Clustering is considered as one of the most prominent solutions to preserve the energy in the wireless sensor networks. However, for optimal clustering, an energy efficient cluster head selection is quite important. Improper selection of Cluster Heads (CHs) consumes high energy compared to other sensor nodes due to the transmission of data packets between the cluster members and the sink node. Thereby, it reduces the network lifetime and performance of the network. In order to overcome the issues, we propose a novel Cluster Head selection approach using Grey Wolf Optimization algorithm (GWO) namely GWO-CH which considers the residual energy, intra-cluster and sink distance. In addition to that, we formulated an objective function and weight parameters for an efficient cluster head selection and cluster formation. The proposed algorithm is tested in different wireless sensor network scenarios by varying the number of sensor nodes and cluster heads. The observed results convey that the proposed algorithm outperforms in terms of achieving better network performance compare to other algorithms.

Automatic recognition of facial emotion plays an effective and important role in Human–Computer Interaction (HCI). There are various emotion recognition approaches have been proposed in the literature. The analytic face model consisted of a 26-dimensional geometric feature vector. These properties are used effectively to identify facial changes resulting from different expressions. The variation and uncertainties of these features make the emotion recognition problem more complicated. For decreasing these complications, we propose a distance-based clustering and uncertainty measures of the base new method for Emotion Recognition from Facial Expression using with automatically selects 19 diagnostic of Action Units (AUs) in 2D facial image using Type-2 Fuzzy inference system. The proposed system includes an automated generation scheme of the geometric facial feature vector. The proposed system has classified six facial expressions using the MUG Facial Expression database. The experimental results show that the proposed model is very efficient in uncertainty management policy and recognizes six basic emotions with an average precision rate of 86.175%.

Drivers drowsiness and fatigue decreases the vehicle management skills of a driver. The operator driving vehicle in night has become a significant downside today. Driver in a drowsiness state is the one among the important reason of increasing amount of road accidents and death. Hence the drowsiness detection of driver is considering as most active research field. Many ways are created recently to detect the drowsiness of driver. Existing methods can be classified in three categories based on physiological measures, performance measures of vehicles and ocular measures. Few ways are intrusive and distract the driver from comfortable driving. Some of the methods need expensive sensors for information handling. Therefore, a low cost, real time system to detect the drivers drowsiness developed in this paper. In this proposed system, real time video of driver records using a digital camera. Using some image processing techniques, face of the driver detected in each frame of video. Facial landmarks points on the drivers face is localized using one shape predictor .And calculating eye aspect ratio, mouth opening ratio, yawning frequency subsequently. Drowsiness is detected based on the values of these parameters. Adaptive thresholding method is used to set the thresholds. Machine learning algorithms were also implemented in an offline manner. Proposed system tested on the Face Dataset and also tested during real-time. The experimental result shows that the system is accurate and robust

Abstract\nPresent study assessed the pathogenic prevalence in municipal water and deep tube well water supplied across the Kashipur zone of Narayanganj city, Bangladesh and its subsequent health impact on the local community through conventional cultural methods. This study was also investigated the drug resistant pattern of the isolated bacteria form the water samples by Kirby-Bauer method. In case of the physico-chemical properties, most of the deep tube-well water was encountered the satisfactory level only sample 1, 3, 5 & 9 were found to be exited the marginal limit for dissolve oxygen however most of the samples of supplied water cross the marginal limit of all parameter (DO Temperature pH EC Salinity TDS Turbidity). Elevated numbers of pathogenic bacteria including Escherichia coli and Staphylococcus spp. were found in Both supplied (WASA) water within the range of (102-106 cfu/ml) and deep tube well water (102-104 cfu/ml). Additionally, proliferation of fecal coliforms, Klebsiella spp., Salmonella spp., Shigella spp., Vibrio spp. and Pseudomonas spp. was monitored among the supplied water but not in the deep tube well water. In both samples the heterotrophic bacteria was present within the range of 102 to 108 cfu/ml. Most of the bacteria was found to be resistant against more than one drug such as ampicillin (10 µg), ciprofloxacin (5 µg), ceftriazone (30 µg), penicillin (10 µg), nalidixic acid (30 µg) and vancomycin (30 µg). Hence, the municipal water of the study area was microbiologically unsafe, and the propagation of drug resistant strains was assumed to escalate the public health threat. A survey on public opinions was also conducted to evidently chalk out the impact of municipal water on the specific community studied.

Mineral oil in transformer is replaced by the ester oil due to its biodegradability and good thermal & dielectric properties. Ester oil plays a vital role in enhancing the design of high voltage apparatus, as it has better electric and thermal properties. In this paper, the impact of dielectric properties on the mixture of 20% ester oil and 80% mineral oil, due to the effect of TiO2 nanoparticles was studied. The optimum volume concentration of TiO2 nanoparticles was found based on the Corona Inception Voltage (CIV) and Break Down Voltage (BDV) and also the optimum concentration of nanoparticles having CTAB surfactant and having oleic acid surfactant was analyzed. The solubility of TiO2 in composite fluid depends upon the percentage weight of nanoparticles and surfactant. It is concluded that Titania (TiO2) nanoparticles dispersed composite oil having CTAB surfactant has greater CIV and BDV when compared to the oleic acid surfactant. It is also found that Negative Direct Current (NDC) voltages have higher breakdown voltage than Positive Direct Current (PDC) voltages and AC voltages. The statistical analysis depending upon the CIV and BDV of the composite oil, nanofluid and nanofluid with surfactants were made.

__The article reveals the essence of methodological and applied recommendations for the development of environmental management systems of industrial enterprises. As a result of the study, the structure of the environmental management system is clarified, alternative options for modeling the development of this system are considered, and the stages of formation of the environmental potential of the enterprise are highlighted.

__The practical importance of formalizing the formation processes of development strategy of national financial sector (NSF) of Ukraine is proved. The existing methodological approaches to the NSF formation depending on the position regarding the participation of foreign capital in the financial sector, as well as on the existing and desired number of functioning financial institutions are revealed. The methodological approach to the forming the NSF development strategy on the basis of its structural parameterization is proposed. The proposed approach ensures the procedure optimality by checking the compliance developed by the input, output and internal parameters of its validity. The essence and features of each stage of the procedure, their sequence are characterized, as well as the reasonably selected parameters and the sequence of integrating the partial parameters into the integral ones with the further interpretation of the obtained values are explained. The proposed structural parameterization is practically suitable for application and provides control to the developers of the NSF development strategy over the logic and efficiency of its development.