposed algorithm is close to the performance of the limited fractional guard channel algorithm for which we need to know all the traffic parameters in advance. © 2005 Elsevier Ltd. All rights... 

The development of emerging smart grid technologies has led to more and more penetration of renewable energy resources and electric energy storage in the residential sectors. Besides, owing to the significant evolution of power electronic devices, there is a rapid growth in penetration of DC loads and generations, such as PV and electric vehicles (EVs), into the buildings and homes as a building block of the future smart cities. This is despite the fact that the electricity infrastructure of the conventional buildings is designed based on AC electricity and as a result, there would be a lot of losses due to the frequent power conversion from AC to DC and vice versa. Besides, according to a... 

With the advent of the Internet of Things (IoT), the development of self-powered sensors has received much attention. Introducing triboelectric nanogenerators (TENGs) as a power source that converts mechanical movement into electrical signals has been admired recently. Moreover, the monitoring of humidity has become enormously essential in several technological contexts from environment monitoring to biomedical applications, thus joining these two subjects provides a huge benefit in achieving self-powered humidity sensors. Here, in this research, facile, low-priced and self-powered humidity sensors are fabricated utilizing transition-metal dichalcogenides (TMD) nanosheets. Semi-vertical SnS2... 

Smart home is a small but an important energy segment that has a significant potential to implement authentic energy policies, where human is a major decision-maker in the home energy management dilemma. Therefore, humans’ emotions and tendencies plays a vital role as the End-User's daily decisions. In this paper, we develop a behavioral home energy management model based on time-driven prospect theory incorporating energy storage devices, distributed energy resources, and smart flexible home appliances. The conventional prospect theory is then modified by considering the psychological time discount effect in the value function. The non-flexible load and photovoltaic generation uncertainties... 

The main contribution of this paper is to present the systematic and low-complexity translation techniques between a class of hybrid systems referred to as automaton-based Discrete-time Hybrid Automata (DHA) and piecewise affine (PWA) systems. As a starting point, the general modeling framework of the automaton-based DHA is represented, which models the controlled and uncontrolled switching phenomena between linear continuous dynamics including discrete and continuous states, inputs and outputs. The basic theoretical definitions on the state trajectories of the proposed DHA with forward and backward evolutions that yield forward and backward piecewise affine (FPWA and BPWA) systems are... 

Battery energy systems are playing significant roles in smart homes, e.g., absorbing the uncertainty of solar energy from root-top photovoltaic, supplying energy during a power outage, and responding to dynamic electricity prices. For the safe and economic operation of batteries, an optimal battery-management system (BMS) is required. One of the most important features of a BMS is state-of-charge (SoC) estimation. This article presents a robust central-difference Kalman filter (CDKF) method for the SoC estimation of on-site lithium-ion batteries in smart homes. The state-space equations of the battery are derived based on the equivalent circuit model. The battery model includes two RC... 

Machine-to-Machine (M2M) communication is an important type of communication in the Internet-of-Things (IoT). How to send data in these high-density communications using relay selection can help improve the performance of this type of communication in various applications. In addition, the possibility of simultaneous use of different Radio Frequency (RF) interfaces helps to use the spectrum more efficiently. In this work, we try to further use machine communication RF equipment and improve the average data rate of networks in some applications such as the IoT, which have their own bandwidth requirements. Therefore, we provide an optimization algorithm for relay selection as well as the... 

Implementation of various incentive-based demand response strategies has great potential to decrease peak load growth and customer electricity bill cost. Using advanced metering and automatic demand management makes it possible to optimize energy consumption, to reduce grid loss, and to release generation capacities for the sake of providing sustainable electricity supply. Executing an incentive-based program is a simple way for customers to monitor and manage their energy consumption, and therefore, to reduce their electricity bill. With these objectives, this paper examines the previously suggested load scheduling programs and proposes a new practical one for residential energy management.... 

In this paper, principal component analysis (PCA) and hierarchical cluster analysis (CA) methods have been used to investigate the water quality of Jajrood River (Iran) and to assess and discriminate the relative magnitude of anthropogenic and "natural" influences on the quality of river water. T, EC, pH, TDS, NH4, NO3, NO2, Turb., T.Hard., Ca, Mg, Na, K, Cl, SO4, SiO2 as physicochemical and TC, FC as biochemical variables have been analyzed in the water samples collected every month over a three-year period from 18 sampling stations along a 50 km section of Jajrood River that is under the influence of anthropogenic and natural changes. Exploratory analysis of experimental data has been... 

