Innovation and Emerging Technologies最新文献

{"title":"Using automation and machine learning to maximize tool use in turning centers for better surface finish","authors":"Akash D. Pandya, Ajay M. Patel, B. Hindocha, M. Kumar, Ankit D. Oza, K. Bhole, M. Kumar, Manish Gupta","doi":"10.1142/s2737599423400030","DOIUrl":"https://doi.org/10.1142/s2737599423400030","url":null,"abstract":"In modern manufacturing industries, automated machining systems have become a necessity. However, optimizing resource utilization and achieving a good surface finish remain challenging tasks. Excessive tool usage and poor surface finish are common problems encountered in turning centers, which affect productivity and product quality. In this research, we propose an approach that leverages automation and machine learning techniques to maximize tool use and improve surface finish. Our objective is to investigate the relationship between tool life and surface roughness and to develop a method that can optimize cutting parameters for turning centers. We have conducted an experimental study to evaluate the proposed approach, which involves the automatic determination of cutting parameters based on machine learning algorithms, and concluded a cutting speed of 43.10[Formula: see text]m/min, the surface finish achieved for aluminum material was 1.98[Formula: see text][Formula: see text]m. In the case of mild steel material, the surface finish was 12[Formula: see text][Formula: see text]m at a cutting speed of 25.13[Formula: see text]m/min. Similarly, for cast iron material, the surface finish was 8.45[Formula: see text][Formula: see text]m at a cutting speed of 30.16[Formula: see text]m/min. Our results show that the proposed method outperforms the traditional manual method in terms of surface finish, tool usage, and machining time. Our approach can be applied to other machining systems, providing a practical and effective solution to improve the efficiency and quality of machining processes. This paper presents an experiment that explores the relationship between tool life and surface roughness. Furthermore, an automated approach is proposed for eliminating G code in machining, which can improve the efficiency of machine tools and result in a better surface finish. Objective: To maximize tool use and improve surface finish in turning centers by incorporating automation and machine learning. Idea: This research aims to explore the use of automation and machine learning in turning centers to optimize the cutting parameters and achieve a better surface finish. Description of the idea: The study was conducted by performing experiments on three different materials, i.e., aluminum, mild steel, and cast iron. The cutting parameters, including spindle speed, feed, and depth of cut, were controlled by a programmable logic controller (PLC) integrated with a tachometer and Vernier scale. The surface finish was measured using a surface roughness tester, and the data was analyzed using a supervised machine learning algorithm.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75638492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-directive multiband microstrip patch antenna for biomedical applications, inspired by metamaterial","authors":"P. Arockia Michael Mercy, K. S. Joseph Wilson","doi":"10.1142/s2737599423500044","DOIUrl":"https://doi.org/10.1142/s2737599423500044","url":null,"abstract":"Recent advancements in medical technology impose a limited number of devices for biomedical applications. A variety of techniques are being proposed to improve the performance of novel antenna designs in response to the rapid development of modern wireless technologies. A miniaturised microstrip antenna structure based on metamaterial (MTM) is presented here. The objective of this work is to present a high-directive antenna for wireless systems utilising MTM properties. Directivity is improved by the incorporation of the MTM structure on the ground structure. In order to improve the performance parameters of the antenna for medical applications, this study provides the design and analysis of a multiband patch antenna employing split-ring MTM. The split-ring resonator (SRR) MTM structures are embedded in a unique and novel way in the ground structure of the antenna. So that subwavelength modes get introduced in the patch cavity and a good performance characteristics is obtained. The reference antenna is a rectangular microstrip patch antenna exhibiting a directivity of 1.1823[Formula: see text]dB that resonates at a frequency of 2.32[Formula: see text]GHz. The optimised SRR MTM is positioned in the ground plane of the suggested antenna to increase the directivity of the antenna. This technology covers the frequency range between 2.24 and 3.96[Formula: see text]GHz used for biomedical applications and the ultra-wideband (UWB) range from 4.48 to 9.08[Formula: see text]GHz used for medical applications, industrial and scientific areas. The number of gaps of the rectangular-shaped SRRs is a key component of the enhancement of directivity from 1.1823 to 8.88823[Formula: see text]dB.