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Millimeter wave components, such as circulators and isolators, frequently use magnetic fields to break symmetry of the signal propagation and provide unidirectional signal transmission. While effective, these components have not seen the level of miniaturization of other millimeter wave components, primarily due to the discrete nature of the magnets used in the components. Using circulators in the 40-50 GHz range as a motivating application, requirements arise for the deposited films, namely immunity to eddy currents, sufficient magnetization to act as self-biasing magnets, and out-of-plane orientation of the self-biasing field. Based on these required properties, hexaferrite materials are selected for their strong magnetocrystalline anisotropy (MCA) and low conductance. The difficulty of integrating these components monolithically with monolithic microwave integrated circuits (MMIC) originates from the incompatibility of crystal structure with standard semiconductor materials and process conditions. Additive manufacturing using a composite of strontium hexaferrite (SrFe12O19) particles and photoresist has been chosen as a method to overcome the difficulties of integrating hexaferrite material to semiconductor substrates. Due to their large internal anisotropy field, the particles of strontium hexaferrite tend to rotate to the field direction instead of changing magnetization direction under application of an external magnetic field (less than the anisotropy field). We have developed a method for 3D printing composites of high strontium hexaferrite concentration (up to 20% by volume) in a liquid photoresist, SU8. Rotation of hexaferrite particles in polymer matrix and thus magnetic anisotropy has been demonstrated in the composite, which is subsequently cured to hold the physical position and orientation of the particles. The anisotropy of the self-biasing field provided by the films has been experimentally characterized, and a ferromagnetic resonance (FMR) frequency ~43 GHz has been observed. We have also characterized the viscosity of the particle-laden polymer at different particle concentrations. 3D printing of this composite with poling will make it possible to directly print magnetic components that require out-of-plane anisotropic magnetization.

BioSentinel is the first biological CubeSat designed and developed for deep space. The main objectives of this NASA mission are to assess the effects of deep space radiation on biological systems and to engineer a CubeSat platform that can autonomously support and gather data from model organisms hundreds of thousands of kilometers from Earth. The articles in this special collection describe the extensive optimization of the biological payload system performed in preparation for this long-duration deep space mission. In this study, we briefly introduce BioSentinel and provide a glimpse into its technical and conceptual heritage by detailing the evolution of the science, subsystems, and capabilities of NASA's previous biological CubeSats. This introduction is not intended as an exhaustive review of CubeSat missions, but rather provides insight into the unique optimization parameters, science, and technology of those few that employ biological model systems.

The biological risks of the deep space environment must be elucidated to enable a new era of human exploration and scientific discovery beyond low earth orbit (LEO). There is a paucity of deep space biological missions that will inform us of the deleterious biological effects of prolonged exposure to the deep space environment. To safely undertake long-term missions to Mars and space habitation beyond LEO, we must first prove and optimize autonomous biosensors to query the deep space radiation environment. Such biosensors must contain organisms that can survive for extended periods with minimal life support technology and must function reliably with intermittent communication with Earth. NASA's BioSentinel mission, a nanosatellite containing the budding yeast Saccharomyces cerevisiae, is such a biosensor and one of the first biological missions beyond LEO in nearly half a century. It will help fill critical gaps in knowledge about the effects of uniquely composed, chronic, low-flux deep space radiation on biological systems and in particular will provide valuable insight into the DNA damage response to highly ionizing particles. Due to yeast's robustness and desiccation tolerance, it can survive for periods analogous to that of a human Mars mission. In this study, we discuss our optimization of conditions for long-term reagent storage and yeast survival under desiccation in preparation for the BioSentinel mission. We show that long-term yeast cell viability is maximized when cells are air-dried in trehalose solution and stored in a low-relative humidity and low-temperature environment and that dried yeast is sensitive to low doses of deep space-relevant ionizing radiation under these conditions. Our findings will inform the design and development of improved future long-term biological missions into deep space.

This work includes fabrication and electrical characterization of Metal/Interlayer/Semiconductor (MIS) structures with methyl violet organic film on p-InP wafer. Metal(Ag)/ Interlayer (methyl violet =MV)/Semiconductor(p-InP) MIS structure presents a rectifying contact behavior. The values of ideality factor (n) and barrier height (BH) for the Ag/MV/p-InP MIS diode by using the current-voltage (I-V) measurement have been extracted as 1.21 and 0.84 eV, respectively. It was seen that the BH value of 0.84 eV calculated for the Ag/MV/p-InP MIS structure was significantly higher than the value of 0.64 eV of Ag/p-InP control contact. This situation was ascribed to the fact that the MV organic interlayer increased the effective barrier height by influencing the space charge region of inorganic semiconductor. The values of diffusion potential and barrier height for the Ag/MV/p-InP MIS diode by using the capacitance-voltage (C-V) measurement have been extracted as 1.21 V and 0.84 eV, respectively. The interface-state density of the Ag/MV/p-InP structure was seen to change from 2.57×1013 eV-1cm-2 to 2.19×1012 eV-1cm-2.

A simple and accurate method based on degenerate four-wave mixing (FWM) to evaluate optical fiber dispersion and nonlinearity is presented. We investigated the continuous wave degenerate FWM characteristics of two photonic crystal fibers (PCFs) and a SMF28 fiber. Simply by measuring and analyzing the continuous wave degenerate FWM conversion efficiency as a function of the wavelength difference between pump and signal waves, fitting between experimental data and analytical FWM conversion efficiency expression is carried out to determine the dispersion, dispersion slope and nonlinear coefficient of the fiber. The fiber parameters simultaneously obtained from a single set of FWM measurement for Single Mode Fiber 28 (SMF28) are found to be agreement with the manufacturer specifications for this fiber, thus validating the PCF results and, more generally, the acceptable accuracy of the simple method proposed here.

