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Smart assistive device for visually impaired /
Patent Number: 202121042792, Applicant: Dr. S. Vijayalakshmi.
The most difficult problem for blind people is to navigate the outside world. Smart devices make it much easier for visual impaired to complete daily tasks like smart speakers, smart bulbs, household smart devices, smart sticks, and many more are easy to control. As a whole, smart devices have the potential to significantly improve the lives of visual impaired people. All apps and devices are used individually for different purposes but for visually impaired person it is very difficult to handle all devices and apps at a particular time. -
Smart assistive device for visually impaired /
Patent Number: 202121042792, Applicant: Dr. S. Vijayalakshmi.
The most difficult problem for blind people is to navigate the outside world. Smart devices make it much easier for visual impaired to complete daily tasks like smart speakers, smart bulbs, household smart devices, smart sticks, and many more are easy to control. As a whole, smart devices have the potential to significantly improve the lives of visual impaired people. All apps and devices are used individually for different purposes but for visually impaired person it is very difficult to handle all devices and apps at a particular time. -
Smart assistive device for visually impaired /
Patent Number: 202121042792, Applicant: Dr. S. Vijayalakshmi.
The most difficult problem for blind people is to navigate the outside world. Smart devices make it much easier for visual impaired to complete daily tasks like smart speakers, smart bulbs, household smart devices, smart sticks, and many more are easy to control. As a whole, smart devices have the potential to significantly improve the lives of visual impaired people. All apps and devices are used individually for different purposes but for visually impaired person it is very difficult to handle all devices and apps at a particular time. -
Smart assistive device for visually impaired /
Patent Number: 202121042792, Applicant: Dr. S. Vijayalakshmi.
The most difficult problem for blind people is to navigate the outside world. Smart devices make it much easier for visual impaired to complete daily tasks like smart speakers, smart bulbs, household smart devices, smart sticks, and many more are easy to control. As a whole, smart devices have the potential to significantly improve the lives of visual impaired people. All apps and devices are used individually for different purposes but for visually impaired person it is very difficult to handle all devices and apps at a particular time. -
Smart Antenna for Home Automation Systems
A smart antenna for home automation systems is suggested in this design. An antenna is a device that minimizes human movements while dealing with electronics systems and software. This smart antenna helps reduce physically challenged peoples movement and supports home automation systems. The presented antennas could be used for any small device, like a mobile, tablet, laptop, Wi-Fi, or WiMAX, which are essential in the current scenario. The presented smart antenna is capable of radiating a large frequency band from 3 to 13.8 GHz, which covers the .5-7 GHz (5G(I) Sub-6 GHz band), Wimax 3.5 and 5.5 GHz bands, WLAN 5.2 and 5.8 GHz bands, C 4-8 GHz Band, X 8-12 GHz Band, and other home automation applications with high efficiency. The impedance bandwidth of the smart antenna is 128%, with a size of 15x15x1.5 mm3. The suggested design includes a modified patch in the shape of a square patch attached with one circular element fed by a microstrip line. Circular pieces have been designed for better resonances at lower modes. The antenna is simulated with an FR4 substrate using a CST Simulator. The design is investigated by simulations and corresponding S-parameter results are presented. The robotics process automation is well described in Table 7.3. The proposed structure also demonstrates stable radiation patterns across the operating bandwidth. The proposed radiator has a high gain of 5.21 dBi and an efficiency of 80%. 2023 Scrivener Publishing LLC. -
Smart Air Pollution Monitoring System Using Arduino Based on Wireless Sensor Networks
Impurity levels in air have risen throughout time as a result of several reasons, such as population expansion, increased automobile use, industry, and urbanization. All of these elements harm the health of individuals who are exposed to them, which has a detrimental effect on human well-being. We will create an air pollution monitoring system based on an IoT that uses a Internet server to track the air quality online in order to keep track of everything. An alert will sound when the level of harmful gases such CO2, smoking, alcohol, benzene, and NH3 is high enough or when the air quality drops below a specified threshold. The air quality will be displayed on the LCD in PPM. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Smart Agriculture: Machine Learning Approach for Tea Leaf Disease Detection
