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A strategy to improve performance in electrochemical discharge machining using periodic bi-directional tool rotation
No full textIncreasing machining depth has imposed challenges to machine high aspect ratio features in electrochemical discharge
machining (ECDM) of hard and brittle materials like borosilicate glass. As depth of machining (DOM) progresses, the
machining is slowed due to insufficient availability of electrolyte at the tool tip. The stagnated electrolyte at the entrance of
the hole causes increased radial overcut (ROC), heat-affected zone (HAZ), and taper (TP) and also reduced material removal
rate (MRR), DOM, and circularity (CR). To overcome these challenges, the present study implemented a novel strategy
using periodic bi-directional tool rotation (PBTR) with tungsten carbide helical drill. Initially, a flow simulation with KOH
electrolyte has been conducted using COMSOL multi-physics platform to understand effect of the tool rotation on machining
characteristics for both unidirectional tool rotation (UTR) and PBTR. It is found from the simulation that the PBTR shows
better electrolyte supply to the tool tip as compared to UTR. Experiments are conducted with experimental plan based on
L16 array. Experimental results disclosed that PBTR has resulted an improvement in MRR, DOM, and circularity and a
decrease in HAZ, ROC, and TP of the machined hole. Parametric optimization is carried out using teaching learning-based
optimization (TLBO) algorithm to evaluate the optimum process parameters. Optimum values are confirmed with by the
experimental result
A molecular dynamics study of thermal behavior of ammonia/Cu nanorefrigerant flow under different initial pressures and electric fields
No full textHydrogen production from electrocatalytic water splitting is one way to tackle the rise of the energy crisis, but it still requires cost-effective, high stable, and high-performance materials to produce hydrogen on a large scale. So far, hydrogen as alternative resource to address energy issue in world is under progress and several attempts have been made to further improve it. Transition metal-based materials have been documented as promising catalysts due to their high electrocatalytic activity, structural tunability, high electrochemical surface area, high conductivity, and high stability under harsh conditions. However, the main challenge of electrocatalytic production of hydrogen through water splitting is in the development of cost-effective earth-abundant catalysts to enable their industrial-scale deployment. In this review work, the authors represent the most key factors in an electrocatalyst performance analysis and a comprehensive review of the most recent development on various material preparation for synthesizing non-precious or precious metal-based electrocatalysts to dissociate water electrochemically into hydrogen and oxygen. The correlation between catalyst structure and related activity for the improved electrocatalytic reaction is discussed. Also, doping with adatoms, composition with other transition metals for synergy effects, and downsizing nanostructure of corresponding materials are reviewed. Finally,
existing challenges and bright prospective paths for catalyst designing and synthesizing methods of catalysts for
electrochemical water splitting are discussed
Image Processing Approaches for Oral Cancer Detection in Color Images
No full textLips, two-thirds of the tongue and inner cheek
lining are all common places for oral cancer to form. It can also
arise in hard and soft palates, pharynx, and sinuses. Head and
neck cancers are subtypes of this malignancy. Unless detected
and treated early on, oral can be dangerous. Using microscopic
biopsy images, the researchers were able to detect mouth cancer and non-cancerous lesions. Using cutting-edge techniques, it is possible to histologically diagnose oral lesions. For example, enhancing microscopic images involves transforming them from RGB to L*a*b color space, classifying the colors using k-means clustering, segmenting the nuclei, and obtaining and classifying their features
Emerging Role of Biopharmaceutical Classification and Biopharmaceutical Drug Disposition System in Dosage form Development: A Systematic Review
Get PDFBiopharmaceutical classification system (BCS) is an advanced tool used for classifying medicines based on dissolution, water solubility, and intestinal permeability, which affect the absorption of active pharmaceutical ingredients (API) from immediate-release solid oral forms. It is useful to the formulation researchers to develop novel dosage forms based on modernistic rather than experimental approaches. The current review focuses on the fundamentals, objectives, guidance of BCS, characteristics of BCS drugs, their importance and applications of BCS. This review explains the challenges in drug development in terms of solubility and in vivo disposition. In the current review, new strategies for improving BCS II drug solubility as well as biopharmaceutical drug disposition properties which are utilized throughout the early stages of drug development and commercialization are mainly discussed
Investigations of Donor–Acceptor Interactions in 1,3,5-Tris-(3-Methoxy & 3-Methyl Carboxy) Phenyl Ethynyl Benzene Derivatives Using Experimental and DFT Study
Get PDFWe have designed and synthesized a series of novel amide derivatives of 1,3,4-oxadiazole-isoxazolpyridine-benzimidazole (10a-j), and their structures are characterized by 1HNMR,
13CNMR and mass spectral data. The preliminary anticancer applications of these compounds are screened towards four
