Torky Sultan

A Proposed Integrated Approach for BI and GIS in Health Sector to Support Decision Makers (BIGIS-DSS)

This paper explores the possibilities of adopting Business Intelligence (BI), and Geographic Information System (GIS) to build a spatial intelligence and predictive analytical approach. The proposed approach will help in solving spatial problem which faces decision makers at health sector. The proposed spatial analytical approach will cover three main health planning issues. These issues are tackling health inequalities through geospatial monitor for inequalities in distribution of health units and its services, support decision-making with predictive analytics for common health indicators, and geoprocessing for input layers through dynamic health map and motion charts to support decision making.

Semantic Conflicts Reconciliation as a Viable Solution for Semantic Heterogeneity Problems

t—Achieving semantic interoperability is a current challenge in the field of data integration in order to bridge semantic conflicts occurring when the participating sources and receivers use different or implicit data assumptions. Providing a framework that automatically detects and resolves semantic conflicts is considered as a daunting task for many reasons, it should preserve the local autonomy of the integrated sources, as well as provides a standard query language for accessing the integrated data on a global basis. Many existing traditional and ontology-based approaches have tried to achieve semantic interoperability, but they have certain drawbacks that make them inappropriate for integrating data from a large number of participating sources. We propose semantic conflicts reconciliation (SCR) framework, it is ontology-based system in which all data semantics explicitly described in the knowledge representation phase and automatically taken into account through the interpretation mediation service phase, so conflicts detected and resolved automatically at the query time.

Dynamic AI-Geo Health Application based on BIGIS-DSS Approach

Public health organizations use GIS on a daily basis for input, storage, manipulation, and output of geographic information which provides a powerful tool for public health assessment and monitoring in remote locations and developing countries (1). Information technology is taking on a new level of importance due to its business intelligence application solutions. Our proposal is aimed at integrating these two different worlds in a single dynamic framework using web technology at health sector. Dynamic AI-Geohealth application based on BIGIS_DSS approach uses GIS tools and techniques to convert geographic information and analysis of data that becomes valuable information to make more informed business decisions and rational. Thus, the approach is not just a technical or business analytical process; But discipline which includes both. This paper explores the adopting Business Intelligence (BI) with Geographic Information System (GIS) to build a spatial artificial intelligence and predictive analytical approach. Also this paper will explores case research for implementation of proposed approach in developing countries like Egypt at health sector as dynamic health map web application. The proposed approach helps in solving spatial problem which faces decision makers at health

A Proposed Defect Tracking Model for Classifying the Inserted Defect Reports to Enhance Software Quality Control

CONFLICT OF INTEREST: NONE DECLARED Defect tracking systems play an important role in the software development organizations as they can store historical information about defects. There are many research in defect tracking models and systems to enhance their capabilities to be more specifically tracking, and were adopted with new technology. Furthermore, there are different studies in classifying bugs in a step by step method to have clear perception and applicable method in detecting such bugs. This paper shows a new proposed defect tracking model for the purpose of classifying the inserted defects reports in a step by step method for more enhancement of the software quality.

Multi-Criteria Business Intelligence Approach

Multi Criteria Business Intelligence approach (MCBI) aims to enhancement Business Intelligence Applications (BIA) by applying Multi-Criteria Decision Making (MCDM). MCBI approach contributes to improve Business Intelligence Decision Support System (BIDSS) for BIA. Also MCBI approach presents a standard method to evaluate and select business decisions. The recommended business decision is the suitable and optimal choice to implement. The proposed model for MCBI approach that consists of five major components. The first component is business objectives, problem definition and main goals. The second component is a business heterogeneous data treatment which gathering from different resources and related with different areas. The third component is a unified business intelligence databases. The fourth component is a business intelligence processing. The fifth component is a evaluating the business decisions to select the suitable and optimal solution.

Bioinformatics data mining tool using data collected from red blood cells hemolysate

The mathematical model described in this paper is based on a discovery of a phenomenon related to red blood cells. In this phenomenon, the hemolysate of red blood cells reacts with antibodies from the plasma of the same patient. Using proteomics approach to identify those hemolysate antigens and then build a database containing those antigens can help in diagnosis, prognosis, and treatment of disease disorders. In this paper, algorithms and a tool, based on the mathematical model and the database, are described. The tool is tested using hypothetically generated data and it achieved satisfying results as it detected the proposed diseases.