Advancements of Medical Electronics

This paper proposed a method to implement an intelligent system to find out the risk of cardiovascular diseases in human being. Genetics play a direct and indirect role in increasing the risks of cardiovascular diseases. Habits and individual symptom viz. suffering from diabetes, obesity and hypertension also can influence the risk of the said diseases. Excessive energy accumulation in ones body can create fatal problem in health. In this paper, method has been proposed to the proposed to investigate three major factors i.e. family history of CVD, Other diseases and Average Energy Expenditure and find out the of level of risks of cardiovascular diseases.

Drowsiness and fatigue of automobile drivers reduce the drivers’ abilities of vehicle control, natural reflex, recognition and perception. Such diminished vigilance level of drivers is observed at night driving or overdriving, causing accident and pose severe threat to mankind and society. Therefore it is very much necessary in this recent trend in automobile industry to incorporate driver assistance system that can detect drowsiness and fatigue of the drivers. This paper presents a nonintrusive prototype computer vision system for monitoring a driver’s vigilance in realtime. Eye tracking is one of the key technologies for future driver assistance systems since human eyes contain much information about the driver’s condition such as gaze, attention level, and fatigue level. One problem common to many eye tracking methods proposed so far is their sensitivity to lighting condition change. This tends to significantly limit their scope for automotive applications. This paper describes real time eye detection and tracking method that works under variable and realistic lighting conditions. It is based on a hardware system for the real-time acquisition of a driver’s images using IR illuminator and the software implementation for monitoring eye that can avoid the accidents.

Automated retinal image processing is becoming a primary important screening tool for early detection of diabetic retinopathy (DR). An automated system reduces human errors and also reduces the burden on the ophthalmologists. The accurate detection of microaneurysms (MAs) is an important step for early detection of DR. This paper present some methods to improve the quality of input retinal image and extraction of blood vessels, as a preprocessing step in automatic early stage detection of DR. Experimental results are performed for preprocessing and blood vessel extraction techniques using standard fundus image database.

This paper proposes a novel methodology for improving the quality of magnetic resonance image (MRI). The presence of noise affects the image analysis task by degrading the visual contents of image. The proposed methodology integrates transform domain method, discrete wavelet transform with spatial domain filter, Non local means to smoothed out noisy interferences leading to the improvement of visual characteristics of MRI insights. The quantitative validation of the proposed technique has been done and experimental result shows the effectiveness of this algorithm over anisotropic diffusion, bilateral, trilateral and wavelet shrinkage filters.

Breast imprint cytology is a well-recognized technique and provides a magnificent cytological clarity. For imprint cytology slide preparation, tissue samples from the needle taken out to touch and rolled over glass slide and finally stained by hematoxilin and eosin (H&E). The aim of this research is to segment breast imprint cytology nucleus. Images from imprint cytology slides were grabbed by an optical microscope. The histogram based threshold technique has been used to segment nucleus. The proposed technique includes pre-processing, segmentation, post-processing, and final output stage. In pre-processing first image colors was normalized by white balance technique. Then the green channel was extracted from the normalized image. In segmentation stage target nucleus was segmented by pixel intensities. Post-processing stage refers to the clear border nucleus or sharpening the edges. Finally, the three channels were concatenated to get RGB image. The proposed technique performs best in imprint cytology nucleus segmentation, and capable of distinguishing nucleus and non-nucleus objects. Performance of our proposed algorithm is quite high and much more useful for further analysis.

Chromosomes are generally thread-like structures present in the nucleus of each living cells. There are twenty three pairs of chromosome in human beings. The additional in chromosome number or missing chromosome will cause chromosome abnormality i.e. chromosome anomaly in human beings. This is mainly occurring due to accident or error while sperm or egg progress in growing. The abnormality in chromosome will cause birth defects, genetic disorders and cancer to the human beings. The twenty three pairs of chromosome can be classified into twenty four different classes by using karyotyping process. In this paper, the main objective is to give idea about how to diagnose the genetic disorder. The genetic disorder can lead to cancer in human. It may happen due to touching or overlapped chromosomes in human beings. In order to overcome these genetic disorders and cancer in human, the touching and overlapped chromosomes were separated. This separation process will be easier to undergo karyotyping analysis and to be handled by a cytogeneticist.