The main goal of this article is to connect some recent perspectives in the study of 4 4 -manifolds from the vantage point of singularity theory. We present explicit algorithms for simplifying the topology of various maps on 4 4 -manifolds, which include broken Lefschetz fibrations and indefinite Morse 2 2 -functions. The algorithms consist of sequences of moves, which modify indefinite fibrations in smooth 1 1 -parameter families. These algorithms allow us to give purely topological and constructive proofs of the existence of simplified broken Lefschetz fibrations and Morse 2 2 -functions on general 4 4 -manifolds, and a theorem of Auroux–Donaldson–Katzarkov on the existence of certain broken Lefschetz pencils on near-symplectic 4 4 -manifolds. We moreover establish a correspondence between broken Lefschetz fibrations and Gay–Kirby trisections of 4 4 -manifolds, and show the existence and stable uniqueness of simplified trisections on all 4 4 -manifolds. Building on this correspondence, we also provide several new constructions of trisections, including infinite families of genus- 3 3 trisections with homotopy inequivalent total spaces, and exotic same genera trisections of 4 4 -manifolds in the homeomorphism classes of complex rational surfaces.

Biodegradable magnesium (Mg) and its alloy show huge potential as temporary bone substitute due to the favorable biocompatibility and mechanical compatibility. However, one issue deserves attention is the too fast degradation. In this work, mesoporous bioglass (MBG) with high pore volume (0.59 cc/g) and huge specific surface area (110.78 m2/g) was synthesized using improved sol-gel method, and introduced into Mg-based composite via laser additive manufacturing. Immersion tests showed that the incorporated MBG served as powerful adsorption sites, which promoted the in-situ deposition of apatite by successively adsorbing Ca2+ and HPO42−. Such dense apatite film acted as an efficient protection layer and enhanced the corrosion resistance of Mg matrix, which was proved by the electrochemical impedance spectroscopy measurements. Thereby, Mg based composite showed a significantly decreased degradation rate of 0.31 mm/year. Furthermore, MBG also improved the mechanical properties as well as cell behavior. This work highlighted the advantages of MBG in the fabrication of Mg-based implant with enhanced overall performance for orthopedic application.

This paper describes the life-saving mechanism in accidents while a force wheeler drives on the lane. Safety systems in automobile have slowly gained attention over the past decade. Airbags are among the greatest significant products for automotive security, as they have been shown to upsurge passenger safety in a variety of ways. An airbag is an automobile safety device used to save both drivers and passenger’s lives during a collision. The airbag modules contains of an initiator inflator, a pad of textiles, and frame. An airbag's function is to shield occupants during a crash and protect their bodies when they hit interior objects like steering or window, etc. The use of the airbag system reduces the number of injuries by decreasing the force exerted at any point on the body by the steering wheel, Windows and dashboard. Many researches are going to improve the airbag's features. However, the effectiveness of any safety equipment depends on its proper implementation and on certain guidelines to be followed.

Extraction of information in enterprise applications due to complex distribution of information in large identical sources. In such a scenario, a single approach or method for extracting information text would limit information needs, which would require a high level of work and time. So, it is an open problem in data analysis application to construct a suitable classification model for unsupervised datasets which having multi level of information attributes. It is vital to analyse and discover the valuable pattern information to support the accurate classification. Selection of attributes and construction of relation model always is a challenging due the increasing attribute dimensionality. So, it is important to learn and select the best attributes patterns to enhance the information association through accurate classification. In this paper, we propose an ARP-RW method for construction of Attribute Relation Pattern (ARP) through computing attributes Relation Weightage (RW) to enhance the information classification. The ARP-RW method provides the solution to identifying the relation class of the multi-attributes documents. It initially constructs an attribute relation class matrix (ARCM) utilizing the set of data collection and the RW value of the MLA. Later, it builds an ARP based on the MLA selected to perform accurate classification. The evaluation of the proposal method using the datasets of UCI Machine Learning Repository shows improvisation in comparison the existing approaches.

Material industry is one of the most seasoned and biggest areas in India. Removal of material factory slime is a significant issue now daily. In this exploration study, an endeavor had been made to reuse material factory ooze in concrete as halfway trade for sand to build mass use of ooze. Properties of new and solidified cement were explored by adding material factory slop in M20, M25 and M30 evaluations of cement. Material factory ooze was included rate by weight differing from 0% to 36% as a swap for fine totals (sand). Workability of solid blend diminished as ooze rate expanded past 16%. Compressive strength diminished with increment in ooze content in solid blend. Greatest measure of ooze which could be added without trading off the compressive strength altogether three evaluations of cement was 16% without settling on mean objective.

Stealth aircraft use Stealth Technology in order to evade recognition by utilizing mix of highlights with the goal that Aircraft can invade with RADAR and furthermore decrease the deceivability in “radio frequency (RF) range”, sound and infrared visual. During the most recent decades, stealth technology has demonstrated to be one of the best methodologies to the extent the undertaking to escape radar systems is concerned. Stealth intends to evade the recognition or attempt to cover up, for planes, avoiding radar implied stealth. The idea utilized in the stealth innovation isn’t so difficult. It utilizes the guideline to retain and mirror the radar waves. Airplane redirects the radar waves in different ways and limits the radar waves which return back to radar. Another marvel which permits the air ship maintain completely the incoming radar wavelengths to inhabit the electromagnetic reincorporated energy in various way. The structure and material used to manufacture air ship choose the degree of stealth accomplish via air ship. The thought for the radar radio wire to release Radio energy that is then returned through any item that occurs to recognize. The time taken for the reflection to come is measure by the radar radio wire and it can tell how far off an object is.

