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Background: FNAC is a rapid, simple, cost-effective, and minimally invasive technique used to diagnose different types of swelling occurring in head and neck masses, and assess its need for biopsy. Methods: The study included 650 patients, who presented with palpable head and neck swelling over a period of 18 months, at our hospital. FNAC procedure has been performed and smears are stained with Papanicolaou stain, Gemisa stain, and H and E stain. Cyto-histopathological correlations were done to evaluate the need for a biopsy. Results: Out of 650 cases, lymph node lesions constitute 370 cases (56.90%) most commonly involved. Thyroid gland lesions constitute 189 cases (29.10%) followed by salivary gland lesions 38 cases (5.80%), and other 53 cases (8.20%). Histo-pathological correlation of 116 cases were done out of 650. Conclusions: FNAC serves as a guide to appropriate therapeutic management whether to locally excise a benign tumor or plan radical surgery and helps as an adjunct to histopathology.

In the present work the crystallization and densification behavior of Lithium-Disilicate (LD) glass compositions were studied with the presence of various nucleating agent and ceramic oxides. A 30 mol% Li2O-70 mol% SiO2 LD system was modified using Al2O3, P2O5 and ZrO2 by keeping SiO2/ Li2O ratio constant at 2.33. The role of 2 to 5 mol% Al2O3, P2O5 and ZrO2 were studied in terms of Differential Scanning Calorimetry, XRD and SEM. The DSC results suggest that glass transition temperature increased with the inclusion of Al2O3 and ZrO2. It is also found that, inclusion of Al2O3 and ZrO2 helped lowering melting temperatures which reduced energy cost for melt processing. The study also suggested that densification was aided by the inclusion of P2O5 and ZrO2. Keywords: Densification; Crystallization; Glass-Ceramics; DSC.

The brain tumor is the 22nd most common cancer worldwide, with 1.8% of new cancers. It is likely the most severe ailment that necessitates early discovery and treatment, and it requires the competence of neurosubject-matter experts and radiologists. Because of their enormous increases in data search and extraction speed and accuracy, as well as individualized treatment suggestions, machine and deep learning techniques are being increasingly commonly applied throughout healthcare industries. The current study depicts the methodologies and procedures used to detect a tumor inside the brain utilizing machine and deep learning techniques. Initially, data were preprocessed using contrast limited adaptive histogram equalization. Then, features were extracted using principal component analysis and independent component analysis (ICA). Next, the image was smoothed using multiple optimization techniques such as firefly and cuckoo search, lion, and bat optimization. Finally, Naïve Bayes and recurrent neural networks were utilized to classify the improved results. According to the findings, the ICA with cuckoo search and Naïve Bayes has the best mean square error rate of 1.02. With 64.81% peak signal-to-noise and 98.61% accuracy, ICA with hybrid optimization and a recurrent neural network (RNN) proved to better than the other algorithms. Furthermore, a Smartphone application is designed to perform quick and decisive actions. It helps neurologists and patients identify the tumor from a brain image in the early stages.

Two different categories of bioactive glasses prepared from biomass using SiO2 and P2O5 as glass formers are reported in this study. These glasses are prepared by melt-quench technique. The glasses are evaluated in-vitro for their bioactivity assessment with the help of simulated body fluid (SBF). The formation of hydroxyapatite (HAp) above the glass surface is taken as an indicator for the glasses to be bioactive. Hence, various experimental techniques like X-Ray diffraction, Scanning electron microscopy, Energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and Microwave plasma atomic emission spectroscopy are employed to assess the formation of HAp layer above the glass surface. All these results confirmed the formation of HAp layer. Further, drug loading and antibacterial studies were carried out to investigate the application of glass samples as drug delivery vehicles and antibacterial agents, respectively. These investigations proved that the as-prepared glass samples have high drug loading efficiency and antibacterial activity.

COVID-19 pandemic has shaken the world and has taught a lesson to maintain personal cleanliness and hygiene. In these tough times, only people with higher degree of cleanliness and hygiene could beat this deadly virus and survive the pandemic. Everyday millions of people are losing their lives due to COVID-19, which is majorly spreading due to lack of sanitization and unhygienic surroundings. Simple remedies to fight corona virus including washing hands with soaps, regular use of hand and air sanitizers, use of face mask etc. In public places such as railway stations, airports, restaurants, hospitals, cafes, shopping malls etc., the maintenance and monitoring of hygiene conditions of visiting people conditions becomes a big challenge. To help the government authorities and local administration in better surveillance and monitoring of Corona positive cases, or people contaminated with any other kind of germs and bacteria, we came up with the prototype design of ‘Germica-A germ detection machine’. It is savvy medical and clinic framework, which has multiple germ detection features installed like UV lights to detect the germ intensity on hands or any other targeted body parts. Another feature of ‘Germica’ is germ detection cameras; which can take the image of different body parts, example nails and based to its colour, it can tell if a person is sick or healthy. In preparing the prototype of ‘Germica’, scientist have vigorously tested and trained the medical data to see its actual application and degree of accuracy. Small portable device like ‘Germica’ can help in maintaining hygiene conditions in hospitals, clinics and other places. ‘Germica’ in long run can help to combat with COVID-19 pandemic and other disease that spread through human carrier.

