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The number of woman with cervical cancer in Indonesia is getting higher. Indonesia becomes the country with the highest number of women with cervical cancer in the world. Cervical cancer became the highest cause of cancer deaths in women globally. There has been a lot of research using data mining techniques with variety of different data mining models that can be used for analyzing cervical cancer...
Data classification in medical field is distinct from that in other fields, because the medical data are heterogeneous, skewed and complex in nature and medical data classification involves multi class classification. In this paper we present the experimental analysis of well-known traditional classification algorithms on bio-medical datasets in order to observe their performance. This experimental...
Crime is one of the most predominant and alarming aspects in our society and its prevention is a vital task. Crime analysis is a systematic way of detecting and investigating patterns and trends in crime. In this work, we use various clustering approaches of data mining to analyse the crime data of Tamilnadu. The crime data is extracted from National Crime Records Bureau (NCRB) of India. It consists...
Energy efficiency measurement and its influence factors is important way of energy efficiency evaluation. In this paper, character identification method has been proposed to determine influence factors of energy efficiency and energy efficiency of 24 provinces in china is analyzed and evaluated by deep learning method. By comparison, two classification and prediction models are built with two other...
Background: Automated disease classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. Proposed model is a classification based an efficient approach in which machine learning concepts are used for the detection of Lung cancer diseases. The algorithm obtained encouraging results but requires considerable computational...
Agile methodology is a famous software development methodology. The methodology stresses on adaptation and collaboration between people. Here, software project managers should agree to an idea of putting the right people in the right jobs. This research puts forward an idea of applying Big Five Personality Traits to predict how people suitable for the Agile methodology. A predicting method is driven...
The background of the research is to analyze data derived from an elucidation of catfish and carp diseases in Kediri, East Java, Indonesia. The research shows that data about fish's disease history have not been used effectively because it is only be collected. Data about fish's symptom history used by fish trainer only present the number of fish that get disease. Data about fish's history should...
Class noise elimination in large databases is a real issue in data mining processing. In fact, class noise may sometimes lead to distortion or inaccuracy. So to overcome this problem, many techniques have been proposed. However, most of them don't have the capacity to deal with huge volume. In this context, this paper presents an architecture for class noise detection and elimination in large datasets...
We propose a new methodology to detect social aspects of crowds in video sequences based on pedestrian features, which are obtained through image processing/computer vision techniques. The main idea is to apply and extend the concepts of Fundamental Diagram (FD) with more features, such as grouping and collectivity. Using crowd features we identify the crowd type and the main characteristics. In addition,...
Streaming data is one of the attention receiving sources for concept-evolution studies. When a new class occurs in the data stream it can be considered as a new concept and so the concept-evolution. One attractive problem occurring in the concept-evolution studies is the recurring classes from our previous study. In data streams, a class can disappear and reappear after a while. Existing studies on...
Unexploded Ordnances (UXO) classification procedure consists of the following: background subtractions, data inversions and targets feature parameters estimations, and separating UXO from non-hazardous anomalies. First, each dataset is normalized by a corresponding Tx-current; then, all data files are background subtracted; third, the background corrected data are inverted and targets intrinsic (effective...
Machine learning is an emerging technique for building analytic models for machines to "learn" from data and be able to do predictive analysis. The ability of machines to "learn" and do predictive analysis is very important in this era of big data and it has a wide range of application areas. For instance, banks and financial institutions are sometimes faced with the challenge...
Data objects are considered as fundamental keys in learning methods that without the objects the mining algorithms are meaningless. Data objects basically direct the accuracy of the selected algorithm in case if they are extracted from inappropriate groups. Knowing the exact type of data object leads the miner to provide a suitable environment for learning algorithms. Supervised and unsupervised learning...
In data science, there are some parameters that affect the accuracy of selected algorithms, regardless of their type. Type of data objects, membership assignments, and distance or similarity functions are the most important parameters that provide or not a proper environment for learning algorithms. The paper evaluates similarity functions as fundamental keys for membership assignments. The issues...
Data mining can be defined as the use of complex tools of data analysis to discover previously unknown relationships and patterns in large datasets. The tools may include mathematical algorithms, statistical models and machine learning methods. Therefore, data mining comprises techniques that enable more processes than data collection and management, including data analysis and prediction. Healthcare...
Web services have been widely used in e-business, banking, and other online applications. web application architecture follows SOAP, UDDI and WSDL. QoS parameters are response time, availability, security and others are most significant for web applications. World into digital devices. the products can be used with efficient resource consumptions. Internet of things is the capability to connect every...
Smoking is one of the major activities that can become highly addictive and can cause major health-related risks. It is one of the major causes of death worldwide. There are various issues revolving around smoking and its complications. To assess the impact of smoking, its complications, and the process of achieving smoking cessation, an online survey was conducted. In this study, the results of the...
Outlier Detection is one of the important research problems in temporal data mining. A pattern in time stamped temporal database is a sequence of probability values. Finding outliers from time stamped temporal databases requires suitable dissimilarity measure to find dissimilarity between input pattern and reference pattern which is of user interest. In the current work, the objective is to propose...
Automated load managements and cost-effective power systems in distribution level are now becoming possible by increasing the number of installed smart meters at end-users side. Monitoring and controlling the massive datasets of demand curves require using data mining and characterizing load profiles. This paper analyses a wide range of data from a comprehensive survey of residential customers. It...
The results of the requirements engineering process are predominantly documented in natural language requirements specifications. Besides the actual requirements, these documents contain additional content such as explanations, summaries, and figures. For the later use of requirements specifications, it is important to be able to differentiate between legally relevant requirements and other auxiliary...
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