Volume 11 | Issue 5 |

 Abstract

This research paper explores the effectiveness of agglomerative clustering as an alternative algorithm for customer segmentation. The study aims to contribute to the existing literature on customer segmentation and clustering algorithms and provide insights into the effectiveness of agglomerative clustering in customer segmentation. The research design is descriptive, and the data was collected from a large retail chain and anonymized to protect customer privacy. The study used agglomerative clustering, a hierarchical clustering algorithm, to identify customer segments based on their purchasing behaviour. The study identified four customer segments based on the similarity of their purchasing behaviour: high-value customers, moderate-value customers, low-value customers, and inactive customers. The findings provide insights into the characteristics and behaviour of each customer segment and can help businesses improve their customer targeting and retention strategies.

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 Keywords

Customer segmentation, agglomerative clustering, K-means clustering, unsupervised machine learning, customer behavior, customer retention, personalized marketing.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social Media has emerged as a popular medium for individuals to express themselves and share their ideas with others. The number of users across various social networks is growing at an exponential rate. Twitter has become a vital source of real-time information and communication, with a plethora of trending topics being discussed by users at any given moment. These topics cover a wide range of subjects, reflecting people's daily lives and interests. Therefore, it is essential to implement an effective methodology to identify short-term, high-intensity discussion topics. The proposed work utilizes a Multiview clustering approach, which has been shown to be highly effective in unfolding underlying patterns. The Multiview clustering approach used in the analysis of trending Twitter topics considers different views of the data, which include the text content of tweets, like count, retweet count, quote count, and reply count. This analysis can offer valuable insights into the latest trends and have practical applications, such as monitoring public opinion, recommending hot products, and detecting incidents. Additionally, artificially intelligent services like web search systems or recognition systems can also benefit from this analysis. The Twitter data is retrieved and a dataset is created for further analysis using Python's snscrape library. The aim of this work is to cluster topics based on multi-view data to identify the most discussed topics during a specific time period. Experiments on real datasets indicate that the Multiview clustering approach is more effective than single-view clustering in detecting trending topics with a reasonably close approximation to the expected outcome. Nonetheless, the proposed approach has some limitations and challenges, such as the requirement for sufficient and diverse data to ensure the accuracy of the clustering results.

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 Keywords

Multi-View Clustering, Snscrape library, Feature Extraction, Dimensionality reduction, Keyword Extraction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Recent studies suggest that in the next five decades, large portion of the NonRenewable sources accessible will be diminishing. This is the prime concern for attracting the attention for the enhancement in the performance of the renewable energy sources which abundantly exist in the nature. Wind, solar photovoltaic, and solar thermal power systems are emerging renewable technologies that can be developed as a viable option for the future generation of electrical energy. In this paper, we have considered a hybrid power system consisting of Wind turbine generator (WG), solar photovoltaic (S-PV), diesel generator (DG), fuel cell (FC), battery energy storage system (BES) and aqua electrolyzer (AE) for simulation studies. The main purpose of controller is to maintain the frequency of the grid to nominal values, for any deviations in these nominal values are due to sudden variations in load or generator or both. To maintain frequency stability of the system we employ controllers designed through conventional methods which is vary tedious and time consuming process,with the introduction of computational techniques opened a new path way for advanced new generation controllers. In this paper PSO (Particle swarm optimization) based PI controller is maintained to regulate frequency deviations. From the results, we can demonstrate the effectiveness of the PSO based controllers in terms of reduced settling time, over shoot, and oscillations. The results are compared with conventional controllers and with the controllers whose gains are tuned by GA (Genetic Algorithm).

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 Keywords

- Load Frequency controller, Particle Swarm Optimization, Genetic Algorithm, Hybrid power system.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Building technology relies heavily on the use of concrete, which is the most commonly utilized construction material. However, cement production releases large amounts of carbon dioxide (CO2) into the atmosphere, contributing to increased global warming. Therefore, an alternative environmentally friendly building material such as photocatalyst concrete has been developed. Photocatalytic concrete, with a more environmentally friendly alternative binder, is an innovative building material to replace Portland cement. This technology introduces nanoparticles such as nano clay into the cement paste to improve its mechanical properties. Concrete materials have also been developed to function as self-cleaning building materials. The self-cleaning properties of concrete are provided by the incorporation of photocatalytic materials such as titanium (TiO2). Self-cleaning concrete containing these photocatalysts would be powered by ultraviolet (UV) radiation and accelerate the breakdown of organic particles. In this way, the cleanliness of building surfaces can be maintained and air pollution reduced. This article briefly discusses self-cleaning concrete.

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 Keywords

Titanium Dioxide (TiO2), Self-Cleaning Concrete, TiO2, Rhodamine B dye, Compressive strength, Photocatalyst.

