Ramani Kannan

Bio: Ramani Kannan is an academic researcher from Universiti Teknologi Petronas. The author has contributed to research in topics: Topology (electrical circuits) & Inverter. The author has an hindex of 9, co-authored 63 publications receiving 362 citations.

Significance of localization of mandibular foramen in an inferior alveolar nerve block.

Abstract: Background: The mandibular foramen (MF) is an opening on the internal surface of the ramus for divisions of the mandibular vessels and nerve to pass. The aim of this study is to determine the position of the MF from various anatomical landmarks in several dry adult mandibles. Materials and Methods: A total of 102 human dry mandibles were examined, of which 93 were of dentulous and 9 were of edentulous. The measurements were taken from the anterior border of the ramus (coronoid notch) to the midportion of the MF and then from the midportion of the MF to the other landmarks such as internal oblique ridge, inferior border, sigmoid notch, and condyle were measured and recorded. Results: The data were compared using Student's t-test. The MF is positioned at a mean distance of 19 mm (with SD 2.34) from coronoid notch of the anterior border of the ramus. Superio-inferiorly from the condyle to the inferior border MF is situated 5 mm inferior to the midpoint of condyle to the inferior border distance (ramus height). Conclusion: We conclude that failures in the anesthesia of the inferior alveolar nerve are due to the operator error and not due to the anatomical variation.

Electrochemical Sensing of Dopamine, Uric Acid and Ascorbic Acid Using tRGO-TiO2 Nanocomposites.

Abstract: This work reports a graphene-based nonenzymatic electrochemical sensing platform for the detection of dopamine (DA), uric acid (UA), and ascorbic acid (AA). Graphene oxide, synthesized by modified Hummers method, was thermally reduced in an induction furnace at 200 °C in an Ar-H2 atmosphere to obtain thermally reduced graphene oxide (tRGO). Nanocomposites of tRGO-TiO2 were obtained by a hydrothermal method, and were characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD). FTIR spectra showed Ti-O-C peaks, indicating covalent linkage between the TiO2 nanoparticles and the reduced graphene oxide sheets. Glassy carbon electrode (GCE) was modified with the nanocomposite (tRGO-TiO2-GCE), and the modified electrode could detect dopamine (DA: 1 to 1000 µM), uric acid (UA: 1 to 900 µM), and ascorbic acid (AA: 10 to 1000 µM) in each other's presence over wide ranges, with adequate separation in peak potentials. Differential pulse voltammetry experiments yielded linear responses with sensitivities of 133.18, 33.96, and 155.59 µA mM(-1) cm(-2) for DA, UA, and AA, respectively.

i Worksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings

Abstract: The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called ${i}$ WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the ${i}$ WorkSafe app hosts a fuzzy neural network model that integrates data of employees’ health status from the industry’s database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users’ proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user.

Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures

Abstract: For the consideration of environmental aspects of the personal transportation, electric vehicle (EV) and plug-in hybrid electric vehicle (PHEV) has the prospective solution nonetheless there is an obstacle to access the charging system plug. Additionally, the charging system delivers its own troubles when we compared it with petrol station since the participation of the different charging alternative. For the last few years, the studies associated with optimization of PHEV/EV charging infrastructure have drawn the researcher׳s consideration. New challenges and chances for the growth of smart grid technologies depend upon the recently introduced electric vehicle charging infrastructure services. In this particular review study, the literature bearing on the use of optimization methods for charging infrastructure is considered.

Design of loosely coupled inductive power transfer systems

Abstract: The model of inductive power system is set up,and how to choose the compensation topology and resonant frequency is analyzed.According to the analysis result,the model of inductive power system is set up,and the impact of the power transfer due to the variety of load is analyzed.

Biosynthesis of Copper Oxide (CuO) Nanowires and Their Use for the Electrochemical Sensing of Dopamine

Abstract: A facile one-step, eco-friendly, and cost-effective approach for the formation of copper oxide (CuO) nanowires by a green method using saponin-rich Sapindus mukorossi fruit extract (SMFE). The physio-chemical characteristics of the synthesized CuO nanowires have been characterized by X-ray Diffractometry (XRD), X-ray Photoelectron Spectroscopy (XPS), FT-IR (Fourier Transform Infrared Spectroscopy, FE-SEM (Scanning Electron Microscopy), and High-Resolution Transmission Electron Microscopy (HR-TEM). Further, the electrocatalytic activity of the CuO nanowires synthesized with SMFE has been investigated, and they have been used as dopamine (DA) sensors. Because of their unique properties, the CuO nanowires/GCE exhibited remarkable electrochemical response for the detection of DA with enhanced current response. The anodic current demonstrated that the CuO nanowires/GCE linearly detects the concentration of DA over the range of 0.1 µM to 0.105 mM of DA with a regression co-efficient of 0.9960. The obtained results illustrated that the synthesized CuO nanowires can easily stimulate the electron transfer reaction between DA and the nanowires modified electrode with the improvement of the conductivity and stability of the electrode. This remarkable electrocatalytic property of CuO nanowires makes it a unique electrochemical sensor for the detection of DA. Furthermore, the sensor is free from the interference of ascorbic acid, uric acid, and other interfering species. Moreover, the anti-interference performance also showed that the CuO nanowires/GCE could be employed for the determination of DA in real samples with good selectivity and sensitivity.

An assessment of recent multilevel inverter topologies with reduced power electronics components for renewable applications

Abstract: The combination of multilevel inverter with renewable energy source power generation is paid more attention among the researchers, because multilevel inverters are widely accepted power converters in for high-power applications. The conventional multilevel inverters are highly implemented in industries, and the success of this has motivated to create newer topologies with the reduced overall power electronics components. In this paper, recent multilevel inverter topologies with reduced number of switches are taken into account and to find a suitable topology for photovoltaic (PV) and wind energy applications. Finally, this paper gives a pathway for the upcoming researchers to consider the design issues and challenges in the development of new multilevel inverter topologies.