The present work describes the synthesis of biocompatibe alkali-free glasses utilizing the agricultural waste rice husk and eggshells. A series of glasses with basic composition SiO2–P2O5–MgO–CaO has been synthesized using melt-quench technique, where P2O5 is partially replaced by MnO. These glasses are characterized to assess their in-vitro reactivity with the help of X-Ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, fourier transform infrared spectroscopy, and microwave plasma atomic emission spectroscopy techniques before and after soaking in the simulated body fluid solution. Further, drug loading and release studies are carried out with the help of UV–Visible spectrophotometer. Wherefore, a multivariable non-linear regression model has been developed to predict the release rate at different manganese oxide concentrations. The proposed model shows a high Pearson correlation coefficient between the observed and predicted absorbance. These results designate that low-cost agro-waste derived alkali-free glasses have potential in medical applications in drug delivery as well as it helps in environmental pollution management.

Smart home is a latest technology in the field of Internet of Things (IoT) through which one can manage the smart devices at home using internet. This communication takes place via insecure channel which makes it vulnerable to many attacks. Hence, a secure authentication protocol is required to transfer sensitive data within smart home. Recently Shuai et al. have designed two factor user authentication protocol for smart home environment. In this paper, it has been discussed that this protocol is vulnerable to offline password guessing attack, insider attack, replay attack, gateway bypass attack and insecure session key agreement problem. To overcome these attacks, a user authentication protocol has been proposed. Its formal security analysis and verification is given using random oracle model and ProVerif tool, respectively. In performance analysis, the proposed scheme is compared with other related scheme to show that it is more reliable and secure than them.

The major growth in computing technology has done wonders for the medical field. Being a significantly favourable research domain, many algorithms have been proposed in the near past to detect the presence of malaria parasites. The target of this work was to originate a technique which detects the parasites of malaria easily and classifies in just a few seconds. A hybrid ant colony optimization and support vector machine approach is developed for this task. In this work, ant colony optimization was used for the detection of the boundaries of microscopic images of malaria parasites and by using multi-class support vector machine, classification of malaria parasites is achieved. In SVM various parameters were taken (HSV colour values, auto correlogram, colour moments, mean amplitude, area and wavelet moments), which are used to build different classes or groups. The performance of this approach is verified by simulation results.

In the present work, silica extracted from the agricultural waste material; rice husk (RH) was utilized for the synthesis of biocompatible glass of general composition SiO2-P2O5-CaO-MgO-MoO3. In the synthesized glasses P2O5 (5%) and CaO (25%) was kept constant whereas MgO and MoO3 was varied from 10% to 20% and 0% to 5% respectively. The structural, morphological, elemental and functional properties of silica as well as the derived glasses were analyzed by X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Energy Dispersive X-ray spectroscopy (EDX) and Fourier Transform Infrared (FTIR) spectroscopy techniques. The effect of MoO3 on the structural and thermal properties of silicate phosphate glasses has been studied in details. The bioactivity of as-synthesized glass samples were further evaluated after immersion in Simulated Body Fluid (SBF) solution which shows bioactive properties thus enabling them to be used as scaffolds in implant materials.

The present work reports on the synthesis and biocompatibility of SiO2–P2O5–MgO–CaO–SrO glass system. The MgO was partially replaced by the SrO to check its influence on the bioactivity of the glass samples. The silica used for the development of glass samples was obtained from rice husk ash using acid-base precipitation technique. The structural, morphological and thermal properties of the synthesized glasses are characterized by X-Ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and differential thermal analysis (DTA) techniques. The bioactivity of the glasses was monitored by surface activity of the glass samples after treatment with the simulated body fluid (SBF). The evolution of the apatite layer was confirmed by observing variations in the crystal structures, morphological features, and evolution of new functional groups. The release of the ions in the SBF solution was examined by microwave plasma atomic emission spectroscopy (MP-AES). Evolution of the hydroxyapatite (HAp) layer was also examined by optical-analytic approach. Further the drug loading efficiency was measured using VANCO as model drug. The incorporation of SrO led to enhancement in the bioactivity of the glass samples as compared to the one without it.

OCDMA is basically a coding method used to spread optical pulses. It can support simultaneous users to access optical channels. 16 code keying encryption enhances received power, confidentiality and security of the OCDMA system. On increasing coding from 2 keying to 16 keying, power improves and trails will enhance which is possible due to the XOR gate and NRZ generator with CMUX. The successive improvement using 16 coding technique is because of 2m codewords. Because of the higher latency of XOR gate, MAI is also reduced. The confidentiality and the power improvement is the best in case of 16 code keying encryption.

