Active Volume Control in Smart Phones Based on User Activity and Ambient Noise

Kumar, Vaibhav; Malathi, S.; Kumar, Abhishek; Mohan, Prakash; Veluvolu, Kalyana C.

doi:10.3390/s20154117

Cited by 28 publications

(9 citation statements)

References 29 publications

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“…Fig. 7 investigates the average classification outcomes analysis of the MOFSS-ODL model on the test dataset [30][31][32][33][34][35]. The figure depicted that the MOFSS-ODL methodology has resulted in maximal average prec n , reca l , F measure , accu y and kappa of 0.9764, 0.9822, 0.9793, 0.96499 and 0.8263.…”

Section: Experimental Validationmentioning

confidence: 99%

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Babu¹,

MathuSoothana²,

Kumar³

2023

Intelligent Automation &Amp; Soft Computing

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Educational Data Mining (EDM) is an emergent discipline that concentrates on the design of self-learning and adaptive approaches. Higher education institutions have started to utilize analytical tools to improve students' grades and retention. Prediction of students' performance is a difficult process owing to the massive quantity of educational data. Therefore, Artificial Intelligence (AI) techniques can be used for educational data mining in a big data environment. At the same time, in EDM, the feature selection process becomes necessary in creation of feature subsets. Since the feature selection performance affects the predictive performance of any model, it is important to elaborately investigate the outcome of students' performance model related to the feature selection techniques. With this motivation, this paper presents a new Metaheuristic Optimization-based Feature Subset Selection with an Optimal Deep Learning model (MOFSS-ODL) for predicting students' performance. In addition, the proposed model uses an isolation forest-based outlier detection approach to eliminate the existence of outliers. Besides, the Chaotic Monarch Butterfly Optimization Algorithm (CBOA) is used for the selection of highly related features with low complexity and high performance. Then, a sailfish optimizer with stacked sparse autoencoder (SFO-SSAE) approach is utilized for the classification of educational data. The MOFSS-ODL model is tested against a benchmark student's performance data set from the UCI repository. A wide-ranging simulation analysis portrayed the improved predictive performance of the MOFSS-ODL technique over recent approaches in terms of different measures. Compared to other methods, experimental results prove that the proposed (MOFSS-ODL) classification model does a great job of predicting students' academic progress, with an accuracy of 96.49%.

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Section: Experimental Validationmentioning

confidence: 99%

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Babu¹,

MathuSoothana²,

Kumar³

2023

Intelligent Automation &Amp; Soft Computing

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“…1 it shows 346 records with 10 attributes and to represents the client active-index score which is worthy or ruthless we used 1 or 0. If it gives yes, it tells the customer is healthier and can consider for the sanction of the client's loan, and on the other hand, if it gives no, then that customer is not eligible [16][17][18][19]. After analyzing the data, how many paid off the previous loan and whoever who made default were also analyzed.…”

Section: Build Data Modelmentioning

confidence: 99%

Performance Analysis of K-Nearest Neighbor Classification Algorithms for Bank Loan Sectors

Hemachandran

George

Rodriguez

et al. 2021

Advances in Parallel Computing

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An attempt has been made to develop an algorithm for banks to check the credibility of borrowers to avoid nonperformance assets. People move towards different banks for loan purpose to fulfil their financial needs. Approaching bank for loan is increasing day by day mainly for child marriage, education, agriculture, business, home loan etc. Some people take the loan and they won’t pay back in time or some will move out of the country without any intimation, so that bank will go in loss. Even now in covid-19 pandemic many industries were closed but they need to give salary to the employees, need to pay rent and electricity bills too for that they will approach bank for loan. For all these cases bank first need to analyse their Credit Information Bureau India Limited score and check whether they had done loan repayments in appropriate time or not. In the present work the effectiveness of K nearest neighbor algorithm were analysed. This research were carried out using python. The accuracy of this classifier is analysed using following metrics such as Jaccard index, F1-score and LogLoss. This helps to find the potential of the customer which is much higher than the data mining classification algorithm and thus it helps in sanctioning loans.

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“…From the above systems we came to know that existing system consists of a microcontroller based antipoaching system which uses WSN. The system consists of sensors [7] for avoiding the deforestation caused by the cutting/falling of trees. It also uses low power msp430 and zigbee modules along with RF modules for long distance coverage.…”

Section: Existing Systemmentioning

confidence: 99%

Implementation of Wireless Sensor Networks to Prevent Deforestation Using Node MCU

Sivasankari¹,

Mounika²,

Priyadharshini³

2020

Intelligent Systems and Computer Technology

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The illegal movement of valuable trees such as sandal wood trees in forests poses a severe risk to natural reserves and it instigates a great loss to our country’s wealth. Almost 24,000 square miles has been lost due to deforestation in the past decade. This paper proposes an antipoaching system using NodeMCU based wireless system that uses 3- axis MEMS accelerometer (GY-61) and tilt sensor for detecting the falling of trees due to cutting of trees or natural calamities and Flame sensor, fire retardant for detecting and controlling the fire. In this project we use NodeMCU which has an inbuilt Wi-Fi module which covers a distance of around 300m range, is used in this project for cost efficiency and also NodeMCU enables the communication with neighbor nodes like client and server nodes. This protocol is used to monitor the trees even using a single node from the server system. The solenoid valve is used to spray the fire retardant to control the fire. Some IOT modules can also be used in this system to provide accurate information and remote monitoring of trees.

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Active Volume Control in Smart Phones Based on User Activity and Ambient Noise

Cited by 28 publications

References 29 publications

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Performance Analysis of K-Nearest Neighbor Classification Algorithms for Bank Loan Sectors

Implementation of Wireless Sensor Networks to Prevent Deforestation Using Node MCU

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