Staging of colorectal cancer constitutes an important part of its diagnosis and prognosis. However, both invasive and non-invasive techniques prevail with their own advantages and disadvantages. The present review focuses on the existence of complementarity between the information obtained from computerized tomography and radioimmunoscintigraphy in the study of hepatic and extra-hepatic lesions of significance and relevant to colorectal cancer. The latter technique utilizes different monoclonal antibodies which are tagged with radioisotopes and imaging done by gamma-camera. For complete diagnosis of recurrent carcinoma or metastases, knowledge form both the pre-surgical procedures is an absolute necessity to choose the correct therapeutic modality.

Segmentation of color images is a tricky task. Regaining the segments in an image using the content image is a difficult and significant problem. Medical imaging is the most alive research topic from the past two decades. From the medical diagnosis of patients suffering from various diseases, abnormal regions in the organs can be easily identified, which is a greatest achievement. It is experimentally proved that graph based segmentation methods are better than the other segmentation techniques, especially when combined with statistical methods. We have proposed color image segmentation by adaptive graph cut method in this paper. It consists of two important stages. During the first phase we enhance the input color image using transformation technique as the image may contain noise, may be of low contrast and missing some color statistics. Then this enhanced color image is processed under graph cut technique to get better results, especially for the analysis of medical and general images. The proposed method contributes to medical imaging by means of image segmentation and also to other general image analysis. Our experimental results are found to very good in segmenting color images.

Automatic detection of Diabetic Retinopathy (DR) abnormalities in fundus retinal images can assist in early diagnosis and timely treatment of DR, to avoid further deterioration of vision. Many Fundus Retinal images contain color distorted regions originated due to noise, extremely uneven or poor illumination and improper exposure of fundus camera. These regions are required to be removed to avoid poor results for feature extraction and erroneous DR abnormality detections, as they introduce high amount of false positive detections. In this paper, we have proposed a totally automatic method for segmentation and removal of the color distorted regions in retinal fundus images, using modified Valley Emphasized Automatic thresholding method and morphological operations. The proposed algorithm accurately defines the well illuminated color undistorted retinal region inside the input fundus image, from which both the normal and disease features can be successfully detected. The proposed method has yield an average accuracy of more than 95 % when tested over around 700 fundus images from diaretdb0, diaretdb1, STARE, HRFDB and DRIVE databases.

This paper presents the human blood reheating technique for the blood tissues after surgery as 37–51 °C temperature is required during surgery with high frequency induction heating system. The surgeon opens the chest by dividing the breastbone (sternum) and connects with the heart-lung machine to operate on the heart. This machine allows the surgeon to operate directly on the heart by performing the functions of the heart and lungs. The length of the operation will depend on the type of surgery that is required for patient. Most surgeries take at least 4–5 h. The preparation for surgery, which requires approximately 45–60 min included in this time. After this operation the patients has required high temperature blood for the continuation of blood flow to the heart as the human body temperature is decreases after operation. Here high frequency converter technique can give better topology for reheating the blood after open heart surgery by taking least time than conventional system.

