Impact of Employee Engagement on Performance

Employee engagement is a vast concept and has a wide area of interpretation and thus each organisation interprets the meaning of employee engagement on its own terms, knowledge, and culture. Employee engagement is a relationship between the employee and the enterprise, an engaged employee is the one who is entirely engrossed in and ardent about their work and so takes positive steps to further the organisation's prestige and interests. The construct employee engagement is built on the foundation of concepts like organisation citizenship behaviour, employee commitment, and job satisfaction. Though it relates to and besets these concepts but employee engagement is broader in scope. In today's scenario organisations have started looking out for ways more stronger than only monetary incentives to keep employees involved and work towards goals, hence comes the role of employee engagement which helps the employees realise they are a part of the organisation and thus employees are emotionally connected to their organization and highly involved in their job with a great enthusiasm for the success of their employer, going an extra mile beyond the employment contractual agreement assuming all their efforts leads to the growth of what already belongs to them. Since Employee engagement is a fairly novel concept thus a lot of measurement metrics are not present to find out direct relationship between employee engagement and its impact on the performance of employees thus the purpose of this paper is to find out an Impact of employee engagement on the performance of the employees

Protein Tertiary Model Assessment Using Granular Machine Learning Techniques

The automatic prediction of protein three dimensional structures from its amino acid sequence has become one of the most important and researched fields in bioinformatics. As models are not experimental structures determined with known accuracy but rather with prediction it’s vital to determine estimates of models quality. We attempt to solve this problem using machine learning techniques and information from both the sequence and structure of the protein. The goal is to generate a machine that understands structures from PDB and when given a new model, predicts whether it belongs to the same class as the PDB structures (correct or incorrect protein models). Different subsets of PDB (protein data bank) are considered for evaluating the prediction potential of the machine learning methods. Here we show two such machines, one using SVM (support vector machines) and another using fuzzy decision trees (FDT). First using a preliminary encoding style SVM could get around 70% in protein model quality assessment accuracy, and improved Fuzzy Decision Tree (IFDT) could reach above 80% accuracy. For the purpose of reducing computational overhead multiprocessor environment and basic feature selection method is used in machine learning algorithm using SVM. Next an enhanced scheme is introduced using new encoding style. In the new style, information like amino acid substitution matrix, polarity, secondary structure information and relative distance between alpha carbon atoms etc is collected through spatial traversing of the 3D structure to form training vectors. This guarantees that the properties of alpha carbon atoms that are close together in 3D space and thus interacting are used in vector formation. With the use of fuzzy decision tree, we obtained a training accuracy around 90%. There is significant improvement compared to previous encoding technique in prediction accuracy and execution time. This outcome motivates to continue to explore effective machine learning algorithms for accurate protein model quality assessment. Finally these machines are tested using CASP8 and CASP9 templates and compared with other CASP competitors, with promising results. We further discuss the importance of model quality assessment and other information from proteins that could be considered for the same

Study On Financial Education Programs For Entrepreneurs

This study investigates how financial education initiatives significantly impact individuals' intentions to pursue entrepreneurship. Through an analysis of these programs' effects on risk management, strategic thinking, and financial literacy, the research demonstrates the variety of ways in which these initiatives influence people's willingness to pursue entrepreneurial endeavors. In order to increase efficacy, the study highlights the significance of program design, delivery excellence, and continuing support systems. Positive effects are further enhanced by real-world case studies and applicability to a variety of entrepreneurial scenarios. Tailored program design, interactive learning strategies, all-inclusive support systems, flexibility in response to technology advancements, association with professionals in the field, and long-term effect evaluations are among the suggestions. By putting these recommendations into practice, financial education programs may become even more successful, producing a resilient and driven generation of company owners ready for the challenges of the competitive business environment

One-Minute Derivation of the Conjugate Gradient Algorithm

One of the great triumphs in the history of numerical methods was the discovery of the Conjugate Gradient (CG) algorithm. It could solve a symmetric positive-definite system of linear equations of dimension N in exactly N steps. As many practical problems at that time belonged to this category, CG algorithm became rapidly popular. It remains popular even today due to its immense computational power. But despite its amazing computational ability, mathematics of this algorithm is not easy to learn. Lengthy derivations, redundant notations, and over-emphasis on formal presentation make it much difficult for a beginner to master this algorithm. This paper aims to serve as a starting point for such readers. It provides a curt, easy-to-follow but minimalist derivation of the algorithm by keeping the sufficient steps only, maintaining a uniform notation, and focusing entirely on the ease of reader