types of human cancer cell lines including PC3 (prostate), A549 (lung), MCF-7 (breast) and DU-145 (prostate). The assay results revealed that many of the target compounds displayed remarkable anticancer activity. Among them, the compounds 10f, 10g, 10h and 10j are found to be more potent than
rest of the compounds. In particularly, one compound 10f displayed most promising anticancer activit
Measuring job satisfaction levels of airport employees using entropy, critic and TOPSIS methods
No full textThe paper utilises the combination of entropy, CRITIC and TOPSIS methods to measure the job satisfaction levels of airport employees working in Vijayawada International Airport, India. To assess satisfaction levels of employees towards the job, a shorter variant of the Minnesota Satisfaction Questionnaire (MSQ) is employed and multi-criteria decision-making
(MCDM) method is applied. The study results show that there is a highly significant positive relationship between the weights obtained by entropy and CRITIC method. The application of the presented approach to evaluate job satisfaction level in airport employees is a novel one. Thus, the findings of the study would lead the literature in the domain further as well as help in giving
better decision-making capabilities to the airport authorities and managers. With this methodology, the perceptual opinions expressed by the employees can be quantified and judged accordingly
Coupled fixed points of ( ϕ ˆ , ψ ˆ , θ ˆ ) -contractive mappings in partially ordered b-metric spaces
No full textAudiobooks that converts Text, Image, PDF-Audio & Speech-Text : for physically challenged & improving fluency
Get PDFAbstract—The primary goal of our technology is to create a
speech recognition system for physically handicapped
persons. Nowadays Many independent gadgets are
increasingly being used for communication reasons. One of
the beneficial trends is the invention of a person’s ability.
This program allows for the conversion of text-to-voice,
image-to-Speech & text, PDF-to-voice, speech-to-text. Voice,
or another style of voice in a speech file, can be transformed
into text. As a result, instead of reading, you can listen to the
book, or instead of writing you can speak, and also you can
extract the text from the image. This application is beneficial
to persons who have physical limitations such as being deaf,
blind, or having different abilities and Users who find typing
difficult, painful, or impossible, as well as those who can
understand what others are saying. This project uses Visual
Studio to display user-friendly Python Code, and this file
contains a GUI/Voice command
Disease analysis using machine learning approaches in healthcare system
Get PDFThis paper addresses congestion avoidance using enhanced blue algorithm (EBA) for data transferring in a network. The congestion of data always afects the data transmission on
the internet for various applications. For developing data transmission performance, the congestion of data is a challenging task. Although, diferent approaches have been used
to avoid data congestion, yet we have considered a data transmission framework for bet- ter performance compare to existing approaches. Thus, we considered the advanced Blue
Algorithm which is used to determine the node’s capacity with middle path and it prevents congestion by monitoring of data during data transmission. The role of gateway is consid-
ered to supervise status of congestion for both data sending and receiving based on positive or negative acknowledgment as well as data size. The gateway is also used for a congestion
notifcation system to alleviate congestion and enhance throughput. During experimen-tal analysis, we have taken comparative performance between existing and our proposed
model. For example, in Enhanced Ad hoc On-demand Distance Vector (EAODV), dur-ing the packet size of 10, the average end-to-end delay is 32.63 ms whereas in proposed advanced Blue algorithm, the average delay is only 19.11 ms. Thus, the proposed model using Blue algorithm is performed better than existing method
Analysis of classification based predicted disease using machine learning and medical things model
Get PDFThis paper addresses the data privacy based on interactive computation using an optimization model in data mining. When
data are computed or sharing among users in online, it needs to maintain privacy for all computation during sharing of data.
But user choice-based privacy is not available when sharing of data is required for data mining computation which is a big
challenge for data privacy. Thus, we proposed the framework for anonymity of data privacy using various methods of
multi-objective models as per the requirement of privacy. The proposed framework is designed with the help of two objects
such as computational cost and privacy based on optimization model. Our framework maintains the balance between above
objects as per user demands, i.e., increasing the privacy with decreasing the computational cost. In this model, the domain
of privacy and computational cost for optimization problem solves the entity privacy requirements in a computing
environment. We have used various methods such as Gaussian and uniform distribution, confidence interval, activation
function, linear membership function with distinguish manner for maintaining of privacy and cost. As per the uniform
distribution and parameter a-cut value for noise data, the optimal value is made accordingly. Example: for a = 0.2, and
uniform distribution (- 1, 1), the optimal value is 0.0058. Similarly, as per different a values, classifiers result is different
like a = 0.2 and 0.4, Multilayer perceptron values are 4.01 and 1.61 respectively. The solution of the proposed model
controls the amount of privacy with complete freedom of choice of users with utmost flexibility