Cardiovascular disease is currently the biggest single cause of mortality in the developed world (Alty, IEEE Trans Biomed Eng 54:2268–2275, 2007) [

1

], (Clerk Maxwell, A treatise on electricity and magnetism, Clarendon, 1892) [

2

]. Hence, the early detection of its onset is vital for effective prevention. Aortic stiffness as measured by aortic Pulse wave velocity (PWV) has been shown to be an important predictor of Cardiovascular disease. However, the measurement of the same is complex and time consuming (Alty, IEEE Trans Biomed Eng 54:2268–2275, 2007) [

1

], (Clerk Maxwell, A treatise on electricity and magnetism, Clarendon, 1892) [

2

]. This paper presents a simple, low-cost, speedy and non-invasive method using Force Sensing Resistors (FSR) strategically placed over the Carotid and Radial arteries to evaluate various arterial wave pulse parameters like heart-rate, Stiffness Index (SI), Reflectivity Index (RI) and Pulse Wave velocity. The pulse rate and shape is used as an estimate of heart-rate. This is used for diagnosis of arrhythmias, tachycardia and bradycardia. The proposed method could be employed as a cheap and effective Cardiovascular disease screening technique, to be later integrated with small wrist watch-like monitors for suitable commercial purposes.

Cognition may be defined as a set of mental activities or processes which deals with knowledge, attention, memory and working memory, reasoning and computation, and judgement and evaluation. In this paper, we aim to study two distinctive cognitive processes dealing with evaluation of two similar stimuli and reasoning and computation of some mathematical problem. Here, we have used Wavelet Transforms and Distance Likelihood Ratio Test for feature extraction and classification respectively. We have also used two feature selection algorithm: ReliefF and Minimum Redundancy Maximum Relevance to select only the best relevant features for classification. The results show a 15 % improvement on accuracy when feature selection algorithms are used in the process. The results also suggests that the brain activation is dominant at the frontal, parietal and temporal region.

Neural information flow in brain during meditation, can be addressed by brain connectivity studies. This work aims to obtain neural connectivity measures based on a strictly causal time varying Multi-Variate Auto-Regressive (MVAR) model, fitted to EEG signals obtained during meditation. The time varying Granger Causality based connectivity estimators as PDC (Partial Directed Coherence), g-PDC (generalized Partial Directed Coherence), OPDC (Orthogonalized Partial Directed Coherence) and g-OPDC (generalized Orthogonalized Partial Directed Coherence) are calculated using the adaptive autoregressive MVAR parameters. The MVAR model parameters have been estimated by Kalman Filter algorithm. In this work g-PDC and g-OPDC have been used to make the connectivity measures scale invariant. These connectivity estimators quantify the neural information flow between Electroencephalograph (EEG) channels. In addition g-OPDC is also immune to volume conduction artifact and gives better result compared to g-PDC. Finally, surrogate data statistics has been used to check the significance of the above connectivity estimators.

Identification is an essential part of our lives. Identification of authentic candidate is essential in E-commerce, in keeping track of criminals, in airport and railway surveillance and many more aspects of the modern world. In this paper an approach has been proposed combining the knuckle and fingerprint biometrics for the purpose of identification of a person using SIFT (Scale Invariant Feature Transform).

A competent and consistent androgen receptor transactivation assay has been developed using pleiotropic drug resistance transporters

Pdr5, Snq2 and Yor1

deleted yeast strain,

Saccharomyces cerevisiae,

intended to express the human androgen receptor and androgen response element (probasin promoter) driving the expression of green fluorescent protein to determine endocrine disruptors from pulp and paper mill effluents (PPME). Stimulation of cells by known androgens, correlated with androgenic activities as measured by other reported bioassay systems. This yeast-based assay system when applied to evaluate anti-androgenic activities, the known anti-androgens effectively inhibited fluorescence reporter gene induction by dihydrotestosterone. The specificity of the assay was experienced by incubating the recombinant yeast cells with supraphysiological concentrations of non-androgenic steroidal compounds and none of them yielded considerable response. Further, the assay was used to analyze the extracted PPME from different mills confirmed strong androgenic activities. In conclusion, these results support the earlier report by us that PPME are rich in androgenic compounds and the employed detection system provides novel high throughput fluorescence based biosensor system for successful well sensitive (picogram level) screening of (anti)androgenic chemicals from various environmental sources.