In this paper we follow two approaches in optimal nonlinear control of a snake-like robot. After deriving the dynamic equations of motion using Gibbs-Appell method, reducing these equations, and some assumptions, feedback-linearization method was used to linearize the nonlinear system. The obtained controller is used in simulations to control robot to track a desired line, with minimum required torques. Two goals are desired. First the robot's head is expected to track a distinct line with a given speed. And next, tracking the serpenoid curve is desired. The simulation results prove the controller efficiency. The robustness of the designed controller is shown by comparing the torques with... 

In this paper, we present new adaptive linear discriminant analysis (LDA) algorithm and apply them for adaptive facial feature extraction. Adaptive nature of the proposed algorithm is advantageous for real world applications in which one confronts with a sequence of data such as online face recognition and mobile robotics. Application of the new algorithm on feature extraction from facial image sequences is given in three steps: i) adaptive image preprocessing, ii) adaptive dimension reduction and iii) adaptive LDA feature estimation. Steps 1 and 2 are done simultaneously and outputs of stage 2 are used as a sequence of inputs for stage3. The proposed system was tested on Yale and PIE face... 

An automated technique based on purge-and-trap coupled to gas chromatography with mass spectrometric detection has been developed and optimized for the trace determination of five of the most important water odorants; 2-isopropyl-3-methoxypyrazine, 2-isobutyl-3-methoxypyrazine, 2-methylisoborneol, 2,4,6-trichloroanisole and geosmin. The extraction method was absolutely solvent-free. Analytes were purged from 20 ml of water sample containing sodium chloride at room temperature by a flow of He and trapped on a Tenax sorbent. The desorption step was performed with helium and temperature programming and desorbed analytes were directly transferred to a gas chromatograph coupled to a mass... 

Integrating humans and robotics technology into one system offers multiple opportunities for creating assistive technologies that can be employed in biomechanical, industrial, and aerospace applications. The present study deals with employing the adaptive neuro-fuzzy inference system (ANFIS) approach in rule base derivation for powered exoskeleton intelligent control to assist paraplegic patient mobility. By employing the hybrid learning algorithm, optimal distributed membership functions to describe the mapping relation in the input and output parameters of the gait cycle were derived. As the proposed control strategy was unaffected by changing human dynamics, the reliability and robustness... 

Developing efficient and appropriate modeling and control techniques for DC-DC converters is of major importance in power electronics area and has attracted much attention from automatic control theory. Since DC-DC converters have a complex hybrid nature, recently several techniques based on hybrid modeling and control have been introduced. These techniques have shown better results as compared with conventional averaging-based schemes with limited modeling and control abilities. But the current works in this field have not considered all possible dynamics of the converters in both continuous and discontinuous current modes (CCM, DCM) of operations. These dynamics are results of controlled... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main... 

Purpose: An abdominal aortic aneurysm (AAA) is known as a cardiovascular disease involving localized deformation (swelling or enlargement) of aorta occurring between the renal and iliac arteries. AAA would jeopardize patients’ lives due to its rupturing risk, so prompt recognition and diagnosis of this disorder is vital. Although computed tomography angiography (CTA) is the preferred imaging modality used by radiologist for diagnosing AAA, computed tomography (CT) images can be used too. In the recent decade, there has been several methods suggested by experts in order to find a precise automated way to diagnose AAA without human intervention base on CT and CTA images. Despite great... 

There are many sites specially designed for mobile phones. In cases such as the registering in websites, some hackers write programs to make automatic false enrolments which waste the resources of the website. Therefore, it is necessary to distinguish between human users and computer programs. These systems are known as CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart). CAPTCHA methods are mainly based on the weak points of OCR (Optical Character Recognition) systems while using them difficult in tools such as PDAs (Personal Digital Assistant) or mobile phones that lack a big keyboard. So the Non-OCR-Based CAPTCHA methods are proposed which are do not need...