Applied System Innovation最新文献

Exploring the Intersection of Ergonomics, Design Thinking, and AI/ML in Design Innovation 探索设计创新中人体工程学、设计思维和人工智能/ML 的交叉点

IF 3.8

Applied System Innovation Pub Date : 2024-07-26 DOI: 10.3390/asi7040065

Celina P. Leão, Vinícius Silva, Susana Costa

{"title":"Exploring the Intersection of Ergonomics, Design Thinking, and AI/ML in Design Innovation","authors":"Celina P. Leão, Vinícius Silva, Susana Costa","doi":"10.3390/asi7040065","DOIUrl":"https://doi.org/10.3390/asi7040065","url":null,"abstract":"This paper conducts a systematic literature review to explore the dynamic interplay among ergonomics, design thinking, and artificial intelligence (AI) or machine learning (ML). In a rapidly evolving world, the convergence of ergonomics and design Innovation plays a critical role in creating products and spaces valued for their comfort, usability, and aesthetics. Using Elicit, academic papers are identified to elucidate the relationships among these disciplines. The team reviews and selects relevant papers, employing a large language model (LLM)-enabled platform to extract key points. The analysis emphasizes the pivotal roles of ergonomics and design thinking in integrating AI and ML into product design. It underscores the enduring significance of considering user experiences and aesthetics within the AI/ML framework. The findings reveal that while AI/ML techniques enhance precision and innovation in design, integrating ergonomic principles ensures user comfort and safety. The study highlights the necessity for interdisciplinary collaboration and methodological diversity to fully harness the potential of AI and ergonomic design. Limitations include the reliance on contemporary web crawlers and the varying quality of available literature, potentially affecting the comprehensiveness of the review. Future research should focus on developing more robust search methodologies, expanding the scope of studies, and conducting longitudinal research to examine long-term impacts. Ethical implications of AI/ML in design should also be explored to ensure responsible and sustainable use of these technologies. Overall, this research contributes to a nuanced understanding of the roles played by ergonomics and design thinking in synergy with AI/ML for product design, highlighting their impact on shaping user experiences and aesthetics. Despite potential limitations, the study underscores these disciplines’ resilience and lasting relevance in the evolving design field.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800179","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}

引用次数: 0

Use of Digital Technology in Integrated Mathematics Education 在数学综合教育中使用数字技术

IF 3.8

Applied System Innovation Pub Date : 2024-07-26 DOI: 10.3390/asi7040066

A. Cirneanu, Cristian-Emil Moldoveanu

{"title":"Use of Digital Technology in Integrated Mathematics Education","authors":"A. Cirneanu, Cristian-Emil Moldoveanu","doi":"10.3390/asi7040066","DOIUrl":"https://doi.org/10.3390/asi7040066","url":null,"abstract":"Digital learning environments create a dynamic and engaging learning and teaching context that promotes a deeper understanding of complex concepts, eases the teaching process and fosters a passion for learning. Moreover, integrating interactive materials into pilot courses can assist teachers in better assessing student learning and adjusting their teaching strategies accordingly. The teachers can also receive valuable insights into students’ strengths and weaknesses, allowing them to provide targeted support and intervention when needed. For students from the defence and security fields, digital learning environments can create realistic simulations and virtual training scenarios that allow students to practise their skills in a controlled and safe environment, develop hands-on experience, and enhance their decision-making abilities without the need for real-world training exercises. In this context, the purpose of this paper is to introduce an approach for solving mathematical problems embedded in technical scenarios within the defence and security fields with the aid of digital technology using different software environments such as Python, Matlab, or SolidWorks. In this way, students can visualise abstract concepts, experiment with different scenarios, and receive instant feedback on their understanding. At the same time, the use of didactic and interactive materials can increase the interest among students and teachers for utilising mathematical models and digital technologies in the educational process. This paper also helps to reinforce key concepts and enhance problem-solving skills, sparking curiosity and creativity, and encouraging active participation and collaboration. Throughout the development of this proposal, based on survey analysis, good practices are presented, and advice for improvement is collected while having a wide range of users giving feedback, and participating in discussions and testing (pilot) short-term learning/teaching/training activities.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798865","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}

引用次数: 0

An Image-Retrieval Method Based on Cross-Hardware Platform Features 基于跨硬件平台特征的图像检索方法