The medical device industry is considered a hub of innovation with constantly improving designs and processes, the possibilities seem endless. Over the past 20 years, dc motors have played its role in the development of medical instruments like surgical robots, plate readers, liquid and specimen handling systems, chromatography, and In Vitro diagnostic machines. Regardless of what ever the application may be, all devices in the medical industry should have high Reliability and flexibility. This paper presents a new controller model using Imperialist Competitive Algorithm (ICA) for efficient search and optimization of Proportional Integral controller parameter in order to achieve a better close loop control of the dc motor in bio-medical application. This control method was simulated using MATLAB/SIMULINK to control dc motor. From the simulation, it was found that the proposed method gives better performance with improved response in any user defined function as the settling time, overshoot and speed error are reduced.

The present proposal revolves around the fabrication of a finger movement based wearable wireless attendant calling system. The system comprised of a flex sensor and a hall-effect sensor coupled with Arduino UNO and worked synchronously with patient hand movement. The concurrent activation of both the sensors enables the conveyance of patient location (ward and bed numbers) to the nurse station through Xbee protocol and a one-way SMS correspondence to a preloaded mobile number through GSM protocol. The device is capable of handling multiple patient requests at a time with minute time interval. A graphical user interface in MATLAB program monitors the patient status at the nursing station. The proposed device is expected to improve the quality of the patient care.

The primary aim of brain computer interface (BCI) is to establish communication link between computers and severely disable people those are partially or totally paralyzed (locked in state) due to neurological disorders. Recently much attention is focused on visual BCI (V-BCI) because of its low cost and minimal user training time. Characteristics of visual stimuli plays important role in V-BCI as it decides the strength of visual signals in brain and system communication rate. Recently new concept called Hybrid V-BCI emerge based on concept of combining advantages of one or more basic V-BCIs to further enhance ITR and accuracy of system. In this paper we review properties of brain signals involved in V-BCI, stimulation methods used, hybrid V-BCI and discuss current challenges in V-BCI with their possible solutions.

Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

The research on electromyography (EMG) signals analysis is allied with clinical/biomedical applications, evolvable hardware chip (EHW) development, and modern human computer interaction era. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the capturing phenomenon of EMG Signal introducing instrumental activity. It further point up some ideas about the block diagram of the EMG Signal recording instrument and the procedural approach towards the EMG recording techniques, provide efficient and effective ways of understanding the signal and its nature. The clinical real-time activity of EMG recording for biceps brachii muscle is presented with flow diagram. This paper provides researchers concrete and valuable information of EMG signal and its analysis procedures.

Brain Machine Interface (BMI) till now is generally preferred only for repairing damaged hearing, sight and movements with the help of neuroprosthetics application. These applications consist of some external unit which gathers some information in the form of signals from the brain and processes it so as to transfer them to the implanted unit. In this way these applications had helped the people to bring back their ability from various neuromuscular disabilities. Similarly, the BMI can be very useful for automation system. It will help in reducing accidents which had contributed to high mortality rate. A brain actuated automation system will also help motor disabled person to move independently. Signals from brain will be acquired with the help of dry electrodes and those signals will be processed in the system processor. The signal after processing will be then applied to the system depending on the instructions given by the person sitting on it.

The present work attempts to classify Electroencephalogram (EEG) signals corresponding to three different cognitive activities using an Interval Type 2 Fuzzy System (IT2FS) classifier. This approach is used in order to account for the fact that EEG signals from the same person for the same stimulus have variations in different observations in the same as well as over different days of experiments. Adaptive Autoregressive Parameters, Hjorth Parameters, Hurst Exponents and Approximate Entropy features are extracted from the acquired EEG signals to obtain the maximum possible discrimination between different classes of activities. A maximum classification accuracy of 85.33 % on an average over all subjects and classes is obtained using IT2FS classifier on a combined feature space. The study is validated using Friedman’s statistical test with respect to four other classification algorithms.

