Computer Communication & Collaboration

Computer Communication & Collaboration

ISSN:2292-1028 (Print)    ISSN:2292-1036(Online)

Vol. 3, Issue 1 (2015.2)

Table of Contents

Editorial Board of CCC

Articles

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1. Neutrosophic Soft Matrix And It's Application in Solving Group Decision Making Problems from Medical Science [Download PDF]

Authors:

Tanushree Mitra Basu, Shyamal Kumar Mondal

Abstract:

The main purpose of this paper is to introduce the concept of Neutrosophic Soft Matrix(NS-Matrix). We have proposed different types of NS-Matrix along with various operations on them. A new methodology, named as NSM -Algorithm based on some of these new matrix operations, has been developed to solve neutrosophic soft set based real life group decision making problems efficiently. Finally NSM-Algorithm has been applied to solve the problems of diagnosis of a disease from the myriad of symptoms as well as to evaluate the effectiveness of different habits of human being responsible for a disease from medical science.

Keywords:

Choice Matrix, Group Decision, Neutrosophic Soft Matrix(NS-Matrix), NSM -Algorithm

2. Closed-loop healthcare data processing system: The use of proteomics and information technology to improve healthcare [Download PDF]

Authors:

Neil G. Siegel(corresponding author), Larry Gold

Abstract:

Clinical care decision-making can be improved though the use of a "closed-loop" information processing cycle that integrates sensed and recorded data on individuals (initially centered around a combination of highly-multiplexed, longitudinal protein measurements, and electronic health-care records), and applies, analyzes, and visualizes those data using "causality cases" (authoritative findings about how sensed data relates to diagnosis), so as to enable personalized diagnostic and treatment guidance for consideration by the patient, the care team, and the healthcare administrator. We integrate scans of the proteome with a "learning" information processing system. The resulting system, soon capable of measuring thousands of proteins simultaneously from very small blood sample sizes, can be the basis for potentially significant improvement at the system level in the healthcare system, helping improve average outcomes while decreasing total costs. Advances in both data processing technology and biotechnology have reached a level to make this approach feasible, and if applied broadly and effectively, can provide a scalable and exportable mechanism for achieving the "triple aim" of simultaneously improving care outcomes, lowering costs, and enhancing the patient experience.

Keywords:

Healthcare Informatics, Proteomics, Information Processing, Systems Engineering

3. New Crossover Operators for Multiple Subset Selection Tasks[Download PDF]

Authors:

Arnab Roy(Correspondence author), J. David Schaffer, Craig B. Laramee

Abstract:

We have introduced two crossover operators, MMX-BLXexploit and MMX-BLXexplore, for simultaneously solving multiple feature/subset selection problems where the features may have numeric attributes and the subset sizes are not predefined. These operators differ on the level of exploration and exploitation they perform; one is designed to produce convergence controlled mutation and the other exhibits a quasi-constant mutation rate. We illustrate the characteristic of these operators by evolving pattern detectors to distinguish alcoholics from controls using their visually evoked response potentials (VERPs). This task encapsulates two groups of subset selection problems; choosing a subset of EEG leads along with the lead-weights (features with attributes) and the other that defines the temporal pattern that characterizes the alcoholic VERPs. We observed better generalization performance from MMX-BLXexplore. Perhaps, MMX-BLXexploit was handicapped by not having a restart mechanism. These operators are novel and appears to hold promise for solving simultaneous feature selection problems.

Keywords:

Multiple Subset Selection, Genetic Algorithm, Crossover Operators, Features With Numeric Attributes, Evoked Response Potential

4. Statistical analysis of a new correlation peak detection method for unimodal autocorrelation[Download PDF]

Authors:

Adam Knapp (Correspondence author), Laszlo Pap

Abstract:

A new, so-called seeking-and-tracking correlators for peak detection is proposed and its impact on synchronization used by the receiver of a binary chirp modulation system is analyzed. In this paper, the probability of the zero delay correlation peak of the correlation function of chirp modulated signals is calculated assuming an AWGN channel in four cases: using the legacy sliding and the new seeking- and-tracking correlators with coherent and non-coherent receiving, respectively. During the calculation of correlation using the seeking-and-tracking correlators we suppose that the noise components are not statistically independent, thus this effect enables to reduce the error probability of correlation peak detection. The results can be used for spectrum spread modulation based systems, where the autocorrelation function of the spectrum spreading code has only one well-determined peak, e.g. DS (Direct Sequence) and FFH (Fast Frequency Hopping). Such systems are unimodal, the code and symbol synchronization are either before or after the carrier synchronization, i.e. the phase of the carrier still unknown or just known during the establishing period of the code and symbol synchronization.

Keywords:

Synchronization, Spectrum Spread Modulation Based System, WLAN-positioning, AWGN Channel, Error Probability

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