In a world where Industry 4.0 is the order of the day, businesses endeavour to find ways to harness technology through innovation or duplication of solutions that have been successfully implemented elsewhere. For some...
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Nowadays, the Internet of things (IoT) is an emerging technology to interconnect the physical things for providing the best services in hands. IoT has different applications in many areas viz., Smart Health, Smart Tra...
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3D human pose estimation is an important premise for human behavior analysis and understanding, which has a wide range of applications in intelligent transportation, human-computer interaction, and animation productio...
3D human pose estimation is an important premise for human behavior analysis and understanding, which has a wide range of applications in intelligent transportation, human-computer interaction, and animation production. Most existing works focus on extracting the feature relationship between frames by combining spatio-temporal information to reduce the error of attitude reconstruction. However, the majority of them often suffer from insufficient joint correlation characteristics. To address this problem, we propose a Graph Expand Spatiotemporal Convolutional Network, named GESC-Net, to improve the limitation of extracting human spatial structure features. To better enrich the feature of extracting local information, we develop a learnable symmetric connection (LSC) block in the spatial structure. Moreover, a CbAttantion block is also designed to obtain a larger view of the acquisition of global structure and get more effective features. We evaluate our approach on two standard benchmark datasets: Human3.6M and HumanEva-I. the quantitative and qualitative evaluation results demonstrate that the GESC-Net can achieve better 3D human posture estimation than existing state-of-the-art methods.
the insurance industry faces a significant challenge concerning insurance claims, particularly due to the prevalence of fraudulent insurance claims. To address this issue, one potential solution is the implementation ...
the insurance industry faces a significant challenge concerning insurance claims, particularly due to the prevalence of fraudulent insurance claims. To address this issue, one potential solution is the implementation of a computer-based decision model. this research presents a fuzzy decision model based on object-oriented method development. the study involves seven stages (i.e. case analyzing, parameter analyzing, objects-parameters linking, detail object relation constructing, parameter exchange analyzing, OOFDM constructing, and model verifying and validating), with an object-oriented approach serving as the foundational method for constructing the model, and fuzzy logic as the primary method for assessing claim risks in proposing the best decision. the model has the capability to simulate insurance claims and offers objective decisions based on 19,611 claims data, categorizing them into two decision categories: acceptance and pending.
the proceedings contain 161 papers. the special focus in this conference is on Signal and Information Processing, Network and computers. the topics include: design of Campus Employment Information Service System Based...
ISBN:
(纸本)9789811947742
the proceedings contain 161 papers. the special focus in this conference is on Signal and Information Processing, Network and computers. the topics include: design of Campus Employment Information Service System Based on Service design Concept;investigation and Analysis of Library Information Service Based on Information Technology;Data Analysis of Village Cultural Knowledge Map Based on VR Virtual Technology;research on Sports Teaching App Based on Internet Statistical Data Analysis;based on the Intelligent Statistical Software Stata15.0 to Study the Impact of Executive Compensation Incentives and Managerial Capabilities on Business Performance in Artificial Intelligence Companies;research on the Transformation Carrier of Scientific Research Achievements in Colleges and Universities Based on computer Technology;analysis on the Application of Big Data Technology in the Curriculum System of Aesthetic Education in Universities;using Digital Technology to Analyze the Degree of Polymerization of Tooth Preparation;using computer Data Analysis Technology to Analyze the Credit Decision-Making Problem of Small and Micro Enterprises with Grey Correlation;application of Artificial Intelligence for Space-Air-Ground-Sea Integrated Network;international Political Economy Analysis of Free Trade Area Construction Under the Background of Big Data;informatization Reform of Market Research Courses in Undergraduate Colleges Based on Informatization Teaching Platform;interactive Training of School Enterprise Cooperation of Hotel Management Major in Higher Vocational Colleges Under the Background of Information Age;intelligent Innovation Management Measures of Rural Agricultural Economy from the Perspective of Information Technology;construction and Research of 4E Performance Evaluation Model of Public Rental Housing Based on Decision-Making Support System;preface.
A resting-state EEG-based computer-aided diagnosis (CAD) system could complement the traditional diagnostic error for post-traumatic stress disorder (PTSD) patients. the aim of this study is to develop an EEG-based CA...
