A glass series sodium cadmium borate glasses doped with titanium has been formed using melt quench technique within the composition 20Na2O-(20−x)CdO–60B2O3–xTiO2 (0 ≤ x ≤ 5 mol%). The composition was prepared to study the effect of dopant (TiO2) on physical, optical and electrical properties of the glass series under study. The results of physical parameter i.e. density and molar volume show some structural changes at higher concentration of TiO2 doping. Some theoretical physical parameters ( $${\Lambda }_{th},$$ Mcriterion, n, Rm, αm, N and R) were calculated and displayed in Tables 2 and 3. The dc conductivity of the glasses is found temperature dependent and is due to thermally activated weak polaron hopping. The conductivity value ranges in between 2.45 × 10–6 and 3.47 × 10–6 Scm−1 at 523 K temperature that indicates the semiconducting behaviour of these glasses.

Lavandula angustifolia (Syn. L. officinalis Chaix) is a member of the Lamiaceae family and an essential oil-bearing medicinal plant. This genus is native to Cape and Canary Islands and Madeira, distributed in different parts of the world from Europe to Asia across the Mediterranean Basin and in Southwest Asia and also to Southeast India. In Lavandula plant, leaves, and flowers have the highest amount of essential oil. Essential oil is extracted from the aerial parts of the plant and is used as a sedative and relaxant agent in aromatherapy. Besides, it can also be used as an antibacterial, antifungal, sedative, and antidepressant agent (Cavanagh and Wilkinson, 2002).

Microwave imaging is one of the emerging technologies for early detection of breast cancer among women having dense mammographic densities. One of the critical and valuable components of an accurate, effective and compact, involving minimum risk - microwave imaging system for early breast cancer detection is an ultra wideband (UWB) antenna. A novel, compact elliptical UWB microwave antenna is presented in this research article that might be suitable for early breast cancer detection. The simulation of antenna structure is carried out using HFSS13 FEM-based EM software. The simulation results yield better UWB response. The antenna structure provides a wide practical fractional bandwidth of more than 156%. A significant performance factor of the proposed antenna is its ability to provide sufficient gain level for short distance communication. Thus, the proposed antenna is a strong candidate for design and development of microwave imaging system for early detection of breast cancer among women with dense mammographic densities.

The transformation matrix based on D-H parameters has been utilized to find the end effector of serial manipulator viz., surgical Robot, single-finger type, nano manipulator, etc. For object manipulation at microscale and texture identification using tactile finger at end effector, it is essential for nano manipulator and tactile finger to be more precise and accurate. The accuracy and precision of these manipulators depend on the orientation and position computed by the used software platform. The present study compares the end effector matrix of the VINCI robotic arm with D-H parameters using MAT LAB and PYTHON. The transformation matrix of order 4 × 4 described the end effectors position and orientation concerning to fixed base. The Forward Kinematics of the Vinci Robot 4 DOF (degree of freedom) is calculated using MAT LAB and Python software compared with the End effector matrix. The comparative study of the end effector matrix shows that Python is more accurate and efficient in orientation and position.

Sensor design using ultra-wideband (UWB) technology is considered powerful emerging technique to extract information about the state of biological and physiological conditions of human organs for diagnostic purposes. Recently, UWB radio sensor technology is being proposed for early stage breast cancer detection in view of some superior characteristics or bio-markers over current methods. In this paper, a RDRA is designed, leading to develop the smart data acquisition system. A novel RDRA structure is simulated, which operates in the range of 3.7–7.4 GHz (67% bandwidth) which lies in the lower European UWB frequency band. The positive gain of the proposed antenna is stable across the active bandwidth and the peak value is 2.5 dB, which makes the RDRA structure highly suitable for body centric applications, especially for early detection of breast cancer. Thus, the proposed RDRA antenna structure can be integrated for early stage breast cancer detection application as well.

A Wideband Rectangular Dielectric Resonator Antenna (RDRA) is presented in this manuscript. The proposed RDRA is designed for wideband body area network (WBAN) applications due to its compact size and wideband characteristics. The proposed antenna can be effectively integrated with modern medical devices for transmitting biological signals. WBAN attract variety of applications in monitoring human health in the domains such as sports, entertainment, defense, and healthcare industry. This manuscript presents a novel RDRA to meet recent research challenges as well as applications for future generation wideband RF-device technology for BANs. The miniaturized RDRA Antenna is designed for biotelemetry using HFSS 13, FEM based 3D EM Simulation Software

A simple solution of simultaneous non-linear equations is one of the most important tasks in the analysis of the systems used in different domains of engineering, social sciences, and medical sciences. Though there are many conventional methods to solve these equations, these methods have high time, cost, and space complexity. In this work, Genetic Algorithm based technique is used to solve both single and multi-objective optimization problems by using standard benchmark problems. The soundness of the work is argued by comparing the results with other methods. The research also opens the door for the application of Genetic Algorithm in getting cost-effective solutions for complex mathematical equations.

The brain responds with high sensitivity in case of cerebral damage. Brain temperature (BT), cerebral blood flow (CBF), cerebral blood volume (CBV) and intracranial pressure (ICP) are essential parameters for brain revival in case of cerebral damage. For this reason, the coordinated learning of BT, CBF and ICP is required for improving the remedial impacts. Thus, in this exploration, a simulation model has been developed for association between brain tissue temperature (BTT), CBF, CBV and ICP to improve the apprehensions of the ICP. It includes the cardiac output, partial pressures of oxygen and carbon dioxide in cerebral artery and vein, temperature variations of brain tissue, cerebral metabolic process and pressure-volume relationship for cranial cavity. The model simulates the interaction between arterial blood pressure, BTT, produced amount of CO2 from brain tissue, changes in CBV and changes in ICP. The results show that the ICP and CBV will increase with an increase in brain tissue temperature. This model elaborates the physiology of BTT and ICP with less complexity.