Across the globe, plant infections from pathogens such as fungi, bacteria and viruses are the major issues in the agricultural sector. Agricultural productivity is one of the most important things on which the nations economy highly depends. The detection of diseases in plants plays a major role in the agricultural field. This study proposes a multi-stage network involving Convolutional neural network, Pattern identification and Classification using Siamese network. The main objective behind this study is to enhance the disease detection technique performance. The image data of Tea leaves chosen for this study will be gathered. The algorithms based on techniques of image processing would be designed. The proposed algorithm was tested on the following diseases namely Red rust, Blister blight, Twig dieback, Stem canker, Grey Blight, Brown Blight, Brown root rot disease and Red root rot disease in Tea leaves. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Smart Affect Recognition System for Real-Time Biometric Surveillance Using Hybrid Features and Multilayered Binary Structured Support Vector Machine
Human affect recognition (HAR) using images of facial expression and electrocardiogram (ECG) signal plays an important role in predicting human intention. This system improves the performance of the system in applications like the security system, learning technologies and health care systems. The primary goal of our work is to recognize individual affect states automatically using the multilayered binary structured support vector machine (MBSVM), which efficiently classify the input into one of the four affect classes, relax, happy, sad and angry. The classification is performed efficiently by designing an efficient support vector machine (SVM) classifier in multilayer mode operation. The classifier is trained using the 8-fold cross-validation method, which improves the learning of the classifier, thus increasing its efficiency. The classification and recognition accuracy is enhanced and also overcomes the drawback of 'facial mimicry' by using hybrid features that are extracted from both facial images (visual elements) and physiological signal ECG (signal features). The reliability of the input database is improved by acquiring the face images and ECG signals experimentally and by inducing emotions through image stimuli. The performance of the affect recognition system is evaluated using the confusion matrix, obtaining the classification accuracy of 96.88%. 2020 The British Computer Society 2020. All rights reserved. -
Small signal stability in a Microgrid using PSO based Battery storage system
This papers covers, modelling and analysis of a small microgrid with Battery Storage System (BSS). A sample microgrid is considered, it is analyzed for small signal stability, with and without BSS. Voltage, frequency and current THD which are considered to be the major attributes of stability in a microgrid, the behavior of these attributes is observed with and without BSS. The Battery storage system is connected to the considered microgrid through PV array, using PSO algorithm, which improves the stability of the system. Simulation is carried out using MATAB/ Simulink and the results are presented. Microgrid considered consists of PV array, Diesel Generator and Battery storage system. These sources are modelled according to the loads connected to the microgrid. BSS acts as emergency backup to the considered system and also provides small signal stability to the microgrid. Simulation is carried out with BSS and without Battery Storage in the Islanded mode. The obtained results show that microgrid with BSS is more stable during small disturbances and also acts as backup power supply. A Properly modelled microgrid can act as power backup for industries. 2022 IEEE. -
Small finance banks and financial inclusion in India /
Research Review Journals, Vol.4, Issue 3, pp.1586-1588, ISSN No: 2455-3085. -
SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans
In this paper, we propose a novel squeeze M-SegNet (SM-SegNet) architecture featuring a fire module to perform accurate as well as fast segmentation of the brain on magnetic resonance imaging (MRI) scans. The proposed model utilizes uniform input patches, combined-connections, long skip connections, and squeezeexpand convolutional layers from the fire module to segment brain MRI data. The proposed SM-SegNet architecture involves a multi-scale deep network on the encoder side and deep supervision on the decoder side, which uses combined-connections (skip connections and pooling indices) from the encoder to the decoder layer. The multi-scale side input layers support the deep network layers extraction of discriminative feature information, and the decoder side provides deep supervision to reduce the gradient problem. By using combined-connections, extracted features can be transferred from the encoder to the decoder resulting in recovering spatial information, which makes the model converge faster. Long skip connections were used to stabilize the gradient updates in the network. Owing to the adoption of the fire module, the proposed model was significantly faster to train and offered a more efficient memory usage with 83% fewer parameters than previously developed methods, owing to the adoption of the fire module. The proposed method was evaluated using the open-access series of imaging studies (OASIS) and the internet brain segmentation registry (IBSR) datasets. The experimental results demonstrate that the proposed SM-SegNet architecture achieves segmentation accuracies of 95% for cerebrospinal fluid, 95% for gray matter, and 96% for white matter, which outperforms the existing methods in both subjective and objective metrics in brain MRI segmentation. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Sm-MOF/rGO/PANI composite as an electrode material for supercapacitor applications