IF 3.8

Applied System Innovation Pub Date : 2024-07-23 DOI: 10.3390/asi7040064

Jun Yin, Fei Wu, Hao Su

{"title":"An Image-Retrieval Method Based on Cross-Hardware Platform Features","authors":"Jun Yin, Fei Wu, Hao Su","doi":"10.3390/asi7040064","DOIUrl":"https://doi.org/10.3390/asi7040064","url":null,"abstract":"Artificial intelligence (AI) models have already achieved great success in fields such as computer vision and natural language processing. However, deploying AI models based on heterogeneous hardware is difficult to ensure accuracy consistency, especially for precision sensitive feature-based image retrieval. In this article, we realize an image-retrieval method based on cross-hardware platform features, aiming to prove that the features of heterogeneous hardware platforms can be mixed, in which the Huawei Atlas 300V and NVIDIA TeslaT4 are used for experiments. First, we compared the decoding differences of heterogeneous hardware, and used CPU software decoding to help hardware decoding improve the decoding success rate. Then, we compared the difference between the Atlas 300V and TeslaT4 chip architectures and tested the differences between the two platform features by calculating feature similarity. In addition, the scaling mode in the pre-processing process was also compared to further analyze the factors affecting feature consistency. Next, the consistency of capture and correlation based on video structure were verified. Finally, the experimental results reveal that the feature results from the TeslaT4 and Atlas 300V can be mixed for image retrieval based on cross-hardware platform features. Consequently, cross-platform image retrieval with low error is realized. Specifically, compared with the Atlas 300V hard and CPU soft decoding, the TeslaT4 hard decoded more than 99% of the image with a decoding pixel maximum difference of +1/−1. From the average of feature similarity, the feature similarity between the Atlas 300V and TeslaT4 exceeds 99%. The difference between the TeslaT4 and Atlas 300V in recall and mAP in feature retrieval is less than 0.1%.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813959","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}

引用次数: 0

Buzzing through Data: Advancing Bee Species Identification with Machine Learning 通过数据嗡嗡作响：利用机器学习推进蜜蜂物种鉴定

IF 3.8

Applied System Innovation Pub Date : 2024-07-22 DOI: 10.3390/asi7040062

A. Ratnayake, H. Yasin, Abdul Ghani Naim, Pg Emeroylariffion Abas

{"title":"Buzzing through Data: Advancing Bee Species Identification with Machine Learning","authors":"A. Ratnayake, H. Yasin, Abdul Ghani Naim, Pg Emeroylariffion Abas","doi":"10.3390/asi7040062","DOIUrl":"https://doi.org/10.3390/asi7040062","url":null,"abstract":"Given the vast diversity of bee species and the limited availability of taxonomy experts, bee species identification has become increasingly important, especially with the rise of apiculture practice. This review systematically explores the application of machine learning (ML) techniques in bee species determination, shedding light on the transformative potential of ML in entomology. Conducting a keyword-based search in the Scopus and Web of Science databases with manual screening resulted in 26 relevant publications. Focusing on shallow and deep learning studies, our analysis reveals a significant inclination towards deep learning, particularly post-2020, underscoring its ability to handle complex, high-dimensional data for accurate species identification. Most studies have utilized images of stationary bees for the determination task, despite the high computational demands from image processing, with fewer studies utilizing the sound and movement of the bees. This emerging field faces challenges in terms of dataset scarcity with limited geographical coverage. Additionally, research predominantly focuses on honeybees, with stingless bees receiving less attention, despite their economic potential. This review encapsulates the state of ML applications in bee species determination. It also emphasizes the growing research interest and technological advancements, aiming to inspire future explorations that bridge the gap between computational science and biodiversity conservation.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814956","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}

引用次数: 0

Examining Hybrid Nanofluid Flow Dynamics in the Conical Gap between a Rotating Disk and Cone Surface: An Artificial Neural Network Approach 研究旋转盘与锥面之间锥形间隙中的混合纳米流体流动动力学：人工神经网络方法

IF 3.8

Applied System Innovation Pub Date : 2024-07-22 DOI: 10.3390/asi7040063

Julien Moussa H. Barakat, Z. Al Barakeh, Raymond Ghandour

{"title":"Examining Hybrid Nanofluid Flow Dynamics in the Conical Gap between a Rotating Disk and Cone Surface: An Artificial Neural Network Approach","authors":"Julien Moussa H. Barakat, Z. Al Barakeh, Raymond Ghandour","doi":"10.3390/asi7040063","DOIUrl":"https://doi.org/10.3390/asi7040063","url":null,"abstract":"To comprehend the thermal regulation within the conical gap between a disk and a cone (TRHNF-DC) for hybrid nanofluid flow, this research introduces a novel application of computationally intelligent heuristics utilizing backpropagated Levenberg–Marquardt neural networks (LM-NNs). A unique hybrid nanoliquid comprising aluminum oxide, Al2O3, nanoparticles and copper, Cu, nanoparticles is specifically addressed. Through the application of similarity transformations, the mathematical model formulated in terms of partial differential equations (PDEs) is converted into ordinary differential equations (ODEs). The BVP4C method is employed to generate a dataset encompassing various TRHNF-DC scenarios by varying magnetic parameters and nanoparticles. Subsequently, the intelligent LM-NN solver is trained, tested, and validated to ascertain the TRHNF-DC solution under diverse conditions. The accuracy of the LM-NN approach in solving the TRHNF-DC model is verified through different analyses, demonstrating a high level of accuracy, with discrepancies ranging from 10−10 to 10−8 when compared with standard solutions. The efficacy of the framework is further underscored by the close agreement of recommended outcomes with reference solutions, thereby validating its integrity.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814396","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}

