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Classification of Hypothyroid Disorder using Optimized SVM Method
Hypothyroidism is an endocrine disorder where the thyroid organ doesn't provide the enough amount of thyroid hormones. It is one of the common diseases found in women. Detection of hypothyroidism needs suitable diagnostic tests to encourage prompt analysis and medication. Accurate and early detection of a disease is more important and compulsory in healthcare domain to facilitate correct and prompt diagnosis and timely treatment. The information generated in healthcare domain is on large scale, crucial and complex with multiple parameters. To interpret and understand such a huge data and retrieve the accurate and relevant information from it is a tedious as well as challenging task. However, there is a need and importance to facilitate the patients with better medical solutions. This will help to reduce the cost, time and give more relief to users by applying advanced and upgraded knowledge. It will also assist to prevent the further complications. The proposed study gains the knowledge from the hypothyroid dataset to predict the level of disease. To identify the level of hypothyroid disorder, we used four classification machine learning techniques, namely KNN (K-Nearest Neighbour), SVM (Support Vector Machines), LR (Logistic Regression) and NN (Artificial Neural Network). The Experimental results compared the classification accuracy of four methods. Logistic Regression method achieved 96.08% accuracy among other three classifiers. But, SVM is found the best classifier after standardizing the data and parameter tuning with accuracy of 99.08%. 2019 IEEE. -
Enhancement of Reflected Faces on Semi-reflecting Surfaces
Face recognition is interesting research area in computer vision. This paper proposes to enhance faces reflected on semi reflecting surfaces such as glass window, glass screens or any other mirror like surfaces. Visibility or clarity of reflected image is depending on the reflecting ability of material surface on which reflection occurs. Other than mirror surfaces, majority of reflected images are less visibility. So recognition of reflected face is a challenge in the proposed method. This paper addresses enhancement of reflected face image. Estimating atmospheric light and medium transmission map, recover haze free image. Apply CLAHE i.e., adaptive histogram equalization by limiting contrast to obtain enhanced reflected face image. 2019 IEEE. -
Utilization of aluminum dross: Refractories from industrial waste
Aluminum oxide (Al2O3) and Magnesium-Aluminum oxides (MgAl2O4) are well known refractory materials used in engineering industries. They are built to withstand high temperatures and possess low thermal conductivities for greater energy efficiency. Dross, a product/byproduct of slag generated in aluminum metal production process is normally comprised of these two oxides in addition to aluminum nitride (AlN). Worldwide, thousands of tons of aluminum dross are generated as industrial wastes and are disposed of in landfills causing serious environmental hazard. This paper explores the potential to synergize the characteristics of the favourable contents of aluminum dross and its availability (in tons) via synthesis of refractories and thereby develop a value added product useful for the modern industries. In this work, Al-dross as-received from an aluminum industry which comprised of predominantly Al2O3, MgAl2O4 and AlN, was used to develop the refractories. AlN possesses high thermal conductivity values and therefore was leached out of the dross to protect the performance of the developed refractory. The washed dross was calcined at 700 and 1000C to facilitate gradual elimination of the undesired phases and finally sintered at 1500C. The dross refractory pellets were subjected to thermo-physical and structural properties analysis: XRD (structural phase), SEM (Microstructure), EDS (chemical constituents) and thermal shock cycling test by dipping in molten aluminum and exposing to ambient (laboratory). The findings include the favourable prospects of using aluminum dross as refractories in metal casting industries. Published under licence by IOP Publishing Ltd. -
GUI-Based Percentage Analysis forCuring Breast Cancer Survivors
The modeling approach is increasing the intensity of research in all the domains. The present paper deals with predictive modeling and probabilities. Data analysis is a technique used to transform, reconstruct, and revise some information that is an essential step to achieve the goal or the end result. The present study involves the usage of logistic regression technique for data analysis. Various domain-specific methods pertaining to science, business, etc., are available for data analysis which plays a key role in decision-making and model building. The significance of this analysis is to get the percentage of the survival of patients with advanced breast cancer. 2020, Springer Nature Singapore Pte Ltd. -
Enhancements to Content Caching Using Weighted Greedy Caching Algorithm in Information Centric Networking