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ISBN:
(纸本)9781728184852
A resting-state EEG-based computer-aided diagnosis (CAD) system could complement the traditional diagnostic error for post-traumatic stress disorder (PTSD) patients. the aim of this study is to develop an EEG-based CAD system for diagnosis of PTSD patients. To this end, eyes-closed resting-state EEG data were recorded from 77 PTSD patients and 58 healthy controls. Two different types of functional connectivity-based features were extracted, i.e., phase locking values (PLVs) and network indices (strength, clustering coefficient, and path length), for both sensor- and source-level. the classification performances of each feature set were evaluated using a support vector machine with leave-one out cross-validation. the best classification performance was achieved when using source-level PLVs (accuracy - 70.37% and area under curve (AUC) - 0.85). In our future studies, we will attempt to enhance the performance of our proposed CAD system by using deep-learning algorithms.
In the healthcare systems, usage of advanced integrated technologies like Internet of things (IoT) and Machine learning (ML) techniques were limited. Different amalgams of IoT devices and ML mechanisms are available f...
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ISBN:
(纸本)9789380544441
In the healthcare systems, usage of advanced integrated technologies like Internet of things (IoT) and Machine learning (ML) techniques were limited. Different amalgams of IoT devices and ML mechanisms are available for medical sector but are limited to certain domains only. these models either provide patients current state data or specific domain analyzing and surveillance pre/post treatment data like heart or brain functions with corresponding medical aid. Also data available is used as clinical study for medical professionals and for better understandings of patients about their state. Specific domain gadgets' like wrist bands or smart bands uses some sensors about vital, temperature and pulse etc., checkups are available but they were not meant for diagnosing or for treatments. In this paper, we proposed an integrated model to use IoT and ML algorithms for a healthcare system. Tracking of patients' status can be done using some sensors such as lightweight, portable, and low-powered sensor nodes. these Sensors sense the patient's status and send the parametric data to the central controller, to take actions during the critical condition of the patients. the data sent to the controller always provided in secure and encryption form. At the same time, patient data is sent to doctors, so that they can provide the instructions to the caretakers of the patients with quick and proper solutions in real-time. For disease prediction, our model uses supervised machine learning algorithms, In order to get the efficient feature set and improve the better accuracy, and pre-processing techniques to eliminate features that are irrelevant, missing values and outliers from biomedical data which aids in better disease prediction. To further strengthen the proposed integrated model design is compared with various traditional classification algorithms to specify its improved accuracy and computational time for accurate prediction of the patient's disease and acts as a decision suppo
JIBAS computer Based Exam is a mobile-based exam application created by Yayasan Indonesia Baca. this study analyzes and evaluates the User Experience (UX) in JIBAS computer Based Exam (CBE) application. Usability test...
JIBAS computer Based Exam is a mobile-based exam application created by Yayasan Indonesia Baca. this study analyzes and evaluates the User Experience (UX) in JIBAS computer Based Exam (CBE) application. Usability testing and System Usability Scale (SUS) methods have been used to obtain the results. this application has 1,5 of 5,0 ratings on Google Play Store. the study participants were students who used the application. through observations and SUS questionnaires, qualitative and quantitative data were collected and analyzed. the result identify the app’s strengths and weaknesses, and provide suggestions for improvements to improve the user experience. the average SUS is 65.9, a low level of satisfaction withthe usability of the application. this study contributes to the development of JIBAS CBE by considering UX and system usability and can be used as a guideline for the improvement of these applications and usability testing of other computer-based applications.
Automatically generating realistic and natural high resolution images from text descriptions is a complicated problem in the cross-modal research field. Recently, multi-stage conditional generative adversarial network...
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Within our project E-BRAiN (Evidence-Based Robotic Assistance in Neurorehabilitation) we have been developing software for training tasks for patients after stroke. It is the idea of the project that a humanoid robot ...
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ISBN:
(纸本)9783031147852;9783031147845
Within our project E-BRAiN (Evidence-Based Robotic Assistance in Neurorehabilitation) we have been developing software for training tasks for patients after stroke. It is the idea of the project that a humanoid robot is instructing and observing the performance of patients. the paper discusses the challenges of developing such interactive system with an interdisciplinary development team. Goals and rules are different for clinicians, psychologists, sociologists and computer scientists. there are different traditions in those sciences. therefore, evaluations with patients have to be planned much more carefully than with traditional users of interactive systems. the role of task models, storyboards and prototypes in the domain of neurohabilitation are discussed in connection with an experience report of the E-BRAiN project.
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