Preprint: Using RF-DNA Fingerprints To Classify OFDM Transmitters Under Rayleigh Fading Conditions

The Internet of Things (IoT) is a collection of Internet connected devices capable of interacting with the physical world and computer systems. It is estimated that the IoT will consist of approximately fifty billion devices by the year 2020. In addition to the sheer numbers, the need for IoT security is exacerbated by the fact that many of the edge devices employ weak to no encryption of the communication link. It has been estimated that almost 70% of IoT devices use no form of encryption. Previous research has suggested the use of Specific Emitter Identification (SEI), a physical layer technique, as a means of augmenting bit-level security mechanism such as encryption. The work presented here integrates a Nelder-Mead based approach for estimating the Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA fingerprinting. The performance of this estimator is assessed for degrading signal-to-noise ratio and compared with least square and minimum mean squared error channel estimators. Additionally, this work presents classification results using RF-DNA fingerprints that were extracted from received signals that have undergone Rayleigh fading channel correction using Minimum Mean Squared Error (MMSE) equalization. This work also performs radio discrimination using RF-DNA fingerprints generated from the normalized magnitude-squared and phase response of Gabor coefficients as well as two classifiers. Discrimination of four 802.11a Wi-Fi radios achieves an average percent correct classification of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a Rayleigh fading channel comprised of two and five paths, respectively.Comment: 13 pages, 14 total figures/images, Currently under review by the IEEE Transactions on Information Forensics and Securit

Service Quality Domains Impelling Patient’s Return Intentions in Nisa Premier Hospital Abuja

Nisa Premier Hospital (Nisa) is a private for-profit hospital established in 1996 in the Federal Capital Territory of Abuja Nigeria. The main purpose of this workis to provide an efficient tool for determining the domains of SERVQUAL that influences patients return intentions in a typical privately owned hospital in Nigeria that is striving towards world class standard. The study adopted across-sectional and case study sample based survey design using a modified SERVQUAL structured questionnaire. A total of 205 questionnaires were analysed in this study, thereby yielding a valid response rate of about 46%. Results of the percentage distribution of items within each domain that influenced patients return intention were rated in the following order; Tangibles (83%), Assurance (77%), Empathy (72), Responsiveness (74%) and Reliability (66%). Binary logistics regression analysis following six-sigma quality improvement methodologyenhanced the modelling approach and indicated two items within the five domains of SERVQUAL, i.e. reliability and empathy with p-values <.05 as responsible for the return intentions. The means by which patients financetheir healthcare did not influence this. However, findings from the study indicated that the employees sympathetic, reassuring and putting patients’ best interests at heart were the key factors influencing patient return intention at Nisa. Suggested improvement strategy entails improving areas of shortfalls, fostering the domain items noted as point of strength, developing new items within the SERVQUAL domains and revalidate findings periodically. It isanticipated that findings from this study can be adapted to other similar business concern in the healthcare industry

Relationship between family and social support and adherence to treatment among outpatient hypertensives in an urban hospital

Background: The study aims to determine the correlation between family/social support and adherence to treatment in hypertensive patients.Methods: This is a cross sectional study. Patients who met the inclusion criteria were recruited by systematic random sampling technique. A physical examination was done to determine their blood pressure, questionnaires were administered to elicit sociodemographic characteristics, Family APGAR, Social support and adherence scores. Data collected was analyzed with Statistical Program for Social Sciences (SPSS)-15.Results: A total of 120 data sets were analyzed. The mean age of the patients was 56 years ±11.6 with 60% of the patients being females. The mean duration of hypertension was 8±7 years and the mean number of antihypertensive medication they were on was 2±1. Majority (94%) of the patients had a caring and supportive relationship. Mean adherence score was 1.55±2.06. Adherence rate was 52.5%. Delay in refill (18.1%), mainly due to financial constraints was the commonest reason for non-adherence. There was a significant correlation between age group, previous history of symptom, family function and social support with adherence. There was however no significant correlation between gender, marital status, duration of hypertension, family member with hypertension and number of medications with adherence.Conclusion: Medication adherence was good in this population of hypertensives. Family and social support were significant predictors of good medication adherence.Keywords: Hypertension; Medication adherence; Family function; Social support; Family APGAR; Outpatient