Comparative Performance Evaluation of DVB-T using Advance Design System (ADS)

Wireless technologies have brought a rapid growth to digital video broadcasting and as such, has played (and still playing) a vital role in communication systems. Orthogonal frequency division multiplexing (OFDM) has also become so popular in wireless communication systems reason been that it has high spectral efficiency, high throughput, high data capacity and resilience to multipath fading. In addition to these, it is very robust to channel impairment; a quality which has made it preferable and ideal in wireless communication systems. This paper evaluates DVB and compares its performance across three different channels (AWGN, Rayleigh and Ricean) and three different modulation techniques (QPSK, 16 QAM and 64 QAM) is employed. DTV_DVB in 2K Mode carriers is transmitted across AWGN, Rayleigh and Ricean and a comparison of BER performance of the different modulation schemes was considered. At the end of the simulation results and analysis, it was found that AWGN in 16QAM carrier modulation is considered the best modulation technique for DVB_T. Keywords: modulation, channel, digital television, digital video broadcasting

Cost and energy efficient operation of converged, reconfigurable optical wireless networks

This paper presents a converged fibre-to-the-home (FTTH) based access network architecture featuring wireless services. In order to fulfill the bandwidth demands from end users, a dynamic architecture is proposed with co-existence of LTE, WiMax and UWB technologies. Hybrid wavelength division multiplexing (WDM) and a time division multiplexing (TDM) based optical access network offer reconfigurable provision. This enhances the ability to allocate different wavelengths to different optical networking units (ONUs) on demand. In addition, two different channel routing modules (CRMs) are introduced in order to address the cost effectiveness and energy efficiency issues of the proposed network. Take-up rate adaptive-mode operation and traffic-adaptive power management are utilized to optimize the benefits of low investment cost with energy efficiency. Up to 26% power consumption reduction is achieved at the time of minimum traffic conditions while 10% consumption is achieved at the time of maximum traffic conditions. Besides, 23% energy saving can be achieved compared to conventional systems in fully operated stage

Next generation optical access networks and wireless integration featuring ultra-wide-band technology

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Factors affecting sustainable adoption of e-health technology in developing countries: an exploratory survey of Nigerian hospitals from the perspective of healthcare professionals

Background E-health technology applications are essential tools of modern information technology that improve quality of healthcare delivery in hospitals of both developed and developing countries. However, despite its positive benefits, studies indicate that the rate of the e-health adoption in some developing countries is either low or underutilized. This is due in part, to barriers such as resistance from healthcare professionals, poor infrastructure, and low technical expertise among others. Objective The aim of this study is to investigate, identify and analyze the underlying factors that affect healthcare professionals decision to adopt and use e-health technology applications in developing countries, with particular reference to hospitals in Nigeria. Methods The study used a cross sectional approach in the form of a close-ended questionnaire to collect quantitative data from a sample of 465 healthcare professionals randomly selected from 15 hospitals in Nigeria. We used the modified Technology Acceptance Model (TAM) as the dependent variable and external factors as independent variables. The collected data was then analyzed using SPSS statistical analysis such as frequency test, reliability analysis, and correlation coefficient analysis. Results The results obtained, which correspond with findings from other researches published, indicate that perceived usefulness, belief, willingness, as well as attitude of healthcare professionals have significant influence on their intention to adopt and use the e-health technology applications. Other strategic factors identified include low literacy level and experience in using the e-health technology applications, lack of motivation, poor organizational and management policies. Conclusion The study contributes to the literature by pinpointing significant areas where findings can positively affect, or be found useful by, healthcare policy decision makers in Nigeria and other developing countries. This can help them understand their areas of priorities and weaknesses when planning for e-health technology adoption and implementation

Miniaturized stacked implant antenna design at ISM band with biocompatible characteristics

Purpose – A vertically stacked, three layer hybrid Hilbert fractal geometry and serpentine radiator-based patch antenna is proposed and characterized for medical implant applications at the Industrial, Scientific and Medical band (2.4-2.48 GHz). Antenna parameters are optimised to achieve miniaturized, biocompatible and stable transmission characteristics. The paper aims to discuss these issues. Design/methodology/approach – Human tissue effects on the antenna electrical characteristics were simulated with a three-layer (skin, fat and muscle) human tissue model with the dimensions of 180×70×60 mm3 (width×height×thickness mm3). Different stacked substrates are utilized for the satisfactory characteristics. Two identical radiating patches are printed on Roger 3,010 (ε r=10.2) and Alumina (ε r=9.4) substrate materials, respectively. In addition, various superstrate materials are considered and simulated to prevent short circuit the antenna while having a direct contact with the metallization, and achieve biocompatibility. Finally, superstrate material of Zirconia (ε r=29) is used to achieve biocompatibility and long-life. A finite element method is used to simulate the proposed hybrid model with commercially available Ansoft HFSS software. Findings – The antenna is miniaturized, having dimensions of 10×8.4×2 mm3 (width×height×thickness mm3). The resonance frequency of the antenna is 2.4 GHz with a bandwidth of 100 MHz at return loss (S11) of better than −10 dB characteristics. Overall, the proposed antenna have 50 Ω impedance matching, −21 dB far field antenna gain, single-plane omni-directional radiation pattern properties and incident power of 5.3 mW to adhere Specific Absorption Rate regulation limit. Originality/value – Vertically stacked three layer hybrid design have miniaturized characteristics, wide bandwidth, biocompatible, and stable characteristics in three layer human tissue model make this antenna suitable for implant biomedical monitor systems. The advanced simulation analysis of the proposed design constitutes the main contribution of the paper. </jats:sec

Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals’ perspective: a survey of hospitals in Benue state, northcentral Nigeria

Abstract Background Cloud based health platforms (CBHP) have tremendous capacity to meet patient’s health needs. The benefits inherent in CBHP position it to be relevant for efficient healthcare delivery. Nonetheless, studies have shown that the adoption of new technologies is sometimes a challenge especially in developing nations. This study, therefore, aim to examine, identify and evaluate the factors affecting healthcare professionals’ intention to accept the cloud-based health center (CBHC) in developing countries. The research study focuses on hospitals in North-central of Nigeria. Methods Using questionnaire adopted from related studies, a cross-sectional study was carried out of 300 healthcare professionals selected from medical health institutions in Benue State Nigeria. The study adopted the Unified Theory of Acceptance and use of Technology Extended (UTAUT2). Data analysis was carried out using SPSS (V20.0) and LISREL (V9.30) generally employed in Structural Equation Modeling to examine components and path model. The Socio technical design method was used to develop the CBHC. Results Findings portrays performance expectancy, cloud based health knowledge, IT infrastructure and social influence to have significant effects on the intentions of healthcare professionals to accept and use the CBHC. These findings, agrees with prior related studies. Conclusions Our findings impacts the body of knowledge in that it identifies important areas the studies can be useful, especially, to managers and healthcare policy makers in the planning/implementation of health cloud. Research findings from the theoretical acceptance model identifies the factors and barriers towards sustainable cloud based health center solutions to meet the healthcare needs of people in remote communities

Machine-based classification of ADHD and nonADHD participants using time/frequency features of event-related neuroelectric activity

Karakaş, Sirel (Dogus Author) -- Doğutepe, Elvin (Dogus Author)Objective: Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is still confronted with many problems.& para;& para;Method: A novel classification approach that discriminates ADHD and nonADHD groups over the time-frequency domain features of event-related potential (ERP) recordings that are taken during Stroop task is presented. Time-Frequency Hermite-Atomizer (TFHA) technique is used for the extraction of high resolution time-frequency domain features that are highly localized in time-frequency domain. Based on an extensive investigation, Support Vector Machine-Recursive Feature Elimination (SVM-RFE) was used to obtain the best discriminating features.& para;& para;Results: When the best three features were used, the classification accuracy for the training dataset reached 98%, and the use of five features further improved the accuracy to 99.5%. The accuracy was 100% for the testing dataset. Based on extensive experiments, the delta band emerged as the most contributing frequency band and statistical parameters emerged as the most contributing feature group.& para;& para;Conclusion: The classification performance of this study suggests that TFHA can be employed as an auxiliary component of the diagnostic and prognostic procedures for ADHD.& para;& para;Significance: The features obtained in this study can potentially contribute to the neuroelectrical understanding and clinical diagnosis of ADHD

Machine-based learning system: classification of ADHD and non-ADHD participants

Karakaş, Sirel (Dogus Author) -- Doğutepe, Elvin (Dogus Author) -- Conference full title : 25th Signal Processing and Communications Applications Conference (SIU); 15 May 2017 through 18 May 2017. Antalya; TurkeyDikkat Eksikliği ve Hiperaktivite Bozukluğu (DEHB), psikiyatri servislerine başvuran çocuklarda en çok rastlanan rahatsızlıktır. Bu bozukluk 20. Yüzyılın başında tanımlanmasına rağmen, teşhisinde halen ciddi sorunlar yaşanmaktadır. Bu çalışmada, Olaya ilişkin Potansiyel (OİP) verilerinden çıkarılan zaman frekans özellikleri kullanılarak DEHB olan çocukların bu bozukluğu taşımayanlara göre sınıflandırılması elde edilmiştir. Bu özniteliklerin DEHB teşhisinde en etkili olanları Destek Vektör Makinesi – Yinelemeli Öznitelik Seçimi yöntemiyle belirlenmiş ve bu özniteliklerle eğitilen Destek Vektör Makinesi, üç öznitelik kullanıldığında %98 ve altı öznitelik kullanıldığında %99.5 doğrulukla DEHB teşhisi koymayı başarmıştır. Sonuçlar Tekrarlanan Çapraz Geçerlilik Yöntemiyle elde edilmiştir. Ayrıca, bu yöntem Kararlılık Seçimi ile desteklenerek DEHB tanısında en etkili öznitelikler belirlenmiştir. Ayrıca yeni bir tasarımla önerilen düzenek test edilmiş ve % 100 doğruluk elde edilmiştir. Sonuçlar, çalışmadaki düzeneğin psikiyatrik bozuklukların tanısında ve seyrinde kullanılabileceğini göstermektedir.Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is confronted with many problems. In this paper, a novel classification approach that discriminates ADHD and non-ADHD groups over the timefrequency domain features of ERP recordings is presented. Support Vector Machine-Recursive Feature Elimination (SVMRFE) was used to obtain best discriminating features. When only three of these features were used the accuracy of classification reached to 98%, and use of six features further improved classification accuracy to 99.5%. The proposed scheme was tested with a new experimental setup and 100% accuracy is obtained. The results were obtained using RCV. The classification performance of this study suggests that TFHA can be employed as a core component of the diagnostic and prognostic procedures of various psychiatric illnesses