Recognition of objects from EEG signals requires selection of appropriate feature extraction and classification techniques with best efficiency in terms of highest classification accuracy with lowest run time for its applications in real time. The objective of this paper is to analyze the performance of various feature extraction techniques and to choose that particular method which can be implemented in real time system with best efficiency. The EEG signals are acquired from subjects while they explored the objects visually and visuo-tactually. Thus acquired EEG signals are preprocessed followed by feature extraction using adaptive autoregressive (AAR) parameters, ensemble empirical mode decomposition (EEMD), approximate entropy (ApEn) and multi-fractal detrended fluctuation analysis (MFDFA). The performance of these features are analyzed in terms of their dimension, extraction time and also depending upon the classification results produced by three classifiers [Support Vector machine (SVM), Naïve Bayesian (NB), and Adaboost (Ada)] independently according to classification accuracy, sensitivity and classification times. The experimental results show that AAR parameter has an optimum dimension of 36 (not too large like EEMD i.e. 7,680 or too small like ApEn i.e. 6) and required minimum extraction as well as classification time of 0.59 and 0.008 s respectively. AAR also yielded highest maximum classification accuracy and sensitivity of 80.95 and 92.31 % respectively with NB classifier. Thus AAR parameters can be chosen for real time object recognition from EEG signal along with Naïve Bayesian classifier.

This paper presents a new element antenna array of rectangular topology microstrip patches is introduced to operate at Ku band. The antenna has been designed as an arrays of patches, where number of elements, spacing’s and feeding currents has been optimized to fulfil the requirements of low side lobe level and good cross polarization. The operating frequency range of antenna array is from 12 to 18 GHz. The antenna has been designed and simulated on FR4 Substrate with dielectric constant of 4.4. This paper also presents that, the detail steps of designing and simulating the rectangular patch antenna and rectangular patch antenna Array, in Ku-band. The design is analysed by Finite Element Method (FEM) based HFSS Simulator Software 14.0 by which return loss, Impedance, 3D polar plot, Directivity and Gain of the antenna are computed. The simulated results are shows that the proposed antenna provides good performance in terms of return loss and radiation pattern for dual frequency applications.

Smoking of cigarettes has been reported to alter the cardiac electrophysiology by modulating the autonomic nervous system. A preliminary investigation of the heart rate variability (HRV) parameters suggested sympathetic predominance in smokers. An in-depth analysis of the time domain and wavelet processed ECG signals indicated that the automated neural networks (ANNs) were able to classify the signals with an accuracy of ≥85 %. This suggested that smoking not only modulates the functioning of the autonomic nervous system but is also capable of modulating the cardiac conduction pathway.

It is increasingly being made aware by various organizations including the WHO (World Health Organization) that Cardiovascular Disease (CVD) is the ‘Silent Killer’ and is the perhaps the most important cause for death globally in the present times. The prime reason being the fact that CVD often goes unnoticed at the early stages and clinical intervention is soughted only during emergency. A thorough understanding of the nature of the disease reveals the association of physiological abnormalities and subdued physiological disorders that might have raised due to stress, lifestyle related disorders, pathological conditions etc. Studies have revealed that all these problems if addressed to at an early stage can be controlled and the potential risks and hazards lessened to a considerable extent. Early detection is possible in developed countries with expensive and advanced machineries, which can keep the data recorded in a user-friendly device affordable by the patient. But in a developing country like ours a low cost affordable device is yet to be available to the rural population especially addressing the problem. The aim of this study is to design an affordable and reliable Cardiac Health Monitoring platform for identification, data storage and availability to the physician even after a considerable time interval for diagnosis of the condition and post diagnosis continued therapy. The Cardiac Health Monitoring Systems (CHMS) was developed to capture and pre-process physiological parameters (ECG, Heart Sound, Heart Rate in Normal, Stressed and Physiologically abnormal conditions) in real-time and transmit the same using wired as well as wireless communication technology. The CHMS has been so designed is designed to capture the patient’s/user’s physiological parameters in electrical form e.g. the ECG signal, apply preliminary adaptive filtering to shape the requisite signals and forward the processed data. This data is acquired by Smart hand held mobile device, and the excess processing power of the device is utilized for further processing as well as storage of medical records and transmission of data to the hospital management system or for isolated diagnosis and assessment. Critical readings crossing the set threshold (per WHO standards) would set off an alarm [locally as well as over the mobile network] and thus alert any imminent life-threatening situation.