These benefits of the Usages-Based Insurances for the car that covers the overall traditional ratings techniques are also have been examined for writing more than the four decades. Despite these adoption in the insurance the markets act as a moderate. This paper looks to set up the practicality of presenting armada the Telematics based Insurances by the investigating the view of the insurance administrators, following specialist organizations and corporate armada proprietors. At its center, the investigation includes a kind of SWOT-examination to assess the Telematics based Insurances against customary premium rating systems. 25 keys partners in the Malta, a nation with an insurance industry that speaks to others in microcosm, were met to build up our investigation. Everyone affirm so that neighborhood back up plans have interests in such insurance conspires as upgraded armada the board and observing convert into an improved insurance hazard. The discoveries introduced here have suggestions for all partners as this is contend for telematics upgradation of armada board, TBI improves risk administration for back up plans and appropriation of this innovation is subject to telematics suppliers expanding the apparent control by safety net providers over dealing with this innovation.

This paper reports at Augmented Reality (AR) as a field, where a real time integration of a 3 dimensional real environment and the virtual 3D objects. This paper explains the applications related to medical, engineering, simulation, route planning, entertainment, and military that have been discussed. Two of the greatest challenges in constructing efficient augmented reality or AR systems are registration errors and sensing errors. In this paper, authors summarize current practices to overcome these issues. A discussion of future strategies and the areas requiring more study is done. Moreover, this survey can serve as an initial point for anyone those who are interested in researching and/or using augmented reality. This is because peoples are at a stage wherein adoption of technologies based on augmented reality for enhancement of our perception and to help ourselves sense our environment in a new and an enriched way is the need of the hour.

Deep learning is the extension of machine learning technique which attracted the researchers in the recent past and hence the literature is also limited. This research focused on the need for deep learning for effective prediction process, when compared with few other machine learning models. As a proof of concept, a dataset of students’ performance of a school is analysed by various machine learning models. The performance measurements by all such models are compared with deep learning. These are assessed by two familiar statistical measures, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The error rates are low for deep learning when compared with other models. It is been evident that the result obtained by the deep learning model is more effective than the other machine learning models. The results are improved by reducing the error rates at the rates of 35% by mean absolute error and 48% by root mean squared error.

The various extensions of the fuzzy set are considerably applied in many complex problems of real world to describes the improper information. The PFS (pythagorean fuzzy set) which is the expanded form of IFS (intuitionistic fuzzy set) is more applicable and precise to measure the uncertainty. The research work presents the novel entropy measure defined on PFS which satisfied axioms of the entropy. The entropy measure is determined the uncertainty that defined the fuzziness degree on the fuzzy set. The applicability of the entropy is verified in selection of the advertising company and results compared to the existing entropies defined on PFS. The outcomes of the illustrative example show that the new entropy measure is more precise, simpler, and consistent as compare to existing entropies on PFS.

The emergence of Web 2.0 tools has changed the consumer habit of using the Web. It can be used for promoting brands and products. This paper investigates the uses and effect of promotional marketing in the Web 2.0 tools on the purchase decision. A structured questionnaire was used to collect fresh-hand information from the Gen Z category. The study results reported that Web 2.0 tools provide more useful information to consumers. The fun and humorous aspects highly attracted the Gen Z category. Hence, they trusted information shared via Internet and social networks. Moreover, Web 2.0 tools highly influence the purchase decision of Gen Z. This study findings will indicate how fast the promotions in the Web 2.0 influence the purchase decision of the young customers.

This paper applies a powerful scheme, namely Bernoulli sub-equation function method, to some partial differential equations with high non-linearity. Many new travelling wave solutions, such as mixed dark-bright soliton, exponential and complex domain, are reported. Under a suitable choice of the values of parameters, wave behaviours of the results obtained in the paper – in terms of 2D, 3D and contour surfaces – are observed.

Gastric ulcer is a major gastrointestinal disease, constituting an important health issue in all societies. Honey is a sugary, flavorful, and nutritious natural product. This comparative study was designed to explore and compare the protective and therapeutic effects of manuka and Saudi Sidr honey in a rat model of gastric ulceration. Forty-two rats were divided into 6 groups: G1: healthy control; G2: ulcerated, ulceration was induced by 4 oral doses of aspirin for 4 weeks (200 mg/kg b.w./week); G3: manuka honey, therapeutic, after induction of gastric ulcer, 2.5 g/kg of manuka honey was administered daily for 30 days; G4: Saudi Sidr honey therapeutic, after induction of gastric ulcer, 0.5 g/kg Saudi Sidr honey was administered daily for 30 days; G5: manuka honey, protective, manuka honey was administered at 2.5 g/kg b.w/daily for 15 days induction then continued for a further 15 days; G6: Saudi Sidr honey, protective, Saudi Sidr honey was administered at 0.5 g/kg daily for 15 days before induction of gastric ulcer, then continued for a further 15 days. Gastric juice parameters, oxidative stress, and inflammatory markers were measured, histological analysis was performed.

Blockchain has become one of the most developing technologies in our country. Blockchain technology is a decentralized, distributed ledger that records the sources of digital assets. Electronic Medical Record (EMR) accommodates patient’s medical history, which has been carried out by a Physician or Doctor in a particular clinic or hospital or Healthcare center. Whereas, Electronic Health Record (EHR) holds patient’s entire health history, including immunization plans, diagnosis, lab reports, inoculation schedule, etc.,. This feature empowers the usage of Health IT in a more secure way with the amendment of blockchain technology. These records are maintained smart contract between the patient and the healthcare sector. In both EMR and EHR, the patient is the owner of his own data. This paper incorporates the features of blockchain technology to provide a collaborative work on Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) and it concentrates highly in diabetes as it has a sharp magnification in current world. Though it is tedious to implement this EHR all over the country, this paper works for its implementation especially in the domain of diabetes.

