Earticle

Time delays, also known as transport lag, dead time or time lag, are components that hold signal flow off inside the systems. They arise in physical, chemical, biological and economic systems, as well as in the processes of measurement and computation. Time delays can be approximated using polynomial series to allow the systems be analyzed in the same manner as the non time-delay systems. In this paper, we study the influences of delay components to system’s stability, derive the Nyquist stability criterion for time-delay systems and use it to analyze stability of the systems, and utilize some polynomial series to approximate the delays and examine their performances. Moreover we study PID controller as delay compensation scheme using two tuning methods: the “iterative method” and Ziegler-Nichols method.

In this paper, we present an inventory model for perishable items with freshness-dependent demand rate and partial backlogging. Because the customers prefer to purchasing fresh items for given price, the demand rate is assumed to be decreasing in the age of the items. The existence and uniqueness of the optimal solution of the profit per unit time are examined although the profit function is not jointly concave. The results are illustrated through numerical example and sensitivity analysis is reported.

In this paper an optimal tracking algorithm for large scale systems has been suggested using orthogonal functions and their operational transform matrices. Orthogonal functions such Walsh and block pulse functions (bpf) belong to the class of piece wise constant basis functions that have been developed in twentieth century and have played an important role in control engineering applications. And Walsh and block pulse functions have been proposed to solve the problems related to systems identification, analysis and optimal control. In addition, orthogonal functions and transforms can be applied to develop signal transduction and communication theory by allowing the application scope has widened its coverage. The applied method is very useful to solve the two point boundary vale problem for optimal tracking of large scale system and it is superior to conventional numerical methods.

So far, many parallel algorithms have been developed under the assumption that a high performance multicore processor uses a bus for inter-core communications. However, this assumption begins to change as the number of processing cores is increased and thus, higher connectivity among cores is required. So, in this paper, three HEVC intra prediction algorithms are ported into a mesh network-based multicore system by using a wavefront-style parallelization. By analyzing parallel performance, this paper shows that UDIP best fits in the mesh network-based multicore system (almost 2 times faster than other algorithms).

The work proposed in this paper aims to design a robust control algorithm for the attitude tracking of a quadrotor UAV system in presence of actuator faults. The attitude dynamic modeling of quadrotor while taking into account various physical phenomena, which can influence the dynamics of a flying structure is presented. Subsequently, a control algorithm which based on robust integral backstepping taking into account the actuator faults is developed. Lyapunov based stability analysis shows that the proposed control algorithm keep the stability of the closed loop dynamics of quadrotor UAV even after the presence of actuator faults. Numerical simulation results are provided to show the good tracking performance of proposed control laws.

Realized Volatility (RV) has been widely used since it was put forward. Some scholars put forward the improved form of RV aiming at better performance in describing the volatility. This paper select 2 main form of improvements: Adjusted Realized Volatility (ARV) and Weighted Realized Volatility (WRV) and make a comparison of RV, ARV and WRV of a contract of stock index of futures in China. Considering 3 methods are all non-negative, the MEM is a proper model. The empirical analysis includes 2 parts: one is statistical information, the other is modeling result. In the first part, the paper shows 4 kinds of statistics and the autocorrelation series; in the second part, the paper choose 3 possible distribution of stochastic error term and modeling MEM for RV, ARV and WRV. Then compare the significance of coefficients and likelihood value of different models.

This paper presents a method to solve the optimal generation and dispatch of electrical power with multiple fuel options at different power levels. In general, the cost function for each generator is considered by a single quadratic function of power, for the optimal generation and dispatch problem. However, it is more realistic to represent the generation cost function for fossil fired plants by non smooth cost function i.e. the total generation cost function has non differentiable points such as segmented piece-wise quadratic function and valve point loading. Some generating units utilize multiple fuels sources (such as gas, coal, oil etc) are faced with the problem of determining which is the most economical fuel to be selected. This problem has been solved by Hota & Das [17] considering equal incremental cost. In this method the program has to be run for a number of times for fuel combinations for different units and then to select the best one out of all combinations. This is a complicated process. Also if some other type of nonlinear cost function is considered along with this, the method will not be applicable. In view of the above mentioned problems of economic load dispatch (ELD) of multiple fuel generation, a more general heuristic method known as Particle Swarm Optimization (PSO) is considered in this paper to solve the problem in which either type of nonlinearity in cost function can be considered. For solution of this problem dynamic PSO is proposed. It is dynamic in the sense that the velocity bound or limit is updated in each iteration. This proposed method is applicable to the generating units that can use multiple fuels through valve at different generation levels as well as other problems which results in multiple intersecting continuous and discontinuous cost curves for any unit. The advantage of the method is that the method is applicable to both continuous and discontinuous cost curves of systems. Also it does not require selection of unit and type of fuel to be used after computation for a number of combination which is a cumbersome task as used in ref [17]. The complete method is explained and validated by taking an example. The simulation is carried out using MATLAB software. It has been shown that the method is simple, direct, and practical. It can be used for real time implementation and operation.