Anultra-wideband (UWB) microstrip antenna with dual band filtering to prevent interference from coexisting WLAN and downlink of X-band satellite communication system is proposed for use in biomedical applications. Dual notch bands are achieved by etching two nearly half wavelength inverted U shaped slots on the radiating patch. Impedance bandwidth has been improved by asymmetric optimization of patch width with respect to the feed line. The antenna achieves −10 dB return loss bandwidth of about 10.45 GHz (2.35–12.796 GHz) while rejecting 4.9–5.98 and 7.15–7.99 GHz bands. The antenna has wide bandwidth, similar and stable radiation performance at the passband frequencies.

Pulmonary vein isolation is a method used for the treatment of arrhythmias originating within pulmonary veins. Cryoablation is a technique which employs extreme freezing to treat diseased or abnormal tissue. Cryoablation has gained importance in the treatment of pulmonary vein isolation for the patients suffering from atrial fibrillation. The proposed ellipsoidal ring shaped cryoprobe tip has eliminated the need of continuous point to point lesion ablation by ablating the entire circumferential area at a time. The aim of this paper is to discuss the design and advantages of the proposed tip. The desired time for the entire tip to reach a uniform temperature is ideally less than 2 s. But with the proposed tip the equilibrium condition was obtained in much lesser time of 0.5 s.

The current study delineates the designing of a three channel biosignals acquisition system. The acquisition system was made using NI USB-6009. A LabVIEW based graphical user interface (GUI) program was made to simultaneously acquire the biosignals. Electrocardiogram, spirogram and body surface temperature signals were used as the representative signals for testing the device. The device was tested successfully and may allow the acquisition of the signals under ambulatory conditions.

As Arsenic contamination in drinking water has become a matter of severe concern, researchers across the globe have been trying to develop an efficient yet economic method for removal of arsenic from water. Authors of this paper investigated combined treatment methodology namely, coagulation followed by microfiltration (MF) to remove arsenic below permissible level of 10 ppb. Simulated solutions of arsenate and arsenite salts (100 ppb) were prepared. A 95.83 % reduction of arsenic for arsenate solution and 91.99 % reduction of arsenic in case of arsenite solution were achieved in suitable pH range (8−10) when the solution was subjected to coagulation using ferric chloride coagulant, followed by MF using 0.45 µm polyethersulphone membrane. In search of more cost effective and ecofriendly yet viable route, authors explored the effectiveness of crushed Shelled

Moringa oleifera

Seed (SMOS) as a natural coagulant. A 91.01 % decontamination of arsenic for arsenate solution and 70.61 % for arenite solution were achieved in suitable pH range 7−9. This alternative method of coagulation, bio-adsorption (amino acid-arsenic interaction) followed by MF achieved in appreciable arsenic removal efficiency compared to inorganic Ferric Chloride, a synthetic coagulant. The sludge generated in case of ferric chloride was found to be toxic and highly corrosive compared to that obtained with

Moringa oleifera

seeds.