Present natural lives shows rising attention in various applications of the wireless sensor networks (WSNs). Significant applications are isolated and stiff regions where human involvement is hazardous or unfeasible. Some examples are space investigation, battlefield observation, costal, and edge security; nowadays, such networks are needful in several manufacturing and customer applications. A WSN is a device system, indicated as nodes; these nodes intellect the atmosphere and transfer the details collected from the ground through a wireless connection. Statistics are sent, probably via many hops, to a target that can use it nearby or is linked to various networks using the gateway. The sensor nodes might be stationary or changeable. Every node has clear data about the neighborhood or not. Communication over WSN over ecological hazards is a key issue. These constraints might impact the performance of the sensors/direction finding protocols and resource utilization; thus, they may show the way to the node crash situation, i.e., software/hardware breakdown, safety threats, extreme power utilization, etc. It is essential to examine the collision of breakdown over system performance. In the projected method, relay nodes are used as secure nodes for the positioned sensor nodes. The projected method is separated into two phases: the intra segregation stage and inter segregation stage. In the intra segregation stage, the unnecessary nodes reach nearer to the segregation border, and dispersion slowly enlarges the coverage. The projected model is examined through simulations and compares the results with existing methods.

The objective of this work to review about interaction of different food additives with Haemoglobin (Hb) and Myoglobin (Mb) proteins. Food additives are the important components which are added in food to preserve its flavour, color, appearance along with its taste. Mb and Hb interacts with numerous food dyes at varying conditions. In this study we will use various spectroscopic techniques like fluorescence spectroscopy, UV–Visible spectroscopy, Rayleigh light scattering (RLS), fluorescence resonance energy transfer (FRET), circular dichroism (CD)alongwithtransmissionelectronmicroscopy (TEM)andmoleculardockingtocharacterize the binding consequences of Mb and Hb. Proteinaggregationisthedistinctivepropertyrelatedtohumanbody. Deformationofprotein along with its aggregation leads to vast conformational change in human body and leads to several blood related (anemia, leukemia) andneurodegenerativediseaseslikeParkinson’sandAlzheimer’s. Foodadditivesaretoxictohumansaswellastoenvironment. Sothe aim of this study to find out the methods for detection of such diseases along with its cure as well as methods to release these toxic dyes via interaction of additives with Hb & Mb.

The parsing of floorplans has been an issue for a long time in automated document processing and with algorithmic methods until recent years. This problem has also improved output with the emergence of convolutionary neural networks (CNN). The job here is to obtain spatial and geometrical data from floorplans as accurately as possible. The aim of this project is to extract the most information from a floor plan image around instance segmentation models like Cascade Mask R-CNN. A new style of key point CNN is being implemented to supplement the segmentation to find correct corner positions. Then the resulting segmentation is combined in a post-processing stage. With a mean IoU of 72.7 percent versus 57.5 percent, the resulting segmentation scores surpass the existing baseline of the CubiCasa5k floorplan data base. Moreover, for almost every class, the mean IoU for each class is increased. Cascade Mask R-CNN has also been shown to be better suited to this role than Mask R-CNN.

Gesture Recognition which is an inevitable part of human computer interaction is an ever evolving active research area. This has been in use under varied applications like smart home systems, sign language recognition, augment reality and in device controls. The acquisition of hand gestures are usually through optical sensors, in this work a radar based hand gesture data set is used for classifying the gestures. Micro doppler signatures were used as the input to the model. Radar dataset has fewer data samples compared to optical based data sets. The proposed work uses separable convolutional neural networks model which does depth wise convolution followed by point wise convolution to reduce overfitting effect of the training data. The proposed model was built in such a way that the model is capable of classifying any unseen data without exactly mimicking the training samples. The proposed model has achieved 94.56% as the testing accuracy which is certainly better than the previous work on this Dop Net data set. Moreover the model has also minimized the computational hours of the model using separable convolutions.

Gold was considered as universal remedies for diseases like inflammation, infections, etc in 19th century. Later in 20th century Robert Koch discovered Gold complex Potassiumdicyanidoaurate(I) showing activity against Mycobacterium tuberculosis, later the treatment was proved to be ineffective subsequently. Further in 1985 Auranofin (Gold salt) was introduced for the treatment of Rheumatoid Arthritis, which had to be taken orally and believed to be the major discovery till injectable gold came into existence. The function of drugs based on gold is majorly related to Rheumatoid arthritis but engrossment has bent towards the adequacy of Gold compounds for anti cancer activities. The review article summarizes the current research on Gold complexes and their biological activities against cancer as well as in case of RA.

The synthesis of metallic Nanoparticles (NPs) has gathered utmost interest over the past decades thank to their distinctive properties that build them applicable in several fields further as including science and technology. This main methods utilized in their synthesis are non-environmental friendly. This review paper describes the green methods within the synthesis of biogenic NPs further as their mechanisms involving various plant extracts which are non toxic, environment friendly and value effective. The natural plant extracts contains metabolites like flavonoids, terpenoids, polyphenols, alkaloids, etc which acts as both reduction and stabilization agents for synthesizing biogenic NPs with desired shape and size. During this review paper the employment of assorted plant extracts additionally the employment of bacteria, fungi, proteins within the biogenic synthesis of NPs has been delineated shortly. Ultimately the importance and applications of biogenic NPs has also been expressed.

Content Based Image Retrieval is ever growing technology for many applications such as medical, remote sensing, social media search engines and surveillance monitoring, etc,. Representing image content with appropriate features is tedious task using traditional low level feature extraction methods. Deep learning models achieved high precision in classification and object detection algorithms by extracting automated high level feature extraction process. This paper proposed a hybrid feature extraction technique by combining the high level features and low level features to improve the robustness of the feature vector. The proposed model used pre-trained Googlenet model as feature extractor and combined with Gabor multiscale texture features. The final feature vector will be used for retrieving the relevant image data from the large scale image dataset. It has achieved the precision of 91 percent which shows better than state of art methods.

