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Things or device under the Internet of Things, when connected to the internet, becomes a product, offers various applications and services for end-users. Existing methodologies offer sensor-based IoT based health-care services, to the end-users populated with lots of sensed values all at a time, making the health-care system with least robustness and inefficient due to unsystematic preview of patient’s health record. In order to address this issue, a novel semantic-based service framework is proposed in this paper which allows the end-user to subscribe for a specific physiological parameter, among all the available sensed data, making the health-care system more efficient. In the SeSem framework, Semantification rules and semantification relationship table are applied to the sensed JavaScript object Notation format (JSON) data, in order to semantically separate the JSON data, into a meaningful format. To list the sensed data according to the significance of health issues, a priority is assigned to the sensors in the semantification relationship table. Hence, semantically separated data can be done along with assigned priority. Sensor-based Sematic (SS) ontology is then applied to the semantically separated data, to transform the sensed data more relevant in terms of particular disease and sensor associated with it. The semantically separated sensed data are then published to the Message Queuing Telemetry Transport (MQTT) interface. Using MQTT subscribe, the end-user along with date and time, requests for a particular service, using a Semantic Similarity mapping algorithm, which compares the entire sensed data to that of requested data and responds with a particular physiological parameter request. To make the health care system deploy services in an intelligent way, deep learning algorithm Feedforward Recurrent Neural Networks are applied, which makes the prediction of sensed data based on the latest update when the end-user subscribes for a certain sensed data without specifying date and time. The proposed methodology is evaluated against IoT performance metrics which had shoed showing better results in terms of service-oriented IoT.

Mobile learning when stored in a cloud server allows contents to be gathered and accessed using mobile devices connected with the cloud. The present problems of limited computing capacity and small space for storage in mobile phones has inspired the blend of mobile learning and cloud computing. This paper primarily focuses on Homomorphic Encryption to achieve privacy over encoded data or search the encrypted information, which is the current research area of majority of the knowledge experts. In this paper, we suggest Shifted Adaption Homomorphism Encryption (SAHE), which is regarded as the better option for all the current research going on. SAHE implements the smallest public key of 32 bit and is able to encrypt integer and real numbers. A major issue in this field of research is difficulty in protecting user's questions, which is addressed by conceiving a public key encryption technique which is based on the reversed index. Our schema preserves search efficiency using inverted index, by solving one time only search drawback encountered in earlier research works. This method is appropriate for mobile learning since the suggested algorithm will not use the mobile memory or power.

The prevailing pandemic situation by SARS-CoV-2 infection is not only worrisome by the disease per se but also for the accompanying opportunistic infection are in the rise especially in diabetic patients. We presented a case series of post-covid rhino orbital cerebral mucormycosis infection in diabetic patients resulting in high morbidity. The need to present this was to emphasis on the timely surgical and medical intervention needed to reduce morbidity and mortality by the infection. The study highlighted the importance of surgical intervention in the deadly infection.

To increase the network lifetime and to save energy clustering method can be used as in most multi hop networks Cluster top being near to primary stations use more energy because of elevated inter cluster communicate traffic load resulting in Hop spot difficulty. By select an Extra CH named as Surrogate Cluster Head (SCH) in order to restore network connectivity which is interrupted because of failure of MCH, this method uses TDMA to allot time slots.

Today we all are suffering from Covid-19, a novel virus and it is the most harmful disease across the world which mainly comes under the domain of health care research. Healthcare system gives importance to health states of the population or individual. Healthcare plays a vital role in promoting physical and mental health and well- being of people around the world. Efficient health care system leads to country’s economy, industrialization and development. Corona virus is dangerous animal and human pathogens and it is threatening people by spreading all over the world. Corona virus patients mostly suffer from lung infection studies have shown it clinically. We proposed detailed analysis on how to predict the expected death, recovered and confirmed cases based on the available data across the world using various machine learning models. Especially we constructed linear regression model (LRM), support vector machine model (SVMM) and polynomial regression models (PRM) and predicted future expected cases over a period of next 15 days. The error between the predicted model and official data curve is quite small in the process of transmission in data modeling. Compare to other models Polynomial regression model performs best prediction of corona positive cases. Forward prediction and backward inference of the epidemic helps to take decisions for necessary actions during Covid-19 propagation.

