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Book Part Citation - Scopus: 7Vibration-Assisted Machining of Aerospace Materials(Springer Nature, 2022) Namlu, R.H.; Sadigh, B.L.Recent technologic advancements, especially in cutting-edge sectors like aerospace industries, call for new materials with superior properties. Like advanced engineering alloys, composites, and superalloys, these new materials provide the required specifications; however, to make use of these materials, they are needed to be formed into a final product. Machining is one of the most used manufacturing processes. Since in this process, the chip removal action occurs with direct contact between the cutting tool and workpiece, therefore, cutting materials with superior mechanical properties become a backbreaking process to be carried out. Along with the desired properties of the new advanced engineering materials in the aerospace industry, superior mechanical properties such as high wear resistance and low thermal conductivity of these materials lead to low machinability and difficulties in producing the desired end products by machining. As traditional machining methods are not efficient enough in machining such materials, new machining techniques have been invented to deal with these problems. Nontraditional machining processes are developed to deal with such obstacles that use chemical, electrochemical, thermal, and mechanical energy sources to facilitate the material removal process, reduce cost, and enhance product quality. However, in some cases, these methods’ low production efficiency forced engineers to combine the advantages of multiple machining methods in one hybrid process and improve the process efficiency by expediting the manufacturing process. One of these hybrid manufacturing methods is vibration-assisted machining. The vibration-assisted machining method aims to improve the material removal process by giving high frequency and low amplitude mechanical energy in vibrations to the workpiece or cutting tool. Vibration-assisted machining methods first emerged in the late 1960s and gained popularity in the early 2000s, and nowadays, research stages have gained momentum and are used even in mass production. Vibration-assisted machining has many benefits over traditional machining processes, like reducing costs, cutting forces, required power, secondary operations, cutting tool wear, and increasing the machined surface quality, tool life, and finally, the process performance. In this chapter, a detailed literature survey on the effects of vibration implementation on the performance of various machining processes, including turning, milling, drilling, and cutting advanced aerospace materials, is systematically summarized and discussed. At the end of this chapter, a case study is provided to understand the topic deeply. The detailed review shows that vibration-assisted machining enhances the cutting process in terms of cutting forces, tool wear, and surface roughness compared to traditional methods. Also, case study outcomes support those findings. Likewise, future studies show that vibration-assisted machining process still needs to be investigated deeply and it is a promising research area. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.Book Part Text Mining and Topic Modeling in Education: Revealing Insights From Educational Textual Data(Springer Nature, 2025) Ekin, C.Ç.; Sabamehr, M.This book chapter explores the transformative potential of text mining and topic modeling in the field of education. With the exponential growth of digital educational content, the need for effective analysis and understanding of large-scale textual data has become crucial. The chapter provides an overview of text mining techniques, covering data preprocessing and information retrieval. It delves into topic modeling algorithm, Latent Dirichlet Allocation (LDA), and its applications in extracting latent themes from educational texts. The chapter highlights the diverse applications of text mining in education, such as analyzing student essays, academic publications, and online discussions. Leveraging sentiment analysis and opinion mining, it enables educators and administrators to gauge learner emotions and attitudes. Ethical considerations, including data privacy and bias, are also discussed, emphasizing the responsible use of text-mining technologies in educational contexts. In conclusion, “Text Mining and Topic Modeling in Education” serves as a valuable resource for educators, researchers, and policymakers, facilitating data-driven decision-making and fostering innovation in education. By empowering stakeholders with powerful analytical tools, this chapter propels education toward evidence-based practices and a more informed, equitable future. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