Based on intelligent traffic system idea and fuzzy logical, a fuzzy control method of the traffic light signal with full countdown function is proposed which can effectively solve the randomness problem in the dynamic system. The method overcomes limitation of traditional mathematical control method and does not build a complex traffic flow model. It makes the action of controlling green light time into a series of roles and these roles can be optimized off-line. This paper studies the deviation in traffic flow data and data bottleneck production problem, and provides a solution based on conjunction of mathematical statistics and time series analysis. Using the conception of flow quantitative to fuzz traffic flow to implement self-adapted fuzzy controller controls intersection signal. Finally, simulation results verify the performance of our proposed method.

Recently, wireless network user increased drastically due to the fast development and evolution of various mobile devices such as Smart Phone, Tablet PC, and etc. Provider provides good quality of services to the customers by giving them the advance functionality and services. Therefore, wireless network services expanded in various multimedia services such as Voice over IP, Video Call, MMS, Video Sharing, Online Video Streaming, etc. In the past, network environment trend used wired network, but it drastically evolved into wireless network which gives fast and efficient communication, more convenience to the users/consumers. Therefore, it emphasized the importance of Mobile Internet Protocol Version 6(MIPv6) which also challenges the providers to develop advance product services by integrating wireless network services. Many researchers studied new protocols and related technology in order to develop and provide an advance services and good quality of service. Therefore, a lot of developments and enhancement was being studied and develop using standard MIPv6 such as Fast handover for Mobile IPv6, Hierarchical Mobile IPv6 and Proxy Mobile IPv6. But, it has many problems until now. In this paper, we proposed a handover protocol over fast handover for mobile IPv6 which enhanced the handover procedure and reduce the delay time of packet transmission.

In this paper, an unaffected interface for an immersive virtual reality environment using the motion templates method was proposed. We made background model with real photographs. The panoramic images were constructed using these photographs from real environment and texture-mapped to virtual sphere surround CAVE. As a user interface for this background model, the motion templates method of computer vision technologies is used. The computer vision module recognizes predefined user’s gestures and sends commands to render module of CAVE system via internet using UDP protocols. Using this method, the users can manipulate the background model unaffectedly. This is efficient for VR applications like looking around a remote scene.

To improve the robot's locomotion performance, it definitely needs the HRI (Human Robot Interaction) technology, the location awareness technology, and the real time location correction technology. In this paper, an HRI method that uses a circular coordinate system is proposed. The proposed method can implement robot locomotion with variable speed and directions instead of conventional method that controls speed and direction separately. Also, the nine characteristics of proposed circular coordinate system are to be described and the principles of user interfaces using the circular coordinate system are to be analyzed. For the performance evaluation, we have used a mobile robot that can be controlled through the wireless LAN and can perform differential drive. In addition, we have configured and tested a smart phone environment that can control the robot. The evaluation results show that the circular coordinate system reduces the locomotion time with accuracy.

In wireless sensor networks with single sink node, the energy consumption of sensors near the sink or on the critical paths is too fast besides other disadvantages. Therefore, we propose an Energy-efficient Multi-sink Clustering Algorithm (EMCA) for wireless sensor networks. In EMCA, residual energy plays a significant role in the procedure of selecting cluster heads. We also design an inter-cluster and intra-cluster routing algorithm aiming at minimizing the energy consumption. Inside a cluster, a multi-hop way is under consideration for a node to relay data instead of direct transmission. Simulation results show that our proposed algorithm consumes much less energy and owns longer network lifetime than the traditional routing algorithm LEACH.

Gradient is an important operator in signal processing. A gradient operation always is sensitive to noisy environment. In this paper, a new differential method is designed in the field of one-dimensional signal processing which is robust in low signal to noise ratio. The proposed scheme is suitable for signal differentiation in analog and digital signal processing applications. For low frequencies, this scheme performs the signal derivative, but for high frequencies recasts to a constant gain. This prevents differentiation of high frequency components of added noise. The proposed differential operator is applied to sound and image signals. Results show superiority of the proposed method.

