bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental investigation of shock train behavior in a supersonic isolator
Authors: Wang Ziao , Chang Juntao , Wu Guangwei , Yu Daren
Published: April 2021

For a better understanding of the shock train structure and its dynamic oscillation features, wind tunnel experiments with linear and stepwise increase backpressure were conducted with supersonic isolator flows at Mach 1.85 and 2.70. High-frequency wall static pressure measurements were performed along the primary and corner regions to capture the behavior of the primary and corner shock train. The fine structures of the shock train were recorded using schlieren visualization with circular, horizontal, vertical, and color knife edges. The pressure results show that the shock train leading shock at Mach 2.70 is more three-dimensional. The flow field exhibits the following features near the corner: the pressure fluctuation amplitude is smaller, the shock train leading shock is closer to the upstream regions, and the oscillation of the shock train leading shock can propagate a longer distance downstream. Schlieren snapshots obtained using horizontal and vertical knife edges show shock train structures with alternating distributions of the vertical and horizontal density gradients. Further application of color knife edges clearly distinguishes these regions. The power spectra analysis of a series of schlieren snapshots was performed to characterize the dominant oscillation structures in the flow field with different visualization variables, and the motion relationship between the structures in the shock train was clarified based on the coherence and phase analyses of the schlieren images. The disturbance downstream first causes the movement of the shock train leading shock, and the closer the downstream shock is to the shock train leading shock, the earlier it moves.
Nonstationary problem of morphological stability of radially displaced fluid in a Hele–Shaw cell
Authors: Chernoskutov A. S. , Martyushev L. M.
Published: April 2021

For the first time, the unsteady Navier–Stokes equation with an inertial term is taken into consideration to study the interface stability of a radially displaced fluid in a finite Hele–Shaw cell. The linear order perturbation theory is used. An equation for the perturbation amplitude is obtained. The dependences of the critical size of morphological stability on the cell size, fluid properties, and displacement rate are obtained and analyzed. In the case of high displacement rates, previously unknown an unusual (reentrant) behavior is discovered in which displacement is initially unstable, and then is stable and then again unstable. The possibility of increasing the critical size of stability in the cell with an increase in the displacement rate is also theoretically demonstrated for the first time.
The effect of confinement on thermal fluctuations in nanomagnets
Authors: Slöetjes Samuel D. , Hjörvarsson Björgvin , Kapaklis Vassilios
Published: April 2021

We study the magnetization dynamics in nanomagnets excited by stochastic magnetic fields to mimic temperature in a micromagnetic framework. The effect of confinement arising from the finite size of the structures is investigated, and we visualize the spatial extension of the internal magnon modes. Furthermore, we determine the temperature dependence of the magnon modes and focus specifically on the low frequency edge modes, which are found to display fluctuations associated with switching between C- and S-states, thus posing an energy barrier. We classify this fluctuating behavior in three different regimes and calculate the associated energy barriers using the Arrhenius law.
Genetic structure and new occurrence records of the iconic Tasmanian mountain shrimp
Authors: Höpel Christoph G. , Ahyong Shane T. , Richter Stefan
Published: April 2021

The iconic ‘mountain shrimps’ of the genus Anaspides Thomson, 1894, are endemic to Tasmania, inhabiting various freshwater habitats such as mountain tarns and creeks, as well as streams inside caves. They are often labelled as ‘living fossils’ because of their close resemblance to their Triassic relatives. Prior to 2015, only two species were recognised but recent studies have uncovered a total of at least seven species. The type species of Anaspides, A. tasmaniae (Thomson, 1893), was previously believed to occur throughout Tasmania, but following a review in 2016, this species was confirmed only from a small range on the east and south-east side of Mt Wellington, with Anaspides from other parts of Tasmania referable to other species. We herein provide a detailed assessment of the distribution and genetic structure of A. tasmaniae based on extensive field surveys throughout the ranges of all species of Anaspides. The distribution of A. tasmaniae is extended to include four separate localities in and around the Mt Field National Park, 50 km north-west of Mt Wellington. The recovered genetic structure of A. tasmaniae based on 48 specimens indicates that the disjunct distribution is unlikely to be the result of artificial translocation but, instead, probably reflects postglacial relictualisation of a formerly continuous range present during Pleistocene glacial maxima. Of particular interest is the record of syntopy in Anaspides, observed at the entrance of Khazad Dum cave, where both A. tasmaniae and A. swaini inhabit the inflow stream.
Cardiolipin aids in lipopolysaccharide transport to the gram-negative outer membrane
Authors: Douglass Martin V. , Cléon François , Trent M. Stephen
Published: April 2021

