This paper present an artificial neural network (ANN) approach for forecasting the electric energy output from a 25-kWp grid connected solar photovoltaic power plant (SPVPP) installed at Vibhuti Khand, Lucknow, Utter Pardesh, India. The main aim is to develop a model of the system using artificial neural network (ANN) that can accurately forecast electrical energy output generated from the grid connected solar PV system. The ANN interpolates among the solar PV generation output and relevant parameters such as average solar insolation, average module temperature and average humidity . In this study, an ANN model is implemented and validated with reasonable accuracy on real electric energy generation output data. The physical layout and salient features of the power plant is also reported. The proposed ANN method can be extended to any solar photovoltaic power plant (SPVPP) for forecasting energy generation.
An error in data communication is very common and it cannot be avoided. The error is of two types, such as single bit and burst error, which is depends upon noise present in the path via the data, is transferred. There are various method used for the detection of this error, and this is done on the basis of even or odd parity. In this paper, a hamming code technique is used to detect and correct the single bit error. An extra bit is sent to receive along with the original data known as a parity bit, this is also done on the basis of even or odd parity. This extra bit will enhance the security of the data being transferred.
A study has been conducted to find out the rheological properties of h-BN nano cutting fluid and then its effects have been analyzed on the machinability of Inconel 625. It is to be noted that addition of nanoparticles with improved rheological behavior helps to enhance the anti-wear and anti-frictional properties of cutting fluid. Hexagonal boron nitride (h-BN) nanoparticles are environmentally safe, chemically inert, and lubricious in nature and hence preparation of BN nano cutting fluid is a reliable option for machining with MQL technique in machining of difficult to cut material like Inconel-625. This paper includes preparation of BN-nano cutting fluid with analysis of its rheological properties and effect on machining of Inconel 625 with h-Bn nano fluid assisted MQL.
Tobacco use is considered as one of the leading causes of lung cancer and Chronic Obstructive Pulmonary Disease (COPD). The use of tobacco is dependent upon many factors, such as age, sex, social class, education and income. Therefore, the trend of tobacco consumption is shifting from the developed to the developing countries. The purpose of this study was to identify the contributing factors which lead to tobacco use among undergraduate university students (18-25 years). A retrospective Case-Control study was carried out on 560 (280 Cases and 280 Controls) undergraduate students in three universities of Khyber Pukhtunkhwa (KP), Pakistan. Data was collected through a self-filled structured questionnaire, which was analyzed using descriptive and inferential Odd Ratio (OR) statistics, via SPSS Version 19. The data revealed that tobacco use is significantly associated with brothers (OR: 1.81), and other family members (father in law, grandfather, nephew, relatives) (OR: 3.62) who are addicted to tobacco use. Tobacco using friends (OR: 15.39), use of tobacco in university (OR: 4.37), hostel (OR: 3.79), and public places (OR: 1.49) are also significantly associated with tobacco use. Staying in social gatherings (OR: 2.23) where people use tobacco and offer it to others (OR: 7.43) is also linked with tobacco use. Getting impressed by media promotion advertisements (OR: 1.81), and beliefs about the beneficial effects of tobacco use (OR: 2.19) are also significantly related to tobacco use. Furthermore, having personal problems (OR: 1.78), physical / medical diseases (OR: 1.78), and financial problems (OR: 1.57) were also found significantly associated with tobacco use. The study concluded that there are many factors like tobacco using family members, peer pressure, social gatherings where tobacco is used and offered freely, and promotion of tobacco by media, etc., are positively associated with tobacco use among undergraduate university students (18-25 years) in KP, Pakistan.
