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A new prediction model is proposed in transient stability analysis based on machine learning in this paper. It extracts features ahead from the time point that we want to make prediction, which produce an interval to take actions. The proposed model also takes network information into consideration, and tried to analyze how nodes in power grid influence each other. Compared to traditional algorithms...
The shift from centralised large production to distributed energy production has several consequences for current power system operation. The replacement of large power plants by growing numbers of distributed energy resources (DERs) increases the dependency of the power system on small scale, distributed production. Many of these DERs can be accessed and controlled remotely, posing a cybersecurity...
This paper describes a model (and the respective guidelines) for the creation of a debate “think-tank” around the thematic of Engineering Education. From this initiative, a first outcome is obtained, in the form of the Engineering Education Forum 2016 (EEF 2016). The Engineering Education Forum is therefore intended to be a place of discussion and debate on this thematic. The model behind Forum encompasses...
With the rapid development of Internet and big explosion of text data, it has been a very significant research subject to extract valuable information from text ocean. To realize multi-classification for text sentiment, this paper promotes a RNN language model based on Long Short Term Memory (LSTM), which can get complete sequence information effectively. Compared with the traditional RNN language...
The objective of this study comprised of two aspects: (1) developing the training curriculum to enhance the system thinking ability of undergraduate students, and (2) finding out its effectiveness due to the curriculum implementation with undergraduate students. The samples were 20 voluntary of Ramkhamhaeng university undergraduate students. The process of curriculum development employed Taba's and...
Before conduct data collecting, enumerators take a course and conduct simulation in the classroom. However, learning in the classroom often doesn't make the enumerators understand perfectly. To solve this problem, we can use 3D virtual game based training as a solution. During the training, enumerators will use 3D virtual learning environment to get more experience, engagement, and expertise. For...
In analysis dictionary learning, the learned dictionary may contain similar atoms, leading to a degenerate dictionary. To address this problem, we propose a novel incoherent analysis dictionary learning algorithm with the ℓ1-norm for sparsity and simultaneously with the coherence penalty. The whole problem is convex but nonsmooth due to the sparsity regularizer and the coherence penalty. Hence, the...
Oil palm plantations cover large areas. One of the main problems is to get an updated census of plants contained in these fields. Nowadays this process is done manually generating subjective results of the number of plants and so economic losses. This paper presents the validation of an oil palm detection and counting system. It uses a logistic regression model to classify images acquired by an unmanned...
State Grid Jibei Electric Power Company (Jibei) has accumulated a large number of operation data through the maintenance of the equipment, devices in power grids. It is of great significance to study this data and extract the useful information by the data mining and statistics techniques. While the theories and methods of Naive Bayes have been widely studied, this paper utilizes such technique to...
Rooted in a basic hypothesis that a data matrix is strictly drawn from some independent subspaces, the low-rank representation (LRR) model and its variations have been successfully applied in various image classification tasks. However, this hypothesis is very strict to the LRR model as it cannot always be guaranteed in real images. Moreover, the hypothesis also prevents the sub-dictionaries of different...
Deep learning has been popularized by its recent successes on challenging artificial intelligence problems. One of the reasons for its dominance is also an ongoing challenge: the need for immense amounts of computational power. Hardware architects have responded by proposing a wide array of promising ideas, but to date, the majority of the work has focused on specific algorithms in somewhat narrow...
An important and widespread topic in cloud computing is text analyzing. People often use topic model which is a popular and effective technology to deal with related tasks. Among all the topic models, sLDA is acknowledged as a popular supervised topic model, which adds a response variable or category label with each document, so that the model can uncover the latent structure of a text dataset as...
Document Categorization is an area of important research over the last couple of decades. The basic task in document categorization is classifying a given document in some predefined classes. Bengali is among the top ten most spoken languages in the world and is spoken by more than 200 million people, but the candid truth is, it still lacks significant research efforts in the area of Bengali Document...
Nowadays MapReduce and its open source implementation, Apache Hadoop, are the most widespread solutions for handling massive dataset on clusters of commodity hardware. At the expense of a somewhat reduced performance in comparison to HPC technologies, the MapReduce framework provides fault tolerance and automatic parallelization without any efforts by developers. Since in many cases Hadoop is adopted...
In order to establish the best practices to instruct the definition of processes and support organizational assessment of the maturity and capability level, quality models and standards guide several Software Process Improvement initiatives. Nonetheless, despite these initiatives, the best practices application in Brazilian public organizations is impaired by various obstacles regarding the process...
Endurance is an important factor of cardiovascular fitness indicating the capacity of an individual to perform exercise for a longer duration with increased intensity. Various subject specific and exercise related parameters affect endurance of an individual. In this work, we propose a statistical technique to model endurance as a function of these factors incorporating the serial dependence of observations...
People with social communication difficulties tend to have superior skills using computers, and as a result computer-based social skills training systems are flourishing. Social skills training, performed by human trainers, is a well-established method to obtain appropriate skills in social interaction. Previous works have attempted to automate one or several parts of social skills training through...
This research was conducted to investigate the management of knowledge flows in a Mauritian multinational organisation. A case study research method was used to gather data which was analysed using the SECI model. Results show that all the four quadrants of this model were applied by the conglomerate in transferring knowledge to its newly acquired manufacturing operations in Madagascar. This paper...
To improve the prediction precision of residential property, the paper brings up a mixed optimizing model based on IPSO-BPNN. The model has adopted gray correlation theory to optimized the the index that influences price and use IPSO to optimize the definition of original weights and threshold value. We take the real estate market in Changsha as an example. The result shows that the speed of convergence...
Artificial neural networks (ANNs) have rarely been used in the field of medical education, especially in the prediction of learning performances. This study aims to evaluate the potential application of ANN models for predicting learning performances, in comparison with multivariate logistic regression models. The predictor variables included demographics, high-school backgrounds, first-year grade-point...
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