This paper proposes a new multi-agent system to solve very short-term solar forecasting problems. The system organizes the training data into clusters using Part and Select Algorithm. These clusters are used to genera...
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This paper proposes a new multi-agent system to solve very short-term solar forecasting problems. The system organizes the training data into clusters using Part and Select Algorithm. These clusters are used to generate different forecasting models, where each one is performed by a different agent. Finally, another agent is responsible for deciding which model will be applied at each forecasting situation. Results present improvements in forecasting accuracy and training performance if compared to other forecasting methods. A discussion of how to use this architecture for the implementation of a more comprehensive model is also addressed.
The development of Internet of Things (IoT) makes the application of smart homes grow rapidly. It is very popular to install smart appliances in the house. However, building a smart control system at home not only cos...
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The development of Internet of Things (IoT) makes the application of smart homes grow rapidly. It is very popular to install smart appliances in the house. However, building a smart control system at home not only costs a lot but also has many limitations. For this reason, this study proposes a smart homes control system to easily integrate IoT, WSN, smart robot and single-board computer to implement smart home applications. We use wireless technology and automatic equipment to avoid excessive communication cable and to make the house more intelligent to keep in-house movement unimpeded and indoor space tidy and to let appliance adjust appropriate environment settings automatically. This system brings intelligence and convenience to home, making living environment more comfortable.
Data aggregation is an efficient method to save energy and prolong the service life of wireless sensor networks (WSNs). In light of this, a data aggregation algorithm was constructed based on self-organizing feature m...
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Cloud Platforms are heterogeneous, and users may face interoperability issues migrating applications or exchanging data among distinct clouds due, for instance, to the lack of standards solutions. Several solutions ha...
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A multi-scale approach to topology optimization has recently emerged due to its lightweight, robust, and multi-functional characteristics. Considering material diversity, an increasing number of materials leads to a c...
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Stress detection is a growing topic in the field of natural language processing. The study of stress detection for mental health prediction has been proven to benefit the development of recommender systems and automat...
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Stress detection is a growing topic in the field of natural language processing. The study of stress detection for mental health prediction has been proven to benefit the development of recommender systems and automated mental health assessments in previous studies. Additionally, the widespread usage of social media has served as a potential data source for developing such models. Our research tried to detect whether the users of social media were under stress or not. We used a dataset from Dreaddit consisting of posts from one of the popular social media platforms, Reddit. We propose a machine learning model consisting of Support Vector Machine (SVM), Naïve Bayes, Decision Tree, Random Forest, Bag of Words, and Term Frequency – inverse document frequency (TF-IDF) for stress detection. The final evaluation of the model achieved an 80.00% F-1 Score and 75.00% accuracy, and both were scored by SVM.
Context: Problem-Based Learning (PBL) and Experiential Learning Theory (ELT) are convergent active learning approaches widely known for their competent integration between theory and practice. Problem/Objective: Howev...
Context: Problem-Based Learning (PBL) and Experiential Learning Theory (ELT) are convergent active learning approaches widely known for their competent integration between theory and practice. Problem/Objective: However, the usual implementation of PBL leaves out the final active experimentation stage of the experiential learning cycle. In this article, we intend to systematically investigate the impacts of this last stage on the learning outcomes of softwareengineering students. Methods: A quasi-experiment was designed and applied in three softwareengineering courses of an undergraduate course, in Rio Branco-Acre / Brazil. Results: students who participated in two of the three treatment groups scored significantly higher on measures of motivation, experience and learning, which means that the PBL method contains gaps that can be significantly improved with the help of ELT, benefiting the learning outcomes of softwareengineering students.
Since the 21st century,the Internet has been updated and developed at an alarming *** the same time,WeChat applets are constantly improving and introducing new *** an enterprise recruitment system based on WeChat appl...
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Since the 21st century,the Internet has been updated and developed at an alarming *** the same time,WeChat applets are constantly improving and introducing new *** an enterprise recruitment system based on WeChat applets for the majority of job seekers and recruiter users,provide job seekers with easy-to-reach employment opportunities,and provide a convenient and clear screening environment for job *** front-end part of the applet is developed using WeChat developer tools,and the back-end system is developed using *** Spring Boot+Spring MVC framework,implemented in Java *** is managed using MySql *** function of this company’s recruitment applet is similar to the ordinary traditional native recruitment *** achieves basic functions such as job search,job search,collection of jobs,delivery of resumes,viewing of the job search process,recruitment of job information,screening of job resumes,notification of interviews,etc.
Teaching equipment management is an important factor for colleges and universities to improve their teaching level,and its management level directly affects the service life and efficiency of teaching *** in recent ye...
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Teaching equipment management is an important factor for colleges and universities to improve their teaching level,and its management level directly affects the service life and efficiency of teaching *** in recent years,our university recruitment of students scale is increasing year by year,the size of the corresponding teaching equipment is also growing,therefore to develop a teaching equipment management information system is necessary,not only can help universities to effective use of the existing teaching resources,also can update scrap equipment,related equipment maintenance,and build a good learning environment to students and to the improvement of the teaching quality of colleges and universities play a reliable safeguard *** paper first introduces some common development tools,and then analyzes the user functional requirements and data requirements of the system,and analyzes the feasibility of the system development from many aspects,finally based on B/S mode,using Java language,JSP technology and MySQL database design and implementation of a teaching equipment management information *** main functional modules of the system include equipment basic information management,equipment loan and return information management,equipment maintenance information management,equipment scrap information management,the interface of each functional module is shown in the paper.
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