The unprecedented COVID-19 pandemic has severely affected the Automobile sector in the Delhi NCR region with Supply chain disruptive innovations and periodic travel restrictions imposed by the government. The present study investigates the influence of the digital value chain on organisational productivity. The study analyses the data collected from Logistics and Supply chain managers working in allied areas of value chain operations in the automobile sector. The target respondents selected for the study are 200, and purposeful sampling is used to identify the target respondents with expertise in the areas of supply chain and marketing. Partial least squares regression is used to analyse the collected data and establish relationships among the variables and explanatory variables. The study contributes to the understanding of value chain strategies and their significance in enhancing organisational productivity in the automobile sector.
As the Indian railway network expands, the demand for reliable and efficient power systems, especially auxiliary converters supporting various on-board systems, grows. By reducing power losses and fuel consumption, it is more crucial to design an energy-efficient and economic auxiliary converter for the railway system. This is partially accomplished by using a 25KVA auxiliary (Aux.) converter, which can accept input electrical energy from a 110V DC battery at Self-Generation (SG) coaches. Biogeography Based Optimization (BBO) method of harmonic elimination for a 25KVA converter is described in this study. The paper explores the 120-degree mode of conduction and compares the existing technique with a proposed 7-switching selective odd harmonic removal method. Results from Matlab simulations demonstrate the effectiveness of the BBO technique in reducing Total Harmonic Distortion (THD). The output voltage waveforms with and without BBO are compared, showcasing a significant improvement in harmonic suppression. The paper concludes by emphasizing the practical implementation of the optimized switching angles using an ATmega2560R3 microcontroller. The online application of stored switching angles on the microcontroller is calculated offline.
The global labor market is experiencing profound transformations driven by technological advancements, demographic shifts, environmental challenges, and economic uncertainties. The Future of Jobs Report 2025 by the World Economic Forum (WEF) offers a comprehensive analysis of these changes, forecasting job creation and displacement, skill disruptions, and strategic responses required by stakeholders. This study delves into macrotrends reshaping industries, highlights the emergence of new roles, and discusses the importance of reskilling and policy interventions to foster an equitable and sustainable labor market by 2030. Recommendations are provided to ensure workers and organizations thrive in this rapidly evolving landscape.
This paper present an artificial neural network (ANN) approach for forecasting the electric energy output from a 25-kWp grid connected solar photovoltaic power plant (SPVPP) installed at Vibhuti Khand, Lucknow, Utter Pardesh, India. The main aim is to develop a model of the system using artificial neural network (ANN) that can accurately forecast electrical energy output generated from the grid connected solar PV system. The ANN interpolates among the solar PV generation output and relevant parameters such as average solar insolation, average module temperature and average humidity . In this study, an ANN model is implemented and validated with reasonable accuracy on real electric energy generation output data. The physical layout and salient features of the power plant is also reported. The proposed ANN method can be extended to any solar photovoltaic power plant (SPVPP) for forecasting energy generation.
An error in data communication is very common and it cannot be avoided. The error is of two types, such as single bit and burst error, which is depends upon noise present in the path via the data, is transferred. There are various method used for the detection of this error, and this is done on the basis of even or odd parity. In this paper, a hamming code technique is used to detect and correct the single bit error. An extra bit is sent to receive along with the original data known as a parity bit, this is also done on the basis of even or odd parity. This extra bit will enhance the security of the data being transferred.
A study has been conducted to find out the rheological properties of h-BN nano cutting fluid and then its effects have been analyzed on the machinability of Inconel 625. It is to be noted that addition of nanoparticles with improved rheological behavior helps to enhance the anti-wear and anti-frictional properties of cutting fluid. Hexagonal boron nitride (h-BN) nanoparticles are environmentally safe, chemically inert, and lubricious in nature and hence preparation of BN nano cutting fluid is a reliable option for machining with MQL technique in machining of difficult to cut material like Inconel-625. This paper includes preparation of BN-nano cutting fluid with analysis of its rheological properties and effect on machining of Inconel 625 with h-Bn nano fluid assisted MQL.
