Laundry is an essential part of people's daily life. Good washing machine can not only save energy, but also carry on a more reasonable washing to the clothes to prolong its service life. Automatic washing machine frees the user's hands, so that the user can better allocate the time to do other work, so as to improve the work efficiency. Therefore, a fuzzy logic controller (FLC) based washing machine needs to be designed. This paper presents an improved fuzzy logic based control system for washing machines. The simulation results show that the system has a shorter washing time.

Sericulture (silk production) is a major occupation of rural community. Producing about 15% share of the world silk produce, India is the 2nd largest silk producer after China whose total produce amounts to a staggering 80%. Analysis of sericulture practices in India shows a clear need of automation especially during pre-cocoon stages. The silkworms undergo crucial bodily changes that determine the quality as well as quantity of the silk produce, during this phase. Maintenance of optimum values of abiotic factors, like temperature, humidity etc. thus yields a dramatic change in quantity and quality of silk produce. An Intelligent Sericulture plant automation system, using zone-based cascade control of physical parameters can be one of the solutions. Currently, such systems for pre-cocoon stages are purely manual, crude, and lack intelligence. The system comprises of a data acquisition sub-system corresponding to the predetermined zones for the rearing unit, an intelligent master controller facility, data repository of past corrective actions, and cheap actuators like fans, bulbs in the zones. The master control facilitates the optimum corrective action and directs the decisions to the identified actuator sub-system based on abiotic data obtained from the respective data acquisition subsystem. The actuator sub-system achieves the corrective measures using the actuators placed in that zone of the unit. A continuous real-time feedback facilitates accurate and quick implementation of corrective steps. The system aims for increased quantity and quality of silk which is determined by reeling factor, holding capacity, roughness of silk. Also, the zonebased implementation decreases production and maintenance cost making it suitable for rural usage.

No abstract

Gait based human recognition system is most important and attractive method of biometrics. Gait the way of walking capture from distance and provide more efficient means of verification. In this paper, we propose an efficient algorithm which works on angle based technique. Initially video converted into frames and then feature abstraction is done. Here we are taking three lower body parts for recognition and a correlation of triangle is derived. Using cosine formula each inner angle of triangle is calculated and stored in database for identification. The gait system is designed using MATLAB to accomplish this research work.

Introduction: Gradient boosting is an intense machine learning method presented by Friedman [2]. The procedure was propelled similar to a gradient descent strategy in work space, equipped for fitting nonexclusive nonparametric prescient models. Gradient boosting has been especially fruitful when connected to tree models, in which case it fits additive tree models. Risk Minimization: Defining the Target: In this area, we will present the loss function. The loss function is the measure of forecast accuracy that we characterize for the current issue. We are at last intrigued by limiting the normal loss, which is known as the risk. The function which limits the risk is known as the target function. This is the ideal forecast function we might want to get. The Loss Function: Loss functions assume a focal part in decision hypothesis [12]. Statistical decision hypothesis can be seen as an amusement against nature, instead of against other vital players [13]. In this diversion, we need to pick a move a to make from the set of admissible activities, i.e. the activity space A. This activity is hence judged in setting of the genuine result y ∈ Y, which is picked by nature. The loss function L: Y × A → R+ gives a quantitative measure of the loss brought about from picking activity a when the genuine