In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.
Abstract-The Holy Quran, due to its unique style and allegorical nature, needs special attention about search and information retrieval issues. Many works have been done to accomplish keyword search from Holy Quran. The main problem in all these works is that these are either static or they does not provide us semantic search. In this paper, we propose that the concepts of ontology of semantic web can be applied for carrying out semantic search in Holy Quran. Index Terms-Framework, information retrieval, ontology, semantic search.
Automated formalization of legal text is a time-and effort-consuming task, but human-based validation consumes even more of both. The exchange of healthcare data in compliance with the medical privacy law requires experts with deep familiarity of its intricate provisions for verification. The article presents a medical relational model (MRM) for the extraction of logical rules from medical law, required to design a medical decision support system (MDSS) that facilitates the process of exchanging data electronically with minimum human intervention. The division of medical law into small concept classes makes it easier to formalize the legal text of medical law into logical rules. These logical rules are then used to make a precise decision in compliance with the law, after evaluating requests from different entities for different purposes in MDSS. Our methodology is to analyze the legal text and release records in compliance with the medical law. For developing countries where medical laws are not as mature as HIPAA (Health Insurance Portability and Accountability Act) in the USA, the proposed methodology can be adapted to build their MDSS based on MRM.
Capability Maturity Model Integration (CMMI) is a framework known for improving the quality of processes on consistent basis. This paper makes an attempt to explore, analyze and describe the impact of CMMI in terms of return on investment (ROI) for the IT industry. An IT organization who has acquired a maturity level of CMMI 2 is taken as case study. At first, in reference to the level of applied CMMI, a thorough study is completed. Afterwards the luxuries and limitations are studied and explored with reference to organizations applying the monetary terms using ROI framework. Finally, the presented research highlights the key benefits and difficulties in switching to CMMI from conventional quality assurance.
ABSTRACT… Introduction: National Health Information Exchange (NHIX) Systems are rapidly evolving. Due to the cyber infrastructure and improvements in communication technology, it is possible to share healthcare related data within a geographic region electronically among healthcare related autonomous entities such as physicians, hospitals, test laboratories, insurers, emerging Health Information Organizations (HIO), and even government departments. Study Design: Whether data are collected with the RCT, Quasi-experimentation or Triangulation etc., we present to explore a NHIX system for EHR that has also been implemented as a test case. We particularly propose to demonstrate a concept application, Medical Drop Box (MDB) with the key technological components of a future NHIX System for medical industry. Setting: Data from different medical settings have been used for testing the new system but the technological development has been done at IIU, Islamabad. Period: The proposed system is not time bond in terms of data collection. Basically the proposed system can handle data collected in any chunk of time in the history and can provide information as and when needed in future. Material & Methods: With MDB, a person is able to collect his/her health data and share it with the whole medical industry according to his/her own preferences and setting. Besides the technology for handing numerous forms of health care data, the main challenge of NHIX system is to allow individuals and associated medical entities to manage and share their medical information based on personal control and preferences given to each by medical laws, information rights and privacy rules. The main focus in this research paper is to make a standard medical application for the medical data that is in exchangeable format according to the standards defined in HL7. Results: The new system is able to make standardized Clinical document for medical data in exchangeable format according to HL7 standard. The MDB is the first step to setup NHIX system. With the help of MDB "Statistical Analyzer" now the health industry of the country can perform a variety of analysis for the future improvements in different health settings. Conclusions: The availability of medical data of patients on MDB cloud has improved Clinical Impact, created new Business & Services opportunities and reduced the overall Treatment Cost.
Keywords:Medical Drop Box (MDB), Randomized Controlled Trial (RCT), Health Information Organization (HIO), Health Law 7 (HL7), Clinical Impact, National Health Information Exchange (NHIX).
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