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Creative Commons Attribution 4.0 and The Open Definition

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In today's era, Online Travel Services Booking has evolved into an essential component of everyday life, and the vast expansion of the internet has brought about significant changes in the lifestyle of the entire world. The advent of this technological revolution has given rise to a newfangled concept of online booking travel services, which has radically transformed how people book their travel arrangements. The Online Travel Booking Application primarily serves as a booking platform that caters to viewing and booking travel services, with the main goal of providing the utmost convenience to customers. In contrast to the traditional offline booking process, which was an arduous and time-consuming procedure, the online travel booking system has gained widespread popularity due to its efficiency and user-friendly features. The availability of booking offers online has made it simple to keep track of bookings, manage client databases, and enhance the quality of travel booking services. This cutting-edge technology empowers users to select packages from a comprehensive catalog. The user's personal information is kept confidential and is only saved in the database when necessary. Furthermore, each user is assigned a unique identification number and password that cannot be shared, thus ensuring the safe and secure booking of travel services.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Business Model,Market, Revenue,Profit

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The improve Transient Stability of a two area power system , UPFC based on conventional P-I control can be connected to verify that the constant power flow from one area to other area, even if severe fault occurs on the line is achieved. For this a Multimachine power system is developed (Kundur test system) and UPFC is connected on line, modeled & designed its series controls. A MATLAB Simulink model for the enhancement of transient stability technique with both without UPFC and with UPFC is developed .By the use and tuning of UPFC controllers (PI regulators) the constant power flow from one area to other area, even if severe fault appears on the line is achieved in transient state. Simulation is carried out in the MATLAB/Simulink platform. Simulations run for duration of 50 sec. with the application of three phase fault, (applied only for the 0.1 seconds and after that it is removed by the auto recloser circuit breakers) to prove that UPFC helps in enhancing transient stability of a Multi-machine power system in the event of severe fault. Detailed simulation studies are carried out with MATLAB/SIMULINK environment for three cases :(a) Without UPFC, without fault (b) without UPFC, with fault(c) with UPFC, with fault.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

FACTS, MATLAB, Simulink, Transient stability, Two-area power system, UPFC

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This correlational study aimed to explore the relationship between the nurses' resilience and quality nursing management. The primary participants in this study were the 310 selected nurses in Guilin Medical University, Guilin City, Guangxi Province, China. According to the data, the correlation coefficient obtained which is +0.997 respectively shows a very high positive correlation between the resilience and quality nursing management of the nurses. Moreover, the nurses exhibited a high level of resilience when fulfilling their professional duties during a disaster. The level of the quality leadership nursing management performed by the nurses during the pandemic gained a grand mean of 4.78 described verbally as "Outstanding". Moreover, the level of the quality nursing management in terms of involvement in quality planning, management, quality results, customer satisfaction and nursing management in terms of information and analysis were all rated as outstanding. It was recommended that future researchers may undertake a comparable or related study to this one to determine whether similar or related nursing trends or conditions exist in other locales.

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 Keywords

Resilience, Quality Nursing Management, Public Health Management.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This researcher aims to examine the role of visual communication in conveying the complex interplay of spatial qualities, aesthetic design, and functional aspects to architecture. This research explored how Architects and designers used visual elements such as color, shape, texture, and form to create visually compelling and functional spaces. The author also discussed the importance of considering the user experience when designing spaces, and how visual communication can help to communicate a sense of space and place. The effective visual communication is essential for creating architecture that is both functional and aesthetically pleasing, and that communicates a sense of purpose and meaning to its users.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Visual communication, spatial qualities, aesthetic design, functional aspects

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Automatic flaw detection in medical images is a rapidly growing subfield used in a variety of medical diagnostics. Automated tumor diagnosis in MRI is significant because it reveals information about aberrant tissues that is required for treatment planning. For this reason, reliable automatic classification systems are crucial for reducing human mortality. Since saving the radiologist's time and achieving a tested accuracy is a priority, automated tumor detection systems are being developed. We propose the use of the CNN machine learning method in this study to identify brain tumors.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Automatic flaw detection, Medical images, MRI, CNN

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The development of neuroscience and subsequent investigation of neurobiological approach to music revealed that music is a brain function. It is processed in different parts of the brain and activates brain's structural and functional aspects. Music influences neurochemicals that are responsible for regulating emotional, physiological, psychological and cognitive functions. With the neurobiological study, which is evidence based and empirical has made a strong base for music therapy to be scientifically use for treatment by professional and in clinical setup. The current study reviews available literature to examine that music's neurobiological processing in the brain is responsible for stimulating the brain and therefore use music as an alternative therapeutic tool

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Music, Brain, Neuroscience, Cognition, Music therapy

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Creative Commons Attribution 4.0 and The Open Definition