Lingaya's Vidyapeeth is a private deemed-to-be university located in Faridabad, Haryana, India. It was established in 1998, as Lingaya's Institute of Management and Technology..
The world is experiencing an increased power demand, hence the need for sustainable sources of power at the expense of conventional sources. This paper explores the minimization of energy waste using the organic flash cycle in combination with a regenerator to recover the waste heat with 1,1,1,3,3-pentafluoropropane as a working fluid. A thermodynamic model was designed to optimize the operating conditions primarily in the heat recovery vapor generator (HRVG) pressure. When HRVG pressure is raised, both cycle efficiency and power will go up, but turbine inlet temperature has a greater influence on the overall performance of the system. The results indicate that boiler pressure reaches a minimum level during waste heat recovery operations compared with traditional fuel-fired facilities, and increasing source temperatures leads to increased pressure in both cases. The optimal operation pressure for the boiler reaches 12.79 bar when the source temperature stands at 150 degrees C. Operating under those conditions allows the system to achieve 13.20% energy efficiency and 19.53% exergy efficiency.
This paper presents the design and analysis of an multiband uniform metasurface antenna. The proposed metasurface comprises a three-by-three array of identical circular radiating elements with cross-slot configurations. Characteristic Mode Analysis (CMA) is employed to investigate and optimize the antenna’s inherent resonant behaviour. Key CMA parameters, including modal significance, characteristic angle, and eigen value responses, are analyzed to identify and excite the dominant modes. Surface current distributions are further examined using CMA, and a micro strip line feeding technique is implemented to efficiently excite the desired operating frequency bands. The proposed antenna exhibits multiple resonant frequencies at 5.5 GHz, 6.3 GHz, 10.0 GHz, 17.4 GHz, and a wideband response spanning 19.5 GHz to 30 GHz, making it suitable for 5G and advanced wireless communication applications. The antenna achieves an average gain of approximately 10 dBi with a radiation efficiency of 85
One of the most prevalent signs of depression is insomnia, which refers to the inability to fall or stay asleep, and can worsen the severity and duration of depressive episodes. Early diagnosis and effective treatment of insomnia are crucial to prevent related health issues. In this work, we present an empirical mode decomposition (EMD) based methodology to identify insomnia from prefrontal EEG signals available in the CAPSleep database. The EEG signals are decomposed with EMD to produce Intrinsic Mode Functions (IMFs), from which features are extracted for each IMF band. These features are then reduced via principal component analysis (PCA). Four machine learning techniques, such as Ensemble KNN (EKNN), Support Vector Machine (SVM), k-nearest neighbor (KNN), and Decision Tree (DT), are used to classify the resultant feature vectors and evaluation through 5-fold cross-validation. The study reports a 79.7% accuracy with the Decision Tree classifier, highlighting the potential of prefrontal EEG signals in diagnosing insomnia.
Abstract - Household Hazardous Waste (HHW) has emerged as a significant environmental and public health concern due to the widespread use of chemical-based products in daily household activities. Common items such as batteries, paints, pesticides, cleaning agents, fluorescent lamps, and expired medicines contain hazardous substances that can adversely affect human health and the environment when disposed of improperly. Despite constituting only a small fraction of municipal solid waste, HHW can lead to soil contamination, groundwater pollution, air quality degradation, and serious health hazards. This study aims to assess the level of public awareness regarding HHW, analyze existing disposal and segregation practices, and promote responsible waste management among households. A descriptive survey methodology was adopted, wherein structured questionnaires were administered to residents through direct household visits. Additional insights were obtained through interactions with waste management officials. The collected data were analyzed using percentage-based statistical methods and graphical representations. The survey findings revealed that only 36% of respondents were fully aware of HHW, while 24% were partially aware and 40% lacked awareness entirely. Furthermore, 60% of households disposed of hazardous waste along with regular garbage, and only 30% practiced waste segregation. These results indicate a substantial gap in public knowledge and proper disposal practices. However, the majority of respondents expressed a willingness to adopt safer waste management methods when provided with appropriate guidance. Based on these findings, an awareness campaign was conducted to educate residents about HHW identification, segregation, safe disposal methods, and environmental protection. The study highlights the critical need for continuous public education, community participation, and effective waste management policies to ensure sustainable environmental protection and improved public health. Key Words: Household Hazardous Waste (HHW), Waste Segregation, Environmental Awareness, Hazardous Waste Management, Public Health, Municipal Solid Waste, Awareness Campaign, Sustainable Waste Management, Environmental Protection, Community Participation.