Significance

The outer membrane of gram-negative bacteria is a major deterrent for antibiotic entry, making it difficult to treat these infections. It is composed of both LPS and glycerophospholipids, where the synchronized synthesis between these two components is essential for the outer membrane’s unique permeability barrier. In this report, we identify a previously unidentified association between LPS and glycerophospholipids, where the presence of the complete repertoire of glycerophospholipids is required for efficient transport of LPS. Our results provide insight into how
E. coli
modifies its lipid composition to maintain the outer membrane’s formidable barrier function.
Hyperspectral interference tomography of nacre
Authors: Salman Jad , Stifler Cayla A. , Shahsafi Alireza , Sun Chang-Yu , Weibel Stephen C. , Frising Michel , Rubio-Perez Bryan E. , Xiao Yuzhe , Draves Christopher , Wambold Raymond A. , Yu Zhaoning , Bradley Daniel C. , Kemeny Gabor , Gilbert Pupa U. P. A. , Kats Mikhail A.
Published: April 2021

Significance

We invented an optical technique—hyperspectral interference tomography—that rapidly and nondestructively extracts nanoscale structural information across large samples of nacre (mother-of-pearl) and other layered materials by combining multiangle and polarization-resolved hyperspectral imaging with optical-interference modeling. We investigated nacre in mollusk shells from two different species, red abalone and rainbow abalone, and discovered a previously unknown relationship between the age of the mollusk and the thickness of aragonite tablets in nacre. Hyperspectral interference tomography will have applications in climate science, since nacre tablet thickness in fossil shells is a proxy for ancient seawater temperature, and in bioinspired mechanics, because the layered structure of nacre inspires engineered materials with exceptional strength and toughness.
Soluble α-synuclein–antibody complexes activate the NLRP3 inflammasome in hiPSC-derived microglia
Authors: Trudler Dorit , Nazor Kristopher L. , Eisele Yvonne S. , Grabauskas Titas , Dolatabadi Nima , Parker James , Sultan Abdullah , Zhong Zhenyu , Goodwin Marshall S. , Levites Yona , Golde Todd E. , Kelly Jeffery W. , Sierks Michael R. , Schork Nicholas J. , Karin Michael , Ambasudhan Rajesh , Lipton Stuart A.
Published: April 2021

Significance

Release of oligomeric/fibrillar α-synuclein (αSyn) from damaged neurons contributes to neuronal cell death in Parkinson’s disease and other neurodegenerative disorders in part via microglial activation. Here, we show that αSyn activates the NLRP3 inflammasome in human induced pluripotent stem cell (hiPSC)-derived microglia (hiMG) via dual stimulation involving TLR2 engagement and mitochondrial damage. Oligomerized amyloid-β peptide (Aβ), as found in Alzheimer’s disease brains, exacerbates this neuroinflammation. Importantly, we found that misfolded proteins such as αSyn and Aβ, when bound to antibody and presented to hiMG, result in enhanced proinflammatory response of the NLRP3 inflammasome. These findings may have important implications for antibody therapies aimed at depleting misfolded/aggregated proteins from the human brain, as they may paradoxically trigger neuroinflammation in human microglia.
Density estimation using deep generative neural networks
Authors: Liu Qiao , Xu Jiaze , Jiang Rui , Wong Wing Hung
Published: April 2021

Significance

Density estimation is among the most fundamental problems in statistics. It is notoriously difficult to estimate the density of high-dimensional data due to the “curse of dimensionality.” Here, we introduce a new general-purpose density estimator based on deep generative neural networks. By modeling data normally distributed around a manifold of reduced dimension, we show how the power of bidirectional generative neural networks (e.g., cycleGAN) can be exploited for explicit evaluation of the data density. Simulation and real data experiments suggest that our method is effective in a wide range of problems. This approach should be helpful in many applications where an accurate density estimator is needed.
Phragmidium hiratsukanum.
Authors:   USA, USDA-ARS
Published: April 2021

There is little published information on this plant pathogenic fungus, which is limited to parts of Asia. It infects Rubus spp., which exist in other regions of the world with similar environmental conditions, therefore this species may pose a threat to native or agricultural plants if introduced.
Orobanche ramosa (branched broomrape).
Authors: Parker Chris
Published: April 2021

O. ramosa does not spread rapidly or aggressively but its introduction in contaminated seed or soil can go undetected, and once introduced it can cause severe damage to important agricultural crops and prove very difficult to eradicate.
Flexible graphene/GO electrode for gel-free EEG
Authors: Ko Li-Wei , Su Cheng-Hua , Liao Pei-Lun , Liang Jui-Ting , Tseng Yao-Hsuan , Chen Shih-Hsun
Published: April 2021

