Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

A Novel Approach for Detecting and Classifying Breast Cancer in Mammogram Images

Abstract: This study uses data mining techniques for computer-aided diagnosis that involves the feature extraction for cancer detection, so as to help doctors towards making optimal decisions quickly and accurately. Features play an important role in detecting the cancer in the digital mammogram and feature extraction stage is the most vital and difficult stage. In this paper, an enhanced feature extraction method named Multiscale Surrounding Region Dependence Method (MSRDM) is proposed to be effective in classifying the mammogram images into normal or benign or malignant. This proposed system is based on a four-step procedure: Regions of Interest specification, two dimensional discrete wavelet transformation, and multiscale surrounding region dependence matrix computation and feature extraction. The performance of the proposed feature set is compared with the conventional texture-analysis methods such as gray level cooccurence matrix features and surrounding region dependence method features. Experiments have been conducted on both real and benchmark data and the results have been proved to be progressive.

Biosorption of Acid Yellow 12 from simulated wastewater by non-viable T. harzianum : kinetics, isotherm and thermodynamic studies

Abstract: The current study deals with the biosorption of Acid Yellow 12 (AY 12) dye using dead fungal biomass Trichoderma harzianum. The dead fungal biomass was characterized using FTIR, XRD, TG–DTA and SEM–EDAX. Effect of various parameters on the efficiency of biosorption like pH, biosorbent dosage and temperature has also been analysed. The adsorption capacity was found to be higher at pH 4, with an initial dye concentration of 100 mg/L and biosorbent dosage of 0.4 g/L. The adsorption kinetics, isotherms and thermodynamic studies of dye adsorption onto the biomass were also investigated. The biosorption between the dye and biomass followed Freundlich adsorption isotherm. The biosorption followed pseudo-second-order kinetics. Negative value of ΔG° shows the spontaneous nature of biosorption process, and positive ΔH° reveals adsorption as an endothermic process. Since T. harzianum is a low-cost industrial by-product, it can be used as an effective novel biosorbent for the removal of textile dyes. It also acts as one of the cheap sources of biosorbent for the removal of dye Acid Yellow 12.

Artificial Intelligence based Smart Door with Face Mask Detection

Abstract: In this pandemic situation, health plays an important role in everyone’s life. Most of the people are not aware of preventing themselves and their surroundings from this pandemic. Face mask is essential to prevent ourselves and others. So, people are in need to wear face mask regularly. People who visit home won’t wear mask due to their unawareness which may affect people. People may not know if someone visits their home when they are not there. AI based smart device (Raspberry pi with AI model with camera) is proposed in this project which identifies whether a person is wearing face mask and gives us an alert message (via mobile app). This device is integrated with a mobile app. Mobile app identifies if someone enters home when people are not physically present in their home. This smart device automatically opens the door only if people wear face mask. This device works both day and night. It can be used in multiple places like malls, shops, hospitals and temples

Room temperature ferromagnetic behavior of nickel-doped zinc oxide dilute magnetic semiconductor for spintronics applications

Abstract: The multifunctional zinc oxide (ZnO) nanoparticles were economically grown through a simple co-precipitation technique Ni-doped (1, 3, and 5 wt%) ZnO nanoparticles were also grown to comprehend their influence on the ferromagnetic property of the ZnO, especially at room temperature The structural and surface morphological features of the prepared nanoparticles were studied through X-ray diffraction (XRD) and Scanning electron microscopy (SEM) techniques, respectively Diffused reflectance, Photoluminescence, and Fourier transform infrared spectroscopic analyses were also carried out to understand the consequence of Ni doping on the ZnO nanostructure The secondary phase formations such as NiO and NiO2 elucidate the solid solubility limit of three percent of nickel in the ZnO matrix Size-strain analysis was performed to evaluate the crystallite size and apparent strain values An increase in the agglomeration of particles is evidenced by SEM micrographs with an increase in the Ni doping percentage The bandgap measurements showed a redshift from 325 to 318 eV for the Ni-doped nanoparticles Photoluminescence study reveals the existence of lattice defects including interstitials and vacancies in the synthesized nanostructures The vibrating sample magnetometer studies divulge that 3% Ni-doped ZnO nanoparticles show an intense ferromagnetic property at room temperature These experimental observations manifested that the Ni-doped ZnO nanoparticles are potential candidates for spintronics device applications