In recent years, scientists have been paying a lot of attention to metal-organic frameworks, often known as MOFs, as a possible material for use as electrodes in supercapacitors. MOFs are capable of functioning as high-quality pseudocapacitors because of their crystalline structure, which enhances the specific surface area and provide mechanical support for composite materials. The objective of this study is to synthesize an electrode material that can be used as supercapacitors by synthesizing Sm-MOF and then combining it with reduced graphene oxide (rGO) and polyaniline (PANI) to make a hybrid material. Here, the effect of incorporation of PANI and rGO in Sm-MOF is investigated, and its application as a supercapacitor is examined. Due to the high surface area and pore size, Sm-MOF/rGO/PANI material exhibits high specific capacitance. The computed specific capacitance of the composite Sm-MOF/rGO/PANI material is 1935.6 F g?1 when subjected to a current density of 1 A g?1. The Sm-MOF/rGO/PANI device is fabricated and exhibits a specific capacitance of 218 F g?1. The specific power and energy are calculated to be 59.3 Wh kg?1 and 581 W kg?1, respectively. 2023 Elsevier Ltd -
SLV voltage regulated DC/DC converter /
Patent Number: 202141046671, Applicant: Radhika S.
The requirement is to develop a DC/DC converter for DC microgrid and charging electric vehicle batteries. The main issue in the DC microgrid is the voltage regulation and it is necessary to implement a regulated DC/DC converter and this can be achieved by the combination of voltage lift and boost circuit giving a regulated DC output voltage of 203.1V DC at 0.4 duty ratio by using LTspice XVII software. -
Slow Violence in Vikram Chandras Sacred Games: An Ecocritical Reading
This article gives insight into the ways in which enforcement and institutional vigilante activities portrayed in Vikram Chandras Sacred Games foreshadow the urban thicket of garbage dump yards and slum dwellings. The text will be analyzed from an ecocritical perspective to establish aspects of slow violence and its explicit and implicit results. Chandras plotline, regarding several entangled human tragedies against the background of refuse, urges a study of the novel through the lens of waste studies. However, he fails to address the reasons for the characters opinion of Mumbai being uninhabitable and infamous for treating human life as expendable. The novelist also seems to normalize the issues of inequalities in waste management and justifies the anthropocentric utilitarian perception of resources. The depictions of Mumbai gang wars against a disturbingly overlooked state of dilapidated lives and misplaced ideologies mention waste as being both created and ignored. Such representation also compels a close reading of consumerism and criminal aspiration. 2023, University of Zadar. All rights reserved. -
Sliced Bidirectional Gated Recurrent Unit with Sparrow Search Optimizer for Detecting the Attacks in IoT Environment
In an era characterized by pervasive interconnectivity facilitated by the widespread adoption of Internet of Things (IoT) devices across diverse domains, novel cybersecurity challenges have emerged, underscoring the imperative for robust intrusion detection systems. Conventional security frameworks, constrained by their closed-system architecture, struggle to adapt to the dynamic threat landscape marked by the continual emergence of unprecedented attacks. This paper presents a methodology aimed at mitigating the open set recognition (OSR) challenge within IoT-specific Network Intrusion Detection Schemes (NIDS). Leveraging image-based representations of data, our approach focuses on extracting geographical traffic patterns. We observe that the Recurrent Neural Network exhibits suboptimal classification accuracy and lacks parallelizability for attack analysis tasks. Our investigation concludes that the Sparrow Search Optimization Algorithm (SSOA) serves as a foundation for constructing an effective assault classification model. This research contributes significantly to the field of network security by emphasizing the importance and ramifications of meticulous hyperparameter tuning. It represents a critical stride toward developing IDSs capable of effectively navigating the evolving cyber threat landscape. In the experimental analysis of proposed model reached the accuracy and 0.963% respectively. 2024 IEEE. -
Skincare Products as Sources of Mutagenic Exposure to Infants: An Imperative Study Using a Battery of Microbial Bioassays