Information-Centric Networks (ICN) or Future Internet is the revolutionary concept for the existing infrastructure of the internet that changes the paradigm from host-centric networks to data-centric networks. Caching in Information-Centric Networks (ICN) has become one of the most critical research areas in today's world, especially for the leading in content delivery over Internet companies like Netflix, Facebook, Google, etc. This paper is intended to propose a novel Caching strategy called Weighted Greedy Dual Size Frequency for caching in Information-Centric networks. In this paper, the WGDSF considers multiple critical factors for maintaining the Web Content efficiently in ICN Caching Router. Simulation is done for the various performance metrics like Cache Hit ratio, Link load, Path Stretch, and Latency for WGDSF cache replacement algorithm, and results shown that WGDSF outperforms well compared with LRU, LFU, and RAND Caching Strategies. 2020 The Authors. Published by Elsevier B.V. -
Ecc-based secure group communication in energy-efficient unequal clustered wsn (Eeuc-ecc)
With an advent of the Internet of things (IoT), wireless sensor networks (WSNs) are gaining popularity in application areas like smart cities, body area sensor networks, industrial process control, and habitat and environment monitoring. Since these networks are exposed to various attacks like node compromise attack, DoS attacks, etc., the need for secured communication is evident. We present an updated survey on various secure group communication (SGC) schemes and evaluate their performance in terms of space and computational complexity. We also propose a novel technique for secure and scalable group communication that performs better compared with existing approaches. Springer Nature Singapore Pte Ltd. 2020. -
Comparison of Various Types of Lubrication During Hard Turning of H13 Tool Steel by Analysing Flank Wear Using ANOVA
Hard machining of components has been a new attraction in the field of manufacturing, as it avoids the need for multiple cost inculcation processes for a single part. Hard machining attracts a wide attention to the researchers because of the usage of hard tools, tougher machinery and enormous quantities of cutting fluids. Optimized use of any of these functionaries can result in reduction of cost as well as safer and clean working environments. In this research new cutting fluid reduction processes were compared along with the use of hard metal inserts. These two methods suggest an enormous amount of cost reduction along with cleaner shop floor. Minimal quantity lubrication (MQL) and minimal cutting fluid application (MCFA) capacities in cutting fluid reduction as mentioned by various researchers in past two decades. These methods were compared in this research paper for finding out the best possible system. Flank wear is considered as a crucial parameter in hard machining as the wear rate affects other deserving product qualities such as surface finish and job profiles. In this research tungsten carbide coated hard metal inserts were used instead of conventional CBN or diamond tipped tools, which are of higher in price margin. The study comprised of Taguchis L9 orthogonal array, which was advised by previous researchers as good tool for optimisation. MQL and MCFA assisted experimentation were performed with same cutting conditions, which were then again compared with dry hard machining and wet machining. Influence of each input parameters where critically evaluated using ANOVA. The results revealed that a promising reduction in tool wear was noticed in MCFA assisted hard machining. 2020, Springer Nature Singapore Pte Ltd. -
Investigation of detoxification nature of activated carbons developed from Manilkara zapota and de oiled soya
Heavy metals are poisonous and detrimental water contaminant. Their existence affects human beings, animals and vegetation as a outcome of their mobility in aqueous ecosystem, toxicity and nonbiodegradability. This work aimed at the development of new adsorbent in the detoxification of heavy metals using Manilkara zapota tree wood and de oiled soya. The study completely focused on the characterization of the developed activation in the view of using it as a adsorbent. The characterization of activated carbon was effected SEM analysis, FTIR, XRD analysis and surface area determination. Both the activation carbon have showed a tremendous characterization in their employability as adsorbent in adsorption of heavy metals in aqueous solution. 2019 Elsevier Ltd. All rights reserved. -
RNA-seq DE genes on Glioblastoma using non linear SVM and pathway analysis of NOG and ASCL5
Differentially Expressed genes related to Glioblastoma Multiforme as an output of RNASeq studies were further studied to conclude new research insights. Glioma is a type of intracranial tumor (within the skull), which can grow rapidly in its malignant stages. Gene expression in Grade II, III and IV Gliomas is analysed using non linear SVM models. The enriched GO terms were identified GOrilla. Pathways related to NOG and ASCL5 gene were studied using Reactome. 2020, Springer Nature Switzerland AG. -
Antecedent Factors in Adolescents Consumer Socialization Process Through Social Media
