The high pace rise in online as well as offline multimedia unannotated data and associated mining applications have demanded certain efficient mining algorithm. Multiple instance learning (MIL) has emerged as one of the most effective solutions for huge unannotated data mining. Still, it requires enhancement in instance selection to enable optimal mining and classification of huge multimedia data. Considering critical multimedia mining applications, such as medical data processing or content based information retrieval, the instance verification can be of great significance to optimize MIL. With this motivation, in this paper, Multi-Instance, Multi-Cluster based MIL scheme (MIMC-MIL) has been proposed to perform efficient multimedia data mining and classification with huge unannotated data with different features. The proposed system employs softmax approximation techniques with a novel loss factor and inter-instance distance based weight estimation scheme for instance probability substantiation in bags.

In this paper we established a traveling wave solution by the ( -expansion method for nonlinear partial differential equations (PDEs).The proposed method gives more general exact solutions for two different types of nonlinear partial differential equations such as the improved Korteweg de Vries equation and the two dimension Korteweg de Vries (2D KdV) equations.

Designing to make use of the climatic conditions of the site has always been a challenge; especially when buildings are to be naturally ventilated. The current study examines how effective orientation is as a parameter for the reduction of cooling loads in multi-storey office buildings. The approach is experimental in nature where a case-study building was selected and a parametric simulation with T as the software was applied. The results indicated among others that whiles the annual cooling load for the actual orientation is 288.43kWh.m².a¹; there is an 11.81kWh.m².a¹ reduction when the orientation is 270° away from the actual of 0°. Again, in terms of cooling loads per unit floor areas, the 270° angle performed better. This indicates that if attention is paid to orientation and aspect ratio as parameters during the design of a structure, it would go a long way in ensuring that the design behaves sustainably. It is recommended that the orientation along the north and south axis should be adhered to as it aids in the free flow of natural ventilation through the indoor spaces.

Bacterial blood stream infections can lead to life threatening sepsis that requires rapid antimicrobial treatment otherwise may lead to morbidity and mortality of patients. Blood culture is gold standard technique which provides essential information for the diagnosis and appropriate medication to save life of affected patients. Present study was conducted to determine the bacteriological profile of blood stream infections and their antibiotic susceptibility pattern in patients visiting Janamaitri Hospital, Balaju, Kathmandu, Nepal. A total of 838 blood samples were collected from the clinically suspected cases of bacteremia and septicaemia. Isolates were identified by standard biochemical tests, and antibiotic susceptibility test was performed by using CLSI guidelines. Positive blood culture was obtained in 61/838 (7.28%) where gram negative accounted for 48/61 (78.69%) in which Salmonella Paratyphi A was leading organisms and gram positive accounted for 13/61(21.31%) in which Staphylococcus aureus was leading organisms.

Women migrants do find themselves at the advanced stages in their struggle to combat life in town. Such stages are what they recognize as achievements to them. However, as women, they do also face challenges. Looking at women achievements and challenges with a gender lens, requires narrowing the inquiry on how patriarchy ideology can influences the two. This work serves to explain how patriarchy ideology determines what rural-urban women migrants regards as achievement; the challenges they face and efforts they make to release themselves from such challenges. In-depth interview was conducted among the Gogo rural-urban women migrants in both Dodoma town and Dar es Salaam city. This aimed at enhancing the respondents to build up their life stories as regards their experiences within patriarchy system in their areas of origin, the way they negotiated through it and how it influenced their integration process in destination areas. It was found out that for women migrants, acquiring whatever they missed within patriarchy system in rural areas is an achievement for them. However, women migrants are still surrounded by patriarchy system in town which becomes sources of challenges in their integration process in town. Moreover, the patriarchy ideology among women and the society at large in town, do affect they way women fight against challenges the face. This implies that patriarchy ideology has got its roots in every place where men are, be it in rural areas or in town. In order to eliminate its intended negative impact over women, much effort has to be directed toward educating men on the need of gender equality in society for their benefit and the society at large. Women will hardly find their right within a strong patriarchy system wherever they are.