Objective. Developments in electroencephalography (EEG) technology have allowed the use of the brain–computer interface (BCI) outside dedicated labratories. In order to achieve long-term monitoring and detection of EEG signals for BCI application, dry electrodes with good signal quality and high bio compatibility are essential. In 2016, we proposed a flexible dry electrode made of silicone gel and Ag flakes, which showed good signal quality and mechanical robustness. However, the Ag components used in our previous design made the electrode too expensive for commercial adaptation. Approach. In this study, we developed an affordable dry electrode made of silicone gel, metal flakes and graphene/GO based on our previous design. Two types of electrodes with different graphene/GO proportions were produced to explore how the amount of graphene/GO affects the electrode. Main results. During our tests, the electrodes showed low impedance and had good signal correlation to conventional wet electrodes in both the time and frequency domains. The graphene/GO electrode also showed good signal quality in eyes-open EEG recording. We also found that the electrode with more graphene/GO had an uneven surface and worse signal quality. This suggests that adding too much graphene/GO may reduce the electrods’ performance. Furthermore, we tested the proposed dry electrodes’ capability in detecting steady state visually evoked potential. We found that the dry electrodes can reliably detect evoked potential changes even in the hairy occipital area. Significance. Our results showed that the proposed electrode has good signal quality and is ready for BCI applications.
Second Hankel determinant for tilted bi-starlike functions of order β
Authors: Soh Shaharuddin Cik , Kamal Zammariyah Mustafa , Dzubaidi Mohamad Huzaifah Mohd , Adam Noor Latiffah
Published: April 2021

Letfbe analytic in the unit diskD={z∈C: |z| < 1}, andSbe the subclass of normalized univalent functions inD. We define the class of tilted bi-starlike functionsSσ*(β,δ), which satisfy the conditionRe{eiδ[zf'(z)f(z)]}>βwhere |δ| <πand cosδ>β. The second Hankel determinant|a2a4−a32|has been determined forSσ*(β,δ). In this paper, we also found the coefficients bound for |a2|, |a3| and |a4|.
Approximation of Fourier and its conjugate series by triple Euler product summability
Authors: Sonker Smita , Sangwan Paramjeet
Published: April 2021

The paper is related to the concept of degree of approximation of Fourier and its conjugate series with the help of triple Euler product means. New theorems based on triple E1 product transform have been established and proved under general conditions.
Discrete Cosine Transformation Based Approach for Offline Handwritten Character and Numeral Recognition
Authors: Sethy Abhisek , Patra Prashanta Kumar
Published: April 2021

Handwritten Character Recognition (HCR) of Indic scripts is one of the most challenging as compared other scripts. Recognition of handwritten character is more difficult one as compares with the printed one due to their similar structure and orientation. To have a proper recognition system for handwritten characters various researchers have adapted various methods and still yet to have more feasibility and high recognition rate to achieve. Here in this proposed work we have completely focused on handwritten characters and numerals of various scripts of different regions of India such as Bengali, Odia scripts. To have a proper solution for the ambiguities that arises in handwritten one and which has been resolved using the Discrete Cosine Transformation (DCT) as feature extraction part. This transformed based featured is used to calculated GLCM values of each images of handwritten numerals and characters. To maintain the novelty of the work in simulation part we have listed up variance nature of the individual’s images. Subsequently we have also harnessed the SVM, Neural Network, and Quadratic Classifier over dataset to report the recognition rate. After validating the proposed work, we can conclude that adopted model is quite helpful in building the automatic recognition system for both handwritten character and numerals to have solution for real time problems.
Detecting Bone Fracture in Medical Images
Authors: Satya Sriveni N , Hema Latha K , Viji Amutha Mary A , Selvan Mercy Paul
Published: April 2021

Bone fracture is one of the most ordinary problems in mortals because of accidents or other causes. Breaking bones can occur in our body, such as the wrist, heel, ankle, hip, rib, leg, chest, etc. Fractures cannot be seen with the naked eye, so X-ray/CT images are used to detect them. But sometimes these images lack sufficient detail for diagnosis. Today image processing plays an important role in detecting bone fractures. Image processing is important for the archiving and transmission of modern data, in particular for image transmission, video encoding, digital libraries, image databases, and remote sensing. This research paper presents detailed research on image processing methods for detecting bone fractures. The following research will help in studying various techniques that can be used to detect fractures in boned through the process of image processing and also includes updating of some new techniques as an improvement.
An Efficient Hybrid Machine Learning Classifier for Rainfall Prediction
Authors: Asha P. , Jesudoss A. , Mary S. Prince , Sandeep K. V. Sai , Vardhan K. Harsha
Published: April 2021

The most leading applications of Artificial Intelligence that seems to witness an immense Progression in the digital era are the Machine Learning (ML) Techniques. It learns itself from the past experiences and attempts at the best prediction of future instances or trends. Such progressive learning does not demand any explicit programming structures. Machine learning finds a wide range of application areas, and out of which accurate real time weather prediction gains importance. An interactive neural network based classification model for better prediction of rainfall has been put forth in this paper; we have proposed an interactive model for predicting rainfall using neural classification. The model is premeditated in a way, that it fetches feature extraction from a database including information about previous rainfalls in a specific area. The features were then pre-processed and further segmented by employing the random forest. The segmented outputs are then classified using neural networks. A comparison of spatial interpolation scheme is done with existing systems by deploying the hybrid classifier. The efficiency of the proposed model is evaluated and is compared with the traditional Deep Learning process and it is observed that the Random forest based interactive model provides better performance. Results of the model seem to be more accurate as the model uses an iterative approach for feature extraction.
Smart Car based on IOT
Authors: Praveena M. D. Anto , Christy A. , Helen L. Suji , Jancy S. , Nandini D. Usha
Published: April 2021

