Performance evaluation of two-fuzzy based cluster head selection systems for wireless sensor networks

Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network’s communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system.Peer ReviewedPostprint (published version

Assessment of health status of the elderly and pre-elderly at a Malaysia elderly care centre

They were once called the baby boomers, born between 1946 to 1964, but now aged above 50 years old, they contribute to the increasing number of elderly population in Malaysia. Age classification for elderly people varies between countries but commonly pre-elderly people is defined as those aged between 50 to 64 years old while those aged more than 64 years old fall in elderly category. In Malaysia, it is projected that the elderly population will make up for 10\% of the total population or 3.4 million by year 2020. Without effective and comprehensive healthcare system, the healthy lifestyle of this elderly population can be affected thus prohibiting them to return to their premorbid function. In this study, the health status of pre-elderly and elderly community residing at an Elderly Care Center in Selangor, Malaysia is assessed. In overall, 12 male occupants (4 elderly and 8 pre-elderly people) aged 50 years and above were interviewed to obtain data on their sociodemographic characteristics, medical history, hand functionality and hand strength measurements. The overall sample mean (standard deviation) age are 63 (8) years. The mean (standard deviation) for BMI is 20.26 (2.73) kg/m2 that falls in the normal category despite the visible nutritional deficiencies sign and symptoms on their physical body and facial. The mean (standard deviation) of handgrip measurements is 12.47 (6.69) kg, which is quite low but reasonable due to ageing factor

The Relationship Between Gender Role Conflict and Academic Progress Comparing Division II Male Student-Athletes to Male Non-Student-Athletes

Data shows that there is a lack of progress in male graduation rates in recent decades in higher education (Diprete & Buchmann, 2013). This study examines the impact of gender role conflict and academic motivation on academic progress with first and second year Division II male student-athletes and male non-student-athletes at a Midwestern, Carnegie classified master’s college and university (larger program institution). Gender role conflict creates a narrow definition for masculinity in which males are expected to behave (O’Neil, 1981). Using general linear regression and binary logistic regression models, the researcher analyzed data of participants’ (N = 116; Nstudent-athletes = 58; Nnon-student-athletes = 58) scores on the Gender Role Conflict Scale (GRCS) factors and Academic Motivation Scale (AMS) factors, alongside the participants’ athlete status (Yes or No), midterm GPA, and composite ACT (Vallerand, et al., 1992; O’Neil, et al., 1986). The study explained mixed findings about GRC and AMS predictors of midterm GPA. GRC factors of Restrictive Emotionality (RE) and Conflict Between Work Family – Leisure (CBWFR) were significant predictors of midterm GPA as a dependent variable, but only CBWFR was a negative significant predictor. The model using athlete status as a dependent variable was not significant. The full models of RE as a dependent variable or Restrictive Affectionate Behavior Between Men (RABBM) as a dependent variable both explained sizable variance (R2RE = .427; R2RABBM = .476). Throughout the research, GRC factors were significant predictors. Findings demonstrate the continued need for further analysis of the GRC factors and how they impact varying subgroup populations of males’ academic progress, including the potential within group variations between different sports and sports types (i.e. contact versus non-contact sports)