Mining Frequent Sequential Patterns

In recent times, the urge to collect data and analyze it has grown. Time stamping a data set is an important part of the analysis and data mining as it can give information that is more useful. Different mining techniques have been designed for mining time-series data, sequential patterns for example seeks relationships between occurrences of sequential events and finds if there exist any specific order of the occurrences. Many Algorithms has been proposed to study this data type based on the apriori approach. In this paper we compare two basic sequential algorithms which are General Sequential algorithm (GSP) and Sequential PAttern Discovery using Equivalence classes (SPADE). These two algorithms are based on the Apriori algorithms. Experimental results have shown that SPADE consumes less time than GSP algorithm.

Capital Adequacy A Moderating Effect of Asset Growth on Performance of Nigerian Agricultural Firms

This study examines capital adequacy and the moderating impact of asset growth on the performance of firms in the agricultural sector. 4 listed agricultural firms were examined over a period of 10 years and data were extracted from their financial statements which were analyzed through a STATA 13 tool of analysis. Regression, correlation matrix and descriptive methods of analysis were employed to present and analyze results. Other post estimation tests like skewness and kurtosis test, Variance Inflation Factor test, specification test, heteroskedasticity tests and hausman test to select between fixed effect and random effect regression model were conducted to ensure robustness of results. The fixed effect stochastic longitudinal regression analysis model was adopted as guided by the hausman test. From the findings posited by the study, liquidity structure, liquidity structure moderated by asset growth and the combined effect of firm size moderated by asset growth were found to be significantly impacting on return on asset of firms at 1% level of significance. Firm size was found not to have any significant impact on return on assets. It was therefore recommended that the management should ensure considerable excess of current assets over current liabilities at all times so that there will always be positive liquidity structure; management should ensure consistent and prudent capital acquisition to ensure larger firm size; management should ensure steady asset growth by asset revaluation and new acquisition over time; the regulatory authority in the agricultural sector should establish a firm size benchmark below which no firm should operate.

Risk Management and Organizational Resilience: Analysis of the Italian Scenario During Covid-19 Pandemic, with A Look at the Challenges of Technology and Sustainability

The Coronavirus emergency represents an epochal challenge for all world health organizations. In these times of profound destabilization of healthcare organizations, become urgent some thoughts on how to deal with the organization and re-engineering process as well as on concepts, relatively new, such as "resilience" and "business continuity". The company management need having to predict, design and plan a profound process of change in their Clinical and Corporate Governance. With the implementation of phases 2 and 3 of management of the pandemic and the coexistence of doctors and citizens with the new Coronavirus, it has become a priority to develop territorial models of assistance to established or suspected Covid patients, starting with the creation of monitoring networks based on the model of the “sentinel” general practitioner. One of the main concerns of Healthcare, since the beginning of the Covid-19 emergency has been to get closer to the citizen-patient. It is therefore necessary to find stimuli to restart with new methods of care, new health and social-health services, moving the current care paradigm for Covid-19 from the hospital to the territory, optimizing the constituent elements of the districts, primary care and general practice in a multidisciplinary approach.

The Location and Diameter of the Primary Maxillary Sinus Ostium in Malaysians: A Cone-Beam Computerized Tomography Study

Rhinosinusitis is one of widely spread diseases in the region and the role of the anatomical variations in its pathogenesis remains unresolved. A retrospective study using CBCT scan was employed to locate and measure the diameter of 320 primary maxillary ostium (PMO) (n = 160 subjects) among the Malay and Chinese populations (Mongoloid race) in Malaysia. Image analysis was performed using the i-CAT Vision Software, employing the multiplanar reconstruction window in which axial, coronal and sagittal planes were visualized in 0.3 mm intervals. The mean diameter of the PMO was significantly larger in the Chinese than the Malay. Females had larger size than the male and bilateral asymmetry was noticed, where the right side PMO was larger than the left side (p < 0.05). In addition, PMO opened more in the posterior third position of the hiatus semilunaris (61.9%) than anterior and middle third. The PMO showed a statistically significant posteriorly placed position in the Chinese than the Malays and this was more evident in the right side PMO (p < 0.01). In conclusion, the PMO commonly opens in the posterior third of the hiatus semilunaris and its diameter is significantly greater in the Chinese female with evidence of bilateral asymmetry. Awareness the anatomical variation of the Ostium diameter and location among the Malay and Chinese populations potentially has important clinical effects during surgical procedures.

5S Dashboard Design Principles for Self-Service Business Intelligence Tool User

Non–information technology (IT) professionals and nonexpert casual users are increasingly adopting self-service business intelligence (SSBI) tools (such as Tableau, Qlik, and Power BI) to create data visualization dashboards. This study identified the most relevant dashboard design principles for SSBI tool users. The research approach included organizing a focus group in which most of the participants were non-IT professionals in health care, extracting recommended principles from the literature, applying these recommended principles by using data on quality of diabetes care to design relevant dashboards, and proposing the following 5S dashboard design principle framework: 1) seeing both the forest and trees, 2) simplicity through self-selection, 3) simplicity through significance, 4) simplicity through synthesis, and 5) storytelling. The third and fourth principles are novel and provide solutions to decision-making problems (such as conflicting results from excessive and discordant indicators) encountered by health care professional in the public sector as well as in other domains. The 5S dashboard design principles are easily memorized and practical and thus enable non-IT professionals and nonexpert casual users to design insightful dashboards efficiently by using SSBI tools.

Big Data Research: Database and Computing

Big data research has become popular and exciting studies in almost all scientific fields such as biology, chemistry, epidemiology, medicine and drug discovery. The various systems and platforms produce large amounts of data every day. It will be very helpful for the researchers and workers to deal with big data if the practical database and useful software are introduced in time. The Journal of Big Data Research (JBR) supplies an efficient and open access publishing platform for big data research. The first issue of JBR aims to foster the dissemination of high-quality big data studies in the biological, medical and chemical database as well as the new algorithm and software for big data processing. The database and computing framework are selected to introduce the development of big data in the biological, medicine and drug discovery. The mature and functional database can be serviced in big data research of scientific fields. It promotes the scientists to extract the useful and essential dataset from the massive data. The grid computing and cloud computing supplies a new paradigm that offers an effective framework of computing and services. The research papers are welcomed from the scopes of the practical database, new algorithm and software for big data studies. All these kinds of papers not only provide the effective application methods and platforms, but also give a good promising future for big data research.