The good automotive, anyone will simply management the system along with the speech recognition and might conjointly supervision the mechanism to hide the checkout distance. The speech should recognize, to tend the square measure victimization Bluetooth module. It will grasp #4 completely various vibrant motion commands and therefore the main feature of this technique is that, if the user desires to track the system with an overt distance, it will acknowledge that conjointly. It will notice existence of universe and therefore the human intervention half is held by the supersonic sensing element. It’s a twin programming mechanism automotive within which it’s each manual and machine mode. In manual mode, we are ready to able provide the speech recognition and in machine mode, it goes on its means within which it can mechanically move once the machine mode is activated and it is often stationary by sensing the obstacle if something on its means and the obstacle detection method is held by the supersonic sensing element. The system is monitored from a laptop named Arduino Uno and the speech is recognized victimization BT speech-controlled APC reorganization engine. It’s not feasible to use custom management for the operational mechanism automotive and simple thanks to control a mechanism is certainly with speech. During the paper, we’ve propounded a speech recognition-based mostly system wherever the dominant method is going to be a great deal expedient to use.
An integrated and Dynamic Wireless Intrusion Exposure Solutions based on Neural Network
Authors: Shabu S.L. Jany , Refonaa J. , Maran Sardar , Dhamodaran S. , Vedanarayanan
Published: April 2021

Intrusion Exposure Solutions in wireless can be categorized into Outlier Intrusion Detection and Exploitation Intrusion Detection. Outlier Intrusion Detection consider the unusual identified wireless attacks. Misuse Intrusion Detection method is the identification of the known attacks. In this proposed solution, present a half breed wireless intrusion Exposure Model. To execute the wireless intrusion Exposure Model, we planned a straightforward lightweight operator. The proposed specialist identifies the most decimating and genuine assaults; Man The Middle and Denial of Provision; with the base chosen highlight set. To assess our proposed Exposure and its operator, we gather a total informational index utilizing open source assault generator virtual products. In the proposed system features are analyzed manually; it extracts the features from the raw dataset. The proposed system utilizes the LSTM systems to deal with the successive idea of the PC organize information. We dole out an edge esteem dependent on cross-approval to order whether the approaching system information succession is irregular or not. In addition, the proposed system can chip away at both stable and adjustable length information arrangement and works productively for unexpected and capricious system assaults. We at that point additionally utilize the unaided rendition of the Long Short Term Memory and Neural Networks.
To Enhance Security Mechanism in ATM Account Using Biometric System
Authors: Refonaa J. , Shabu S.L. Jany , Dhamodaran S. , Joshila Grace L.K. , Vedanarayanan
Published: April 2021

The services we use on our day-to-day life like ATM will raise a confidence that it is safe to use for daily transactions that have withdrawals, balance enquiry and take care of all other transactions ATM machine reads the card, which could be Savings or Current accounts. After verification process one can withdraw or transfer or deposit the amount. In such situations, some fraud may occur where some individuals notice others ATM account details and perform transaction process. To overcome such disturbances Biometrics can be applied. Every individual can perform his/her transactional process with Two step verification process i.e., with pin number and biometric verification process. In this way, for some extent the ATM account fraud can be controlled.
Application of Artificial Intelligence in the field of Medicine for Diagnosis
Authors: Selvan Mercy Paul , Gladence Mary , Viji Amutha Mary A. , Abitha Memala W. , Sravya M , Navya M
Published: April 2021

Because of data mining progress in biomedical and human services networks, precise investigation of clinical data benefits early illness acknowledgment, persistent consideration and network administrations. At the point when the nature of clinical data is inadequate the precision of study is diminished. In addition, various locales display one of a kind appearances of certain territorial maladies, which may brings about debilitating the forecast of illness flare-ups. In the proposed framework, it gives AI calculations to viable forecast of different illness events in sickness visit social orders. It try the adjusted gauge models over genuine medical clinic data gathered. To beat the trouble of inadequate data, it utilize an inert factor model to reconstruct the missing data. It probe a territorial interminable sickness of cerebral dead tissue. Utilizing organized and unstructured data from emergency clinic it use Machine Learning Decision Tree calculation. It predicts likely infections by mining informational indexes and gives recommended specialists and healing arrangements. It will likewise direct the clients by offering tips to carry on with a sound life, some eating routine tips and furthermore value of plants and nourishment things. As far as we could possibly know in the territory of clinical large data examination none of the current work concentrated on the two data types. Contrasted with a few run of the mill gauge calculations, the estimation precision of our proposed calculation arrives at 94.8% with a union speed which is quicker than that of the Decision tree ailment hazard forecast calculation.
Extracting image frames using image property matching technique
Authors: Saravanan D. , Immanuel Y.
Published: April 2021

Retrieve the needed content based on the users input query one of the challenging task today especially the input if it is image. This extraction procedure be different compare to the existing retrieve operation. In image data extraction user need to know the input field, based on his knowledge only the extraction take place because the complexity of the input data set. The given visual picture converted into meaningful static picture after eliminating the unwanted information from the data set then only user need to extract the needed information. This brings the huge demand in this field.

