Deriving Value From Change Management

A theoretical analysis on the perception of change management initiatives, with a focus on how one can one optimize and derive increased value from change management efforts. The context of this capstone is to determine the degree to which change management initiatives are successful. I intend to explore and catalogue reasons that control and predict change management success, and provide best practices identified from the scholarly literature. Creating a base level of knowledge, I present a literature review in which I summarize from the body of knowledge key theories and contributions to effective change management in the modern workplace. Building upon this baseline, I present the details of why it is important to derive specific value from a change management initiative, outlining the key areas where the facilitation of the strategy of change can promote impact. Based on the research, it is apparent that change should always be results driven. It is imperative for change agents; leaders, managers or even consultants to create a sense of urgency amongst the community chartered to implement change. A collaborative environment that facilitates two-way communication from leadership and the community at large creates a heightened sense of change ownership and active involvement which are crucial to the change effort’s success. A change path must be outlined and defined, planning a change effort is involved as various facets of an organization and its people need to be considered. Communication initially, and throughout the change process is imperative

Geneva Thorne : A Narrative Poem and A Picture of Pioneer Life Revealing The Grave Foundations of Culture In Kansas and The Slight Structure Built Thereupon

This thesis is a narrative poem about frontier life in Kansas

Effects of Photoperiod on the Occurrence of Symbiotic Rotifers, Nematodes and Branchiobdellids of Two Orconectid Species of Crayfishes

Representative specimens of O. immunis and O. pellucidus were brought to the laboratory in order to investigate the influence of light on the occurrence of the symbionts encountered during the preliminary field study. After one week of acclimating the crayfishes they were distributed among environments control chambers that permitted exposure of the hosts and symbionts to 1) continuous light (C.L.), 2) a daily cycle of 12 hours of light and 12 hours of darkness (12L-12D) and 3) continuous darkness (C.D.)

Location based Continuous Query Processing over Geo-streaming Data

In recent years, many data-intensive and location based applications have emerged that need to process stream data in applications such as network monitoring, telecommunications data management, and sensor networks. Unlike regular queries, a continuous query exists for certain period of time and need to be continuously processed during this time. The algorithms used for data processing for the traditional database systems are not suited to tackle complex and various continuous queries over dynamic streaming data. The indexing for finite queries is preferred to indexing on infinite data to avoid expensive operations of index maintenance. Previous related work focused on moving queries on static objects or static queries on moving object. But now-a-days queries as well as objects are dynamic. So, hybrid indexing for queries significantly reduces the space costs and scales well with the increasing data. To deal with the speed of unbounded data, it is necessary to use data parallelism in query processing. The data parallelism in query processing offers better performance, availability and scalability

Bacterial vaginosis: impact of treatment and associated risk factors: a cross section study

Background: Bacterial vaginosis (BV) is a condition caused by an overgrowth of normal vaginal flora. Many socio-demographic factors are associated with bacterial vaginosis. Antibiotic resistance to some organism is a challenge in treatment of bacterial vaginosis. Methods: This cross-sectional study was conducted including 100 women with reproductive age group presenting with complain of vaginal discharge. After clinical examination, vaginal swab was collected of patients who gave consent for same. Socio-demographic characteristics were recorded and risk factors were assessed. The slide smears were prepared from vaginal swabs, and the slides were heat-fixed, gram-stained and examined under oil immersion objective. Each slide was then graded as per the standardized quantitative morphological classification method developed by Nugent. Identification of bacteria to genus and/or species level was done by employing an array of routine biochemical tests for Gram-positive bacteria for Gram-negative bacteria. In vitro antibacterial susceptibility testing of bacterial isolates was performed by the Kirby-Bauer disc diffusion method. Sensitivity test results were interpreted according to the Clinical and Laboratory Standards Institute. Results: High incidence of bacterial vaginosis was found among 35 to 45 years age group (63.8%), married females (63.9%), illiterate (100%), females with more than 3 sexual partners (66.7%), those with any co-morbidity (80%) and females not using any method of contraception (100%). E coli (28%) was predominant organism causing bacterial vaginosis followed by Gardenella vaginalis (20%) among the gram-negative bacteria. Among gram positive bacterial S. pyogen (2%) and S. agalactiae (2%) were present. Drug resistance to trimethoprim/sulfamethxazole, erythromycin, cefoxitin, ceftriaxone and gentamycin was detected. Conclusions: Higher age, illiteracy, multiple sexual partners and absence of contraception use can increase risk of bacterial vaginosis. Gram negative organisms are common cause of bacterial vaginosis and they are resistant to trimethoprim/sulfamethoxazole and erythromycin.

Characterising two-pathogen competition in spatially structured environments

Different pathogens spreading in the same host population often generate complex co-circulation dynamics because of the many possible interactions between the pathogens and the host immune system, the host life cycle, and the space structure of the population. Here we focus on the competition between two acute infections and we address the role of host mobility and cross-immunity in shaping possible dominance/co-dominance regimes. Host mobility is modelled as a network of traveling flows connecting nodes of a metapopulation, and the two-pathogen dynamics is simulated with a stochastic mechanistic approach. Results depict a complex scenario where, according to the relation among the epidemiological parameters of the two pathogens, mobility can either be non-influential for the competition dynamics or play a critical role in selecting the dominant pathogen. The characterisation of the parameter space can be explained in terms of the trade-off between pathogen's spreading velocity and its ability to diffuse in a sparse environment. Variations in the cross-immunity level induce a transition between presence and absence of competition. The present study disentangles the role of the relevant biological and ecological factors in the competition dynamics, and provides relevant insights into the spatial ecology of infectious diseases.Comment: 30 pages, 6 figures, 1 table. Final version accepted for publication in Scientific Report

Third Annual Report of the Better Farming Club of Steele County

Farm Management,

Research Review on Plant Leaf Disease Detection utilizing Swarm Intelligence

Plants are both a source of food and resource for mankind. In country like India, plants have a wide application keeping in mind the agricultural and medicine research area. Out of several thousands of classes of medicinal plants, few may get vanished soon due to global warming, lack of knowledge of different species and several other diseases. Plants assume a significant job in human life being one of the critical variables of natural way of life; on the other hand couples of them are toxic and harmful to mankind as well. Thus, protecting the plants with medicinal and food values, as well as identifying the unknown species of the plants is the need of an hour. The study of plants classification with the help of different features of the leaf can be done in order to build an ideal database for the farmers and professional botanist. This could also serve for the automatic plant leaf disease detection system. The loss of crops as well as plants with medicinal values due to diseases is of the core concern to plant security. It is utmost important to design the essential infrastructure for the detection of the diseases that are observed in plant leaves. An optimal system for plant leaf detection can further guide for remedial solution. This work reviews different methodologies for plant leaf detection, its classification and detection of plant leaves diseases. Swarm Intelligence based techniques impressively address the real time optimization problems which motivates the further research work