The unconventional machining processes are popular in machining the difficult to cut type complex contour/ profile. The key parameters are to be machined with care as they directly affects the function and non key dimensions are machined with other than consideration of functional aspect, like design, passage. That means accuracy is less important in those dimensions but finish is to be good. So the machining of engineering materials does not always require optimizing parameters based on multiple responses. This investigation focuses on the sensitiveness of Wire EDM of 12X18H10T - Stainless Steel and identifying the parameters contribution and establish mathematical model to predict values without trial. An austenitic alloy 12X18H10T - Stainless Steel exhibits its inherent mechanical properties even when it expose to extremely high temperature. Ithas potential application in aerospace engine components manufacturing. This investigation utilized the Taguchi L9 experiential Design with factors of Pulse off Time, Wire Tension, Pulse on Time, and Wire Feed Rate. This study aims to examine Maximize the rate of machining with Taguchi approach in the process of Wire EDM of 12X18H10T - Stainless Steel and establish a mathematical model to predict the highly influencing parameter(s) for desired rate of machining.

Electric discharge machining (EDM) routehas capability of machining hard materials. Even intricate shapes can be machined by this process. Traditional machining routes develop machining issues like tool wear and pitiable surface finish. It can be overcome by the EDM process. The objective of this work is to prepare AA6351-10wt%Al2O3-5wt%Gr composites through stir casting process. The manufactured composites were machined via EDM route and their machining characteristics material removal rate (MRR) and surface roughness (SR) were studied via Taguchi process. The results display that for MRR current is the major influencing parameter and for SR voltage is the foremostpersuading parameter.

Prediction of the facts about any topic always sounds fascinating. It becomes more important and useful when it can predict the facts about healthcare information. In computer science, machine learning techniques/models can be used to predict important health care facts, further the study of the sentiments related to health care information can also play a significant role in the generation of important information. There are many international and national organizations like United States Centers for Disease Control and Prevention (CDC), World Health Organization (WHO), etc. that publish important healthcare data. These data sets can be used to predict important facts about the disease. Further, the datasets related to sentiments of the people like tweets on Twitter, posts on Facebook, and blogs are useful to study the sentiments of the people on a particular topic. Sentiments related to health care information, diseases, and epidemics are very useful. The study of these sentiments can help make better prediction systems and to generate fruitful health care facts. Further, the real datasets related to infectious diseases like COVID-19 can be used for regression analysis for making predictions regarding the upcoming cases. In this paper, we have presented a survey on the application of different machine learning techniques, that are used in the classification and regression analysis related to health care predictions and the study of sentiments. We have presented a review of major research studies related to healthcare between the years 2010 to 2020.

According to the latest news, the 3rd Generation cooperation Project has been taken the inventiveness of creating an interworking architecture involving cellular and WLAN as an additional feature to the cellular network requirements of 3GPP. This article provides an overview of an interworking infrastructure that allows mobile operators to provide the public WLAN dependent entrance service to various 3GPP network subscribers. The enabling features include 3GPP membership reuse, network availability, authentications relying on 3GPP systems, security keys agreement, USIM /SIM card authorization, user data service access and routing, as well as end-user paying. The function of interworking is accomplished without setting any particular 3GPP specifications for the new WLAN entrance networks, but instead by depend on existing features available in the traditional WLAN entrance networks centered on the IEEE 802.11 principles. In this paper, authors have focused on two key aspects of MTC devices, as currently discussed in 3GPP-Release 10. These are named as “the control of subscriptions” and the “congestion/overload control of the network”. A new solution is proposed for the latter one based on the handling of the bulk signals.

Chitosan (CS) is a natural and biopolymer that are suitable biomedical properties such as; biocompatibility, non-toxicity, biodegradability and bioactive polymer that’s reason with a very large application (fabrication of biomedical scaffolds, implants). Some of the biocompatible thermoplastic polymers (PLA, PEEK, PLGA, PE, PP, PMMA, PET and etc.) are most widely used in biomedical field as per their properties from last two decades. Poly-vinyl chloride (PVC) thermoplastic polymer are most widely used in medical field but there are some limitations of their uses. For enhancement of PVC thermoplastic polymers properties sometimes add some bioactive and biocompatible fillers or other bioactive thermoplastic polymers. In this review paper try to link and discussed about the possible reinforcement CS in PVC thermoplastic polymer for biomedical applications.

Many organizations view themselves as market driven in this digitalized society, where the decision making depends solely on the customer feedbacks and suggestions. This massive amount of unstructured data produced, affects query processing performance adding to the difficulty in managing or retrieving the data. Many organizations are progressively exploring ways to comprehend and analyse this huge unstructured data to infer operational insights from it. We could solve many of the storage issues of unstructured data using the document-based NoSQL databases. But applying artificial intelligence to make exact matching predictions with the text data is remaining as a challenge. With the new method proposed here, the intelligent processing of the textual data stored in document-based NoSQL databases is made possible, and it is really an added benefit to those, who opt or use NoSQL databases for unstructured data storage.

The data surveying this study mines methods for extracting informative and interesting knowledge from learning student datasets. The amount of data stored in education big databases is growing at an alarming rate. As such, data processing and knowledge discovery techniques can be used to discover interesting relationships between different characteristics and assessments of students. Initially to propose a novel self-analysis model which performs analysis about the different big data learning services. From the result provided by the user, the service will be ranked and analyze about the knowledge from daily activity gathered by the learner. The proposed model performs analysis to provide efficient Educational Data Mining (EDM) E-Learning system based on machine learning to ranking the users and performance evaluation in their activities. The existing method does not consider the learner activities, ranking and it focus on single feature based classification so the system doesn’t provide a better classification result. These issues to overcome introduce an Extended Multi-Labeled Gradient Boosting (XMGB) improve the classification performance both of imbalanced dataset. The method initial stage apply the Adaptive Expectation-Maximization Mixture (AEMM) method cluster the data various group and extract the E-learning multiple feature set. In this method to compute the classification time and memory provide an efficient result. Then introduce an academic activity based weight score analysis model to evaluate the learner daily activates and exam score its help to the ranking and cluster the data groups. In this proposed method analysis result to evaluate the following performance matrix: Recall, precision, F measure, classification accuracy. In this simulation analysis of the proposed method XMGB are provide an efficient classification with less time complexity compared to other existing methods.

