The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Type-2 Diabetes (T2D) is a dreadful disease affecting hundreds of millions of people worldwide, and is linked and worsen by unhealthy lifestyles, especially the poor diet style. However, managing daily diet effectively remains highly challenging for both T2D patients and doctors. In this paper, we proposed, built, and evaluated an effective food classification tool using mobile computing and predictive...
For medical research purposes, having access to large sets of data, often from various regions, improves statistical outcomes of analysis. However, patient data is usually considered to be sensitive and access to it is restricted by law and regulation. This paper employs privatization techniques which enable sharing of sensitive data. We demonstrate a case study on four medical data sets.
Low cost pervasive electrocardiogram (ECG) monitors is changing how sinus arrhythmia are diagnosed among patients with mild symptoms. With the large amount of data generated from long-term monitoring, come new data science and analytical challenges. Although traditional rule-based detection algorithms still work on relatively short clinical quality ECG, they are not optimal for pervasive signals collected...
Management of ship designing is difficult because of the complexity in modeling of the process and large amounts of data throughout the process. Though existing technologies of BPMN can solve the first problem, BPMN does not provide sufficient supports on dealing with complex dependencies in the process, e.g., storage and search problems of correlated data with “many to many” relations. In this paper,...
Deep learning algorithms such as convolutional neural networks (CNN) have been successfully applied in computer vision. This paper attempts to adapt the optical camera-oriented CNN to its microwave counterpart, i.e. synthetic aperture radar (SAR). As a preliminary study, a single layer of convolutional neural network is used to automatically learn features from SAR images. Instead of using the classical...
Remote sensing images provide essential data source for monitoring the land cover and land change on the Earth with a fast revisiting period. To fully utilize the remote sensing data, supervised classification methods are good choices to convert the data to land cover types due to their good abilities. One of the great challenges is to effectively collect training samples, especially for remote sensing...
Predictive modeling competitions provide a new data mining approach that leverages crowds of data scientists to examine a wide variety of predictive models and build the best performance model. Competition hosts, who provide their own dataset and specify the problem to be solved, are not only able to obtain the best model from among those submitted but also to aggregate the submitted models to obtain...
Online social networks have found a significant increase in their popularity in recent years. All the networks have community structure, and one of the research problems mostly frequently tackled is the discovery of communities. An overlapping community is a network structure that allows one node to be a member of multiple communities. The method presented in this paper aims at detecting overlapping...
Supervised learning methods rely on large sets of labeled training examples. However, large training sets are rare and making them is expensive. In this research, Latent Semantic Indexing Subspace Signature Model (LSISSM) is applied to labeling for active learning of unstructured text. Based on Singular Value Decomposition (SVD), LSISSM represents terms and documents as semantic signatures by the...
In this paper, we develop a new meta-clustering approach using possibility and rough set theories to handle imperfection in real-world retail datasets. Our proposal is a soft meta-clustering approach that provides a framework for handling uncertainty in the belonging of an object to different clusters. The soft meta-clustering approach is based on the k-modes algorithm devoted for categorical data...
Applying for research funding projects is becoming one of the most important ways for scientists to carry on the research. How to find an appropriate collaborator/applicant is a major concern for scientists. Social networks provide one means of visualizing existing and potential collaborations. In this paper, we study the funding collaborators recommendation problems. We solve the problem by starting...
Detection of community structure in complex networks is a significant aspect in social network analysis. A novel fuzzy clustering method is proposed in this paper, by which the community structure can be divided. In contrast to previous studies, the proposed method processes similarity of connecting vertices with fuzzy relation. In our method, we globally consider the fuzzy relation between vertices...
Time series is a ubiquitous form of data and the analytics of time series is attracting increasing interest recently. In the context of time series data mining, similarity measure has the fundamental importance because many data mining techniques depend on it. Dynamic time warping (DTW) is considered to be the most popular similarity measure for time series and it is alignment-based. However, it has...
Accompanying increasing competition among the communication industry, maintaining and improving the stability and loyalty of customers has become the key determinant of profitability. In order to prevent the loss of customers, we need to identify the stable users by data mining model. Through the evaluation of three models, Random Forest model performs with better robustness. This model can describe...
The U.S. recently adopted a post-grant opposition procedure to encourage third parties to challenge the validity of newly granted patents by providing relevant prior patents that are missed during patent examination (i.e., missing citations). In this paper, we propose a recommendation system for missing citations for newly granted patents. The recommendation system, based on the patent citation network...
One of the major steps for opinion mining is to extract product features. The vast majority of existing approaches focus on explicit feature identification, few attempts have been made to identify implicit features in reviews, however; people tend to express their opinions with simple structures and brachylogies, which lead to more implicit features in reviews. By analyzing the characteristics of...
Random unique number generator can be used for generating a series of unpredictable and unrepeatable numbers within limited ranges of data and numbers. These numbers are usually distributed equally, random, independent, unpredictable and unrepeatable. A good random number generator has to be effective for a long period and has good statistical distribution and efficient generating performance. This...
The Internet of Things and the Web of Things have focused on context awareness as a central issue in defining complex autonomic systems that rely on various layers, including devices, communications and applications. The spread usage of mobile devices that allow users to generate and to access distributed data makes it extremely important to organize the forwarding and gathering of such data in a...
We consider a cloud as a cluster of processors holding each a large XML tree. We present a statistical representation which can be built online on each processor and allows to approximate boolean, unary and Aggregation queries. The main result of the paper shows how these statistics can be efficiently Reduced to a master node of the cloud. We obtain an approximation of the global tree structure built...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.