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The HEVC(H.265) has brought in significant improvements in terms of coding efficiency. However, the reduction in bitrates comes along with an increment in computational complexity. This paper presents a data mining approach to reduce the complexity of inter partition modes in HEVC. Determining the CU-splitting in inter partition modes requires substantial resources, so the goal of the work is to terminate...
This paper proposes a multi-level meta-classifier for identifying human activities based on accelerometer data. The training data consists of 77 subjects performing a combination of 23 different activities and monitored using a single hip-worn triaxial accelerometer. Time and frequency based features were extracted from two-second windows of raw accelerometer data and a subset of the features, together...
Spatial analysis in many fields requires effective address extraction from text reports. This problem is of particular importance in social science where news reports contain information about socially relevant incidents. Previous address extraction work focuses on web pages where addresses are separated from other text, however news reports contain addresses embedded in text. Hence, the need for...
The massive amount of data collected by healthcare sector can be effective for analysis, diagnosis and decision making if it is mined properly. Hidden information extracted from the voluminous data can provide help and remedy to handle critical healthcare situations. Chronic kidney disease is a fatal illness of kidney which can be prevented with early correct predictions and proper precautions. Data...
Data mining can be used in various fields' i.e. mobile computing, web mining, expert predictions, crime analysis, engineering, management and medicine. In medical field, data mining techniques can be used by the researchers for the diagnosis and prediction of various diseases. A framework is proposed to predict Syncope Disease using Ensemble technique that contains Naïve Bayes, Gini Index and Support...
Discriminative patterns describe significant differences between different types of subjects, and often provide insights to critical properties of the problem at hand. Pattern-based classifiers can directly utilize discriminative patterns to predict unseen samples by a majority voting or aggregation mechanism. Therefore, we are concerned with not only finding useful individual patterns, but also the...
Cardiovascular disease is a worldwide health problem and according to American Heart Association (AHA), it also causes an approximate death of 17.3 million each year. Therefore early detection and treatment of asymptomatic cardiovascular disease which can significantly reduce the chances of death. An important fact regarding such life-threatening disease prognosis is to identify the patient's physical...
We deal with the problem of initial analysis of data coming from evaluation sheets of subjects with Autism Spectrum Disorders (ASDs). In our research, we use an original evaluation sheet including questions about competencies grouped into 17 spheres. In the paper, we are focused on a feature selection problem. The main goal is to use appropriate data to build simpler and more accurate classifiers...
A standard data set is useful to empirically evaluate classification rules learning algorithms. However, there is still no standard data set which is common enough for various situations. Data sets from the real world are limited to specific applications. The sizes of attributes, the rules and samples of the real data are fixed. A data generator is proposed here to produce synthetic data set which...
This paper presents a salary prediction system using a profile of graduated students as a model. A data mining technique is applied to generate a model to predict a salary for individual students who have similar attributes to the training data. In this work, we also made an experiment to compare five data mining techniques including Decision trees, Naive Bayes, K-Nearest neighbor, Support vector...
In major colleges and universities, in order to mobilize students enthusiasm for studying and participating in extracurricular activities, all colleges make an evaluation on students comprehensive quality and set different rewards regulations for the various level. The main way is to provide financial incentives, they distribute scholarship for students of meeting requirements. The Decision Tree algorithm...
Data mining is commonly used in the healthcare industry and managing Intensive Care Unit (ICU) is no exception. This study aims to examine how data mining techniques can be employed to predict mortality and length of stay in an ICU and to evaluate various classification techniques. Real-life healthcare datasets, like MIMIC 2, incorporate an unbalanced distribution of sample sizes, which means that...
As blogs widely spread, the need to extract information is necessary in order to deal with different issues such as social, political, criminal and others. This research takes off from Gharehchopogh et al. [2], [3] who used the C4.5 and K-Nearest Neighbor (K-NN) algorithms to classify bloggers whether they are professional or otherwise from the Kohkilooyeh and Boyer Ahmad province in Iran. As a comparative...
In response to globalization, International Financial Reporting Standards (IFRS) has become the norm of the global capital markets. Companies preparing financial statements using IFRS may make the financial situation fully disclosed. Nevertheless, an overestimated accrual expense of a balance sheet may not only underestimate the earnings data, but also increase the cash outflows of the statement of...
Large-scale production lines aim to realize 0 ppm defects. This is getting more and more complicated, due to all the so far achieved process optimizations. However, our research showed that a huge amount of unpredictable disturbance variables influences production systems, which promote defects. Here, the modelling of every single influence like temperature, machine condition, tool wear and quality...
Customer churn is one of the main problems in the telecommunications industry. Several studies have shown that attracting new customers is much more expensive than retaining existing ones. Therefore, companies are focusing on developing accurate and reliable predictive models to identify potential customers that will churn in the near future. The aim of this paper is investigating the main reasons...
In upholding the Islamic way of life, effort to seek for moderation can be in the form of obesity prevention. Obesity is becoming the future burden of nations and actions have been taken to curb the problem of obesity. Most nations predict obesity based on the national past trend using data from population-based health surveys which are costly. Alternative method now points to data analytics which...
Decision tree algorithms are very popular in the field of data mining. This paper proposes a distributed decision tree algorithm and shows examples of its implementation on big data platforms. The major contribution of this paper is the novel KS-Tree algorithm which builds a decision tree in a distributed environment. KS-Tree is applied to some real world data mining problems and compared with state-of-the-art...
The possibility of extracting useful medical information from data collected by nurses for management purposes is investigated. An alternating decision tree for predicting pressure ulcer development is generated from nursing needs score data (NNS) usually recorded in Japanese hospitals.
This paper based on the analysis of the basic meaning in data mining and the structure of decision tree uses the decision tree algorithm — C4.5 to establish a soil quality grade prediction model and combines the soil composition in Lishu to be a training sample. C4.5 algorithm also expresses the acquired knowledge by means of quantitative rules. The experiment results manifest that the expression...
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