The primary objective of university education is to provide students with the required information and skills to enable them to make a successful contribution to the national development effort. In order to evaluate the level of expertise and skill of students, this preparation includes frequent examination and appraisal in the form of tests. Manual exams are carried out by most universities; Post Graduate and Under Graduate in India. Due to multiple uses made of the outcomes of the students, these examinations have high stakes. Consequently, the experiments became subject to different types of malpractice. Test malpractice affects the success of students in exams and leaves the scores/grades earned inaccurate, hence a challenge to examination bodies and the nation's education system (India). These are all disturbing signs that pose a danger to the nation. Examination malpractice has eaten deep into the Indian culture of education. Therefore, the object of this paper is to explore the problem of examination malpractice in India. The paper covered relevant measures, procedure setting/implementation and suggestions for this action. And finally, a model is proposed to stop malpractices in the examination. This IoT based model is used for detecting any metallic object or object in a range more than normal IR proximity sensor range. The block diagram of proposed model and circuit diagram for that model discussed in detail. This proposed model may be used for any investigation in the universities examinations.

Chatbots are becoming increasingly popular as virtual assistants, many businesses are launching If-This-Then-That programs to help them get started. Such systems, on the other hand, often generate chatbots that are stagnant and difficult to handle. The market for chatbots is increasing. Computer systems are often required, and online connections are improved by allowing users to express their needs, desires, or questions naturally and clearly by speaking, tapping, and talking. They're easy to use, perfect for people of all ages, and have the most detailed responses to questions. The majority of today's education is distributed through e-learning. A chatbot is one of the most powerful ways for students to read, as it can answer questions at any time without the need for human interaction. This chatbot is highly capable of overcoming student uncertainty without the need for human interaction. The IF THIS Then THAT paradigm is used by the bulk of chatbots. Natural language processing and deep learning technologies were used to build this chatbot. As a consequence, the chatbot will comprehend questions at a higher level.

Surface water bodies are getting contaminated day by day. Pollutants like 2-Chloropyridine (a class of halogenated pyridine derivative which are widely used in pharmaceutical and agrochemical sector) is detected in surface water bodies. It is toxic and carcinogenic. One of the reason of its presence in water bodies can be attributed to effluents from sewage treatment and industrial waste treatment plants, which may be due to inefficient conventional treatment technologies. Use of Advanced Oxidation technologies like Fenton’s oxidation has proven to be a promising alternative to degrade these recalcitrant and non-biodegradable compounds. The Present study accesses the applicability of laterite soil as a source of iron catalyst in Fenton’s oxidation process to degrade2-chloropyridine (2-CP) at various concentrations. Parameters like pH, dosage of laterite iron, hydrogen peroxide are optimized. Effect of initial concentration of the target compound on degradation kinetics is also investigated. Up to 75% degradation was achieved in a total reaction time period of 10hrs corresponding to Laterite iron: H2O2 ratio of 1:50 at a pH of 3 for a sample containing 2-CP compound at 10 mg/L. Use of iron in Fenton’s oxidation process harnessed from the laterite soil can be a suitable alternative to treat polluted water bodies contaminated with pharmaceutical halopyridine compounds.

Carbon Reinforced Plastics/polymers are metamaterials, widely used for diversified purposes for their unique features. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Carbon Reinforced Plastics”. All published articles related to “Carbon Reinforced Plastics” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps. This article had set the objective to consolidate the scientific literature regarding the “Carbon Reinforced Plastics” and also to find out the trends related to the same. The most active journals in this research domain were Mechanics of Composite Materials, Journal of Materials Processing Technology, and Applied Mechanics Reviews. The most active countries were China, Japan, Portugal, and the United Kingdom. The leading organizations engaged in the research regarding Carbon Reinforced Plastics were the University of Tokyo of Japan, the Russian Academy of Sciences of Russia, and the Ministry of Education of China. The most active authors who had made valuable contributions related to Carbon Reinforced Plastics were Yates B. Davim J.P. Reis P. and Ishikawa T.

This paper depends on safeguarding newborn children who have fallen into the bore well. A bounty kid demise reports have been accounted for up until this point. In India, for recent days’ individuals are confronting a troubled pitiless circumstance like kids have fallen in the bore well and struck in the opening which is revealed and getting caught. Salvage of caught kid from bore well is the hazardous and troublesome procedure when contrasted with different mishaps. Because of sparseness of water level, bore well are burrow to more profundity. The premise of this undertaking is to protect the baby. The salvage is finished by burrowing a parallel pit, which takes over a day and even have not discovered a certified outcome. The high purpose of this task is that the kid will be protected before it arrives at high profundity, which depends on correspondences utilizing Infra-Red Signals. At the point when the IR signal, put 2 in. oppositely inside the surface of the bore-well, but if breaks because of some blocking paper, a ringer begins rings as some alarm of a mobile. After a stake which is set as couple of ft. lower inside the surface bore well, shuts it so as to keep the babies safe from falling further inside any kind of well. Moreover CCTV cameras can be utilized for ceaselessly screen so the kid’s present situation. This framework uses a powerful LED that goes inside like a light source so light force inside these gap would be very less. These mishaps are significantly found in agrarian bore-well. The different dangers related to the salvage of children can be limited by utilizing this framework. In this elective situation, there won't be any necessities to dig the hole in parallel with the underground bore well. These kids can be spared inside a brief timeframe with no troubles.

