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.
Gait analysis aims to study human motion and its potential association with chronic diseases, such as Parkinson's disease and hemiplegic paralysis, by extracting various gait characteristics. It has been a challenging problem to accurately extract temporal and spatial gait parameter and to explore the relationship between gait signal and a disease of interest. In this study, we introduce a gait sensing...
Cyanobacteria bloom is a serious public health threat and a global challenge. Literature on the bloom prediction and forecasting has been accumulating and the emphasis appears to have been on the relation between the blooms and environmental factors, whilst the complexity of the bloom mechanism makes it difficult to reach adequate output of the models. Rapid development of next generation sequencing...
In this paper, we discuss the importance of feature subset selection methods in machine learning techniques. An analysis of microarray expression was used to check whether global biological differences underlie common pathological features for different types of cancer datasets and to identify genes that might anticipate the clinical behavior of this disease. One way of finding relevant gene selection...
In the last years social networks have emerged as a critical mean for information spreading. In spite of all the positive consequences this phenomenon brings, unverified and instrumentally relevant information statements in circulation, named as rumours, are becoming a potential threat to the society. Recently, there have been several studies on topic-independent rumour detection on Twitter. In this...
We present an application of a Multiple Instance Learning (MIL) approach to image classification. In particular we focus on a recent MIL method for binary classification where the objective is to discriminate between positive and negative sets of points. Such sets are called bags and the points inside the bags are called instances. In the case of two classes of instances (positive and negative), a...
Diabetic retinopathy (DR) is an eye abnormality caused by long term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR, yielding a large body of diagnostic work focused on automatic detection of MA. However, automated detection of MAs is difficult because (1) the small size...
Down syndrome (DS) is a genetic disorder with genome dosage imbalances and micro-duplications of human chromosome 21. It is usually associated with a group of serious diseases, including intellectual disabilities, cardiac diseases, physical abnormalities, and other abnormalities. Currently, since there is no cure for human DS, screening and early detection have become the most efficient way for DS...
Support vector data description (SVDD) is a popular technique for detecting anomalies. The SVDD classifier partitions the whole space into an inlier region, which consists of the region near the training data, and an outlier region, which consists of points away from the training data. The computation of the SVDD classifier requires a kernel function, and the Gaussian kernel is a common choice for...
Extracting stop purpose information from raw GPS data is a crucial task in most location-aware applications. With the continuous growth of GPS data collected from mobile devices, this task is becoming more and more interesting; a lot of recent research has focused on pedestrians (mobile phones) data, while the commercial vehicles sector is almost unexplored. In this paper we target the problem of...
With the advent of smart devices and lowering prices of sensing devices, adoption of Internet of Things (IoT) is gaining momentum. These IoT devices come with greater threat of being attacked or compromised that could lead to Denial of Service (DoS) and Distributed Denial of Service (DDoS). The high volume of IoT devices with high level of heterogeneity, magnify the possibility of security threats...
Selecting an efficient classifier for medical data is considered as one of the most important part of today's computer aided diagnosis. The performance of single classifiers such as decision tree classifier can be increased by ensemble method. However, this approach relies on the data quality and missing values. In this paper, we propose a new ensemble classifier to overcome overfitting and biasness...
Depression is a mental disorder of high prevalence, leading to a negative effect on individuals, their families, society and the economy. In recent years, the problem of automatic detection of depression from the speech signal has gained more interest. In this paper, a new multiple classifier system for depression recognition was developed and tested. The novel aspect of this methodology is the combination...
Class imbalance exists in many applications of bioinformatics and biomedicine, while dimension reduction in the feature space is often needed when building prediction models on a dataset. When the above two issues need to be considered simultaneously for skewed/imbalanced datasets, practitioners and researchers in machine learning may raise the following question: should feature selection be conducted...
The recent progress of motion sensor system enables to the personal identification from the human behavior observed from the sensor. Kinect is a motion sensing input device developed by Microsoft for Xbox 360 and Xbox One. The personal identification using the Microsoft Kinect sensor, shortly Kinect, is presented in this study. The use of the Kinect estimates the pedestrian's body size and walk behavior...
We consider the semi-supervised dimension reduction problem: given a high dimensional dataset with a small number of labeled data and huge number of unlabeled data, the goal is to find the low-dimensional embedding that yields good classification results. Most of the previous algorithms for this task are linkage-based algorithms. They try to enforce the must-link and cannot-link constraints in dimension...
Predicting early signs of illness in older adults by utilizing a continuous, unobtrusive nursing home monitoring system has been shown to increase the quality of life and decrease the cost of care. Illness prediction is based on sensor data such as motion and bed and uses algorithms such as support vector machine (SVM) or k-nearest neighbor (kNN). One of the greatest challenges in developing prediction...
Emotion is closely related to healthy and abnormal mood is the alarm of our body. This paper is concentrated on the objective and accurate emotion classification using EEG signal. We propose emotional patches and combine it with the deep belief network(DBN) to achieve high-precision emotion classification. DBN is able to fit the distribution of the EEG signal and mapping the extracted feature to the...
This paper focuses on accuracy improvement of human activities detection and classification by using single Inertia Measurement Unit sensor (IMU sensor: an acceleration sensor, a gyro sensor, a magnetometer, and an air pressure sensor) which is a type of the wearable sensors. Generally, performance of classification model is determined by these methodologies; number and type of sensors, coordinate...
This paper presents an interfacing system of a photovoltaic (PV) array with an electrical grid based on a dual cascaded inverter. The PV array is connected to the main inverter through a boost converter, for maximum power extraction, while the dc-side of the auxiliary inverter is connected to a capacitor bank. The main and auxiliary inverters are controlled to deliver the harvested maximum power from...
Aerosol optical depth (AOD), one of the key factors affecting the atmosphere visibility, has great influence on the prediction of radiation intensity and photovoltaic power generation. Considering the problem that AOD is difficult to obtain real-timely and conveniently with high accuracy, in this paper, PM2.5 concentration, PM10 concentration and temperature, wind speed grade and relative humidity...
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.