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135319310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-performance thermosets for additive manufacturing","authors":"Thamires Andrade Lima, Anh Fridman, Jaclyn McLaughlin, Clayton Francis, Anthony Clay, Ganesh Narayanan, Heedong Yoon, Mohanad Idrees, Giuseppe R. Palmese, John La Scala, Nicolas Javier Alvarez","doi":"10.1142/s2737599423300039","DOIUrl":"https://doi.org/10.1142/s2737599423300039","url":null,"abstract":"Additive manufacturing (AM) has come a long way since its initial inception. Previously considered a fast prototyping method, it offers significant benefits for use as a method of producing user-end parts that are limited in quantity, customizable, and/or complicated geometries. For AM to be considered in high-performance applications, such as automotive and aerospace, we must consider AM technology and the available and compatible printing materials. Typically only thermoset plastic resins are capable of meeting high-performance specifications, such as sufficiently high strength, stiffness, and toughness, as well as excellent chemical and environmental resistance. This review presents a broad overview of the available high-performance thermoset chemistries and formulations, i.e., resin blends. The base resin chemistries that are covered are: vinyl, epoxy, imides, cyanate ester, urethanes, benzoxazine, and click chemistries (e.g., Michael addition). Subsequently, more application-relevant blends of these base resins are discussed. Each section focuses on resin details such as reaction mechanisms, typical monomer structure, mechanical properties, and applications specific to AM. The review is organized as follows. We begin with an introduction on the state-of-the-art, the challenges still faced by the field, and a benchmark definition of “high performance.” This is followed by a discussion of the available AM technologies for thermoset printing, with a focus on their advantages and disadvantages. Next, we cover the details of different resin chemistry, followed by their blends. The following section details the difficulties in developing AM technologies that allow for the incorporation of fillers, such as rheological modifiers and reinforcements. The review ends with a perspective on the future of AM technologies that would bridge the gap between pure resin printing and the much needed composite printing for high-performance applications.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modular structural elements incorporating decommissioned flexible flowlines and geopolymer concrete","authors":"F. Aslani, Yifan Zhang, A. Valizadeh, Lendyn Philip","doi":"10.1142/s2737599423300027","DOIUrl":"https://doi.org/10.1142/s2737599423300027","url":null,"abstract":"This study proposes the design of modular structural geopolymer concrete elements incorporating decommissioned flexible flowlines. To evaluate and assess the feasibility of the proposed modular structural elements, this study aims to investigate its feasibility from the perspectives of sustainability including cost analysis, circular economy (CE) analysis and CO2 emission estimate. Moreover, a series of numerical analyses using finite element modelling (FEM) is conducted to provide insight into the mechanical behaviour of such modular columns and beams. Apart from the cost-saving, CE and social impact benefits of the proposed elements, the results indicate that modular structural elements incorporating flowline have shown very high axial, shear and flexural capacities, which make them suitable to be used in high-rising buildings, bridges, etc. The proposed elements can be a solution to decommission and reuse the flexible flowline on a large scale in construction.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88478065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industrial and market opportunities in hybrid additive manufacturing","authors":"Soni Kumari, K. Abhishek, Din Bandhu, Pardeep, B. Sunil, Manish Gupta","doi":"10.1142/s2737599423400029","DOIUrl":"https://doi.org/10.1142/s2737599423400029","url":null,"abstract":"In the realm of manufacturing, the use of hybrid manufacturing has led to high-speed production by combining additive manufacturing (AM) with other digitally driven manufacturing machines. Despite its rapid growth over the past decade, the acceptance of hybrid AM within the industry has been limited due to various constraints. To achieve industrial acceptance, it is necessary to address the challenges and limitations of AM. As an effort to mitigate environmental concerns, manufacturers have recently started to explore integrating additional and