The objective of this work is to analyse the performance of an underlay cognitive radio network which incorporates a variable-gain amplify-and-forward relay to enhance its performance. The system is based on extended generalised-K fading distribution and works under the constraint of interference temperature. As a result, the secondary source and the relay transmit powers will be curbed to avoid secondary signal interfering with the primary transmission when both the networks communicate simultaneously. This is the basic principle of an underlay system where both primary and secondary networks are active at the same time. The influence of fading and shadowing on the different radio links of the system is also taken into account. The analysis begins with finding the end-to-end signal-to-noise-ratio and then derives its cumulative distribution function and moment generating functions. This is followed by the derivation of the analytic closed form expressions for the outage probability, the channel capacity and the error probability of the dual-hop AF relayed underlay cognitive radio network. Numerical plots following the mathematical analysis illustrate the effects of various parameters on the system performance under the constraints of interference temperature and the secondary transmit powers.

Research on cerebrospinal fluid (CSF) circulation in human brain has significant role to diagnose the several brain diseases. There are many internal and external factors which cause the unbalanced condition of CSF circulation in the human brain. Due to this unbalanced condition, the hydrocephalus condition may occur in the human brain. In this research paper, we develop a MATLAB based fuzzy model to establish the relationship between intracranial pressure (ICP) and unbalanced condition of cerebrospinal fluid in the brain and track the how intracranial pressure changed with unbalanced condition of CSF. This unbalanced condition of CSF is created by changing the CSF absorption rate of venous system.

The major concepts developed in the 19 th and 20 th centuries about the effectors of cerebral blood flow (CBF) are considered in this research paper. These effectors (arterial physiological parameters) are: arterial partial pressure of oxygen (PaO 2 ), arterial partial pressure of carbon dioxide (PaCO 2 ) and mean arterial blood pressure (MABP). This research is focused to evaluate the most dominant factor which is accountable for the changes in the cerebral blood flow out of these three arterial physiological parameters by using the fuzzy logic modeling. The fuzzy membership functions and their linguistic classes with their optimal range of these physiological parameters are defined with the help of literature. The evaluation of dominant factor of CBF will contribute significantly in clinical use for both health and disease.

This work explores a perspective for solving system of nonlinear equations which is an eminent problem in all scientific disciplines. An evolutionary computational technique is used to handle the nonlinear system of equations by converting it into a multi-objective optimization problem. A new fitness function has been proposed, the parameters have been chosen by prior empirical analysis. To validate the performance of the proposed methodology, sensitivity analysis has been carried out by varying the parameters of Genetic algorithm. The results obtained by new approach are quite encouraging and are also compared with other existing work.

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

Filtering is most important and critical task to immaculate information like edge detection, object identification, brightness, contrast etc. from the noisy image. Various types of noises are due to faulty instrument, temperate rise of camera and some time added intentionally to preserve other useful information of the image and also depends on its transmission over various media like space to earth through vacuum media and Sea to earth station through water media etc. In this paper we presented essential used noises and filtering techniques and simulated in matlab. We discussed the noise effects and its corresponding filters. We also simulated and discussed best suitable filter to various type of noise and its results on standard image in matlab.

Nonlinear equations represent highly complex systems and their solutions by conventional methods have high computational complexity. Methods like Bisection, Regula Falsi, Newton–Raphson, Secant, Muller, etc., are used to solve such problems. This work find gaps in the existing methods and justifies the applicability of Genetic Algorithm to the problem. A Genetic Algorithm-based method has been proposed, which is more efficient and produces better results as compared to the existing methods.

The monitoring of Intracranial pressure (ICP) is necessary for the patients who are suffering from the hydrocephalus disease. But the Intracranial pressure is monitored generally by invasive method in clinics. Cerebrospinal fluid circulation also plays an important role in the changes of intracranial pressure. Therefore, by using the simulation blocks in MATLAB 7.0 the cerebrospinal fluid model is designed in this paper to study the changes in intracranial pressure with the changes in volume of cerebrospinal fluid. Paper also considered some initial conditions which are taken from literature. This model provides the similar results as provided by the literature.

With the extensive use of technology particularly internet by users, banking is becoming more dependent on technology.Unfortunately, with this the cyber-crimes related to banks are also increasing stupendously.The tendency of cyber security attacks aimed at financial sector is much high than any other sector.Some of the common cyber security attacks aimed at banks include Phishing, Cross site scripting, Cyber-squatting, Botnets, Spoofing, etc.This causes a tremendous loss of money to the customer and bank, declines bank's reputation and decreases the trust that users place in a bank.Banks are obligated to provide a safe online banking environment to its users.Although banks have taken a lot of steps for safety and security of their assets, yet these conventional security mechanisms are no longer optimum as still attackers are able to bypass these security mechanisms.Thus banks should tighten their security mechanisms and take appropriate countermeasures to ensure safety and privacy to bank's most valuable assets.In this paper, the emerging challenges in security and privacy faced by banks are analyzed.The security mechanisms used by banks have been identified.The security and privacy issues in financial sector have been recognized particularly the cyber security attacks aimed at banks.Lastly, the countermeasures that should be adopted by banks to provide protection against these attacks and ensure a safe banking environment to users have been suggested.