Ant colony optimization (ACO) is algorithm used for optimization motivated by the natural behaviour of species of ants. In this ants retain pheromone for foraging at the ground. ACO has been originated to detect the edges of microscopic images of blood samples which are affected by malaria disease. The edge detection approach of ACO is used to maintain pheromone matrix which determines the information of edges provided at every image pixel position, based on no. of ants movement that are dispatched to be in motion on the image. Thus, changes in the intensity values of images determine the movement of the ants. The results have been taken to study an approach for Ant Colony Edge Detection method.

Due to dynamic topology and non-wired infrastructure of Wireless Sensor Networks (WSN), they are prone to attacks. Wormhole attack is one of the most popular and serious attack in WSNs. In Wormhole attack two or more malicious nodes makes a covert channel which attracts the traffic towards itself by depicting a low latency link and then start dropping and replaying packets in the multi-path route. This paper proposes promiscuous mode method to detect and isolate the malicious node during wormhole attack by using Ad-hoc on demand distance vector routing protocol (AODV) with omnidirectional antenna. This paper proposes that the nodes which are not participating in multi-path routing generates an alarm message during delay and then detects and isolate the malicious node from network.

Recommender systems are a subclass of information filtering system and are widely used in the ecommerce domain [13]. They filter huge amount of data to provide personalized recommendations on services or products to users. Most of the existing approaches to develop a recommender system do not take into account contextual information such as weather, day, time, distance and location to provide recommendations. This paper proposes a location based context aware recommender system [9] that uses a ranking function to provide top-k recommendations to the user. The contextual data is defined by the users in the form of rules and RuleML [1] is chosen as a rule based language. When an active user needs recommendations of nearby places then contextual data in the user-defined RuleML rules is extracted, evaluated and top-k recommendations of nearby places based on the ranking function are presented to the user.

With the advancement in technology, industry, e-commerce and research a large amount of complex and pervasive digital data is being generated which is increasing at an exponential rate and often termed as big data. Traditional Data Storage systems are not able to handle Big Data and also analyzing the Big Data becomes a challenge and thus it cannot be handled by traditional analytic tools. Cloud Computing can resolve the problem of handling, storage and analyzing the Big Data as it distributes the big data within the cloudlets. No doubt, Cloud Computing is the best answer available to the problem of Big Data storage and its analyses but having said that, there is always a potential risk to the security of Big Data storage in Cloud Computing, which needs to be addressed. Data Privacy is one of the major issues while storing the Big Data in a Cloud environment. Data Mining based attacks, a major threat to the data, allows an adversary or an unauthorized user to infer valuable and sensitive information by analyzing the results generated from computation performed on the raw data. This thesis proposes a secure k-means data mining approach assuming the data to be distributed among different hosts preserving the privacy of the data. The approach is able to maintain the correctness and validity of the existing k-means to generate the final results even in the distributed environment.

Grid Resource Management and security issues have become critically important with the fast expansion of grid systems. The present day research is moving towards achieving a secured architecture for resource management in Grid System. We hereby, through this paper, wish to present a secured grid resource management for global grids by addition of a trust-based layer whereby allowing grid resource to enter the commercial area, wherein it shall help the grid consumer in Decision Making, as the system will offer only those gird resources which assure of a high degree of trust relationship of grid resource provider. For the successful deployment of a Grid infrastructure, it is essential to access and make maximum use of the resources that are available on the Grid and this is possible only if the secured resources can be tracked effectively and efficiently. It is achieved by presenting a secured Grid Resource Management System based on Trust-Management System.

Grid Resource Management and security issues go hand in hand in the success of any Grid application. The present day research is moving towards achieving a secured architecture for resource management in Grid System. We hereby, through this paper, wish to present a secured grid resource management for global grids by addition of a trust-based layer whereby allowing grid resource to enter the commercial area, wherein it shall help the grid consumer in Decision Making, as the system will offer only those gird resources which assure of a high degree of trust relationship of grid resource provider. For the successful deployment of a Grid infrastructure, it is essential to access and make maximum use of the resources that are available on the Grid and this is possible only if the secured resources can be tracked effectively and efficiently. It is achieved by presenting a secured Grid Resource Management System based on Trust-Management System.

The synthesis of several epoxides ranging from monoterpenes to sesquiterpene lactones using urea hydrogen peroxide as oxidant and tungstophosphoric acid as catalyst is reported.

A Web-services based grid infrastructure is evolving to be readily available in the near future. In this approach, the Web services are inherited (encapsulated or functioned) into the same existing Grid services class. In practice there is not much difference between the existing Web and grid infrastructure. Grid services emerged as stateful web services. In this paper, we present the key components of web-services based grid and also how the resource discovery is performed on web-services based grid considering resource discovery, as a critical service, to be provided by any type of grid.