The research paper attempts to find the antecedent factors that influence in adolescents consumer socialization process through social media and its impact on family purchase. Consumer socialization of adolescents through social media has become a key indicator in the area of marketing because of predominant online interaction of consumer. Socialization process framework is adopted to investigate among 254 respondents. The results show there is positive influence of antecedent variables like age, social media and peer identification on Purchase Intention and the variable social media also influences Product Involvement in family decision making. The outcome of this research benefits the academicians and marketers to explore the impact of social media on adolescent in their family decision making. Springer Nature Switzerland AG 2020. -
Geometry of Variably Inclined Inviscid MHD Flows
A steady plane variably inclined magnetohydrodynamic flow of an inviscid incompressible fluid of infinite electrical conductivity studied. Introducing the vorticity, magnetic flux density, and energy functions along with the variable angle between magnetic field and velocity vector, governing equations are reformulated. The resulting equations are solved to analyze the geometry of the fluid flow. Considering streamlines to be parallel, stream function approach is applied to obtain the pattern for magnetic lines and the complete solution to the flow variables. Next considering parallel magnetic lines, magnetic flux function approach is applied to obtain streamlines and the complete solution of the flow. A graphical analysis of pressure variation is made in all the cases. 2020, Springer Nature Singapore Pte Ltd. -
A Survey on Various Handoff Methods in Mobile Ad Hoc Network Environment
Communication has never been the same since the advent of cellular phones and numerous applications with different functionalities seem to crop up on a daily basis. Various applications seem to crop up on a daily basis. Ad hoc networks were developed with the intent of creating networks made up of interconnected nodes, on-the-go. Ad hoc networks have numerous applications, the most popular being vehicular ad hoc networks (VANETs). In VANETs, moving vehicles are considered to be the mobile nodes and mobile vehicular nodes move at high speeds. Mobility of the nodes makes it difficult to maintain stable communication links between the nodes and the access points. A process known as handoff is used to bridge this gap and is considered to be one of the solutions for unstable communication links over larger distances. Handoff can usually be seen when the nodes are mobile and start to move away from the access points. This paper discusses and compares various handoff methods that were proposed by various researchers with an intent to increase positive attributes while negating the rest of the components that do not support in increasing the efficiency of the handoff process. 2020, Springer Nature Singapore Pte Ltd. -
Sentimental analysis on voice using AWS comprehend
Sentimental analysis plays an important role in these days because many start-ups have started with user-driven content [1]. Sentiment analysis is an important research area in natural language processing. Natural language processing has a wide range of applications like voice recognition, machine translation, product review, aspect-oriented product analysis, sentiment analysis and text classification etc [2]. This process will improve the business by analyse the emotions of the conversation. In this project author going to perform sentimental analysis using Amazon Comprehend. Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to extract the content of the document. By using this service can extract the unstructured data like images, voice etc. Thus, will identify the emotions of the conversation and give the output whether the conversation is Positive, Negative, Neutral, or Mixed. To perform this author going to use some services from Aws like s3 which is used for the data store, Transcribe which is used for converting the audio to text, Aws Glue is used to generate the metadata from the comprehend file, Aws Comprehend is used to generate the sentiment file from the audio, Lambda is used to trigger from the data store s3, Aws Athena is used to convert text into structured data and finally there is quick sight where he can visualize the data from the given file. 2020 IEEE. -
Business and Environmental Perspectives of Submarine Cables in Global Market
If an individual uses any of the social media networking sites, such as Facebook, Instagram, YouTube, Twitter and the like, a subsea cable is involved there. Submarine cables are considered as critical global communications infrastructure. These cables are used by various telecom providers and content provider companies such as Google, Facebook, and Microsoft to provide seamless transmission of data for their services. Growing internet users and increasing internet traffic for various social media sites is the major reason for the growth of this market. Submarine cables enable data services such as the email, internet banking, social media networking, search engines and all other aspects related to internet that are taken for granted in daily life. These submarine cables scales up the ubiquity of cloud computing and builds digitization of activities. Undersea cable network is the new economic trade route and acts a commodity in Information age. This paper reviews the business and environmental impacts of submarine cables in the global market. Springer Nature Switzerland AG 2020. -