The prime objectives of this study is to analysis the individual behavior in both bull and bear markets of Pakistan. In this paper, we have examined the preferences, attitude towards risk and varying market condition. We have taken the data of 100 companies from various sectors for this purpose the data of four years have been collected. Empirical evidences have shown that we have used the abnormal returns, volatility and systematic risk for the purpose of measure of risk. Due to various behavior biases, the overall individual behaviors are the different. This study is showing that bull and bear behaviors are associated with the Book to market valuation we are also trying to show that overconfidence has impact on the investment decision. The objectives of this study are 1) To analyze the individuals behavior in the different market condition.2) In the Bull and Bear market individuals towards risk.3) impact of overconfidence on the different market situation.

The emerging paradigm called ‘Workplace Spirituality’ is interpreted by many in many ways. The recent researches on ‘Workplace Spirituality’ reveal that there is a common set of theme that most of the sources agree upon. Most of the researchers in this field use reference from “The Handbook of workplace Spirituality and Organizational Performance” by Giacalone and Jurwierokz (2003). Ashmos and Duchon(2000) describe workplace Spirituality as involving three levels, individual, work-unit and organization-wide. The work-unit dimension (group level) entails how much employees have a sense of connection and community with their management, principal, head of the department, colleagues and students; as well as assessing the extent to which they are caring and encouraging.

In a previous tutorial article I looked at a proximity coefficient and, in the light of that proximity created a vectordistance matrix and used it to construct a hierarchical tree using different hierarchical clustering methods which will be the basis for exploratory multivariate analysis. The present article deals with three topics: (i) standardization for variable scales variation, (ii) normalization for sample length variation, and (iii) dimensionality reduction or minimization of data space. These techniques reflect the author’s academic background and particular area of interest and are, by necessity, not a particular purpose and are straightforwardly applicable to other kinds of data, and thus to a wide range of analysis in Linguistics. My treatment of these techniques is, necessarily, introductory and brief. I hope that this article will provide practitioners with an introductory overview of these techniques used for cluster analysis of electronic corpora of linguistic data. The assumption is that the data is in the form of an m x n matrix D in which, may require to transform it in various ways prior to cluster analyzing it. Standardized data matrix enables practitioners to measure the variation between n-variables and to cluster the cases they describe in common scales and values, regardless of their original scales and values. Normalized data matrix enables practitioners to eliminate the effect of variation in length among n-samples and to cluster them as if they were all (about) the same length, regardless of their original length. Dimensionality-reduced space data matrix enables practitioners to select and/or extract n-most interesting variables relevant to the research question and to visualize an existing pattern, regardless of the original space. A worked example is given to illustrate the effect each transformation technique has on a given data matrix. These transformation techniques have their own strengths and weakness but are beyond the scope of

The article is on a particular type of cluster analysis, agglomerative hierarchical analysis, and is a series of four main parts. The first part deals with proximity coefficients and the creation of a vector-distance matrix. The second part deals with the construction of the hierarchical tree and introduces a selection of clustering methods. The third deals with a variety of ways to transform data prior to agglomerative cluster analysis. The fourth deals with deals with measures and methods of cluster validity. The fifth and final part deals with hypothesis generation. The present article covers the first and second partsonly. It explains how agglomerative cluster analysis works by implementing it in a data matrix step by step. Different types of agglomerative hierarchical clustering methods are applied on purposely-made data matrix so different types of cluster structures are made from that same dataset. The last three parts will be covered in the next publication(s).There are many articles, tutorials, and books on this subject. The article has two main objectives: (1) to keep the discussion short and easy to understand by (hopefully) any reader and (2) to develop the motivation for using agglomerative hierarchical clustering to analyse any highdimensional data of interest with respect to some research question.

Conservation Voltage Reduction (CVR) is employed for peak load reduction and energy savings by electric utilities. Selecting feeders where the most benefit is realized from CVR is of interest. In the work here the theoretical CVR performance of over 1000 distribution feeders is evaluated based on circuit models and available load data. The feeders with the best CVR performance are identified, and characteristics of the efficient performing feeders are described. In identifying efficient performing feeders, load-voltage dependency factors for summer and winter are used in quasi-steady state power flow analysis. In addition, the Volt/VAR Control (VVC) scheme of a feeder with poor CVR performance is redesigned to improve its CVR performance. Results show that there can be considerable energy savings from investments in control schemes to improve CVR performance