Volume 9 | Issue 2

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Creative Commons Attribution 4.0 and The Open Definition

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Entrepreneurial Intentions (EI) congregates its importance from the concept of EO, which focuses on apprehending the strategic decision making process of an enterprise. This paper aims to study the emerging antecedents of Entrepreneurial Intentions. The published research papers in notable journals have been used in this paper to validate the knowledge furbished. Areas like Sustainability, Social Entrepreneurship, Family Climate and Internationalization have gained relevance in recent years of study and research. Technology stands out as an ever-emerging driver of Entrepreneurial Intentions.

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- Entrepreneurial Intentions, Drivers of Entrepreneurial Intentions, Literature Review

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The Finger-Print identification, acts as the significant role in the security environment, custom-access, enforcement of the law and for investigation in the forensics department. This finger-print detection problem faces the elastic-distortion in the finger-prints which turns out to be the main case in the false-matching of the images. In this cases, prevailing in some of the application this problem will give a chance to malicious-users to indulge purposely for the distortion of images and to omit the identification-process. Effective detection system would enable the individuals to obtain the secure-based and enjoyable life-style. Hence to overcome this distortion and to pursue the detection process, several machine-learning approach, classification techniques and the neural-approached were employed for the acquisition of finger-prints, finger-prints classification, detection-phases and in the analysis phase of finger-prints. In this paper, the recent literature-evaluation of the fingerprints-classification algorithms, machine-learning approaches for handling the distortion, neural-network approaches, various finger-prints applications, detections and rectification of the original fingerprint images by the various classifiers and involving the several feature-extraction methods. Additionally, the comparative-analysis is generated by the comparisons of machine-learning algorithms, classifiers studies in accordance to the classification terms, matching phenomena, extraction of the features and the spoof-detections. At the conclusions, the challenges associated to the finger-print analysis is discussed and the future plans is also stated.

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Finger-print Recognition, Distortion, SVM-Support-Vector machine, AGNN-Adaptive genetic-neural-networks, CNN-convolutional neural-networks, Fuzzy rules, Zig-Bee devices

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The present study relies on the satisfaction of Confectionery products among the consumers. The sample survey of 100 respondents was undertaken to search out the satisfaction level of confectionery Products in karur City. The study mainly focused on general Price, quality, quantity, taste, innovation, Attractive package and consumer expectations overall satisfaction about Confectionery Products

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consumer satisfaction , confectionery products

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Demonetarization is an economic activity to cancel the existing currency in an economy. In India, 2016 November 08 witnessed such an act from Government of India. The government proposed the demineralization with an objective of saving the economy from black money, counterfeit notes and terrorism funding. This study proposed to evaluate the impact of demonetarization for a period of pre and post 100 days and what was the trend if there was no demonetarization. Data for analyzing the study taken from secondary market ,particularly from NIFTY-50. Liner regression and Graphs are the tools using here in this study.

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Creative Commons Attribution 4.0 and The Open Definition

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In this paper we study some fixed point theorems in probabilistic G-metric spaces. We also generalized some previously known results.

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G--meric spaces , Menger spaces, probabilistic G-metric space, t-norm,

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Crop yield prediction, Data mining, Indian agriculture, Machine learning, Supervised algorithm

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A retrospective study was carried out at tertiary care centre in west coastal region of INDIA over a last 10 years. During the procedure some incidental finding was found like misplaced IUCD,unruptured ectopic pregnancy,uterine prolapse,PID,endometriosis and fibroid.

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Laparoscopic tubal ligation, ectopic pregnancy, Ectopic pregnancy, Contraceptive procedure, Endometriosis

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php, web development, web application development, web , application, current trends

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Blockchain, Cryptography, Digital Certificate, Hash code, Tansaction.

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Abstract: For easy and safe navigation of visually challenged people, by detecting obstacles & people, through a detection system which uses UVC camera. This visual detection system detects obstacles up to 300cm using Sonar and sends back the feedback by beep sound and alerts the person with the objects location. Along with this an UVC webcam is affixed with 32 bit ARM micro-controller. This is featured along with algorithm to the visually challenged people walking sticks. The above mentioned setup supports image-processing, which processes images and sends response post detection, which measures the properties of the obstacle i.e., identifying human through facial & object detection. Algorithms is implemented in open CV which executes in LINUX.

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nil

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Construction & Demolition Waste, Landfill, Debris Recycle Plant, Sustainable Construction & Management

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Creative Commons Attribution 4.0 and The Open Definition

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Black Board, Broadband, Virtual learning environment, Moodle, ICT.

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Creative Commons Attribution 4.0 and The Open Definition

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Diabetes, Insulin resistance, Insulin sensitivity, Beta cell rejuvenation, Diabetic Diet

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Stock market investment is one of the most complex and sophisticated way to do business. Stock market is very uncertain as the prices of stocks keep fluctuating because of several factors that makes prediction of stocks a difficult and extremely complicated task. Nowadays investors need fast and accurate information to make effective decisions and highly interested in the research area with exponentially growing technological advances of stock price prediction. Understanding the pattern of stock price of a particular company by predicting their future development and financial growth will be highly beneficial. This paper focuses on the usage of a type of recurrent neural network (RNN) based Machine learning which is known as Long Short Term Memory (LSTM) to predict stock values.

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Long Short Term Memory, Recurrent Neural Network, Machine learning, Stock Price Prediction

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For any complex digital systems, design and analysis through state machine approach is preferred. In this paper, sequence detector using Mealy finite state machine is designed with reversible logic circuits. Reducing power dissipation is the main requirement for low power VLSI design. Reversible logic circuits have received more attention in the recent years because of their ability to reduce the power dissipation. The behavior of these circuits are described in Verilog HDL, Simulated and Synthesized in Xilinx ISE environment. In this work, sequence detectors with and without overlap sequence are considered

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Finite state machine, Sequence detector, Verilog HDL, Xilinx, Reversible logic

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Suppressed emotions, catharsis, intense emotions, repressed.

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In more recent times, there has been an increase in the number of people using computers, as a result of which there is a widespread use of the Internet. The use of the Internet enables hackers to access computers using new, more sophisticated, and more complex forms of attacks, to protect computers from them Intrusion Detection System (IDS) is used, which is trained with few machine learning algorithms along with datasets. The datasets used are collected over a period of time in some networks and usually contain up-to-date data. Furthermore, they are unbalanced and incapable of storing adequate data for all forms of attacks. These uneven and outdated datasets reduce the effectiveness of current IDSs, especially for attacks that are rarely encountered. In this paper, Using Random Forest, Linear Discriminant Analysis, K-Nearest Neighbor, Decision-Tree, Adaboost, and Gradient Boosting algorithms, we suggest six machine-based IDSs. To make IDS more logical, an up-to-date security database, CSE-CIC-IDS2018, is being used in place of older and more widely used datasets. The selected database is also not balanced. As a result, the rate of inequality in the dataset is reduced using a data model called the Synthetic Minority Oversampling Technique (SMOTE) to improve the reliability of the system based on the types of attacks and to eliminate unreliable access and false alarms. Data processing is done for small classes, and their numbers increase to medium data size in this way. Experimental results have shown that the proposed method significantly increases the acquisition rate of the attacks that are rarely encountered.

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machine-learning, intrusion detection, IDS, SMOTE, CSE-CIC-IDS2018 dataset.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Heartbeat sensor,Event recorder, Holter Monitor; RaspberryPi and IoT.

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Creative Commons Attribution 4.0 and The Open Definition