V ASHOK
@psvpec.in
ASSOCIATE PROFESSOR AND DEPARTMENT OF MECHANICAL ENGINEERING
PRINCE SHRI VENKATESWARA PADMAVATHY ENGINEERING COLLEGE
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Energy, Renewable Energy, Sustainability and the Environment, Waste Management and Disposal
Scopus Publications
Scopus Publications
Amit Upadhyay, Sandip Kulkarni, Sharmistha Roy, K. Yuvaraj, V. Ashok, and Sunil D. Kale
IEEE
comfy Shell (SSH) is an effective community protocol used to securely connect devices over a computer community. It gives information encryption for relaxed conversation among clients and servers, and can be used to guard information at the same time as being transmitted over a wi-fi community. But, as with every protocol, there are positive obstacles that should be considered when the usage of SSH to relaxed wi-fi networks. Because of the character of wireless networks, in which records is transmitted through the air, SSH is at risk of numerous vulnerabilities. First, SSH is susceptible to man-in-the- center attacks, which can permit an attacker to intercept the network traffic and examine, alter, or block positive packets. Specially, using SSH makes it viable for an attacker to perform password sniffing, for the reason that protocol does not encrypt the user's login credentials. Additionally, the usage of SSH protocols does now not shield against malware or different malicious software, making it feasible for an attacker to monitor or manipulate an affected system.
Pravin R. Futane, Rakesh Kumar Yadav, Saniya Khurana, Amar Shankar, Abhijeet Kar, and V. Ashok
IEEE
Optical communication networks suffer from excessive peak bit quotes today's the physical and environmental constraints present day fiber optic cables. Adaptive modulation techniques offer a potential approach to the trouble with the aid of making an allowance for increased facts throughput with the aid of tailoring the information rate latest the signal to the channel's country. Those techniques have the ability to modify modulation formats and facts fees in real-time to optimize the height bit fee and universal throughput modern the network. This paper examines the software trendy adaptive modulation strategies for enhancing top bit prices in excessive-velocity fiber optic verbal exchange networks and evaluations the to be had strategies for fixing this hassle. The evaluation additionally critiques the present day adaptive modulation algorithms and their overall performance in terms modern-day top bit fee and throughput modern-day the verbal exchange networks. Finally, this paper affords an overview modern day several future research challenges important for further improvements in this discipline.
Jambi Ratna Raja Kumar, Mukesh Chaturvedi, D. ANandhasilambarasan, V. Ashok, Ashwini R. Nawadkar, and Manoj Va
IEEE
This study aimed to evaluate the efficiency of synthetic Intelligence (AI) for multivariate records analysis. Multivariate statistics evaluation is a complicated venture that historically requires considerable manual labor and information in information science and machine mastering. AI can offer an extra green and accurate method to the venture. Consequently, this study employed a ramification of AI-based total methods to identify patterns and generate insights from the dataset. Traditional and ML algorithms were used to generate models based on the records. The models have been evaluated based on their metrics—accuracy, precision, and keep in mind. In the end, the effects from the models were analyzed to identify trends and institutions among the variables. The findings concluded that AI may want to provide a robust and accurate technique to perform multivariate records analysis. However, further research is needed to develop novel tactics to utilize AI for multivariate statistics evaluation with increased accuracy and precision.
Sethukarasi T, V.Samuthira Pandi, D. Karunkuzhali, V. Ashok, G Chamundeeswari, and Deepa A
IEEE
Patients in severe condition are treated at the Intensive Care Unit (ICU). In such life-or-death situations, doctors must have continuous access to vital signs including blood pressure, heart rate, and temperature. What's the deal with asthma, the planet, and salt levels? The manual process is excessively time- consuming, and when applied to a large number of patients, it becomes nearly impossible. This Internet of Things-based technology has the potential to implement automated network communication with medical professionals, keeping them fully informed at all times. The sensors in the ICU monitoring system for the Internet of Things ( IoT ) are controlled by an Arduino board. Networked sensors, either worn by the patient or installed in our homes, alter the inductive data collection of our physiological and mental states. A patient may be tracked around-the-clock with a smart health monitoring system based on the Internet of Things ( IoT ). One of the most noticeable uses of the Internet of Things in the present day is in health monitoring systems. In this research, the AD8232 signal conditioning module was presented as the basis for a wireless ECG monitoring system capable of collecting data in real time. The ESP32 will be linked up to the AD8232 ECG Sensor. Then, we'll get an Electrocardiogram (ECG) reading by attaching the leads to the patient's chest or hand. The measured value exceeded the set limit of the sensor. Users of this module of the healthcare system should expect to get an updated prescription for their current medical condition within minutes of any significant change in their health status. Doctors are informed of their patients' conditions on an LCD screen, which they may then use for further assessment. When a patient requires a hospital's Intensive Care Unit, a smart ICU may be used to keep tabs on vital signs including oxygen levels, heart rates, body temperatures and more.
Ramesh Chandra Patra, G. Saritha, G. Ashish Raghuwanshi, P. Parthiban, and V. Ashok
IEEE
In the realm of healthcare, the integration of Deep Learning (DL) stands as a potent force, propelling advancements in medical diagnosis and treatment. This paper navigates recent strides, persistent hurdles, and emerging applications within this synergy. DL basics are elucidated initially, demonstrating neural networks' role in data analysis. Progressing further, we unveil DL's robust applications in medical diagnosis, particularly via Convolutional Neural Networks, revolutionizing image-based disease detection. Yet, this frontier is not devoid of challenges, encompassing data privacy concerns and model interpretability. In tandem, DL empowers personalized treatment by predicting disease trajectories and expediting drug discovery. Expanding horizons, DL streamlines healthcare management through resource optimization and digitized records. In conclusion, this synthesis of DL and healthcare signifies a transformative trajectory, promising refined diagnostics and patient-centric treatments, though not devoid of ethical and technical intricacies.