This paper attempts to apply two different equations of thermophoresis (applicable to micro-fluids) to nanofluids. Three significant parameters namely thermophoretic diffusion coefficient, thermophoretic velocity and thermophoretic mobility are used to analyse thermophoresis in a nanofluid. Both experiments and CFD simulations (ANSYS Fluent) are performed for water-alumina nanofluid under transient pool boiling conditions. A hollow stainless steel/glass chamber with a brass heater is used to boil water-alumina nanofluid under sub-cooled conditions. Three different heater surface temperatures (60, 70 and 80°C) are investigated to realize thermophoresis phenomena of the nanofluid. Random variation of temperature measurements in experiments is justified using an uncertainty analysis. Although, volume fraction of nanoparticles (diameter 46 nm) dispersed in the fluid is only 2% by volume, they are featured to exist in every frame of the numerical model for better understanding. 2-D transient implicit pressure based Navier-Stokes solver with SIMPLE (Semi-implicit Method for Pressure Linked Equation) pressure correction technique is used to discretize the numerical grid. Gauss-Seidel iterative procedure is used to solve the discretized equations. Simulation results are validated using a sequence of investigation (thermal property variation of water-alumina nanofluid with respect to pure water under steady-state/transient conditions, thumb rule from literature and experiments). A thin line of differentiation is found to exist between viscosity induced particle migration and thermophoresis induced particle migration for the nanofluid. Implications of equations and parameters used for estimating thermophoresis of nanofluid are discussed.

Background: Cervical cancer is the fourth most common cancer among women worldwide. The prevention and control of cervical cancer depends on awareness about the disease, screening procedures, and preventive measures. Objectives of this study was to assess the awareness levels on various aspects of cervical cancer among women aged 25-65 years, and to assess the impact of health education intervention among them.Methods: This community-based interventional study was conducted for a period of 15 months among 250 women aged 25-65 years by cluster sampling method in a rural population. Data on all aspects of awareness about cervical cancer, i.e., risk factors, signs and symptoms, diagnosis and treatment and prevention were collected using a pre-tested semi-structured proforma. This was followed by a post-test 2 months after health education.Results: Overall awareness for cervical cancer was found to be very poor among the study subjects in the pre-test. Awareness on risk factors, signs and symptoms, diagnosis and treatment, and prevention of cervical cancer was found to be 6%, 3.6%, 1.2%, and 1.6% respectively. A significant increase in the knowledge level was found after health education.Conclusions: As the awareness levels regarding the cervical cancer was poor among the study population, health education programme and campaigns, along with periodic screening is need of the hour to effectively prevent cervical cancer.

Emails and social communication is the newest and easiest way of data communication. Although Electronic communications are facile in nature, it is equally easy to attack these services with an intention of fraud and trickery motivation. The cyberpunks use emails to obtain valuable credentials which could be used in many ways. A simple looking mail can include phishing URLs for purloin of important information. To avoid such criminal activities, perceive and filter such kinds of mails, an integrated approach is used. Each email provider has their own filtering system or technique, but most of them don't work to their full capacity. There are instances where an email in native language or any other language other than English can be considered genuine. The objective of the paper is to overcome this problem by using an integrated technique to increase the efficiency of detecting and filtering the emails.

A wide variety of underwater applications, such as warning systems and deep water positioning systems used to track autonomous underwater vehicles etc, warrant underwater wireless communication in ...

Active Electrodes (AEs) are electrodes which have integrated bio-amplifier circuitry and are known to be less susceptible to motion artifacts and environmental interference. In this work, a low-power and high-input impedance amplifier for active electrode application is implemented based on subthreshold biasing strategies. In this proposed Application Specific Integrated Circuit (ASIC) device was versatile and numerical to achieve a high degree of programmability. It could be adapted to any other external part of one cochlear prosthesis, the sound analyzer that could be driven by a Digital Signal Processor (DSP). This research work also discusses the measurement of the electrode-skin impedance mismatch between two electrodes while concurrently measuring a bioelectrical signal without degradation of the performance of the amplifier, the efficient, noise-optimized analysis of bioelectrical signals utilizing two-wired active buffer electrodes. The reduction of power-line interference when using amplifying electrodes employing autonomous adaption of the gain of the subsequent differential amplification. The amplifier’s features include offset compensation, Common Mode Rejection Ratio (CMRR) improvement in software and a bandwidth extending down to DC. The proposed active electrode amplifier is designed using 90 nm CMOS technology. Simulation results exhibit up to the change in noise immunity and lessening in power utilization contrasted with the traditional bio-amplifier design at a similar delay.