Infant skin is highly absorptive and sensitive to exposure from external agents (microbes, toxicants, heat, cold, etc.). Many specialized infant skincare products are currently commercially available. Although the manufacturers claim that their products are mild enough to suit the infant skin, these products need to be studied for their safety. Using animal models to examine the safety of the ever-increasing number of skincare products is not economically or logistically feasible. To overcome this problem, we suggest using a battery of microbial bioassays as a robust system for monitoring the mutagenic potential of skincare products. We picked popular infant skincare products from the Indian market and assessed them by using a battery of three microbial mutagenicity bioassays. Most of them showed significant and reproducible mutagenic potential. Our study results raise concerns about regular use of infant products and emphasize the need to enforce strict regulations for the manufacturing and safety assessment of infant products. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Skin lesion classification using decision trees and random forest algorithms
Any superficial skin growth that does not resemble the surrounding area is referred to as skin lesion. It can occur in the form of mole, bump, cyst, rash or other changes that can be classified either as primary or secondary lesion. While primary skin lesions correspond to those changes in color or texture, secondary lesions occur as a primary lesion progression. Skin lesion image segmentation and classification at the early stages can help the patients recover through proper medication and treatment. Many algorithms for segmentation and classification are available in the literature but they all fail to extract lesion boundaries perfectly and classify them with more accuracy. To improve the reliability of the skin image segmentation and classification, we propose to use decision trees and random forest algorithms in this works and compare them with different data sets. The proposed method can generate high-resolution feature maps that can help to preserve the spatial details of the image. While tested against the ISIC 2017 and HAM10000 dataset, we found that the proposed method is more accurate as compared to the existing algorithms in this domain and is also very robust to artifacts or hair fibers present in the skin images. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
Skin cancer classification using machine learning for dermoscopy image
Skin cancer is highly ambiguous and difficult to identify and cure in the last stage. To increase the survival rate, it is important to recognize the stages of skin cancer for effective treatment. The main aim of the paper is to classify the various stages of skin cancer using dermoscopy images from the data repository of ISIC and PH2. The data is pre -processed with the help of median filter and wiener filter for removing the noise. Segmentation is processed using Watershed and Morphological. After the segmentation, features were extracted using Grey Level Co-occurrence Matrix (GLCM), Color, Geometrical shapes in order to improve the accuracy of dermoscopy image. Finally, the dataset is classified with some popular methods like KNN with 89%, Ensemble with 84% and SVM works better than the other two methods by giving the highest accuracy of 92%. BEIESP. -
Skill sets required to meet a human-centered Industry 5.0: A systematic literature review and bibliometric analysis
The first industrial revolution, known as Industry 1.0, was primarily concerned with mechanical engineering and water and steam. Electric power systems and mass production assembly lines were established during the second industrial revolution (Industry 2.0). The third industrial revolution (Industry 3.0) was defined as automatic manufacturing and the incorporation of electronics, computers, and information technology into manufacturing. The fourth industrial revolution (Industry 4.0) is automating business operations and advancing manufacturing to a level based on connected devices, smart factories, cyberphysical systems (CPS), and the internet of things (IoT), where machines will change how they interact with one another and carry out specific tasks. Industry 5.0, with all modern technologies, is aimed to be a harmonious balance between human and machine interaction, and has an emphasis on sustainable growth. The present study uses an interpretive-qualitative research method to review the skill sets required to meet a human-centered Industry 5.0. 2024, IGI Global. All rights reserved. -
Skewed Food Policies, Distorted Inter-crop Parity, and Nutri-cereal Farmers - An Empirical Analysis
Farmer profitability, cost of food production, and associated issues of nutri-cereals are analysed by leveraging a large database spanning a 35-year period. The skewed food policies being followed in India are highlighted here. An unacceptably high distortion in inter-crop parity was found, which led to loss of profitability, increased costs, and lower prices for the nutri-cereals. The policymakers must take corrective measures in several aspects, including technologies, prices, input provision, processing, storage, and distributional policies to promote the production and consumption of nutri-cereals in India. 2023 Economic and Political Weekly. All rights reserved.