secondary production methods into their manufacturing processes. Integrated production solutions have shown promise in overcoming present-day barriers in production systems by utilizing the best available integration technology. In this context, this article focuses on three critical points in the manufacturing sector. First, recent developments in the integration of AM processes have been significant. Second, integrated technical planning has been improved, which is essential for the successful implementation of hybrid manufacturing. Finally, there is a growing need to understand the mixed supplement production industry that combines both traditional and AM techniques. Thus, it is essential to emphasize advances in AM processes, integrated technical planning, and mixed supplement production industry to meet the demands of a rapidly evolving manufacturing sector.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76812120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting compressive strength of geopolymer concrete using machine learning","authors":"Priyank Gupta, N. Gupta, K. Saxena","doi":"10.1142/s2737599423500032","DOIUrl":"https://doi.org/10.1142/s2737599423500032","url":null,"abstract":"The anaconda software required python code in order to run the utilized individual K-nearest neighbor (KNN), random forest regression (RFR), and linear regression (LR) models. The results show that RFR machine learning (ML) technique out of the other utilized models shows the best performance for a used dataset. The findings of this article indicate that the dataset utilized proposed model provides an acceptable algorithm for FACC design and optimization. In the current study of preparation of geopolymer concrete (GPC), relevant variables such as curing, fly ash, calcined clay, added water, super plasticizer, coarse aggregate, quarry stone dust, caustic soda, and water glass were used as input parameters. The ranges, mode, median, standard deviation, and other identifying details were checked using descriptive statistical analysis for the input parameters. The strength due to the compression of FACC GPC was predicted using RFR, LR, and KNN ML techniques, all based on Python coding. The ensemble ML technique, RFR outperformed the individual ML technique, KNN, in terms of prediction. The RFR indicates that the maximum amount of [Formula: see text] is 0.92, and LR provides 0.58, although the KNN was less accurate, with a coefficient of determination of 0.56. The RFR technique’s lower values of errors, mean absolute error (MAE), MSE, and root mean square error (RMSE) yield 1.99, 7.17, and 2.67[Formula: see text]MPa, respectively. The excellent accuracy of the RFR methodology is confirmed by a statistical analysis of errors. Curing temperature, curing hours, molarity of NaOH, and FACC ratio significantly affect the compressive strength (CS) of FACC GPC. The findings indicate that the proposed model provides an acceptable algorithm for FACC design and optimization using RFR among the three combinations of ML methods for a given dataset.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86276045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An overview of image processing for dental diagnosis","authors":"Rahulsinh B. Chauhan, Tejas V. Shah, Deepali H. Shah, Tulsi J. Gohil, Ankit D. Oza, Brijesh Jajal, K. Saxena","doi":"10.1142/s2737599423300015","DOIUrl":"https://doi.org/10.1142/s2737599423300015","url":null,"abstract":"Dental disease evaluation and clinical assessment are frequently accomplished through radiographic penetration. The difficulty of obtaining an accurate clinical diagnosis from radiographs rises due to the minimal mineral density change in demineralized tissue of tooth and gum disorders. Dental abnormalities may not be visible on radiographs until the demineralization is higher than 40%, according to the literature. As a result, a dental practitioner’s judgment can have a big impact on how accurately the radiography penetration depth is determined through visual inspection. To counteract this effect, image processing-based clinical diagnosis methods have become widely adopted, transforming dentistry from traditional to advance in recent years. The efforts made in the area of image processing-based digital dental diagnosis of the most challenging dental issues are outlined in the presented comprehensive literature evaluation, which also identifies any research gaps in the scope of work already done. The included studies’ quality was evaluated using Quality Assessment and Diagnostic Accuracy Tool-2 (QUADAS-2). A total of 52 out of 178 articles, published from 2012 to February 2023, were reviewed and data like image-processing approach, the size of datasets, approach results, advantages and disadvantages, name(s) of diagnosed diseases, imaging type, author, and publication year were extracted. Results show