In the proposed article focus the drawback on the existing technique and provide the efficient model for extracting the needed information. The investigation outcome verifies this statement.
Modified Chorological Coded Data Compression Methodology for Wireless Sensor Networks
Authors: Jancy S. , Helen Suji , Selven Mercy Paul , Viji Amutha Mary A. , Antopraveena M.D , Roobini M.S.
Published: April 2021

Wireless Sensor Network (WSN) is a fast evolving current technology which is being employed in various applications. Despite its wide usage, WSNs have a few challenges to overcome to be called as an ideal technology. Some of the challenges are battery life time, memory storage and deployment issues. Batteries are the primary source of power supply to WSN and one of the major challenges is the energy constraint. This paper aims to propose a few techniques to better the energy efficiency of the sensor networks by saving sensor energy using data compression methodology. In this paper, a modified chorological coded data compression methodology is proposed (MCDC). This algorithm deals with assigning the sequence value to the given input information. If the assigned sequence value is a double digit number, it is converted in to single digit number. Double digit numbers and single digit numbers are combined. Separate location tables are generated for all double digit and single digit numbers. This procedure continues until all the sequence values are changed in to single digit number. Then the final single digit is assign with an equivalent Sequence Code (SC). MCDC algorithm is compared with DELTA compression and RUNLENGTH compression and a better compression ratio was achieved when compared with DELTA compression and RUNLENGTH compression algorithms.
Detection and Prevention of Spam Mail with Semantics-based text classification of Collaborative and Content Filtering
Authors: Prayla Shyry S. , Bevish Jinila Y.
Published: April 2021

Eventhough, conventional technologies are quiet good in separating spam messages, still soo many measures have to be considered to make more accuracy in spam filtering. In this work, we worked towards detecting spam mails and filtering it during its transmission. We proposed Collaborative filtering approach hybrid with text classification (semantics based). The related feature are retrieved from the text content. Also, another filtering method known as Content-based filtering is proposed which filters the same spam mail with more precision and better accuracy. Along with the semantic texts the Content-based filtering filters the special symbols such as HTML tags, @,/etc. Results are compared and the accuracy of detecting spam e-mails of Content-based filters is more than that of Collaborative filters. Both Collaborative and Content-based filters perform keyword check available in the spam keyword database and detects whether the mail sent by the sender is genuine or spam. Genuine emails are sent successfully and the spam emails are blocked at the server side. Content-based email classification requires an understanding of both structural and semantic attributes of email. Conventional research is focussed on semantic properties through structural components of email. After analysing the emails as events (as a major subset of the class of email), a rich contextual test-bed representation for an understanding of the semantic attributes of emails has been devised. The event-based emails have traditionally been studied based on simple structural properties.
Regulation of Speed for Driver Assistanceand Removal of Haze using Imageprocessing Algorithm
Authors: Delsy T. Thaj Mary , Krishnamoorthy N R , Rani D. Jamuna , Rajalakshmi G , Rani V. Amala , Thoomas Ebin.G.
Published: April 2021

The clarity of the outdoor scene images very bad due to the environmental condition result in hazy image. The process of removing the fog from that image is called dehazing. The dehazing process is very difficult in the moving image or video image. The proposed method should improve this problem for the smooth driving of the vehicles by controlling the speed by comparing the image and the scene of video taken during driving. The proposed method should remove the haze so that it will increase the visibility of the image and multi scene. The proposed method can improve the colour changes in the image which is caused by airlight. The single frame is used for the enhancement of the foggy image remove the fog using the transmission map which contains multilevel. We make use of boundary constraints and global airlight estimation is taken into account. The method is fast and noise-free that generally arise in such enhancement techniques.
Industrial Parameter Monitoring and Alarming System using IOT
Authors: Rajalakshmi G , Delsy T.Thaj Mary , Jamunarani D. , Amalarani V. , Chakravarthy P Kalyan Sai
Published: April 2021

Today, smart grids, smart homes, smart water systems, intelligent transportation, are infrastructure systems that connect our world more than we thought possible. The common vision of such systems is usually associated with a single concept, the Internet of Things (IOT), where through the use of sensors, the entire physical infrastructure is closely related to the information e-communication technologies where intelligent monitoring and management can be achieved through the use of integrated networks devices. These devices will connect to the Internet to share different types of data. The proposed system uses the ubidots server and detection applications for the internet of things for an industrial monitoring system. In this document we use detection devices to check different parameters such as the number of production, the intensity of lighting, the detection of toxic gases and the ambient temperature.
Secure K-NN Query on Encrypted Cloud Data with Multiple Keys
Authors: Vignesh R. , Deepa D. , Mana Suja Cherukullath , Keerthi Samhitha B.
Published: April 2021