One-Minute Derivation of the Conjugate Gradient Algorithm

One of the great triumphs in the history of numerical methods was the discovery of the Conjugate Gradient (CG) algorithm. It could solve a symmetric positive-definite system of linear equations of dimension N in exactly N steps. As many practical problems at that time belonged to this category, CG algorithm became rapidly popular. It remains popular even today due to its immense computational power. But despite its amazing computational ability, mathematics of this algorithm is not easy to learn. Lengthy derivations, redundant notations, and over-emphasis on formal presentation make it much difficult for a beginner to master this algorithm. This paper aims to serve as a starting point for such readers. It provides a curt, easy-to-follow but minimalist derivation of the algorithm by keeping the sufficient steps only, maintaining a uniform notation, and focusing entirely on the ease of reader

Verification of knowledge shared across design and manufacture using a foundation ontology

Seamless computer-based knowledge sharing between departments of a manufacturing enterprise is useful in preventing unnecessary design revisions. A lack of interoperability between independently developed knowledge bases, however, is a major impediment in the development of a seamless knowledge sharing system. Interoperability, being an ability to overcome semantic and syntactic differences during computer-based knowledge sharing can be enhanced through the use of ontologies. Ontologies in computer science terms are hierarchical structures of knowledge stored in a computer-based knowledge base. Ontologies have been accepted by all as an interoperable medium to provide a non-subjective way of storing and sharing knowledge across diverse domains. Some semantic and syntactic differences, however, still crop up when these ontological knowledge bases are developed independently. A case study in an aerospace components manufacturing company suggests that shape features of a component are perceived differently by the designing and manufacturing departments. These differences cause further misunderstanding and misinterpretation when computer-based knowledge sharing systems are used across the two domains. Foundation or core ontologies can be used to overcome these differences and to ensure a seamless sharing of knowledge. This is because these ontologies provide a common grounding for domain ontologies to be used by individual domains or department. This common grounding can be used by the mediation and knowledge verification systems to authenticate the meaning of knowledge understood across different domains. For this reason, this research proposes a knowledge verification framework for developing a system capable of verifying knowledge between those domain ontologies which are developed out of a common core or foundation ontology. This framework makes use of ontology logic to standardize the way concepts from a foundation and core-concepts ontology are used in domain ontologies and then by using the same principles the knowledge being shared is verified. The Knowledge Frame Language which is based on Common Logic is used for formalizing example ontologies. The ontology editor used for browsing and querying ontologies is the Integrated Ontology Development Environment (IODE) by Highfleet Inc. An ontological product modelling technique is also developed in this research, to test the proposed framework in the scenario of manufacturability analysis. The proposed framework is then validated through a Java API specially developed for this purpose. Real industrial examples experienced during the case study are used for validation

Mobile Computing in Physics Analysis - An Indicator for eScience

This paper presents the design and implementation of a Grid-enabled physics analysis environment for handheld and other resource-limited computing devices as one example of the use of mobile devices in eScience. Handheld devices offer great potential because they provide ubiquitous access to data and round-the-clock connectivity over wireless links. Our solution aims to provide users of handheld devices the capability to launch heavy computational tasks on computational and data Grids, monitor the jobs status during execution, and retrieve results after job completion. Users carry their jobs on their handheld devices in the form of executables (and associated libraries). Users can transparently view the status of their jobs and get back their outputs without having to know where they are being executed. In this way, our system is able to act as a high-throughput computing environment where devices ranging from powerful desktop machines to small handhelds can employ the power of the Grid. The results shown in this paper are readily applicable to the wider eScience community.Comment: 8 pages, 7 figures. Presented at the 3rd Int Conf on Mobile Computing & Ubiquitous Networking (ICMU06. London October 200

