Applications of Multi-Agent System in Power System Engineering

Power system needs a continuous upgrade to overcome the challenges like distributed control, self-healing, power quality, demand side management and integration of renewable system. At present, power system needs an advance and intelligent technology to perform various system level tasks. Centralized control of the system has efficient operation during integration of the renewable resources and lag of communication between the stations. Smart grid provides the intelligent and efficient power management system. Upgrade of present power system with multi-agent system (MAS) provides the solution for most of the power system issues. More number of MAS are used in the power system network based on acquires of the system. MAS are communicating with each other for the more acquired result. Better implantation of MAS can achieved by providing the high speed and secured communication protocol. In this chapter, we discussed about the MAS fundamental architecture and intelligent controller design tools and case study of real time tariff management using MAS

Automatic Leather Species Identification using Machine Learning Techniques

Content: Identification and classification of leather species becomes valuable and necessary due to concerns regarding consumer protection, product counterfeiting, and dispute settlement in the leather industry. Identification and classification of leather into species is carried out by histological examination or molecular analysis based on DNA. Manual method requires expertise, training and experience, and due to involvement of human judgment disputes are inevitable thus a need to automate the leather species identification. In the present investigation, an attempt has been made to automate leather species identification using machine learning techniques. A novel non-destructive leather species identification algorithm is proposed for the identification of cow, buffalo, goat and sheep leathers. Hair pore pattern was segmented efficiently using k-means clustering algorithm Significant features representing the unique characteristics of each species such as no.of hair pores, pore density, percent porosity, shape of the pores etc., were extracted. The generated features were used for training the Random forest classifier. Experimental results on the leather species image library database achieved an accuracy of 87 % using random forest as classifier, confirming the potentials of using the proposed system for automatic leather species classification. Take-Away: Novel technique to identify leather species Non destructive method Machine learning algorithms to automate leather species identificatio

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes

IN VITRO CYTOTOXICITY OF BIOSYNTHESIZED GOLD NANOPARTICLES FROM SHELLS OF PISTACIA VERA L

Objective: To synthesize the gold nanoparticles by a biological method using the extract obtained from the shells of Pistacia vera (P. vera) and to study its effective role in the anticancer activity.Methods: The synthesis of gold nanoparticles using the extract obtained from the shells of Pistacia vera was confirmed by the color change and substantiating the same using ultraviolet (UV) visible spectroscopy. The size and the shape of the particles were studied using field emission scanning electron microscopy (FESEM). The stability of the nanoparticles was assessed by using the UV visible spectroscopy and Fourier-transform infrared spectroscopy (FTIR). The anticancer activity of the gold nanoparticles on the cancer cell lines was studied on PA1 ovarian cancer cell lines using 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Nature of cell death was analyzed using the fluorescence microscopy.Results: The ruby red color confirmed the formation of gold nanoparticles and it was substantiated by the absorption peak at 543.2 nm in the UV visible spectroscopy. The gold nanoparticles synthesized from the Pistacia vera shell showed the spherical shape and were in the size of around 10-40 nm when analyzed with FESEM. The different functional groups were indicated in the FTIR spectra which were consisting of phenol, alcohol, alkenes and aromatics.Conclusion: The synthesis of the gold nanoparticle using the extract obtained from the shells of Pistacia vera has effective anticancer activity

High Exhaustion Sytem (HES) for leather process: Role of biocatalyst as an exhaustive aid for wet-end

Content: Application of biocatalyst becomes an imperative due to their eco-friendly advantages. Enzymes in pretanning for unhairing, fiber opening, defleshing and bating are well reported and practiced. However, the role of enzymes as a chemical aids is less explored and consider as a secondary applications. Leather enzymes are known for its hydrolytic behavior which makes it more suitable for pretanning operations. However, typical chemical exhaustive aids acts as a vehicle for the diffusion of chemicals, whereas enzymes aids in the splitting of fibers which facilitate the diffusion of chemicals and create more functional sites for the tanning and post tanning chemicals to interact. In this research, pickled pelts are treated with acid protease and subsequently tanned using chrome tanning agent. Enzymatic treated pelts resulted in better uptake of chromium as compared to conventionally processed leathers. Similarly, after neutralization, chrome tanned leathers are treated with alkaline protease to conventional post tanning has been carried out. Enzymatic treated wet blue leathers showed high uptake of post tanning chemical, uniform dyeing and reduction in the pollution load. From the preliminary research, an interesting finding has augmented that application of enzymes at an optimized concentration, temperature, pH and time would lead to better uptake of chrome which reduces the pollution and minimization pollution load in post tanning. This study, emphasize on the application of enzymes in tanning and post tanning for higher diffusion of chemicals. Take-Away: 1. Replacement of conventional exhaustive aids using biocatalyst 2. Higher exhaustion rate of tanning and post tanning chemicals 3. Futuristic technology for sustainable leather manufactur

Load-Deflection Characteristics Of Steel, Polypropylene And Hybrid Fiber Reinforced Concrete Beams

Concrete is the most widely used construction material because of its specialty of being cast into any desired shape. The main requirements of earthquake resistant structures are good ductility and energy absorption capacity. Fiber reinforced concrete possesses high flexural and tensile strength, improved ductility, and high energy absorption over the conventional concrete in sustaining dynamic loads. The aim of this paper is to compare the properties of concrete beams in which three types of fibers are added individually. Steel fibers, polypropylene fibers and hybrid fibers were added to concrete in the weight ratio of four percentages in the preparation of four beam specimens. The fourth specimen did not contain fibers and acted as a control specimen. The dimensions of the beam specimens were 150 mm × 150 mm × 700 mm. The reinforced concrete beams of M30 grade concrete were prepared for casting and testing. Various parameters such as load carrying capacity, stiffness degradation, ductility characteristics and energy absorption capacity of FRC beams were compared with that of RC beams. The companion specimens were cast and tested to study strength properties and then the results were compared. All the beams were tested under three point bending under Universal Testing Machine (UTM). The results were evaluated with respect to modulus of elasticity, first crack load, ultimate load, and ultimate deflection. The test result shows that use of hybrid fiber improves the flexural performance of the reinforced concrete beams. The flexural behavior and stiffness of the tested beams were calculated, and compared with respect to their load carrying capacities. Comparison was also made with theoretical calculations in order to determine the load-deflection curves of the tested beams. Results of the experimental programme were compared with theoretical predictions. Based on the results of the experimental programme, it can be concluded that the addition of steel, polypropylene and hybrid fibers by 4% by weight of cement (but 2.14 % by volume of cement) had the best effect on the stiffness and energy absorption capacity of the beams