Rajiv Gandhi Institute of Technology, Kottayam, India (RIT) is a government engineering college owned and operated by the Government of Kerala. Located 14 km from Kottayam near Pampady, the institute was founded in 1991 by the Government of Kerala with a view of making it a centre of postgraduate and research studies. It was named after Shri Rajiv Gandhi, former Prime Minister of India.
With the exponential rise of open data exchange and machine learning applications, there has been an increase in the demand for a reliable method to protect ownership and verify the integrity of data. Although traditional cryptographic techniques provide confidentiality, they do not provide any way of preventing someone from modifying or using the dataset without authorisation. This paper proposes a Robust Data Watermarking and Verification Framework for Tabular datasets based on the Teaching-Learning-Based Optimization (TLBO) algorithm. The framework embeds a binary watermark into statistically stable attributes and optimally selects the location of the watermarks based on a fitness function that minimises distortion while maximising robustness using TLBO. The verification algorithm that is based on tolerance provides validation of the extracted watermark against various perturbation conditions. The experimental results provide evidence of a very good balance between the imperceptibility, robustness, and the ability to detect tampering. Future development of this framework will focus on hybrid TLBO-based methodologies and incorporation of a blockchain to create a watermark registry.
Modern digital hearing aids typically employ multiband filtering, noise reduction, and dynamic range compression to compensate for hearing loss. However, most existing systems rely on uniform filter banks, high order FIR implementations, or independently optimized processing stages, which often lead to increased computational complexity, higher latency, and suboptimal audiogram matching. This paper introduces a novel 17 band auditory compensation system based on a multirate IIR filter bank that is specifically structured for efficient and accurate audiogram matching. The IIR analysis bank provides sharp stopband attenuation and flat passband behavior with far fewer coefficients than comparable FIR structures, thereby reducing arithmetic load and memory requirement for low power hearing aid processing. The multirate Chebyshev Type II filter bank provides a nonuniform frequency decomposition with low complexity and low latency, covering the audiometric range. An all pass filter network is designed to linearize phase response, aligning group delays across bands to preserve waveform fidelity. For noise suppression, combined discrete wavelet transform (DWT) thresholding and spectral subtraction, leveraging the strengths of both methods are used to reduce background noise while minimizing artifacts. The wide dynamic range compression (WDRC) module applies level dependent gain in each band with static calibration to match prescribed insertion gains and adaptive attack/release dynamics to accommodate varying inputs. In this work the algorithms for filter design, phase equalization, denoising, and compression are derived, and a detailed mathematical formulation of the overall system is done. MATLAB simulations demonstrate the filter bank’s frequency response, phase characteristics, noise reduction performance, and input output behavior. Results show that the 17 band filter bank achieves close matching to target gains with less than 2dB error across frequencies for speech inputs, and phase linearization reduces group delay variation to below 11ms. The combined wavelet and spectral subtraction approach improves system performance and reduces musical noise. The adaptive WDRC restores audibility of soft sounds while limiting loud outputs, with a processing delay under 11ms meeting real time requirements. The proposed system advances hearing aid signal processing by delivering finer frequency resolution, reduced distortion, and improved management of noise and dynamic range.
Rapid urbanisation and industrialisation are driving employment opportunities for all categories of people. Due to land availability constraints and the high cost of settling near industrial regions and urban hotspots, working professionals are often compelled to settle on the outskirts of urban centers where the cost of living is lower. Consequently, these professionals must commute from their residences to their workplaces, typically relying on private transportation, which has a significant negative impact on the environment and traffic congestion. To mitigate these issues and promote sustainable commuting, infrastructure enhancements are being developed to encourage the use of public transport. The main objective of this study is to understand the dynamics of mode choice and develop a behavioural model for working professionals in response to these infrastructure enhancements. Focusing on Info Park in Kakkanad, Ernakulam, data was collected through a stated preference questionnaire survey targeting working professionals. The findings indicate that as income rises, people show a stronger preference for cars and two-wheelers over public transportation. However, commuters’ willingness to switch to the metro and water metro increases when the cost of these options is reduced. This study provides stakeholders with valuable insights into the feasibility of infrastructure enhancements and informs the development of policies to effectively encourage the use of public transport, reducing reliance on private vehicles and alleviating urban transportation challenges.
Effective cooling mechanisms are crucial for electronic apparatus to improve dependability and prevent premature failures. This study investigates the impact of pin–fin heat sink design on heat transfer performance in electronic apparatus cooling, employing Phase Change Materials (PCMs). Two-dimensional transient simulations are conducted by varying the thickness of pin fins in heat sinks, while maintaining the pin fin length and the volume fraction of Thermal Conductivity Enhancer (TCE) constant. Heat sinks equipped with fins of thickness 1 mm, 2 mm, and 3 mm are utilized while maintaining a consistent fin volume fraction of 9
Abrasive flow machining (AFM), one of the several mechanical non-conventional machining (NCM) techniques, is a non-conventional machining technique utilized for varied surface finishing and polishing applications. In this work, we examine the effects on surface finish quality of three process factors in Abrasive Flow Machining (AFM): the number of cycles, extrusion pressure, and abrasive grain size, in combination. An unconventional finishing method called AFM is very useful for improving the surface finishes of internal channels in IC engines and precision-required components, especially in aerospace applications. The experimentation focuses on SS 430 material and evaluates finish quality and machining time. Grey relation analysis and the Taguchi technique are used in the study for optimization. The research attempts to comprehend these elements’ impact on surface finish by methodically altering them, offering insights into the ideal circumstances for AFM. This study not only advances knowledge of AFM’s use in aerospace and IC engine applications, but it also provides a useful approach for adjusting process variables to effectively provide better surface finishes.