引用次数: 0

A Novel Intelligent Condition Monitoring Framework of Essential Service Water Pumps 基本服务水泵的新型智能状态监测框架

IF 3.8

Applied System Innovation Pub Date : 2024-07-19 DOI: 10.3390/asi7040061

Yingqian Liu, Qian Huang, Huairui Li, Yunpeng Li, Sihan Li, R. Zhu, Qiang Fu

{"title":"A Novel Intelligent Condition Monitoring Framework of Essential Service Water Pumps","authors":"Yingqian Liu, Qian Huang, Huairui Li, Yunpeng Li, Sihan Li, R. Zhu, Qiang Fu","doi":"10.3390/asi7040061","DOIUrl":"https://doi.org/10.3390/asi7040061","url":null,"abstract":"Essential service water pumps are necessary safety devices responsible for discharging waste heat from containments through seawater; their condition monitoring is critical for the safe and stable operation of seaside nuclear power plants. However, it is difficult to directly apply existing intelligent methods to these pumps. Therefore, an intelligent condition monitoring framework is designed, including the parallel implementation of unsupervised anomaly detection and fault diagnosis. A model preselection algorithm based on the highest validation accuracy is proposed for anomaly detection and fault diagnosis model selection among existing models. A novel information integration algorithm is proposed to fuse the output of anomaly detection and fault diagnosis. According to the experimental results of modules, a kernel principal component analysis using mean fusion processing multi-channel data (AKPCA (fusion)) is selected, and a support vector machine using mean fusion processing multi-channel data (SVM (fusion)) is selected. The overall test accuracy and false negative rate of AKPCA (fusion) are 0.83 and 0.144, respectively, and the overall test accuracy and f1-score of SVM (fusion) are 0.966 and 1, respectively. The test results of AKPCA (fusion), SVM (fusion), and the proposed information integration algorithm show that the information integration algorithm successfully avoids a lack of abnormal status information and misdiagnosis. The proposed framework is a meaningful attempt to achieve the intelligent condition monitoring of complex equipment.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821129","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}

引用次数: 0

Towards a Blockchain Hybrid Platform for Gamification of Healthy Habits: Implementation and Usability Validation 实现健康习惯游戏化的区块链混合平台：实施与可用性验证

IF 3.8

Applied System Innovation Pub Date : 2024-07-16 DOI: 10.3390/asi7040060

J. Lopez-Barreiro, Luis M. Álvarez-Sabucedo, José Luís García-Soidán, Juan M. Santos-Gago

{"title":"Towards a Blockchain Hybrid Platform for Gamification of Healthy Habits: Implementation and Usability Validation","authors":"J. Lopez-Barreiro, Luis M. Álvarez-Sabucedo, José Luís García-Soidán, Juan M. Santos-Gago","doi":"10.3390/asi7040060","DOIUrl":"https://doi.org/10.3390/asi7040060","url":null,"abstract":"(1) Background: In developed countries, public health faces a number of problems, including sedentary lifestyles and poor diets, which collectively contribute to the occurrence of preventable diseases. Noncommunicable diseases represent the leading cause of global mortality. Despite the promotion of healthy living, compliance remains a significant challenge. The integration of gamification into health apps has been demonstrated to facilitate behavioral change. Blockchain technology enhances the effectiveness of gamification by providing data trustability and support for auditable incentives. This feature is possible and easy due to the inherent characteristics of blockchain automating processes through Smart Contracts, rewarding participants and creating leaderboards in a transparent and reliable manner. The use of smart contracts and events enhances the traceability and reliability of decentralized applications, including healthcare. Interoperability in blockchain tools facilitates the deployment of complex environments. The aim of this research is the deployment of a tool for the implementation and testing of a gamification platform based on blockchain technology. (2) Methods: Pre-experimental research was carried out to assess the usability of the decentralized application developed. (3) Results: A decentralized application was developed with the objective of gamifying healthy habits. The application was evaluated using the System Usability Scale, obtaining a score of 80.49, and the Cronbach’s Alpha score, which was found to be 0.75. (4) Conclusions: A prototype of a decentralized application connected with a blockchain network to reward challenge fulfilment was deployed. Despite being in early development, it demonstrated high usability. Employing blockchain technology guarantees transparency and traceability while remaining in compliance with legal requirements like the General Data Protection Regulation.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832437","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}