Tobacco use is considered as one of the leading causes of lung cancer and Chronic Obstructive Pulmonary Disease (COPD). The use of tobacco is dependent upon many factors, such as age, sex, social class, education and income. Therefore, the trend of tobacco consumption is shifting from the developed to the developing countries. The purpose of this study was to identify the contributing factors which lead to tobacco use among undergraduate university students (18-25 years). A retrospective Case-Control study was carried out on 560 (280 Cases and 280 Controls) undergraduate students in three universities of Khyber Pukhtunkhwa (KP), Pakistan. Data was collected through a self-filled structured questionnaire, which was analyzed using descriptive and inferential Odd Ratio (OR) statistics, via SPSS Version 19. The data revealed that tobacco use is significantly associated with brothers (OR: 1.81), and other family members (father in law, grandfather, nephew, relatives) (OR: 3.62) who are addicted to tobacco use. Tobacco using friends (OR: 15.39), use of tobacco in university (OR: 4.37), hostel (OR: 3.79), and public places (OR: 1.49) are also significantly associated with tobacco use. Staying in social gatherings (OR: 2.23) where people use tobacco and offer it to others (OR: 7.43) is also linked with tobacco use. Getting impressed by media promotion advertisements (OR: 1.81), and beliefs about the beneficial effects of tobacco use (OR: 2.19) are also significantly related to tobacco use. Furthermore, having personal problems (OR: 1.78), physical / medical diseases (OR: 1.78), and financial problems (OR: 1.57) were also found significantly associated with tobacco use. The study concluded that there are many factors like tobacco using family members, peer pressure, social gatherings where tobacco is used and offered freely, and promotion of tobacco by media, etc., are positively associated with tobacco use among undergraduate university students (18-25 years) in KP, Pakistan.
The unprecedented COVID-19 pandemic has severely affected the Automobile sector in the Delhi NCR region with Supply chain disruptive innovations and periodic travel restrictions imposed by the government. The present study investigates the influence of the digital value chain on organisational productivity. The study analyses the data collected from Logistics and Supply chain managers working in allied areas of value chain operations in the automobile sector. The target respondents selected for the study are 200, and purposeful sampling is used to identify the target respondents with expertise in the areas of supply chain and marketing. Partial least squares regression is used to analyse the collected data and establish relationships among the variables and explanatory variables. The study contributes to the understanding of value chain strategies and their significance in enhancing organisational productivity in the automobile sector.
As the Indian railway network expands, the demand for reliable and efficient power systems, especially auxiliary converters supporting various on-board systems, grows. By reducing power losses and fuel consumption, it is more crucial to design an energy-efficient and economic auxiliary converter for the railway system. This is partially accomplished by using a 25KVA auxiliary (Aux.) converter, which can accept input electrical energy from a 110V DC battery at Self-Generation (SG) coaches. Biogeography Based Optimization (BBO) method of harmonic elimination for a 25KVA converter is described in this study. The paper explores the 120-degree mode of conduction and compares the existing technique with a proposed 7-switching selective odd harmonic removal method. Results from Matlab simulations demonstrate the effectiveness of the BBO technique in reducing Total Harmonic Distortion (THD). The output voltage waveforms with and without BBO are compared, showcasing a significant improvement in harmonic suppression. The paper concludes by emphasizing the practical implementation of the optimized switching angles using an ATmega2560R3 microcontroller. The online application of stored switching angles on the microcontroller is calculated offline.
The global labor market is experiencing profound transformations driven by technological advancements, demographic shifts, environmental challenges, and economic uncertainties. The Future of Jobs Report 2025 by the World Economic Forum (WEF) offers a comprehensive analysis of these changes, forecasting job creation and displacement, skill disruptions, and strategic responses required by stakeholders. This study delves into macrotrends reshaping industries, highlights the emergence of new roles, and discusses the importance of reskilling and policy interventions to foster an equitable and sustainable labor market by 2030. Recommendations are provided to ensure workers and organizations thrive in this rapidly evolving landscape.
