The purpose of this study is to focus on the indicators related to motivation in the Work Mind, and to organize the concepts by Pile Sort experiments using the sentences of the question items that compose each indicat...
详细信息
This research develops an intelligent automatic production loading and unloading solution for a multi-process part. According to the posture required for each processing operation of each part, a novel gripper and car...
This research develops an intelligent automatic production loading and unloading solution for a multi-process part. According to the posture required for each processing operation of each part, a novel gripper and carrier that can implement multi-position clamping are designed. The Beckhoff controller is adopted as the host controller in the control system to integrate the robotic arm (including the vision system), the automated guided vehicle (AGV), and the computer numerical control (CNC) machine. The main topic of this research is to meet the requirements of automatic loading and unloading in the processing of the entire production line. It will significantly reduce the workforce consumption of the processing production line and avoid human error, thereby improving processing reproducibility and product production stability.
Automatic Identification System (AIS) data contains static and dynamic information for identification, tracking, and collision avoidance of vessels, as well as management of maritime activities. In the utilization of ...
详细信息
ISBN:
(纸本)9798350345728
Automatic Identification System (AIS) data contains static and dynamic information for identification, tracking, and collision avoidance of vessels, as well as management of maritime activities. In the utilization of AIS data, a data pipeline framework is needed which includes the process of capturing messages, translating messages, detecting data corruption, cleaning damaged data, reconstructing trajectories, visualizing data, and storing data for analysis needs. Usually, the analysis and storage of AIS data are done offline which makes it not conducive to understanding vessel dynamics. In addition, large AIS data contains incomplete and noisy information that affects the quality of the trajectory. In this context, this article has proposed an AIS data pipeline framework in the form of pre-processing and real-time trajectory reconstruction. Pre-processing is intended to eliminate data anomalies caused by transmission errors. While the trajectory reconstruction process to overcome missing values due to noise is based on the Cubic Spline interpolation technique. All processes in the data pipeline framework are streamed using Apache Kafka. The simulation results show that the proposed AIS data pipelines framework has succeeded in visualizing the data flow in the form of a map application and trajectory reconstruction in real-time.
This study investigates the impact of feature selection results using the filter method on the performance of predictive models for the nutritional status of children aged 0-23 months. This study aimed to understand h...
详细信息
ISBN:
(数字)9798331517601
ISBN:
(纸本)9798331517618
This study investigates the impact of feature selection results using the filter method on the performance of predictive models for the nutritional status of children aged 0-23 months. This study aimed to understand how correlation-based feature selection methods affect the efficiency and accuracy of predictive models. The dataset comes from the Basic Health Research survey, which consists of 84 variables and around 130,000 data, including anthropometric, family, socioeconomic, and environmental information. In this study, various filter-based feature selection methods were applied to evaluate and identify features that have significant relationships with children’s nutritional status, both linearly and non-linearly. The mutual information method was used to identify complex relationships between features and target variables, while the Pearson Correlation Coefficient and information gain were used to assess the relevance of numerical and categorical features. Of the 84 variables in the dataset, 37 features were selected after the selection process. The model performance evaluation was carried out using the Random Forest (RF) and Gradient Boosting (GB) algorithms, by comparing the results between the dataset that had been selected and without feature selection. The RF model without feature selection produces accuracy: 0,84600, precision: 0,83958, recall: 0,84600, F1-score: 0,78962, and a computation time of 9 seconds. The GB model without feature selection produces accuracy: 0,86330, precision: 0,84722, recall: 0,86330, F1-score: 0,84925, and a computation time of 2 minutes 50 seconds. After feature selection and cross-validation, the RF model shows accuracy: 0,85701, precision: 0,83599, recall: 0,85701, and F1 score: 0,83484. The GB model shows accuracy at 0,86124, precision at 0,84226, recall at 0,86130, and F1 score at 0,84120.
Stemming, an essential procedure in natural language processing (NLP), diminishes words to their base forms, facilitating tasks such as information retrieval and sentiment analysis. Although stemming techniques for hi...