Cloud computing has become an undeniably famous assistance for its adaptability and versatility, which rouses numerous associations, foundations and organizations to want to re-appropriate data administrations to cloud stage. Simultaneously, much consideration has been paid to adapt to the extraordinary security and protection issues in recloud cloud. The general methodology is to scramble data by the data owner (DO) before re-appropriating; the approved query user play out an unpredictable arrangement of encryption and decoding tasks during question execution. In any case, the above plans have accepted that the question clients are completely trusted and have the entrance to the key for scrambling and unscrambling recloud data. It will achieve a few issues in reality. So we propose a novel plan for secure KNN inquiry on encoded cloud data with various keys, in which the data owner and each question client all hold their own various keys, and don’t impart them to one another; in the interim, the data owner scrambles and decodes re-appropriated data utilizing the key of his own. Our plan is built by set of conventions to jelly the data classification and question over scrambled cloud data without key-sharing.
Experimental Study on Concrete With Partial Replacement of Coarse Aggregate with Cashew Shells
Authors: Priyadharshini B , Nirmala R , Eshanthini  , Manoj Kumaar C
Published: April 2021

Concrete is a mix of cement, fine aggregate and coarse aggregate with water in correct proportion. Many attempts had been to replace the fine aggregate, coarse aggregate and cement in concrete. In this row replacement of coarse aggregate by cashew shells was tried. Over 66% of the overall country export cashew kernels. The cashew seeds is well acclaimed for its good quality and appearance. Concrete cubes and beams had casted using cashew shell as a partial replacement of the coarse aggregate in the proportion of 10%,20% and 30% replacement. the specific gravity of the shell was analyzed and 16mm shell were selected for the experiment. The characteristic of concrete was determined and the result showed that 10% replacement of shell with coarse aggregate gives the optimum strength.
Design of an Efficient System to Harvest Energy from Structural Load
Authors: Premi M.S.Godwin , Sheeba G.Merlin , Livinsa Z.Mary , Valantina G.Mary
Published: April 2021

Human has needed and used energy at an increased rate for their various uses. As a result, huge amount of energy is exhausted and lost. Our objective is to harvest energy from the vehicle with or without load using mechanical gear system and to increase the efficiency level of the energy. The gear system will make the generator rotate, thus producing energy. This work is a real-time work as lot of vehicles moving daily will cross over the setup, generating efficient amount of electrical energy. It is an eco-friendly system as it doesn’t harms anything. It is a conventional power generation system when compared to existing systems. The work deals with the design of the model in real-time of the energy harvester using gear arrangements and increase in efficiency level of energy. The most challenging part in this assignment is the material that is to be used as top plate assembly, such that it can absorb heavy loads like buses, trucks with water tanks etc. Below the plate there are springs in which deformation will take place. The gear assembly is connected to the bottom of the spring through its teeth. When the spring gets deformed due to load, the gear assembly will be rotated which in turn will rotate the generator as it is coupled to the gear assembly. So energy will be produced. To increase its efficiency, gear assembly consisting of different sizes of gears, is used to increase the rotation of the generator which will produce more electrical energy. Generally, the output will be AC (alternating current), so AC to DC (direct current) converter is used. Amplifiers can also be used to make the energy more efficient and store it in battery for further application.
Critical flow over an uneven bottom topography using Forced Korteweg-de Vries (fKdV)
Authors: David Vincent Daniel , Bahar Arifah , Aziz Zainal Abdul
Published: April 2021

This research examined the critical flow over an uneven bump using forced Korteweg-de Vries (fKdV) model. The forced KdV model containing forcing term which represent an uneven bump is solved using Homotopy Analysis Method (HAM). HAM is a semi-analytic technique whereby its solution contains a series of approximated solution in which it converges immediately to the exact solution. A particular HAM solution is chosen with an appropriate convergence parameter by referring to horizontal line segment. The convergent HAM solution depicts that waves only exhibited over the sloping region and no rise of waves found on flat part of bottom topography.
Network Simulation Model for Free Convective Flow from a Vertical Cone
Authors: yovan Immanuel , pullepu Bapuji
Published: April 2021

An axisymmetric, mathematical models is obtainable for the laminar natural convective laminar flow with effects of heat as well as mass transmission on an incompressible viscid liquid past a cone by uniform wall concentration, variable surface temperature including with effect of chemical reaction. The solutions of non-dimensional leading boundary layer equation of flow which are coupled, unsteady and nonlinear PDE’s were obtained using NSM, a robust statistical method which demonstrate elevated effectiveness and accurateness and the computer code Pspice. The different profiles of temperature, velocity and concentration were analyzed for different parameter, namely λ (chemical reaction), Sc (Schmidt number), Pr, N (buoyancy ratio constraint) and power law exponential of wall temperature n are discussed graphically. The current experiment result is compare with the existing outcome in the open literature and is found to be in outstanding conformity.
Computational Fluid Dynamic Analysis of Flow around Mangrove roots.
Authors: Rahuman Sini , Ismail A. Mohamed , Varghese Shyla Manavalan
Published: April 2021

