Application of Library Least-Squares Analysis to Human Whole-Body Counter Spectra Derived From Low Level Gamma Emissions

The method of library least-square analysis (LLSA) has been applied to gamma ray spectra obtained from the Grand Forks Human Nutrition Research Center whole body counter. The validity of the method was tested under various conditions. Mathematical formulation of the method is presented along with a detailed description of the computer program algorithm used. Special features, schemes and pitfalls of the computer program (or the method as a whole) are discussed in detai

DYNAMIC SMART GRID COMMUNICATION PARAMETERS BASED COGNITIVE RADIO NETWORK

The demand for more spectrums in a smart grid communication network is a significant challenge in originally scarce spectrum resources. Cognitive radio (CR) is a powerful technique for solving the spectrum scarcity problem by adapting the transmission parameters according to predefined objectives in an active wireless communication network. This paper presents a cognitive radio decision engine that dynamically selects optimal radio transmission parameters for wireless home area networks (HAN) of smart grid applications via the multi-objective differential evolution (MODE) optimization method. The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. Simulation results highlight the superiority of the proposed system in terms of accuracy and convergence as compared with other evolution algorithms (genetic optimization, particle swarm optimization, and ant colony optimization) for different communication modes (power saving mode, high throughput mode, emergency communication mode, and balanced mode)

A NEW AND ADAPTIVE SECURITY MODEL FOR PUBLIC COMMUNICATION BASED ON CORRELATION OF DATA FRAMES

Recent developments in communication and information technologies, plus the emerging of the Internet of Things (IoT) and machine to machine (M2M) principles, create the need to protect data from multiple types of attacks. In this paper, a secure and high capacity data communication model is proposed to protect the transmitted data based on identical frames between a secret and cover data. In this model, the cover data does not convey any embedded data (as in normal steganography system) or modify the secret message (as in traditional cryptography techniques). Alternatively, the proposed model sends the positions of the cover frames that are identical with the secret frames to the receiver side in order to recover the secret message. One of the significant advantages of the proposed model is the size of the secret key message which is considerably larger than the cover size, it may be even hundred times larger. Accordingly, the experimental results demonstrate a superior performance in terms of the capacity rate as compared to the traditional steganography techniques. Moreover, it has an advantage in terms of the required bandwidth to send the data or the required memory for saving when compared to the steganography methods, which need a bandwidth or memory up to 3-5 times of the original secret message. Where the length of the secret key (positions of the identical frames) that should be sent to the receiver increases by only 25% from the original secret message. This model is suitable for applications with a high level of security, high capacity rate and less bandwidth of communication or low storage devices

Asian Pacific Society of Cardiology Consensus Statements on the Diagnosis and Management of Obstructive Sleep Apnoea in Patients with Cardiovascular Disease

Obstructive sleep apnoea (OSA) is strongly associated with cardiovascular disease (CVD). However, evidence supporting this association in the Asian population is scarce. Given the differences in the epidemiology of CVD and cardiovascular risk factors, as well as differences in the availability of healthcare resources between Asian and Western countries, an Asian Pacific Society of Cardiology (APSC) working group developed consensus recommendations on the management of OSA in patients with CVD in the Asia-Pacific region. The APSC expert panel reviewed and appraised the available evidence using the Grading of Recommendations Assessment, Development, and Evaluation system. Consensus recommendations were developed and put to an online vote. Consensus was reached when 80% of votes for a given recommendation were in support of ‘agree’ or ‘neutral.’ The resulting statements provide guidance on the assessment and treatment of OSA in patients with CVD in the Asia-Pacific region. The APSC hopes for these recommendations to pave the way for screening, early diagnosis and treatment of OSA in the Asia-Pacific region

A Fuzzy Predictive Handover Mechanism based on MIH Links Triggering in Heterogeneous Wireless Networks

Abstract. The wireless networks of the near future will capable of successfully handling various kinds of communication systems. The cross platform communication is a very serious issue that has to be immediately addressed. The main factor for successful implementation of 4G wireless networks is the Media Independent Handover (MIH). It can provide the information about the parameter that impacts the handover prediction. The aim of this work is to provide link trigger intelligence and a general interface for the handover between heterogeneous wireless networks. It is noteworthy that the information of link trigger is very vital for the link trigger to carry out precise decision and execution. This paper proposes a fuzzy based prediction algorithm with dynamic of links triggering for vertical handover by applying the Information Server (IS) of IEEE 802.21. The propose solution can minimize unnecessary handover

Automatic white matter lesion detection and segmentation on Magnetic Resonance Imaging: A review of past and current state-of-the-art

White matter lesion (WML) is an abnormal tissue occurring in white matter. It indicated the damage of the myelin sheath that used to surround the axon of a neurone. This resulting neurological and vascular disorder occur in the patient, also commonly developed in the healthy brain of elderly. Magnetic Resonance Imaging is a non-invasive medical equipment preferred choice by the clinician to diagnose and observed the injury of brain tissue. However, WML quantitative assessment and analyse on the large volume of MR imaging is a challenge. In this paper, we provide an intensive review of the past and recent WML delineation and detection methods. This review included visual scoring assessment, a common preprocessing step for WML segmentation, false positive elimination, and the latest automatic WML segmentation approaches will be presented

Gaussian mixture model - Expectation maximization algorithm for brain images

Segmentation of human brain can be performed with the aid of mathematical algorithm as well as computer-based system to assist radiologists and medical related profession to monitor the condition of one's brain comprehensively. Due to the complex structure of the human brain, one cannot simply analyze them just by looking at the MRI images. This research examines the brain segmentation and the validation of the segmentation using ground truth data for seven subjects. The segmentation of brain regions such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) can be accomplished by using Gaussian Mixture Model (GMM) and Expectation-Maximization (EM) Algorithm. The results of segmentation are shown by the Gaussian distribution graph that indicates the volume of brain regions. The segmentation results are validated by the value of Dice index, Jaccard index, and positive predictive value (PPV). It is found that all seven subjects have high value for every index as the values ranging from more than 0.6 to almost approaching 1. For all subjects, the lowest percentage for Dice is 77.82% while the highest is 84.28%, the lowest percentage for Jaccard is 63.70% while the highest is 72.84%, and the lowest percentage for PPV is 94.44% while the highest is 98.75%. In conclusion, the index values for all subjects are acceptable and this means the segmentation by using GMM and EM Algorithm is accurate after going through the process of validation of segmentation

A 3-year observation on analyzing cloud-to-ground lightning in Peninsular Malaysia using graph theory

Malaysia has a high amount of lightning events due to its geographical location and tropical climate, leading to substantial destruction of electrical systems and human injuries. Despite numerous studies connecting lightning activity with environmental factors, few had explored the multi-year correlation between strike patterns and times. The present study proposed a new approach employing graph theory to express Cloud-to-Ground Lightning (CGL) strike data. Using data mapping and vertex matrices, this technique visualizes CGL behavior, offering insights into lightning characteristics. The relationship between the CGL strike data across three years (2013, 2014, and 2015) was studied by using simple matching coefficient technique. Results indicate a robust positive correlation between directed graphs created across these years, suggesting consistent CGL strike behaviors in certain regions at Malaysia. The proposed method, in the form of directed edges, reduces the complexity of computation hence making it a promising integration to existing lightning prediction systems