International Journal of Intelligent Engineering and Systems

7

Authors: Minghua Niu, Jianmin Zhang, Gen Li

Lane recognition is a kind of technology which can reconstruct either continuous or discontinuous lanes in the driving region into the continuous curves from the images of the road containing the lane markings. It is the basis and prerequisite for the whole lane departure warning system and the key technology in intelligent traffic safety assistant driving now. Generally speaking, the road images which the camera captures are processed by three steps: image preprocessing, image threshold segment and lane recognition. This paper proposed an efficient system to detect the lanes and mainly made experimental research on the images simulation of the three kinds of algorithms of the threshold segment and used the principle of Hough Transform in the lane recognition. Finally, the relatively efficient and accurate lane recognition processing algorithm was obtained according to the experimental results. Undoubtedly, this would lay a theoretical foundation for putting lane detection algorithm into practical application.

13

Authors: Senthil Murugan Balakrishnan, Arun Kumar Sangaiah

Internet of Things refers to a paradigm consisting of a variety of uniquely identifiable day to day things communicating with one another to form a large scale dynamic network. The integration of these heterogeneous things in the constrained network is a challenging issue, for which service oriented and architecture based solutions are considered to be useful. The key element of any service oriented paradigm is service discovery which allows the client to get access to the right service at the right time to complete the requested tasks. This paper presented a comprehensive survey of major solutions for service and resource discovery detailing techniques and features used in existing systems. The survey presented the findings in tabular representation and outlined the proposed aspect oriented middleware framework for IoT highlighting context awareness and solving certain pitfalls in the existing service discovery approaches. The survey results might be helpful in deriving the limitations of the existing protocols in literature and identify future research opportunities in service discovery.

6

Authors: Dun Liu, Qian-Fu Cheng

This paper elaborates the basic operation principle of the Doherty power amplifier (DPA) and analyzes the method of improving the linearity of the DPA. A novel DPA with dual DC power supplies and a high linearity is designed and implemented at the operating frequency of 4 GHz. EM (Electro Magnetic)/Circuit Co-Simulation shows that under one tone test, the DPA can obtain the high performance of the 40.4 dBm saturated output power, about 63% maximum power added efficiency (PAE) and about 50% PAE at 6 dB output power back-off (OBO). Under two tones test, the third order inter-modulation distortion (IMD3) is less than -30 dBc when the input power is less than 27dBm. Moreover the DPA delivers the maximum PAE of 61% with the corresponding input power of 26.5 dBm and output power of 38.5 dBm respectively.

6

Authors: Abderrahmen Bouguerra, Djamel Saigaa, Kamel Kara, Samir Zeghlache

The work has done in this paper concern the passive fault tolerant control. Based on Gain-Adaptive Proportional-Integral-Derivative (PID) using the approach from the theory of Lyapunov and their application to the model vertical flying drone Quadrotor type, the PID controller with fixed parameters may fail to provide acceptable control performance. To improve the PID control effect, new designs of the Lyapunov gain Scheduled PID controller (LGSPID) were presented in this paper. The proposed techniques were applied to the Quadrotor, where adaptive PID controllers were proposed for fault-tolerant control system in the presence of actuator faults. The parameters of PID controller were adjusted by an adaptation algorithm gradient type, used to tune in real-time the controller gain, the proposed adaptive PID controller was compared with the conventional PID. The obtained results confirm the effectiveness of the proposed method.

7

Authors: Hongbing Zhu, Jun Wu, Jinguang Gu

Immune algorithms (IAs) are microscopic view of evolutionary algorithms (EAs) and applied in combinatorial optimization problems. This paper addresses to a clonal selection algorithm (CSA) that is one of the most representative IA and was applied into the protein structure prediction (PSP) on AB off-lattice model, in which the memory B cells of the CSA was innovated by employing different strategies: local search and global search in the phase of the mutation. And the CSA was further improved by adding aging operator to combat the premature convergence. However the pure aging operator didn’t achieve effective results and sometimes the optimum solution was eliminated. To resolve this problem, the current best solution was reserved by an antibody and it was not eliminated when its age reached its life span. In our experiments the improved algorithm was compared with the standard CSA and the pure aging CSA, which of the results demonstrated that the improved strategy with the memory B cells and long life aging was very effective to overcome premature convergence and to avoid trapped in the local-best solution, and it was also effective in keeping the diversity of the small size population. On the other hand, one novel hybrid algorithm Quantum Immune(QI), which combines Quantum Algorithm (QA) and Immune Clonal Selection(ICS) Algorithm, has been presented for dealing with multi-extremum and multi-parameter problem based on AB off-lattice model in the predicting 2D protein folding structure. Clonal Selection Algorithm was introduced into the hypermutation operators in the Quantum Algorithm to improve the local search ability, and double chains quantum coded was designed to enlarge the probability of the global optimization solution. It showed that the solution mostly trap into the local optimum, to escape the local best solution the aging operator is introduced to improve the performance of the algorithm. Experimental results showed that the lowest energies and computing-time of the improved Quantum Clonal Selection(QCS) algorithm were better than that of the previous methods, and the QCS was further improved by adding aging operator to combat the premature convergence. Compared with previous approaches, the improved QCS algorithm remarkably enhanced the convergence performance and the search efficiency of the immune optimization algorithm.