MATRIX Academic International Online Journal Of Engineering And Technology

Problems of improving transactions on the blockchain

2024-04-01T06:39:38+00:00

Abstract. The article discusses the main directions of growth of the develop-ment of a decentralized system based on Blockchain technology. The system will make it possible to store all information on multiple computers, which will be available anytime, anywhere, without the participation of intermediaries. By employing Blockchain technology for the establishment of a global and distrib-uted database, it is possible to ensure a completely transparent movement of electronic documents.

Forecasting Number of Inbound Tourists in India Adopting ARIMA Model

2024-03-26T12:44:12+00:00

This study focuses on estimating the occurrence of inbound tourists in India using univariate time series econometrics, the ARIMA model in particular. The tourism industry plays a significant role in India's economy, making accurate forecasts essential for effective planning and decision-making. The ARIMA model is known for its ability to analyze time series data, making it an appropriate tool for predicting future tourist arrivals. Data from previous years of inbound tourist arrivals in India, including factors such as historical trends, seasonality, and economic conditions, is utilized form world bank open data. The ARIMA model will be employed to capture the patterns and correlations within the data, enabling the prediction of future tourist numbers accurately. By adopting this forecasting model, policymakers, tourism authorities, and industry stakeholders can make informed decisions regarding infrastructure development, resource allocation, marketing strategies, and policy formulations. This research aims to contribute to the tourism sector by providing reliable insights into the future trends of inbound tourism in India, facilitating sustainable growth and development in the industry.

Adaptive Illumination: Designing a Smart Street Lighting System for Sustainable Urban Environments

2024-04-01T06:37:31+00:00

In the age of rapid technological advancement and increasing urbanization, the need for sustainable and efficient infrastructure has never been more pronounced. As cities grow and evolve, so do the challenges related to managing their energy consumption, safety, and environmental footprint. One of the critical components of urban infrastructure that has a direct impact on all these areas is street lighting. Traditional street lighting systems, while essential for safety and visibility, often consume excessive amounts of energy, contribute to light pollution, and require significant maintenance. This is where the concept of adaptive illumination comes into play as shown in Figure 1.

Adaptive illumination refers to the design and implementation of street lighting systems that can adjust their brightness and intensity based on real-time environmental conditions and human activity. Unlike conventional systems that remain uniformly lit throughout the night, adaptive systems use sensors, data analytics, and connectivity to dynamically modify their output. This not only results in significant energy savings but also reduces light pollution and enhances the overall safety and comfort of urban residents.[1]

The sustainability aspect of adaptive illumination cannot be overstated. As the world grapples with climate change and the pressing need to reduce carbon emissions, every kilowatt-hour saved has a cascading positive effect on the environment. By ensuring that street lights are only as bright as they need to be, cities can dramatically decrease their energy consumption. This is particularly relevant in the context of urban areas, which are often the largest consumers of electricity within a region.

Emotional recognition from facial expressions

2024-04-01T06:38:27+00:00

The field of emotional recognition from facial expressions represents a fascinating intersection of psychology, neuroscience, and technology. This area of study delves into understanding how human emotions can be identified through the analysis of facial expressions. The complexity lies in deciphering the subtle variations in facial muscle movements that convey a wide range of emotions. Recent advancements in artificial intelligence and machine learning have propelled this field forward, enabling the development of sophisticated algorithms capable of analyzing and interpreting facial expressions with remarkable accuracy. These technologies hold immense potential in various applications, from enhancing interpersonal communication and empathy to improving customer service and security. However, the pursuit of accurate emotional recognition raises important ethical and privacy concerns. It underscores the need for responsible use of technology, ensuring that emotional detection respects individual privacy and is used for constructive, non-invasive purposes. This emerging field continues to evolve, promising deeper insights into human emotions and their expression, while challenging us to consider the implications of technology that can 'read' our emotions.