引用次数: 0

A Residual Deep Learning Method for Accurate and Efficient Recognition of Gym Exercise Activities Using Electromyography and IMU Sensors 利用肌电图和 IMU 传感器准确高效识别健身房锻炼活动的残差深度学习方法

IF 3.8

Applied System Innovation Pub Date : 2024-07-02 DOI: 10.3390/asi7040059

S. Mekruksavanich, A. Jitpattanakul

{"title":"A Residual Deep Learning Method for Accurate and Efficient Recognition of Gym Exercise Activities Using Electromyography and IMU Sensors","authors":"S. Mekruksavanich, A. Jitpattanakul","doi":"10.3390/asi7040059","DOIUrl":"https://doi.org/10.3390/asi7040059","url":null,"abstract":"The accurate and efficient recognition of gym workout activities using wearable sensors holds significant implications for assessing fitness levels, tailoring personalized training regimens, and overseeing rehabilitation progress. This study introduces CNN-ResBiGRU, a novel deep learning architecture that amalgamates residual and hybrid methodologies, aiming to precisely categorize gym exercises based on multimodal sensor data. The primary goal of this model is to effectively identify various gym workouts by integrating convolutional neural networks, residual connections, and bidirectional gated recurrent units. Raw electromyography and inertial measurement unit data collected from wearable sensors worn by individuals during strength training and gym sessions serve as inputs for the CNN-ResBiGRU model. Initially, convolutional neural network layers are employed to extract unique features in both temporal and spatial dimensions, capturing localized patterns within the sensor outputs. Subsequently, the extracted features are fed into the ResBiGRU component, leveraging residual connections and bidirectional processing to capture the exercise activities’ long-term temporal dependencies and contextual information. The performance of the proposed model is evaluated using the Myogym dataset, comprising data from 10 participants engaged in 30 distinct gym activities. The model achieves a classification accuracy of 97.29% and an F1-score of 92.68%. Ablation studies confirm the effectiveness of the convolutional neural network and ResBiGRU components. The proposed hybrid model uses wearable multimodal sensor data to accurately and efficiently recognize gym exercise activity.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684378","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}

引用次数: 0

Boosting Engineering Education with Virtual Reality: An Experiment to Enhance Student Knowledge Retention 用虚拟现实技术促进工程教育：提高学生知识保留率的实验

IF 3.8

Applied System Innovation Pub Date : 2024-06-13 DOI: 10.3390/asi7030050

Fernando Elemar Vicente dos Anjos, Adriano de Oliveira Martins, Gislene Salim Rodrigues, M. Sellitto, Debora Oliveira da Silva

{"title":"Boosting Engineering Education with Virtual Reality: An Experiment to Enhance Student Knowledge Retention","authors":"Fernando Elemar Vicente dos Anjos, Adriano de Oliveira Martins, Gislene Salim Rodrigues, M. Sellitto, Debora Oliveira da Silva","doi":"10.3390/asi7030050","DOIUrl":"https://doi.org/10.3390/asi7030050","url":null,"abstract":"This article is about experiments investigating teaching and learning processes and their effects on students. Specifically, the laboratory experiment method aims to determine if using virtual reality in classes leads to better learning outcomes, knowledge retention, satisfaction, engagement, and attractiveness compared to traditional teaching methods. The study found that students who used VR (Experimental Group—EG) had significantly better learning outcomes (with an average of 5.9747) compared to the control group (Control Group—CG), who only had traditional classes (with an average of 4.6229). The study employed a Likert scale from 1 to 7. The difference between EG and CG was 29.2%. Furthermore, the study found that students in the EG had higher knowledge retention, satisfaction, engagement, and attractiveness compared to the CG. All measurements were above 6.4 on the same scale. This study is important because it explores innovative teaching methods and their potential to improve learning outcomes, satisfaction, and efficiency. It also opens up avenues for further research on teaching methodologies for undergraduate students.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141347770","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}

引用次数: 0

Meat Texture Image Classification Using the Haar Wavelet Approach and a Gray-Level Co-Occurrence Matrix 使用哈尔小波方法和灰度共生矩阵进行肉质纹理图像分类

IF 3.8

Applied System Innovation Pub Date : 2024-06-12 DOI: 10.3390/asi7030049

K. Kiswanto, H. Hadiyanto, Eko Sediyono

引用次数: 0