The objective of this paper is to study the flow patterns around mangrove roots to understand its significance in coastal risk reduction. A computational model of two-dimensional Pneumatophores mangrove roots is developed, and flow is simulated using ANSYS software with a predefined mathematical model and boundary conditions. Computational fluid dynamic analysis of a two-dimensional, viscous, incompressible, turbulent flow under steady and unsteady boundary condition is performed using the Finite volume method. Detailed velocity profiles, residual plots, pressure distributions, vectors of the velocity magnitude and pressure and velocity at different positions around the mangrove roots are presented to visualize the importance of mangroves in reducing the wave velocity. The simulation outcome confirms that the mangrove roots of mangrove species can reduce the initial velocity of water flow. The flow patterns and flow structures around the root in the mangrove forest establishes precious data in increasing the effectiveness of current breakwater model.
Analysis of MHD free convective stream past a vertical permeable plate and a warmth source through permeable material underneath oscillatory pull
Authors: Sheeba Juliet S , Vidhya M , Govindarajan A , Priyadarshini E
Published: April 2021

The mass exchange with the warmth source on the free convective progression of a gooey incompressible electrically directing liquid past vertically permeable plate through a permeable medium in nearness of a cross over attractive field with time dependant penetrability and oscillatory pull is considered in this paper. The arrangement is acquired by the Perturbation strategy for speed field temperature and fixation dissemination. The impacts of different boundaries on the speed field, temperature, and fixation dissemination are examined through diagrams. Likewise, the skin contact and Sherwood number are determined.
A Study on Exponential and Linear Density Stratification on Rectangular Channel Problems
Authors: Venkatesh L. Prasanna
Published: April 2021

In this paper we analyze viscous oscillatory MHD inhomogeneous fluid flow through the rectangular channel with one wall being porous through which suction or injection is taken place with constant rate and the other wall being rigid. The density function in the equation of incompressibility are considered in first case as exponentially distributed and that in the second case as linearly distributed. The governing equation of motion in both cases are solved using similarity transformation and the graphical representation in both cases are analyzed and compared for velocity profiles. Further for second-degree approximation, the exponential stratification reduces to the results of linear stratification results, which are already available in the literature.
Fuzzy number conjoint method to measure students’ expectation on the learning of mathematics
Authors: Osman R , Ramli N , Badaruddin Z , Ayub H , Karim S N A Syed Abdul
Published: April 2021

The issues related to students’ expectation on the learning of mathematics is considered crucial because one can never decide the appropriate educational path that suits the students according to what they are supposed to study and should engage in the learning process. This study performed analysis on the secondary data of a previous research conducted on students’ expectation on the learning of mathematics. Due to the vague and imprecise human judgment and preference, fuzzy approach is used in this study. The fuzzy conjoint method based on fuzzy set is being widely used to analyse human preference. However, the method cannot produce the weight of attribution in various degrees of confidence. The aim of this study is to improve fuzzy conjoint method based on trapezoidal fuzzy number and investigate the students’ level of preferences on the learning of Mathematics and to compare the result with the secondary data. Hence, by incorporating fuzzy number in continuous form, it will enable the respondents to express their opinion in a more detailed interpretation. This study improvised the existing procedure by employing trapezoidal fuzzy number in representing the predefined linguistic terms and the aggregation of preference level of the respondents based on each criterion. The highest priorities of degree of agreement for students’ expectation is lecturers should focus more on developing and understanding the concept of learning mathematics, followed by student-lecturer interaction and lecturers and lecturers should have sufficient time to complete all the syllabus.
Design and analysis of inverse fuzzysoft set for triangular and trapezoidal membership function in decision making
Authors: Kavitha C , Prabakaran Christina
Published: April 2021

Decision making plays a vital role within uncertain, imprecise situations in recent years. A numerical actualize called soft set by Molodtsov was started to bargain uncertain condition. Herein article, inverse triangular and trapezoidal fuzzy soft set theory is analyzed in decision making. Inverse fuzzysoft set theory is an extension of fuzzy soft set theory which gives deeper insights in decision making and gives a technique to portray the character of each object in the universe. An application of inverse triangular and trapezoidal fuzzy soft set is established in the course of case study in multi-criteria decision making.
Integration of Sorensen and Cosine Similarity Measure for Solving Fuzzy Decision Making Problems
Authors: Mohamad Daud , Suboh Nurmaizatul Nabilah
Published: April 2021

