Karpagam College of Engineering

Emotion detection, empathy modeling, and emotion and empathy modeling in the presence of digital social systems and low-resource languages such as Tamil have been important areas to focus upon in recent times. The Emotion and Empathy-Aware Knowledge-Augmented Transformer (EEAKAT), proposed in this paper, is based upon multi-task learning with assistance from external knowledge graphs such as ConceptNet and EmoNet, designed to improve emotional content understanding in this aspect. Emotion-driven attention is used in EEAKAT to give importance to key emotional indicators, contrastive learning to highlight subtle emotional differences, and reinforcement learning based on knowledge feedback to develop emotional content-related responses in empathy appropriately. The proposed framework is designed to facilitate emotional assistance in real-world areas such as mental health support services, analysis in social media, by learning to undertake emotional aspects in unison in real-world contexts. The achievement of EEAKAT is measured in terms of accuracy at 0.735, F1-score at 0.725, and Mean Squared Error at 0.030 in empathy prediction, along with BLEU Score of 0.640 in response generation, reflecting EEAKAT’s effectiveness in being a proficient emotion and empathy modeling framework to improve sentiment-driven social systems in low-resource linguistic settings.

Interest in waste-to-energy technologies, especially the co-pyrolysis of biomass, food, and plastic waste, has grown as a result of the world’s significant increases in waste production and energy demand. In this study, energy-rich biofuel and value-added chemicals were recovered from waste materials. The feedstocks used were fish waste, sugarcane bagasse, and waste plastics. The plastics included polyethylene (PE), polypropylene (PP), low-density polyethylene (LDPE), and high-density polyethylene (HDPE). These wastes were collected from commercial, agricultural, and residential sectors. The experiments were carried out with the motive of producing more pyrolysis liquid by blending fish waste with waste plastics (FWP) and sugarcane bagasse with waste plastics (SBP) in equal proportions in a fixed bed reactor under different operating temperatures between 350 °C and 550 °C. The maximum oil product yields for the pyrolysis of FWP were 52.0 wt

Reduced graphene oxide (rGO) composites demonstrate favorable energy storage characteristics, including adjustable porosity, superior conductivity, chemical stability, and remarkable charge storing capacity. Nonetheless, the intrinsic rigidity of rGO constrains its application in contemporary disposable and flexible energy storage systems. This paper details manufacture of flexible composites based on reduced graphene oxide and iron sulfide, utilizing natural fibers derived from discarded bioresources, specifically pineapple leaf fiber, as a binder. The novelty of this work lies in the sustainable utilization of pineapple leaf fiber (PALF) as a bio-binder combined with microwave-assisted rapid synthesis and electrodeposition-controlled tuning of Fe₃S₄ to fabricate highly flexible and eco-friendly paper electrodes. The rGO and iron sulfide (Fe₃S₄) nanoparticles are produced by a rapid microwave-assisted method. Additionally, Fe₃S₄ nanoparticles are electrochemically coated on synthesized rGO- paper electrodes to improve energy storage and electronic conductivity properties. Highly flexible paper electrodes were analyzed using several characterization techniques, including Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy and scanning electron microscopy (SEM) examined their chemical bonding and morphology. Electrochemical assessments, comprising Galvanostatic Charge/Discharge (GCD), Electrochemical Impedance Spectroscopy (EIS), and Cyclic Voltammetry (CV) were conducted to analyze capacitive and kinetics characteristics of electrodes. LC/rGO/Fe₃S₄ at 2400 s demonstrates a specific capacitance 69.79 F/g, rGO/LC, which were 60 F/g. The value of 69.79 F/g was obtained in a three-electrode configuration, whereas the 39.8 F/g value corresponds to the assembled symmetric device configuration. The synthesized tertiary composite (rGO/LC/Fe₃S₄) exhibits exceptional charge-discharge performance. The LC/rGO/Fe₃S₄ configuration has a power density 4.6 W/kg on 12 Wh/kg a specific capacitance 39.8 F/g over 2400 s. The rGO/LC/Fe₃S₄ (2400 s) electrode has superior electrochemical properties, evidenced by lower Rs (1.8 Ω) and Rct (0.3 Ω) values in comparison to the binary composite (rGO/LC). These composites offer profound understanding of the fabrication of electrodes exhibiting strong ionic and electrical conductivity for rapid energy storage systems. The electrochemical performance obtained in this study is comparable to or exceeds previously reported rGO/iron sulfide-based flexible electrodes, highlighting the effectiveness of the proposed fabrication strategy.

The utilization of fiber-reinforced composite materials is increasingly prevalent in the aerospace, structural and automotive industries, owing to lightweight characteristics. This research evaluates tamarind seed shell powder (TSSP) reinforced Waru bark-Banana pseudostem (WBBP) fiber composites, fabricated using compression molding. TSSP was incorporated at weight ratios of 0, 2, 4, 6, and 8 wt

Concrete is the primary and most often utilized structural material in civil engineering. Prompt assessment of concrete strength is crucial for ensuring structural integrity and reducing construction delays, therefore preventing potential structural failures. This preliminary assessment guarantees concrete structures support loads throughout their operational lifespan and during construction. A major problem in the construction sector is the precise assessment of concrete strength and detection of possible damage without resorting to destructive testing. Traditional methods frequently necessitate labor processes and may be unfeasible for real-time monitoring. To address this challenge, IoT-based monitoring systems with Polyvinylidene Fluoride Film (PVDF) sensors offer an effective solution for damage detection and ongoing strength assessment at concrete structures. This research employed a polyvinylidene fluoride film sensor, utilizing surface-bonding method to affix sensor to cylindrical specimens. Trial phase lasted four weeks, incorporating assessments on 5th, 10th, and 15th days to detect any structural damage and evaluate required strength levels. This investigation confirmed that the findings achieved by PVDF-based wireless sensor were both dependable and practical. The correlation coefficient values are examined to confirm the relationship between data from IoT-based testing and compressive strength. All results are displayed graphically, demonstrating that this non-destructive method can precisely forecast concrete strength and detect structural problems. This work distinctly contributed by verifying the application of PVDF sensors for continuous, in-situ monitoring of concrete, offering an innovative method for early damage detection and assessing the structural integrity of the structure.