that, in 52 studies, more than 14 image-processing approaches were used on different types of radiographs for the diagnosis of a single or more than one disease by a single approach with an accuracy range from 64% to 93%. Most studies have used artificial intelligence (AI) for computer-aided diagnosis and used dental experts to label their dataset and validate the outcome of proposed methods. Efforts done by different research groups for image processing-based digital diagnosis are appreciable but still, they are lagging to meet clinically expected accuracy. There looks to be a great requirement for the development or standardization of existing methodology and it is also needed to construct standard public dental datasets to attract a greater number of research groups in the dental field.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83523939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A robust, flow-based, microfluidic device for siRNA-mediated gene knockdown in glioblastoma spheroids","authors":"Ines Hosni, Alex Iles, John Greenman, Mark A. Wade","doi":"10.1142/s2737599423400054","DOIUrl":"https://doi.org/10.1142/s2737599423400054","url":null,"abstract":"Glioblastoma (GBM) is a deadly disease with a poor prognosis, there is therefore a crucial need for novel therapeutic targets. Current preclinical models of GBM fail to predict clinical outcomes, thus, new translationally relevant models are urgently needed for reliable therapeutic target validation. 3D spheroid culture of cancer cells has been shown to better reflect tumour biology than 2D monolayer culture, as has culturing cells in flow-based microfluidic devices, which mimic key aspects of the tumour microenvironment. Gene knockdown by siRNA is a key preclinical target validation tool, however, siRNA-mediated knockdown of cancer spheroids in microfluidic culture has not yet been demonstrated. Here we describe a simple and robust microfluidic device that can maintain GBM spheroids (U87 cells) for at least 7 days. Via RNA sequencing analysis, we demonstrate that spheroids grown in microfluidic culture are more proliferative than spheroids grown in static plate culture and downregulate genes associated with cell adhesion, potentially offering insights into the metastatic process. Comparison of target gene (PRMT2 and RAB21) knockdown using siRNA between 2D monolayer cultured cells, static spheroid culture and spheroids maintained in the microfluidic device showed that gene expression (as measured by quantitative-PCR) was significantly reduced in all culture systems. Knockdown was most efficient in cells grown in 2D monolayer culture followed by static spheroid culture, but we also demonstrate [Formula: see text] knockdown efficiency using the microfluidic device. In summary, this study describes an easy-to-use microfluidic culture platform and provides evidence that pre-clinical siRNA-mediated target validation studies will be possible in flow systems that mimic tumour physiology.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135319309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward negative capacitance electronics","authors":"M. Hoffmann","doi":"10.1142/s2737599422400023","DOIUrl":"https://doi.org/10.1142/s2737599422400023","url":null,"abstract":"Progress in electronics is limited by power dissipation constraints. Ferroelectric materials with a negative capacitance could help to overcome these limits. Especially, HfO2 and ZrO2 based ferroelectrics are promising for negative capacitance electronics due to their compatibility with modern transistor manufacturing processes. Recently, first negative capacitance transistors have been demonstrated. However, further investigations on the microscopic origin of negative capacitance in HfO2- and ZrO2-based ferroelectrics are needed. Lastly, opportunities for negative capacitance beyond transistors are discussed.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77744259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging transportation innovations: Promises and pitfalls","authors":"S. Labi, K. Sinha","doi":"10.1142/s2737599422400011","DOIUrl":"https://doi.org/10.1142/s2737599422400011","url":null,"abstract":"Rapid growth in information and communication technologies has spawned a number of major innovations in transportation area, including automation and connectivity. At the same time, the advancement in battery technology has accelerated the electrification of transportation vehicle propulsion. This paper, focusing on highway-oriented surface transportation, examines the current development of these innovations, along with their synergies, benefits, pitfalls, trends, possible barriers to deployment, and wider impacts.","PeriodicalId":29682,"journal":{"name":"Innovation and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88778585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}