Velu Aiyyasamy, A Thenmozhi, P. Malathi, S. Karkuzhali, V. Ashok, and J. Lakshmi Priya
IEEE
Any kind of data may be conveyed using light and the primary goal of this research is to build a device that can communicate through audio signals employing the LiFi technological advances, which makes use of Visible Light Communication (VLC), a way to send data by light. Light-based innovation, or LiFi, is relatively new. Instead of utilizing ordinary radio waves, it uses light to transfer data. At the moment, WiFi is the best way to send data over the electromagnetic spectrum's radio waves. When people talk about 'light frequency technological innovation', these are usually referring to visible light communication, which uses light to transmit data at a rate far higher than WiFi. The LiFi data is sent in several bit flows, and an infrared detector on the receiving end deciphers the information. Binary data, where 0 indicates that the Light is off and 1 indicates that it is on, is used for transmission. We also evaluate and compare the performance of the LiFi-based audio transmission system to that of current systems. While WiFi is ideal for indoor coverage, LiFi offers superior coverage in tight spaces due to its high density wireless data. Compared to WiFi, it offers superior protection, connectivity, communication rate and effectiveness while simultaneously alleviating the serious issue of radio interference. For biological sensors to assess a variety of health metrics, new technology called LiFi allows for high-density wireless data transfer without radio interferences in tight spaces. Light in the room is envisioned as an affordable and renewable medium for data transmission for mobile devices such as tablets and android mobiles in this technology's future development.
Ranjeet Kumar, Santosh Kumar Behera, Kalpana K, Amit V Kadam, V. Ashok, and D. Suganthi
IEEE
Recent increases in healthcare spending have made early disease detection a pressing concern. The growth of populations has a direct correlation with the rising death toll from breast cancer. Breast cancer ranks second among the deadliest cancers the proposed approach knows about. An autonomous disease detection system minimizes the likelihood of fatalities by providing a rapid response from medical personnel who can effectively treat the condition. The proposed approach entails three steps: preprocessing, segmentation, and model training. The proposed approach employed a combination of Contrast Limited Histogram Equalization and Fuzzy Histogram Equalization as a preprocessing technique. More and more comprehensive segmentation regions are produced when numerous segmentation regions are connected. After accumulating the attributes, the models are trained with RA-UNet. The proposed technique outperforms its counterparts, including RLM and U-Net. The probability of this strategy succeeding is 97.36 percent.
Pauline T., Sangeetha P., Janardhanan G., and Ashok V.
Informa UK Limited
Abstract Previous earthquakes have proven that failure of framed structure particularly at joints of beam and column caused disastrous collapse in structures that are built without seismic codal provisions. Most of the traditionally built Reinforced Cement Concrete (RCC) framed structures existing are lacking adequate reinforcement at structural joints and these joints are shear deficient. The main objective of the research studies was to enhance behaviour and performances of exterior structural joints by retrofitting and testing for displacement-controlled reversed cyclic loading. The joints retrofitted exhibits higher levels of ultimate displacements, higher levels of ultimate capacity previous to failure and the joints failed prior to failure of column. The variable novelty in research were size and shape of mesh, woven mesh, mesh orientation and wrapping in all direction around joints, cementitious matrix laminates with aggregate chips less than 5 mm, epoxy resin to increase bond between old and new concreting and chicken wire mesh near to cover and displacement controlled reversed cyclic loading was applied to column. The experimental research work indicated that, retrofitting with woven wire mesh strengthening technique will enhance the displacement ductility, stiffness, energy dissipation and strain. Thus the proposed retrofitted method anticipated in predicting the shear strength of joints.
T. Pauline, G. Janardhanan, P. Sangeetha, and V. Ashok
Springer Singapore
Ashok V, Geetha N.B., Rajkumar S, and Pauline T
Informa UK Limited
ABSTRACT Due to the enormously increasing population in metropolitan cities of India, most of the transmissions of ozone exhausting substances are expected from metropolitans, of which the building structures may contribute significantly. To limit these levels, one of the inevitable structures of the metropolitan plan is to adopt green buildings. In this regard, integration of Nano-enhanced Bio Phase Change Material (NeBPCM) in buildings is an innovative technology that has a high potential to reduce the thermal energy penetration into the buildings, The green buildings enhance the thermal comforts inside the building with energy conservation. A novel integration of NeBPCM composite is introduced to a Solid Concrete Hollow Block of size 400 mm x 200 mm x 100 mm. The experimental building of size 1 m x 1 m x 1 m is constructed to analyze the thermal effects of this phase change material (PCM) integration within the buildings. A drop in temperature is observed in PCM integrated building from 5.3°C to 1.1°C compared to that of building without PCM. The error between the measured data and numerical predictions is found to be within the range of 0.3°C and 1.6°C. The experimental investigations also revealed a reduction in maximum room temperature up to 5.3°C in the building integrated with NeBPCM vis-à-vis building without NeBPCM. Also, NeBPCM integration in building increased the temperature by 1.8°C when the outside ambient temperature averagely dropped below 23.6°C, thus improving the thermal comfort in the buildings all over the seasons. Therefore, NeBPCM integration in buildings is advantageous in terms of maintaining the room temperature to provide passive cooling of buildings with energy savings.