Similarity measure has been used in many fields of study to measure common features between objects. The fuzzy similarity measure is popularized when elements of vagueness and subjectivity are incorporated in the comparison process. It is a preferred approach to some distance methods since in obtaining the distances, the defuzzification process will be involved that may cause loss of some vital information due to simplification process to a single value. Several fuzzy similarities have been proposed to cater different setting and for better discrimination. Nevertheless, in many cases, an extreme degree of similarity may occur due to the characteristic of the similarity measure itself. In particular, the Cosine similarity measure gives a too low degree of similarity while the Sorensen similarity measure gives a too high degree of similarity where in return the utilization of these similarities may not give the acceptable measurement of similarity. An integration of two or more similarity measures may assist to eradicate this problem. In this paper, the Sorensen and Cosine similarity measure were integrated based on the variation coefficient representation under fuzzy environment. A procedure of ranking alternatives is proposed using the new integrated similarity measure and is used to solve the grading problem of oil palm fruit bunch. The proposed integrated fuzzy similarity measure of Cosine and Sorensen has an advantage of being able to compromise the extreme values produced by the two similarity measures and has the potential to be applied to solving various fuzzy decision making problems.
Isometric Path Partition Problem on Tree Derived Architectures
Authors: Prabha R , Kalaiyarasi R
Published: April 2021

An isometric path partition of a graph G is defined as a set of isometric paths that partition the vertex set of G. The problem of isometric path partition is to obtain a minimum isometric path partition of G. The isometric path partition number of a graph G, denoted by ip
p
(G) is the minimum cardinality of isometric path partition in G. In this paper, we compute the isometric path partition number of certain tree derived architectures like hypertrees, 1-rooted sibling trees, k-rooted sibling trees, l-complete binary trees, and l-sibling trees.
Connected edge rm
– distance monophonic number of a graph
Authors: Shanthi M. , Anto Kinsley A.
Published: April 2021

Let X be a graph of order at least two, which is connected. In this paper we define a new set called the connected edge rm
- distance monophonic set of a graph X. Some properties of the connected edge rm
-distance monophonic sets are determined. The parameter for connected edge rm
- distance monophonic number is introduced. Many important results are determined and proved. Also, for every two integers a and b such that 2 ≤ a ≤ b, there exists a connected graph X with a as the edge rm
-distance monophonic number and b as the connected edge rm
-distance monophonic number of X is verified.
Center Smooth Sets and Center Smooth Numbers of Graphs
Authors: kinsley Anto A. , princiya J.Joan
Published: April 2021

For any proper set S of V in a graph G(V, E), the S-eccentricity, eG, S
(υ) (in short eS
(υ)) of a vertex υ in G is

max

x
∈
S

(
d
(
υ
,

x
)
)

. The S-center of G is CS
(G) = {υ ∈ V | eS
(x) ≤ e
S(x)∀x ∈ V} and S
1-eccentricity, eG,S1

(v) (in short eS1

(V)) of a vertex v in S is

max

x
∈
V

=

S

(
d
(
υ
,

x
)
)

. S
1-center of G is CS1

(G) = {υ ∈ V | eS1

(x) ≤ e
S1
(x)∀x ∈ V}. Then G is called a center-smooth graph if CS
(G) = CS1

(G) and the set S is defined to be a center-smooth set. We identify the center smooth sets of certain classes of graphs namely, Kq,p
, Kp
– q, Kp
, wheel graphs and lollipop graph and enumerate them for many of these graph classes. We also introduce the concept of center smooth number, which is defined as the number of distinct center smooth set of a graph G, and determine the center smooth number of some graph classes.
Some classes of Trivially Perfect Graphs
Authors: Gandal G. R. , Mary Jeya Jothi R.
Published: April 2021

A graph G is supposed to be trivially perfect if, in each induced subgraph H of G, the number of maximal cliques in H equivalents to the size of a maximum independent set in H. Trivially perfect graphs is subclasses of notable perfect graphs and its characterization have numerous continuous applications and it is adequate to research its subclasses. Along with this idea, in this paper, it is discussed trivially perfect graphs on the windmill graph and demonstrated a few outcomes on trivially perfect graphs.
MMD labeling of complete tripartite graphs
Authors: Revathi R , Angel D , Mary Jeya Jothi R
Published: April 2021

A simple, connected and undirected graph with n vertices is said to have (MMD) modular multiplicative divisor labeling if there exist a one to one and on to function f from vertices of the graph to set of all natural numbers from 1 to n and label induced on the edges by the product of labels of end vertices modulo n such that addition of all edge labels is congruent to 0 (mod n). This paper studies MMD labeling of complete tripartite graphs and some open problems.
Structural Behaviour on Slope Number of Jahangir Graphs
Authors: mary A.Antony , Amutha A.
Published: April 2021

The slope number is defined to be the minimum number of slopes required to draw the graph. In the present paper, investigation on slope number of Jahangir graph is focused and studied elaborately, since the defined graph has an excellent application on transmitting confidential information between nuclear sites. In this paper, slope number of Jahangir graph J2,m is determined and studied elaborately. This is an optimization problem and is NP-hard to determine for any arbitrary graph.