Earticle

In VLSI design the reduction of power is an important criterion. The performance of a system mainly depends on the method of designing of various blocks of that system. To provide an efficient and meaningful architecture of a VLSI chip, a devoted design is needed which is power serviceable with less intricate. As computer systems have sequential circuit mostly, hence it is very necessary to design a sequential circuit which is more efficient and less power consuming. As different kind of counters are the important segments for different sequential circuits. Here, in paper we have proposed an efficient clock gating 4-bit Johnson counter using low power d flip flop. Power of d-flip flop is reduced by using power gating technique. By doing analysis in cadence at 180nm technology it is counted that our proposed design has lower power consumption i.e. power of the proposed design comes to be reduced by 40.3% which is 62.63e-6 and the reduced output is 37.4e-6. This is a great achievement in the VLSI industry than the conventional design, with a little enhancement of delay.

The difficulty of CNC machine tools fault diagnosis is bigger than other general equipments because of the complex structure and the coupling among subsystems. The fault diagnosis model based on multi-level information fusion and hybrid intelligence is studied to improve reliability of fault diagnosis. Information from built-in sensors is used to monitor the status of CNC machine tools. The diagnosis principles of internal parameters-motor current, torque, temperature and following error are analyzed. Internal information and external sensors are two main sources which provide data to diagnosis. In order to detect effective fault signal, features of time domain, frequency domain and time-frequency domain are extracted. All these features constitute the feature set. The features are selected by the method of Kernel Principal Component Analysis (KCPA). Then the sensitive feature set is obtained. The method of multiple classifier fusion based on fuzzy comprehensive evaluation is researched. The determination method of weight based on information entropy is proposed. This diagnosis model has been tested feed system mechanical fault diagnosis of CNC machine tools and the results show which is effective and versatile.

The determining method of the weights of multiple attributes decision making needs to be improved. Firstly, three entropy measures are deduced through a similarity measure of intuitionistic fuzzy sets. Most of the entropy measures are not able to fully describe the uncertainty of things. So the weight determining results which based on the entropy, becomes somewhat inaccurate. The method of improving the effective information is proposed to determine the attribute weights in order to improve the accuracy of weights determining. Ultimately the ideal multiple attributes decision making analysis results are determined by adjustment weights with the parameter.

Efficient and optimal planning of economic electrical power dispatch problem is an integral part of economic electrical energy generation planning and it is the need of time for the electrical engineers to browse this area in multi-scale planning scenarios. Intelligent and Optimization techniques based on evolutionary computing, metaheuristic,biological base,nature inspired, search method establish their applications in the area of electrical economic power dispatch planning(EEPDP) to reach global optimal solution for this multi scale, multi-decision, multi-objective combinatorial problem subjected to different constraints. In this paper, water cycle algorithm (WCA) has been proposed to solve electrical economic power dispatch problem for three and six unit system.This is based on how the streams and rivers flow downhill towards the sea and recycle in nature The suggested technique is tested on small scale system of three and six unit system of EEPDP considering various equality and inequality constraints . Test results are compared with other techniques grey wolf optimization(GWO),cuckoo search(CS),artificial bee colony(ABC),firefly algorithm(FA),particle swarm optimization(PSO),shuffled frog leap (SFL) ,bacteria foraging algorithm(BFO),harmony search(HS) applied in literature.Convergence of solution with iteration is presented for both cases.Simulation results proved that the WCA technique is better as compared to other nature inspired,heuristic,metaheuristic techniques to find global minima and maintain the solution quality in terms of low fuel cost.

The purpose of this study is to understand the characteristics of proper binding force to harvest blue honeysuckle. After tracking such force over 16 days for four breeds of blue honeysuckle during the harvest period, we find that the binding force is mainly distributed in the range of 0.1 ~ 1.7N (P<0.05). This distribution range varies slightly between breeds: the picking forces of L.caerulea subsp.altaicai and Berel are greater than Bluebird and wild L.caerulea var.edulis of Changbai Mountain, and the binding forces of all breeds decrease over time with different slopes. Moreover, we also find that the binding force in the afternoon are significant larger than in the morning for the same day (P<0.05), and no significant difference is found between sunny and rainy days. We categorize factors affecting the binding force, such as testing day, morning and afternoon, relative humidity, temperature, weather conditions into environmental factors and time factor.

After the image decomposition with Non-subsampled Shearlet Transform (NSST), the transform coefficients have a larger redundancy. In order to reduce the redundant information, an image fusion algorithm based on NSST and non-negative matrix factorization (NMF) is introduced. The source images are decomposed with NSST into the low-frequency coefficients and the high-frequency sub-band coefficients. The low-frequency coefficients are fused based on NMF theory. The high-frequency coefficients are fused based on Regional Sum Modified-Laplacian (SML) Maximum. Finally, the inverse NSST is used to reconstruct the final fused image. The proposed algorithm can effectively remove redundant information, extract global features and capture more direction details information of multi-source image. Experiments show that the proposed algorithm has obvious advantages and the fused image quality has been greatly improved. The presented algorithm is superior to other fusion algorithms from the objective parameters.

Surface mount technology is a method of applying lead solder to PCB pads to fix Surface Mount Device (SMD) components on PCBs. SMT facilitates the pickup of the electronic component and accurate placement on PCBs. Heads and nozzles for each axis use suction cups to pick up electronic components from tape feeders. The components are inspected before a vision camera to check pickup location and alignment, and then are moved to PCBs waiting on the conveyer for placement. This paper presents an algorithm that identifies the shortest path from sLa to pLb without stopping before the camera for visual inspection. The simulations verified that the fly motion method reduced the time involved by 16% compared to the stop motion method.

There are many characteristics that can be calculated by the movement of people, such as distance, speed, slope and difference in length or height for each type of the movement. For the purpose of finding the most important of which features and high priority weight in the classification of the movement of people, we have been employed Taguchi method to determine the weight of each characteristic and the extent of their influence and weight in determining the behavior and the type of people movement. In this paper we employ Taguchi method in video tracking application to determine high value of weight for best parameters. We have been relying on the formula Signal to Noise Ratio (S/n) in order to find the most effective characteristic.