In the recent past, the cloud materials computing plays a vital role for keeping higher range of information in state of art of cloud environment. The information has to be kept in cloud may have large size that occupies more memory space in the cloud environment. The service provider have limitations in getting cloud space and providing space to the users to store more data limited and available space of cloud. We have proposed in this paper, an accurate and efficient video/image materials compression algorithm to minimize the data size to store in the cloud with less memory space. The novel algorithm for compression of image materials using block compressive sensing double density wavelet transform (BCS-DDWT) algorithm is proposed to compress materials. Compression of the image materials could be prepared based on various wavelets at variouspositions of decomposition. The concert investigation of BCS-DDWT with wavelets at 4 various positions of decomposition using BCS-DDWTcould be shown in the results. The performance of BCS-DDWTcompression is balanced by calculating parameters such as peak signal to noise ratio, mean square error, and bits per pixeland compression ratio.

In the growing technology automobile industries plays an importance role. The tire industry is a part of automobile industry. The growing practice in the tire industry is to replace Initial wheel size machinery of a car of a greater wheel dia. and a smaller aspect tyre with the similar diameter is replaced by the pneumatics. This activity is usually synonymous with retailing, and automotive manufactures are facing an increasing inclination for new vehicles to suit the bigger tyres. This paper explores general practise and its influence on the performance characteristics of the automobile. This research is aimed at demonstrating how the plus-size pneumatic affects all vehicle performance as well as stability. Any complex tyre influence that could impact the performance of the system will be addressed and preliminary performance data will be provided on the dynamic influence of plus sizing.

Cybercrime is a daily threat against organizations and partners of all sizes and with the rapid development of technology and the great dependence on it in some transactions, a type of serious threats has emerged that pose a high degree of risk to companies and organizations that rely on financial transactions in their work. This type of threat is called Business Email Compromise (BEC), which is a type of email phishing for financial purposes. This attack increased dramatically and caused very high financial losses to companies, especially in the period of remote work and in the Corona crisis, as it increased in the third quarter of the century of this year by 94%. This type of threat does not require a high percentage of knowledge, experience, or skills in deception and fraud, it requires only a reasonable level of social engineering. In this paper, we contribute to analyze this threat is, how it occurs, ways to avoid it or reduce its incidence, and impact on the organization.

In the current research wear behaviour of nano B4C particles with Al2214 alloy composites were studied. Al2214 alloy with 2 to 6 varying weight percentages of nano B4C particles composites were developed using stir cast route. Further, these developed composites were evaluated for the microstructural studies using SEM and EDS. The wear behaviour of Al2214 alloy and Al2214 with 2, 4 and 6 wt% of nano B4C composites were analysed using pin-on-disc wear apparatus. The dry wear tests were conducted at various loads and sliding speeds with 2500 m sliding distance as a constant parameter. The microstructural explanations revealed the thorough circulation of nano particles in the Al2214 alloy matrix, further the boron carbide particles were confirmed in the composites in the form of boron and carbon components. The Al2214 alloy with nano B4C composites displayed the greater wear resistance properties. The applied load and speed were impacted the wear of as cast alloy and its composites. Various wear mechanisms were identified by using SEM images of wear surfaces.

Diagnosing a disease consumes a part of time, needs high technical methods but nowadays the smart technologies have been grown rapidly in the field of healthcare industries and also it improves the routine life of the patients, reduces the amount of work, treatment cost in the health care organization. Diseases prediction is one of the major challenges faced by society nowadays. The recent survey also stated that the death rate is remarkably high in CAD because most of the people are affected by cardiovascular diseases. Prediction and diagnosis of cardiovascular diseases is very essential nowadays to reduce the death rate and diagnosing it preliminary stage itself. In earlier studies, they worked with machine learning techniques to predict the diseases, but they are not given proper attention to identifying the feature with the help of proper feature selection methods. This paper proposed a new-found feature selection technique HRFLC (RANDOM FOREST + ADABOOST + PEARSON COEFFICIENT). This method helps to predict the diseases in a very efficient manner, and it improves the accuracy level in prediction.

IoT has started capturing the market all over the world. Nearly all household appliances are available and consumer can buy them. Lack of security leaves the customer potentially exposed to various risk factors. Risk might be ranging daily routine data theft to great financial risk, even in some cases there is life threating risk for specific or group of persons. On analyzing various devices, through that come to know that many are not devices enforced strong passwords are not devices applied, or brute-force attacks is not protected, physical replacement of faulty sensors or wiretapping the traffic. As per approximation, every two among ten applications of mobile which are being used for managing and handling IOT devices are vulnerable and are not using SSL for communication data encryption. IoT involve billions of sensors spreading all around the world. Many of them are not physically protected. Attacker could access those sensors/devices and manipulate them or replace them. Captured data through sensors is also not safe if transmitted without encrypting them. Further many devices don’t have such power to perform heavy encryption. In this research Proposed a PUF (Physically unclonable function) and light weight encryption technique-based solution. Physically unclonable function create a class for new embedded and its security purpose. PUF mainly concentrate on shift the security challenges and issues. It has a very simple architecture and can solve problem of energy-constrained IoT devices. Through this research work introduced PUF functionality with hardware sensors. Since PUF function cannot be cloned therefore sensors are safe and any modification or replacement can be easily detected. Further data received from sensors will be encrypted using light weigh encryption technique. In future this proposed methodology explore a how to store safely vast amount of data generated through billions of sensors.