A GPS-Gradient Mapped Database-Based Fuzzy Energy Management System for a SeriesParallel Hybrid Electric Vehicle
The Energy Management System developed for the hybrid electric vehicle operates using a database with GPS co-ordinates and corresponding altitudes mapped, thereby giving a predictive control to optimize the operation of the seriesparallel hybrid system. The system aims at extracting the maximum potential of the seriesparallel hybrid power train architecture. The mapping of the latitude and longitude obtained from a global positioning system (GPS) to the altitude measured to create a database which generates a predefined driving cycle prior to the actual motion of the vehicle. The created database is then used in a MATLAB/Simulink model to simulate the operation of the seriesparallel hybrid system and implement the Energy Management System. The validated data is then tested in a Raspberry Pi (RPi)-based prototype. The Energy Management System regulates the vehicle dynamics based on the input drive cycle. The fuzzy logic-based control mechanism is implemented in the RPi to optimize the load sharing between the IC engine and the brushless DC motor. 2020, Springer Nature Singapore Pte Ltd. -
Impact of Meltdown and Spectre Threats in Parallel Processing
[No abstract available] -
Secure Data Processing System Using Decision Tree Architecture
[No abstract available] -
Nano ZnO@PEG catalyzed one-pot green synthesis of pyrano[2,3-d] pyrimidines in ethanol via one-pot multicomponent approach
A facile one-pot multicomponent protocol for the synthesis of bio-active Pyrano[2,3-d]pyrimidine derivatives by a one- step condensation reaction of substituted aldehyde, malononitrile/methyl cyanoacetate, barbituric acid has been demonstrated using nano ZnO@PEG as a catalyst at room temperature. The present approach offers several advantages, such as shorter reaction time, higher yields, and environmental friendliness. Easy isolation of products, absence of column chromatographic purification, use of commercially available low-cost starting materials and reusability of the catalyst make the methodology viable in organic synthesis. 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Second International Symposium ''Functional Nanomaterials in Industrial Applications: Academy - Industry Meet''. -
Effect of basalt fiber hybridization on mechanical properties of silk fiber reinforced epoxy composites
Poor mechanical properties and constraints on production presently limit the utilization of bio-based reinforcing agents to non-structural and structural automotive elements. The conjugation of natural fibre with volcanic rock fibre provides a way to improve the mechanical properties of composites over natural fibre alone. In this study, physico-mechanical properties of hybrid fibre (silk and basalt) reinforced epoxy composites were found by experimentation following acceptable ASTM standards. Hybrid composites were produced by combining silk/basalt fibres in the ratio of 50:0, 25:25 and 30:20, whereas overall weight fraction was maintained at 0.5. The experimental results showed that the performance of combined fibres were superior compared to that of silk fibre bolstered epoxy composites. Among the 2 varieties of hybrids, the silk/basalt (25:25 by weight ratio) combination offered the very best hardness, strength, modulus, and toughness to the epoxy matrix owing to the similar modulus and synergistic interaction between the two reinforcing fibres. The results also steered that the morphology and surface adhesion affected the strength of the hybrid composites. These observations give insight into the advantages of various fibre reinforcements to the mechanical performance of epoxy matrix which is considered to be brittle. The failure mechanisms and the adhesion between fibres and matrix were studied by analysing the photomicrographs of broken coupons. 2020 Elsevier Ltd. -
Response surface optimization and process design for glycidol synthesis using potassium modified rice husk silica
Glycerol, an inexpensive by-product from biodiesel production can be converted into many useful products notably glycidol, which has a wide range of uses. In this study, glycidol synthesis has been done using a biowaste mediated catalyst in a single step process. Silica and potassium incorporated silica were synthesized from biowaste rice husk. These catalysts were characterized by different spectroscopic techniques. Basic sites in the catalysts were estimated using temperature-programmed desorption study. Four operational parameters were optimized using Box Behnken Design (BBD) of response surface methodology (RSM). Potassium incorporated rice husk was found to be one of the best catalysts for glycidol production with 60.8% glycerol conversion and 62.9% selectivity within one hour of reaction time. 2020 Elsevier Ltd. All rights reserved.