Designing a highly efficient patient care and monitoring system which can handle multiple patients and multiple parametric measurements from every single patient in real time will lead in improvising the data handling capability at Central Nurse Stations (CNS) and Decentralized Nurse Stations (DCNS). The Bio signal Data Acquisition Systems have been designed to suit patients located at CNS and DCNS in a hospital. The RTL design of Bio signal Data Acquisition System was successfully simulated using Model sim. The design was placed and routed using Xilinx ISE 8.2i tool and the bit stream generated is used for downloading into the targeted FPGA. The FPGA used is XC3S400-5ft256, common for both schemes shown. At 50 MHz operation, the system is capable of wireless communication of 32 numbers of Bio signals up to 400,000 bits/s although the maximum frequency of operation of this design is 89 MHz reported by Xilinx ISE tool. This system is truly upgradeable, be it in extending the capabilities to more number of patients or in improving throughput.

ZnO nano-particles have some unique properties like piezoelectric, semiconducting, catalytic properties and antibacterial activities. Thus these particles are widely used in optoelectronics, sensors, transducers, energy conversion and also in medical sciences. Zinc oxide nano-particles have the potential to function as natural selective killers of all highly proliferating cells, whether cancerous or not. The application of zinc oxide nano-particles in cancer therapy looks intriguing and exciting, specific tumor cell targeting will be essential (e.g., by nano-particle functionalization with cell ligands) because these nano-particles are killers of all rapidly proliferating cells, irrespective of their benign or malignant nature. So the cellular level biocompatibility and biosafety of ZnO is studied here. Hela cell line showed a complete biocompatibility to ZnO nanostructures from low to high NW concentrations beyond a couple of production periods. The L929 cell line showed a good reproduction behavior at lower NW concentration, but when the concentration was close to 100 μg/ml, the viability dropped to ~50 %. Our study shows the biocompetability and biosafety of ZnO NWs when they are applied in biological applications at normal concentration range.

Characteristic wavelength carrying the signature of virus is analytically determined through its match with the radiating wavelength comes out from computation of intersubband transition energies of different circular quantum dots, namely quantum ring and quantum disk. Time-independent Schrödinger equation is solved subject to the applied electric field along the axis, and first and second order Bessel functions are considered for computation of energy subbands. Non-monotonic spacing of quantized energy states have been observed by changing different dimensions of the quantum dots. Three lowest confinement states along with subband energies are plotted with different structural parameters, and also with external field. Comparative study reveals that better tuning of intersubband transition energy can be achieved in quantum ring than quantum disk having similar structural parameters; which reveals the fact that characteristic wavelength from quantum ring can track wider rage of virus signature. Tailoring of wavelength can be revealed by notifying the blueshift/redshift in absorption spectra in the choice of frequency region.

Stroke is a life threatening phenomenon throughout the world caused due to the blockage (by clots) or bursting of arteries. As a result permanent or semi-permanent neurological damage may occur that requires proper rehabilitation to overcome the deficiency of communication or communication disorder of the stroke patient with the outer world. This causes delay in overall recovery and affects the general hygiene of the patient. Computer vision based interaction using gazes may be helpful for such cases. In all those methodologies as a mandatory step eye tracking has to be performed. Present work uses a low cost web camera for eye tracking using Haar feature-based cascade function in comparison with the costlier eye tracking systems available in the market. This method easily detects the eye balls from the video online with less computational load. Several experiments have been carried out to evaluate the performance in different background, lighting conditions and quality of images.

The present review outlines recent advances in coacervate based research, their historical background and area of diversification. Methods of their preparation, encapsulation, theoretical overview, coacervation induced nano particle formation, applications in various fields have been covered. Chemically modified coacervates used in drug delivery research are discussed critically to evaluate the usefulness of these system in delivering bioactive molecules. From literature survey, it is realized that coacervate based research in drug delivery as well as in proto cellular biology have increased rapidly. Hence the present review is timely.

In this paper, we report, a simulation study of nanoscale ultra thin body InAsSb channel n-MOSFETs. Our work is based on numerical simulation using ATLAS, a 2-D device simulator. Accuracy of the model has been verified by comparing simulation results with the reported experimental data. The proposed model has been employed to calculate the drain current, transconductance of InAsSb channel MOSFETs for different gate and drain voltages and also to compute Short Channel Effects.