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Clustering is an important branch in the field of data mining as well as statistical analysis and is widely used in exploratory analysis. Many algorithms exist for clustering in the Euclidean space. However, time series clustering introduces new problems, such as inadequate distance measure, inaccurate cluster center description, lack of efficient and accurate clustering techniques. When dealing with...
Banks and financial institutions around the world must comply with several policies for the prevention of money laundering and in order to combat the financing of terrorism. Nowadays, there is a raise in the popularity of novel financial technologies such as digital currencies, social trading platforms and distributed ledger payments, but there is a lack of approaches to enforce the aforementioned...
Subgroup discovery is a local pattern mining technique to find interpretable descriptions of sub-populations that stand out on a given target variable. That is, these sub-populations are exceptional with regard to the global distribution. In this paper we argue that in many applications, such as scientific discovery, subgroups are only useful if they are additionally representative of the global distribution...
Motion vectors extracted from a compressed video file can be used to track objects in the video and it could be efficient as motion vectors provide trajectory information of the objects. However, tracking objects represented by the motion vectors can be inaccuracy because of camera movement, small size sets of motion vectors acting as noise, unmoving of the object and occlusion. These are conditions...
The paper introduces the research of tube-type bottle defects detection algorithm based on machine vision system, and the implementation method of detection system using machine vision and digital image processing technology. Industrial camera is used to collect the image of tube-type bottle, then the image is processed and analyzed by image processing technology. On this basis, by comparing with...
In this paper, syllabus visualization tool based on standard curriculum is proposed. To visualize the difference of syllabuses, the proposed tool uses correspondence analysis. Using the proposed tool, we can know the relationship between syllabuses and standard curriculum (CS2013).
Method noise which is the difference between a noisy image and its denoised version, often contains image structure and detail information due to imperfect denoising. This paper analyzes the method noise and establishes a model to extract image information submerged in the method noise. Then the extracted image information is fed back to the denoised image to conduct the next denoising step. The whole...
The Open University of Japan (OUJ) and National Institute of Informatics (NII) have started collaborative study for learning analytics. OUJ is the largest distance education institution in Japan. In the academic year of 2015, OUJ launched interactive online courses. One of the essential features of online courses is the possibility to collect and analyze educational big data. To utilize such educational...
The construction of knowledge graph of dangerous goods (KGDG) is with great significance of inferring relative information of dangerous goods, developing corresponding policy for its storage and transport, preventing disaster caused by dangerous goods(DG), and providing emergency plan when the disaster happens. Since distributed representation of natural language is an effective method for knowledge...
Evaluating motion quality has many applications in health promotion and exercise coaching. This study aimed to develop an approach for automatic and cost-efficient evaluation on motion quality using the Nintendo Wii Balance Board (WBB) and machine learning techniques. We conducted a pilot study with twelve participants to collect data of chest rotation and hip joint rotation. We used support vector...
Educational Data Mining is a prominent area to explore information in educational fields using data mining algorithms. In this paper we have used few learning algorithms to effectively rate the faculty belonging to an educational institute on the basis of feedback submitted by the students. Our proposed model uses sentimental analysis and machine learning classifier algorithms for capturing the emotions...
In this paper, we present a new method for detecting professional skills (as noun phrases) from resumes written in natural language. The proposed method uses an ontology of skills, the Wikipedia encyclopedia, and a set of standard multi word part-of-speech patterns in order to detect the professional skills. First, the method checks to see if there are, in the text of the resumes, skills that are...
A general methodology of device array mismatch characterization is introduced, analyzed and verified. Instead of measuring each device's parameter individually, the device array is configured as a data converter and the mismatch information is extracted from the differential linearity (DNL) of the converter. Systematic and random mismatch are characterized separately using the proposed decomposition...
Intrauterine devices (IUDs) are highly-effective contraceptive methods for preventing unintended pregnancy and related adverse outcomes. Clinical Decision Support (CDS) systems could aid care providers in identifying patients at risk for pregnancy due to lack of contraceptive use. However, research suggests that this information is not reliably documented in structured data fields for query, but rather...
The widespread adoption of Electronic Health Records (EHRs) has enabled data-driven approaches to clinical care and research. However, the performance and generalizability of those approaches are severely hampered by the lack of syntactic and semantic interoperability of EHR data across institutions. Towards resolving this problem, Common Data Models (CDMs) can be used to standardize the clinical...
We present the Modernizing Analytics for MELanoma (MAMEL) dataset: a real-world, dermatologyspecific research dataset specifically crafted to advance data mining and machine learning research in the field of melanoma diagnosis, analysis, and treatment. This dataset was collected and curated from Modernizing Medicine’s EMA DermatologyTM application, a cloud-based Electronic Health Record (EHR) platform...
In recent times, there has been significant interest in the machine recognition of human emotions, due to the suite of applications to which this knowledge can be applied. A number of different modalities, such as speech or facial expression, individually and with eye gaze, have been investigated by the affective computing research community to either classify the emotion (e.g. sad, happy, angry)...
Integration of automated ECG analysis techniques with the home monitoring devices can incorporate the necessary “smartness” which can help in earlier diagnosis of Myocardial Infarction (MI), better known as heart attack, thus reducing the mortality rate. Most of the reported techniques suffer from the disadvantages of large feature dimension, computational complexity of the features and complex classifiers...
Spatial co-location pattern mining is employed to identify a group of spatial types, the instances of which are frequently located in spatial proximity. Current co-location mining methods have two limitations: (1) it is difficult to set an appropriate proximity threshold to identify close instances in an unknown region and (2) those methods neglect the effects of distance values between instances...
To diagnose the specific reasons that lead to deterioration of controller performance and improve the diagnostic accuracy, a performance diagnosis method based on eigenvector subspace K-mean clustering is proposed. Firstly, the number of standard deterioration performance subspace with different degrees of deterioration information is increased on the basis of the eigenvector subspace distance diagnosis...
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