Cloud was visualized as the authentic elucidation for rising storage space and service expenditure for Information Technology Applications. Outsourcing the data to cloud storage servers ease the client accountability by facilitating stumpy cost, secure, locality independent platforms and scalable resources. With the proliferation of cloud technologies, outsourced data is scrolling among the nodes, client unaware of storage location and no longer have possession of data. Data privacy and integrity are formidable concerns for data owners. So, verification of data integrity is vital. Thus, an efficient auditing scheme is required to guarantee data possessor so as to assure them data safety and accuracy. In this paper, we propose zero knowledge proof interactive system for data integrity verification on cloud. Our method strengthened by using Homomorphic encryption tags, generated on encrypted data with zero knowledge to the interactive members. We consider TPA (Third Party Auditor) as audit agent inside the cloud on behalf of client to reduce the communication cost. The scheme drastically reduces input and output costs by generating the probabilistic proof of possession using sampling sets of data blocks from the server. Client maintains meta data of file for verification, which reduces huge communication cost on network. Our theoretical analysis and experimental results show the efficiency of the scheme for integrity proofs.

In the present computer era of cloud computing and its security issues pertaining identification and restricting malicious users or unknown users is considered to be critical as they tend to hack or attack cloud tenant's bilinear data. The proposed work protects data pertaining seller, retailer and carrier from attacker by classifying various cloud users. Bilinear Computational Diffie-Hellman (BCDH) and Bilinear Decisional Diffie Hellman (BDDH) are used to implement Analytical Cloud Model. The classification is performed based on classification of working of processing time at Virtual Machine VM and Physical Machine PM based on their threshold values calculated based on the life time of the arrival job in Instance Allocation Pool Access Tree.

The main objective of this paper is to detect the existence of secr et information hidden within an image. Cryptography is one of the most interesting and important area in the computer industry that deals with secure transmission of information. Encryption, the process which helps for such secure transmission, prevents hackers from accessing the information. Decryption helps to retrieve the original information. Cryptography provides many methods and techniques for secure communication. The new scheme is designed to be backward-compatible, that is, a file compressed wit h our error-resilient algorithm can be still decompressed by the original decoder. In this paper, we deal with the popular Lempel -Ziv-Welch compression scheme. The algorithm manipulates a 128 -bit input using flipping, substitution, and permutation to achieve its encryption/decryption.

The use of FRP bars in place of steel rods in concrete structures plays a significant role due to non-corrosive nature. These materials possess high tensile strength and low modulus of elasticity and exhibit a linear stress–strain response up to the failure. The present study focuses on gaining an insight into the behavior of concrete beams reinforced with GFRP bars subjected to two-point loading system by varying the grade of the concrete and diameter of the bar. The modes of failure and the crack width at each stage of loading were observed. The results of load-deflection and load-crack width characteristics are discussed. The crack pattern of the GFRP beams under loading is also reported. The comparisons between the flexural capacity of GFRP beams and steel beams from theoretical analysis and GFRP beams with that of the experimental were done. The structural behavior of tested GFRP beams is validated by developing FE models using the ANSYS software.

Wireless sensor networks consist of large number of nodes often battery operated, which have ad hoc topology and variable traffic rates. The medium access control (MAC) protocol designed for the network must be stable and should consume less energy. This paper presents a novel hybrid MAC protocol that uses the information of clusters to divide the MAC layer functionality into two types, namely, bit map assisted (BMA) protocol and nanoMAC protocol for the intra and inter-cluster communication respectively. Performance of the hybrid MAC protocol is evaluated in terms of energy, delay and offered traffic load and compared with the conventional MAC schemes. Simulation results show that the hybrid MAC protocol considerably reduces the energy consumption and delay to maximize the lifetime of the sensor network. is proposed for this high contention resolution. It incorporates dynamic scheduling of non-cluster head nodes and when utilized for intra-cluster communication (5), it can significantly reduce the idle listening of nodes and conserve energy. With low contention, TDMA based MAC protocols give much lower channel utilization, higher delay and energy consumption compared with CSMA (5), (6). In inter-cluster communication, channel contention is less, hence a CSMA based MAC protocol called nanoMAC is proposed. NanoMAC protocol incorporates sophisticated sleep algorithm and collision avoidance techniques with CSMA to minimize energy consumption. Hence this paper suggests a novel hybrid MAC approach with BMA and nanoMAC and utilizes clustering scheme to reduce energy consumption. The main feature of the hybrid MAC protocol is that it can adapt to the level of contention in the network either high or low. The analysis of the proposed hybrid MAC protocol is evaluated to maximize the lifetime of the network and compared with np-CSMA and conventional TDMA schemes. The reminder of the paper is organized as follows. Section II describes the system model. Section III presents the hybrid MAC protocol scheme and its energy model for the intra and inter-cluster domain. The simulation framework and results are discussed in section IV and finally section V presents the conclusion of the suggested method.