详细信息
ISBN:
(数字)9798331513320
ISBN:
(纸本)9798331513337
Stemming, an essential procedure in natural language processing (NLP), diminishes words to their base forms, facilitating tasks such as information retrieval and sentiment analysis. Although stemming techniques for highresource languages are well-developed, numerous low-resource languages, including dialect of Tulang Bawang, suffer from inadequate solutions owing to a scarcity of linguistic data and resources. Existing systems, including rule-based stemmers, have demonstrated efficacy in processing low-resource languages such as Indonesian and Javanese by utilizing established morphological rules. Nonetheless, these methods encounter considerable obstacles, such as restricted adaptability, inability to accommodate unusual root structures, and excessive dependence on fixed rules that might result in over- or understemming. Rule-based methodologies frequently misidentify roots when faced with intricate affixes or unconventional word forms. We introduce an improved rule-based Tulang Bawang Stemmer aimed at overcoming these constraints by enhancing current linguistic rules and integrating new patterns specific to the language's morphology. Assessed on 500 test samples and 200 independent test samples, our improved stemmer attained gold standard evaluation metrics of 96.2% and 94%, respectively, surpassing prior implementations in both precision and generalization. The findings demonstrate the potential of enhanced rule-based techniques to improving NLP for lowresource languages. Improved stemming performance enables better downstream applications, promotes more efficient text analysis, and advances research in underrepresented languages.
This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models d...
详细信息
ISBN:
(数字)9798350389302
ISBN:
(纸本)9798350389319
This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98
%
), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67
%
), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36
%
) and lowest (59
%
). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG.
作者：
Daim, Tugrul UTechnology Management Doctoral Program
Department of Engineering and Technology Management Maseeh College of Engineering and Computer Science Portland State University PortlandOR United States
As the world has struggled against a virus, technology enabled our survival in many dimensions. In many cases adoptions of technologies which would have lasted years happened in weeks if not days. For example, remote ...
As the world has struggled against a virus, technology enabled our survival in many dimensions. In many cases adoptions of technologies which would have lasted years happened in weeks if not days. For example, remote health care adoption was accelerated immensely to deal with the challenged health system. We are about to see similar technological innovations ramp up the hard hit economies through many different sectors. As always said, challenges create opportunities. Our field of engineering and Technology Management is growing. IEEE Technology and engineering Management Society (TEMS) just finished the first virtual conference: TEMSCON 2020. As a part of it we held an editors’ panel. Holding the conference on line enabled many editors of the leading journals in the field attend the event.
Ontology is an organization of knowledge that can represent knowledge in a structured manner. An ontology-based Knowledge Management System is a system that combines elements of knowledge management with the applicati...
Ontology is an organization of knowledge that can represent knowledge in a structured manner. An ontology-based Knowledge Management System is a system that combines elements of knowledge management with the application of ontology as a knowledge base. Meanwhile, knowledge is dynamic and continues to develop all the time, giving rise to new knowledge. Therefore, the ontology must be updated regularly through ontology enrichment to meet adequate knowledge requirements. Ontology enrichment is carried out to ensure that the ontology remains relevant and responsive to developments in its knowledge domain. However, there are no standard stages in implementing enrichment in ontology-based Knowledge Management systems. Therefore, this research conducted a literature review to determine when and how to apply enrichment in ontology development. Data was obtained from related journals in 2018 - 2023. The method used in this research is the Systematic Literature Review method to systematically identify, review, evaluate, and interpret all available research in the area of interest with specific relevant research questions. The research results show that the ontology enrichment procedure generally includes preprocessing stages, relation extraction, and enrichment processes. Ontology enrichment is generally applied during the development of a new ontology as part of the ontology development cycle and on existing ontologies, which are a separate stage from the initial ontology development cycle. Based on these findings, the researcher provides recommendations for researchers who want to use or develop new ontology enrichment methods.
Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce these resources, some researchers propose to implement artificial intelligence technology. This paper aims are to conduct a syste...
详细信息
The decline in physical, cognitive, and sensory functions for most elderly people leads to the development of several health issues such as memory loss, a tendency to fall, dizziness, and reduced ability to care for o...
详细信息
暂无评论