Task scheduling is an important and challenging issue of Cloud computing. Existing solutions to task scheduling problems are unsuitable for Cloud computing because they only focus on a specific purpose like the minimization of execution time or workload and do not use characteristics of Cloud computing for task scheduling. A task scheduler in Cloud computing has to satisfy cloud users with the agreed QoS and improve profits of cloud providers. In order to solve task scheduling problems in Cloud computing, this paper proposes a task scheduling model based on the genetic algorithm. In the proposed model, the task scheduler calls the GA scheduling function every task scheduling cycle. This function creates a set of task schedules and evaluates the quality of each task schedule with user satisfaction and virtual machine availability. The function iterates genetic operations to make an optimal task schedule. Experimental results show effectiveness and efficiency of the genetic algorithm-based task scheduling model in comparison with existing task scheduling models, which are the round-robin task scheduling model, the load index-based task scheduling model, and the ABC based task scheduling model.

Recently, cooperative communications have been proposed that allows single antenna system in a multi user environment to share their antennas. And cooperative communications make a virtual multiple antenna transmitters that can achieve transmit diversity. But cooperative communications reduce transmission rate because the relay can re-transmit the received signals from the source. In this paper, new technique is proposed for high transmission rate based on decode-and-forward (DF) protocol. This technique adversely affects the bit error rate (BER) performance. But because transmission rate is increased, the throughput is increased.

In these days, smaller devices are possible to show graphics output, through attaching customized LCD panel displays. Our target system is a small embedded system with an LCD panel. As a typical low-tier embedded system, it has a low-end CPU and restricted memories. We aimed to build-up a full-scale 2D graphics module on it. After analyzing system requirements, we found that the most hardiest restriction is the size of available memory. As an alternative to the full-scale modules, our design shows a TUI (text user interface) model, which is similar to the Unix Curses library and/or primitive graphics system used on earlier PC user interfaces. Our design has a drawback of restricted controllability of 2020 character resolutions on the screen, rather than 240x320 pixel resolutions, while it enables pop-up menus and screen back buffering, with less than 7K extra memory usage. User Interface features including pop-up menus, push buttons, and customizable windows are also provided.

The expanded bandwidth for air interfaces has made a solid ground for streaming media application on wireless networks. With the advantages of wireless system in time and place, mobile streaming media service is very attractive. With the further increasing popularity of multimedia devices, such as laptop computers, personal digital assistants (PDAs), and smart phones, there is a rapidly growing demand for efficient real-time playback and transmission of large amounts of multimedia data, but most users’ connections are not fast enough to download large chunks of multimedia data. Moreover, when switching to another device while in the middle of downloading content, users have to download the same multimedia content all over again. A streaming service technology is therefore needed in which users can seamlessly download on the network large multimedia data based on the user’s history of preferred content. This study suggests a server–client streaming system that enables seamless multimedia content download that allows the user accessing the data to switch conveniently to another device or client without having to repeat the download to the beginning. The proposed system is also designed to be compatible with many users and different device environments through the home network by storing/managing information in the home server factors such as user preferences, device character information, the indication on the exact point the download was interrupted, and other related information.

Design of an intelligent flow measurement technique using ultrasonic flow meter is reported in this paper. The objective of the work are; (i) to extend the linearity range of measurement to 100% of the input range, (ii) to make the measurement system adaptive to variations in pipe diameter, liquid density, and liquid temperature, and (iii) to achieve the objectives (i) and (ii) by an optimal Artificial Neural Network ((ANN). An optimal ANN is considered by comparing various schemes and algorithms based on minimization of Mean Square Error (MSE) and Regression close to one. The output of ultrasonic flow meter is frequency. It is converted to voltage by using a frequency to voltage converter. An optimal ANN block is added in cascade to frequency to voltage converter. This arrangement helps to linearise the overall system for 100% of full scale and makes it adaptive to variations in pipe diameter, liquid density, and liquid temperature. Since the proposed intelligent flow measurement technique produces output which is adaptive to variations in pipe diameter, liquid density, and liquid temperature, the present technique avoids the requirement of repeated calibration every time there is change in liquid, and/or pipe diameter, and/or liquid temperature. Simulation results show that proposed measurement technique achieves the objectives quite satisfactorily.