High sensitive C reactive protein as an inflammatory indicator in preeclampsia

Background: Preeclampsia is one of the most serious complications of pregnancy and one of the leading cause of maternal, prenatal morbidity and mortality. The present study was carried out to estimate serum high sensitive C- reactive protein in both mild and severe preeclampsia as an indicator of inflammation and to correlate Hs-CRP with blood pressure.Methods: A case control study was conducted in the Department of Biochemistry and Department of Obstetrics and Gynecology, MIMER Medical College and Bhausaheb Sardesai Rural Hospital Talegaon Dabhade, Pune. The study group include 50 cases of normal pregnant women, 43 clinically diagnosed cases of mild preeclampsia and 7 cases of severe preeclampsia in second and third trimester of pregnancy. 2 ml venous blood samples was collected from all the study participants for estimation of Hs-CRP by ultra-sensitive immunoturbidometric assay spin react method.Results: There was significant increase in the mean serum Hs-CRP levels in normal pregnant women and mild preeclamptic women (p<0.001). Serum Hs-CRP levels were significantly higher in severe preeclamspia than mild preeclamptic women (p<0.001). The degree of inflammation increases as HsCRP rises. Hence, present study shows that HsCRP levels increases as disease progresses from mild to severe condition. Significant positive correlations was found between Hs-CRP and Blood Pressure in preeclampsia.Conclusions: In preeclampsia there is an exaggeration of systemic inflammatory response that might induce reactive oxygen species which further induces endothelial dysfunction. This leads to clinical symptoms of hypertension and proteinuria in preeclampsia. Early detection might minimise systemic complications and maternal death due to preeclampsia. Hence, HsCRP may be used as an important indicator of severity of preeclampsia

Introducing medical parasitology at the University of Makeni, Sierra Leone

The file attached to this record is the author's final peer reviewed version.Capacity building in Sierra Leone (West Africa) is critical to prevent potential future outbreaks similar to the 2013-16 Ebola outbreak that had devastating effects for the country and its poorly developed healthcare system. De Montfort University (DMU) in the United Kingdom (UK), in collaboration with parasitologists from the Spanish Universities of San Pablo CEU and Miguel Hernández de Elche, is leading a project to build the teaching and research capabilities of medical parasitology at the University of Makeni (UniMak, Sierra Leone). This project has two objectives: a) to introduce and enhance the teaching of medical parasitology, both theoretical and practical; and b) to implement and develop parasitology research related to important emerging human parasites such as Cryptosporidium spp. due to their public health significance. Two UniMak academics, hired to help initiate and implement the research part of the project, shared their culturally sensitive public health expertise to broker parasitology research in communities and perform a comprehensive environmental monitoring study for the detection of different emerging human parasites. The presence of targeted parasites are being studied microscopically using different staining techniques, which in turn have allowed UniMak’s academics to learn these techniques to develop new practicals in parasitology. To train UniMak’s academics and develop both parts of our project, a DMU researcher visited UniMak for two weeks in April 2019 and provided a voluntary short training course in basic parasitology, which is currently not taught in any of their programmes, and was attended by 31 students. These sessions covered basic introduction to medical parasitology and life-cycle, pathogenesis, detection, treatment and prevention of: a) coccidian parasites (Cryptosporidium, Cyclospora and Cystoisospora); b) Giardia intestinalis, Entamoeba and free-living amoebas; c) malaria and d) microsporidia. A theoretical session on common staining techniques was also provided. To facilitate the teaching and learning of these parasites, the novel resource DMU e-Parasitology was used, a package developed by the above participating universities and biomedical scientists from the UK National Health Service (NHS): http://parasitology.dmu.ac.uk/ index.htm. Following the two weeks of training, UniMak’s academics performed different curriculum modifications to the undergraduate programme ‘Public Health: Medical Laboratory Sciences’, which includes the introduction of new practicals in parasitology and changes to enhance the content of medical parasitology that will be subjected to examination. Thus, a new voluntary practical on Kinyoun stain for the detection of coccidian parasites was introduced in the final year module of ‘Medical Bacteriology and Parasitology’; eighteen students in pairs processed faecal samples from pigs provided by the Department of Agriculture and Food Security from a nearby farm. Academics at UniMak used the Kinyoun staining unit (available at http://parasitology.dmu.ac.uk/learn/lab/Kinyoun/story_html5.html; [1]) to deliver this practical. Although our project is at a preliminary stage, it has been shown to be effective in promoting the introduction and establishment of medical parasitology at UniMak and could be viewed as a case-study for other universities in low-income countries to promote the United Nations (UN) Sustainable Development Goals (SDGs) and improve public health understanding of infectious diseases