This paper presents a literature review exploring the potential of piezoelectric field-effect transistors(piezo-FETs)as bionic microelectromechanical systems(MEMS).First,piezo-FETs are introduced as bionic counterpart...
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This paper presents a literature review exploring the potential of piezoelectric field-effect transistors(piezo-FETs)as bionic microelectromechanical systems(MEMS).First,piezo-FETs are introduced as bionic counterparts to natural mechanoreceptors,highlighting their classic configuration and working ***,this paper summarizes the existing research on piezo-FETs as sensors for pressure,inertial,and acoustic *** selections,design characteristics,and key performance metrics are reviewed to demonstrate the advantage of piezo-FETs over traditional piezoelectric *** identifying the limitations in these existing studies,this paper proposes using bionic piezoelectric coupling structures in piezo-FETs to further enhance the sensing capabilities of these artificial *** validated manufacturing methods for the newly proposed piezo-FET structures are also reviewed,pointing out a novel,feasible,and impactful research direction on these bionic piezoelectric MEMS sensors.
Our comprehensive application provides a versatile solution for managing attendance, events, and on-duty assignments within college administrative operations. Developed meticulously, our application comprises three co...
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Workforce attrition is a significant challenge faced by educational institutions, particularly in the context of college faculty members. In this implementation paper, we propose a novel approach for envisaging and re...
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ISBN:
(纸本)9798350394474
Workforce attrition is a significant challenge faced by educational institutions, particularly in the context of college faculty members. In this implementation paper, we propose a novel approach for envisaging and retaining college workforce attrition using machine learning and ensemble learning *** primary objective of this study is to develop a predictive model that can accurately forecast the likelihood of faculty attrition based on various factors such as salary, job satisfaction, environment satisfaction, and institutional characteristics. By understanding the underlying patterns and drivers of attrition, educational institutions can proactively implement strategies to mitigate attrition rates and improve workforce *** achieve this objective, we employ a combination of machine learning algorithms, including logistic regression, decision tree, SVM, random forest, XGBoost and AdaBoost, as part of an ensemble learning framework. We leverage a dataset collected from our college, encompassing information related to faculty members, their attributes, and historical attrition *** rigorous experimentation and evaluation, our results demonstrate the effectiveness of the proposed approach in accurately predicting faculty attrition with a high degree of precision and recall. Moreover, we identify the key factors that contribute significantly to attrition, enabling institutions to target specific areas for intervention and retention *** implications of this research are twofold. Firstly, it provides educational institutions with a valuable tool for early identification of faculty members who are at a higher risk of attrition, allowing proactive measures to be taken to retain them. Secondly, it contributes to the existing body of knowledge by showcasing the efficacy of ensemble learning techniques in addressing workforce attrition ***, this implementation paper offers a practical and data-driven solution for tackling c
Elastic, on-demand, and completely managed computer system resources and services are some of the highly alluring aspects of cloud computing. Several challenges include not being able to access data entering or leavin...
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The global appeal of football is fueled by its exhilarating dynamic and unpredictable nature. Football match prediction is still a challenging issue due to its growing interest. The accurate prediction of football mat...
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In recent times, CNNs, or convolutional neural networks have become pivotal in revolutionizing agriculture technology. Early-stage classification, analysis, and detection of leaf diseases, coupled with proactive solut...
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作者：
Solainayagi, P.
Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India
Accurate diagnosis and treatment for patients depend on highly developed prediction models, which are becoming more important in the field of biological signal categorization among healthcare professionals. This resea...
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One of the most ubiquitous examples of modern mechanism is the computer. In order to effectively interact with a computer, it is necessary to choose the most appropriate method. Color information plays a major role in...
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In task offloading,the movement of vehicles causes the switching of connected RSUs and servers,which may lead to task offloading failure or high service *** this paper,we analyze the impact of vehicle movements on tas...
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In task offloading,the movement of vehicles causes the switching of connected RSUs and servers,which may lead to task offloading failure or high service *** this paper,we analyze the impact of vehicle movements on task offloading and reveal that data preparation time for task execution can be minimized via forward-looking ***,a Bi-LSTM-based model is proposed to predict the trajectories of *** service area is divided into several equal-sized *** the actual position of the vehicle and the predicted position by the model belong to the same grid,the prediction is considered correct,thereby reducing the difficulty of vehicle trajectory ***,we propose a scheduling strategy for delay optimization based on the vehicle trajectory *** the inevitable prediction error,we take some edge servers around the predicted area as candidate execution servers and the data required for task execution are backed up to these candidate servers,thereby reducing the impact of prediction deviations on task offloading and converting the modest increase of resource overheads into delay reduction in task *** results show that,compared with other classical schemes,the proposed strategy has lower average task offloading delays.
Banks make the majority of their income from loans. A lot of individuals apply for loans, and it is difficult to choose the real candidate who will repay the loan. A lot of misunderstandings may occur when selecting t...
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