The Internet of things is gaining a lot of interestfrom day to day forvarious applications like Smart cities, Industrial health monitoring, smart homes, etc. IoT systems consist of sensor devices with communication capabilities, actuators, edgegateways, Back end Servers, and IoT applications. The Ultimate goal of an IoT network is to collect sensor data, reliable Transfer sensor data to the backend serverthrough the edgegateways. Back end server delivers the sensor data to the IoT Applications. IoT application process the Sensor data and apply the appropriate decision. Reliable Transfer of sensor data tothe Backend server isessential considering wireless sensor network characteristics, low computation power, and sensor devices' bandwidth. The IoT network deployment signaling protocol plays a crucial role in communicating sensor data to the IoT program. Various application messaging protocols are currently available, like MQ TELEMETRY TRANSPORT, COAP, HTTPetc. These protocols aredesigned, developed considering richcomputation powerand bandwidth. These protocolsare notenergy efficientfor sensor devices. MQ TELEMETRY TRANSPORT-SN protocol specified for sensor devices considering wireless sensor networks. In this article, Message Telemetry Transfer Protocol-sensor networks were planned, built, and validated according to the MQ TELEMETRY TRANSPORT-SN specification.

Organic fertilizers have been used since the dawn of mankind to improve soil fertility and promote crop growth. However, the process of preparing organic fertilizers for use in agricultural activities is a labour-intensive and time-consuming procedure. Thus, in order to reduce labour costs and improve the efficiency of organic fertilizer preparation, automated organic fertilizer mixers were developed. For this research work, an improved organic fertilizer mixer based on the Internet of Things (IoT) technology capable of monitoring the status of fertilizer production remotely and providing updates and alerts to workers was developed. The aim of this work was to further reduce labour workload and costs, thus increasing efficiency of the organic fertilizer mixing process. In order to accommodate the IoT monitoring system, several modifications and design changes were carried out on the prototype of an automated organic fertilizer mixer. Tests conducted on the prototype unit showed that it performs as required. The IoT monitoring system successfully captures and uploads information on the weight of agricultural waste mixture in the storage drum to the IoT platform. This information can then be used to alert workers on when to add more agricultural waste material to the mixture or remove the processed organic fertilizer. Furthermore, an overall operational cost comparison of different organic fertilizer production methods showed that the automated organic fertilizer prototype provides operational cost savings of over 5 times when compared to current automated systems. Future work includes further automation to the agricultural waste filling and organic fertilizer removal process.

The Crime against the women in our country today is becoming a daily routine. There continues to be increased demand in the development of safety devices to ensure a secure and safe environment for the women. The key objectives are to develop a kind of “Virtual Friendly” machine to protect you from serious troubles. These suggested systems are made up of the GPS, the GSM transmitter, the Microcontrollers (LPC812), Voice Recognizer, a RF transceiver and Temperature Sensors. GPS Receiver receives satellite locations information’s I n the indirect form of the longitude and the latitude. It information is handled by the Microcontroller and this gathered information the sent to the main control point of POLICE. These special temperature sensors continuously sense the body temperature. In a case of a very low temperature indicating some emergency conditions, a kind of SMS alert would be automatically sent. The device can be triggered by the consumer on its own when self-defense is necessary. To ensure maximum performance, functionality such as warning tone, voice recognition is applied to the device. Using the SAVE ME and Support ME commands, for the voice recognizers this circuit is utilized to transmit voice commands. The device is designed as a small package and is easy to operate, so that a simple women can conveniently take these along everywhere.

The uniaxial ratchetting-fatigue interaction of extruded AZ31 magnesium (Mg) alloy is investigated by uniaxial stress-controlled cyclic tests at room temperature and with addressing the roles of different plastic deformation mechanisms. Different stress levels are prescribed to reflect the cyclic plasticity of the alloy controlled by diverse deformation mechanisms (i.e., dislocation slipping, deformation twinning and detwinning ones), and then the influences of stress level and stress rate on the ratchetting and fatigue life are discussed. The experimental results demonstrate that different evolution characteristics of whole-life ratchetting and fatigue life presented during cyclic tests with various mean stresses, stress amplitudes and stress rates are determined by the dominated plastic deformation mechanisms. It's worth noting that the ratchetting can occur in the compressive direction even in the cyclic tests with a positive (tensile) mean stress, and the fatigue life increases first and then decreases with the increase of mean stress on account of the interaction between dislocation slipping and twinning/detwinning mechanisms. Comparing the fatigue lives obtained in the asymmetric stress-controlled and symmetrical strain-controlled cycle tests, it is seen that the ratchetting deformation causes an additional damage, and then leads to a shortening of fatigue life.

To clarify the anodic dissolution mechanism of Mg, the hydrogen evolution from pure Mg in acidic solutions under galvanostatic conditions were systematically measured. With increasing anodic current density, the cathodic hydrogen evolution rate decreased, and the anodic hydrogen evolution became faster while some surface area on the Mg was becoming dark under anodic polarization. Based on the surface analysis results and the generally accepted basic electrochemical equations, the evolution kinetics of hydrogen from Mg was deduced, and the most possible surface intermediate active species that could facilitate the anodic Mg dissolution and anodic hydrogen evolution were proposed. This paper further develops the model of incomplete film Mg+ dissolution, explains many reported experimental phenomena, and clarifies misunderstandings of current mechanism.

The study aimed to identify important variables associated with policies, processes and procedures for culturally diversified organizations. Further to identify which factor among the policies, processes and procedures is the most prerequisite for culturally diversified organizations. For the study, a survey method was employed. 153 Data were collected from companies in the service industry. For the study HR managers were considered as the samples. The data samples were chosen using a simple random sampling technique. From the result obtained, it was found that; the Retention Strategies, Talent Management and Salary Reviews policies are most important for the culturally diversified organization. Also, evaluation by observing how people spend their time in the job, interviewing with existing company people periodically and Understand the career path progression of employees and their desire are important process to be considered for a culturally diversified organization. Similarly, the Compensation system, hiring guidelines and Chain of Command procedures are considered to be important for evaluating procedure in a culturally diversified organization. It can be further perceived that the male HRs indicates Procedure and Policy are an important factor to be considered for a culturally diversified organization. While the female HRs indicates Procedure and Process are an important factor to be considered for a culturally diversified organization.