The first principles tight-binding linear muffin-tin orbital method within the local density approximation (LDA) has been used to calculate the ground state properties structural phase transition and pressure dependence of the band gap of BeS, BeSe and BeTe. We have calculated the energy-volume relations for these compounds in the B3 and B8 phases. The calculated lattice parameters, bulk modulus and the pressure-volume relation were found to be in good agreement with the recent experimental results. We have also calculated the cohesive energy for them and they are consistent with the bulk modulus. The calculated B3 to B8 structural transition pressure for BeS, BeS and BeTe agree well with the experimental results. Our calculations show that these compounds are indirect band gap (Γ-X) semiconductors at ambient conditions. The calculated band gap values are found to be underestimated by 20–30% which is due to the usage of LDA. After the structural transition to the B8 phase BeS continues to be indirect band gap semiconductor and ultimately it becomes metallic above 100 GPa. BeSe and BeTe are metallic at B3 to B8 structural transition.

A detailed description of the electronic band structures of MgS and MgSe were investigated using the tight binding linear muffintin orbital method. The calculations were done in the zinc blende (B3) and the NaCl-type (B1) structures. The calculated ground-state properties were found to be in agreement with the experimental values. Under compression both MgS and MgSe are found to undergo a structural phase transition from the B3 to the B1 structure at pressures of 377 and 317 kbar, respectively. At ambient conditions both MgS and MgSe are found to be indirect band gap semiconductors and exhibit the phenomenon of metallization at about 50% volume compression.

Record matching is an essential step in duplicate detection as it identifies records representing same real-world entity. Supervised record matching methods require users to provide training data and therefore cannot be applied for web databases where query results are generated on-the-fly. To overcome the problem, a new record matching method named Unsupervised Duplicate Elimination (UDE) is proposed for identifying and eliminating duplicates among records in dynamic query results. The idea of this paper is to adjust the weights of record fields in calculating similarities among records. Three classifiers namely weight component similarity summing classifier, support vector machine classifier and one class support vector machine classifier are iteratively employed with UDE where the first classifier utilizes the weights set to match records from different data sources. With the matched records as positive dataset and non duplicate records as negative set, the second classifier identifies new duplicates. Then, one-class support vector machine classifier is employed for further detecting the duplicates. The iteration stops when no duplicates can be identified. Thus, this paper takes advantage of dissimilarity among records from web databases and solves the online duplicate detection problem.

Due to various reasons, the cluster based architecture has been rarely used for efficient broadcasting. In this paper, we propose to develop an Energy Efficient Broadcasting protocol using cluster based approach for the MANETs. Our protocol uses a target radius and a locally defined connected graph, to preserve the connectivity. In our algorithm, the broadcasting nodes select a subset of their neighbors using an efficient clustering technique, to forward the message using an efficient forward node selection mechanism. By simulation results, we show that our proposed protocol attains good delivery ratio with reduced delay, energy and overhead.

Changes in resonant frequencies of a winding can identify the location of breakdown during impulse tests. This is difficult with a uniform winding. We propose the use of concurrent UHF antenna and winding currents in order to locate breakdown. The work can be extended to identify partial discharge events in dry type transformers.

Capillary hemangioma is a common condition but a capillary hemangioma arising from the columella of the nose is rare. Here we report a 24 year old man who presented with a pedunculated swelling in the nasal columella. This was excised. Histopathological examination showed features suggestive of capillary hemangioma, the case was presented here due to rare occurrence in the nasal columella. Patients present with epistaxis and cosmetic alterations. Wide excision and cauterization of the base gives excellent results.