Sentiment analysis plays a crucial role in identifying and interpreting emotions within textual data such as customer feedback, social media posts, and reviews. This study presents a sentiment classification system categorizing text into neutral, negative, and positive sentiments, aiding organizations in understanding public opinion and enhancing decision-making. To ensure accuracy, the system preprocesses data using cleaning algorithms to remove noise and irrelevant elements.The proposed model employs the TextBlob library for sentiment classification, leveraging its built-in predictive capabilities, while the clean-text library optimizes preprocessing by eliminating punctuation, stopwords, and unnecessary spaces, and standardizing text to lowercase. Key metrics such as polarity and subjectivity assess model performance to ensure reliable outcomes.A Streamlit-based interface enables user-friendly interaction, allowing organizations to extract actionable insights from large datasets. This sentiment analysis tool facilitates improved customer satisfaction, product refinement, and data-driven decision-making.
Drying serves as both a preservation method and a processing step for certain products. It is utilized in both rural and industrial settings,particularly within the food processing industry Dryers that operate on fossil fuels consume significant amounts of energy.Given the rising costs of oil in recent years, which are likely to continue increasing, it is essential to develop drying systems that do not rely on traditional energy sources. Solar drying is one such method that harnesses solar radiation as a free and renewable energy source Solar dryers are relatively easy to construct using locally available materials and tools, and they can function through natural or forced convection The drying process requires energy and heat, which depend on various factors, including the relative humidity of the air, the drying temperature, the characteristics of the product (such as thickness, surface area, and air resistance), and the moisture content of the item being dried.Consequently, the performance of the dryer is directly influenced by the level of solar irradiation and the relative humidity in the area where it is used.
This review examines the dynamic intersection of digital dentistry and material science, exploring current trends and advancements shaping modern dental practice. The integration of digital technologies, including intraoral scanners, cone-beam computed tomography (CBCT), and computer-aided design/computer-aided manufacturing (CAD/CAM) systems, has revolutionized diagnostic and restorative workflows. Concurrently, material science innovations, particularly in ceramics, composites, and 3D printing resins, are expanding the possibilities for dental restorations and prostheses. This review analyzes the accuracy, efficiency, and clinical outcomes associated with these technologies and materials, emphasizing the impact on patient care. It further explores the integration of digital workflows, including virtual treatment planning and teledentistry, and discusses the role of emerging technologies like artificial intelligence (AI), VR in future dental applications. By synthesizing current research and clinical evidence, this review provides a comprehensive overview of the evolving landscape of digital dentistry and material science, highlighting the potential for enhanced precision, predictability, and patient satisfaction in dental treatments, while also addressing current limitations and future directions.
The study examined the role of motivation, self-efficacy, and career counseling in the expansion of engineering and metallurgical sciences, with a focus on colonial and post-colonial educational policies in developing nations such as Nigeria, Ghana, Kenya, South Africa, India, and Brazil. The study was conducted in these nations, with three research questions guiding the investigation. The population comprised 948 respondents, including 520 career counselors and 428 psychologists. Due to its manageable size, no sampling was conducted, aligning with Nworgu (2015), who advocated studying the entire group to avoid sampling errors. The Motivation, Self-Efficacy, and Career Counseling in Engineering and Metallurgical Sciences Questionnaire (MSECCEMSQ) was used for data collection. The instrument was validated by two experts in the Department of Educational Foundations and one expert in the Department of Counselling and Human Development Studies, all in the Faculty of Education, University of Nigeria, Nsukka. The reliability index was established at 0.84. Data were analyzed using mean and standard deviation for the research questions. The findings revealed that motivation and self-efficacy significantly influenced students’ interest in engineering and metallurgical sciences. Additionally, career counseling played a crucial role in guiding students toward these fields, particularly in the post-colonial era. The study contributed to knowledge by highlighting the impact of educational policies on student enrollment and retention in engineering and metallurgical sciences. It was recommended that policymakers should integrate structured career counseling programs into the curriculum to enhance student participation in these fields.
In the recent times, low salinity water flooding (LSWF) has been observed as a promising enhanced oil recovery (EOR) technique both in sandstone and carbonate reservoirs. It involves injection of low salinity water which alters the wettability and interfacial properties of the reservoir rock and crude oil, thus leading to improved oil recovery. This paper presents an overview of the current state of knowledge on the mechanisms of LSWF, gained from both experimental studies and field applications. The results obtained from laboratory analysis and field applications of LSWF have been critically reviewed showing a mixed response in sandstone and carbonate reservoirs. However, the efficacy of LSWF is dependent on various factors, like, reservoir properties, injection water composition and operating conditions. In this paper, a review of the various mechanisms like fines mobilization, wettability alteration, pH reversal, multicomponent ion exchange (MIE), mineral dissolution, micro-dispersion formation etc., affecting the improved oil recovery with LSWF in both sandstone and carbonate reservoirs have been highlighted. This review work can be helpful in proper designing of LSWF in view of the operating parameters and its successful implementation, through a better understanding of its mechanisms depending on different reservoir properties.
