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.
The full behavior of software-intensive systems of systems (SoS) emerges during operation only. Runtime monitoring approaches have thus been proposed to detect deviations from the expected behavior. They commonly rely on temporal logic or domain-specific languages to formally define requirements, which are then checked by analyzing the stream of monitored events and event data. Some approaches also...
Social media plays an important role in shaping the beliefs and sentiments of an audience regarding an event. A comparison between public data sets that have holistic features and social media data set that include more user features would give insight into the spread of misinformation and aspects of events that are reflected in user behavior. In this research, we compare the trends identified in...
Text segmentation is an important problem in document analysis related applications. We address the problem of classifying connected components of a document image as text or non-text. Inspired from previous works in the literature, besides common size and shape related features extracted from the components, we also consider component images, without and with context information, as inputs of the...
Social engineering has emerged as a serious threat in virtual communities and is an important means to attack information systems. The services used by today's knowledge workers prepare the base for complicated social engineering attacks. Phishing is a kind of technically generated social engineering attack and is the type of identity theft that uses the social engineering techniques and complex attack...
This paper presents a rapidly and lower neural networks to treat those waste water index that is difficult to be measured. Model called soft sensor is composited two parts: one is used to estimate the principal linear output, the other one is used to adjust estimated error to obtain better accuracy. Selection of features that effects greatly computation scale and predict accuracy is discussed also...
Natural language processing methods are widely used to study the relationship between traditional Chinese medicine (TCM) prescriptions and diseases in textual data, and the results can discover the essence of TCM literature. In this paper, we get TCM treatment information from the abstract text at first by using the web crawlers. Second, the eigenvectors will be selected from the cleaned abstract...
The unified Parkinson's disease rating scale (UPDRS) is the most widely employed scale for tracking Parkinson's disease (PD) symptom progression. However, conventional way to achieve UPDRS, mainly based on the physical examinations of clinic patients performed by the trained medical staffs, involves the disadvantages of inconvenience and high medical expense. Hence, in this study, we try to explore...
Online opinions play an important role in supporting consumers make decisions about purchasing products or services. In addition, customer reviews allow companies to understand the strengths and limitations of their products and services, which aids in improving their marketing campaigns. Such valuable information can only be obtained via appropriate analysis of the opinions provided by customers...
In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spa-tiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of...
To utilize asynchronous multichannel recordings with different start and end time of recordings for acoustic scene analysis, we propose a combination method for estimating unrecorded durations and extracting spatial features. Focusing on the fact that amplitude information is relatively robust to the estimation error of the unrecorded durations and the synchronization mismatch of multichannel recordings,...
It is a simple task for humans to visually identify objects. However, computer-based image recognition remains challenging. In this paper we describe an approach for image recognition with specific focus on automated recognition of plants and flowers. The approach taken utilizes deep learning capabilities and unlike other approaches that focus on static images for feature classification, we utilize...
Given the growing interest in soft biometrics and its application in many areas related to biometrics, this paper focuses on the automatic extraction of body-based soft biometric attributes from single-shot images. The selected body soft biometrics are: height, shoulder width, hips width, arms length, body complexion and hair colour. For the extraction of these attributes, the Southampton Multi-Biometric...
Because of the worldwide aging population, more and more elders suffer from dementia. Nowadays, it is inconvenient and time-consuming for doctors to diagnose whether elders who live independently have dementia because lots of diagnostic questions on a checklist must be asked first, and part of them even require a long-term observation. In order to help doctors and make this diagnostic process easier,...
To effectively reuse existing NC machining process of similar part and feature, an effective data mining approach of existing CAM models in machining process data is proposed. First, a machining feature based multilevel structured CAM model is proposed to reveal the relations between machining features and machining operations. Then, the structured machining know-how database is automatically generated...
The random Fourier Features method has been found very effective in approximating the kernel functions. Our former studies show that through a mixing mechanism of the feature space formed by random Fourier features and certain linear algorithms, the fuzzy clustering results in the approximated feature space are comparable to or even exceed the classical kernel-based algorithms. To increase the robustness...
Keyword extraction is an automated process that collects a set of terms, illustrating an overview of the document. The term is defined how the keyword identifies the core information of a particular document. Analyzing huge number of documents to find out the relevant information, keyword extraction will be the key approach. This approach will help us to understand the depth of it even before we read...
Wireless cameras can be used to gather situation awareness information (e.g., humans in distress) in disaster recovery scenarios. However, blindly sending raw video streams from such cameras, to an operations center or controller can be prohibitive in terms of bandwidth. Further, these raw streams could contain either redundant or irrelevant information. Thus, we ask "how do we extract accurate...
The field of opinion mining is expanding rapidly with the widespread use of internet for e-commerce and social interaction. One of the interesting use of opinion mining is in the field of online producer-consumer industry. The primary goal of the work presented in this paper is to perform a semi-automated sentiment classification on online product reviews for product evaluation using machine learning...
Phishers often exploit users' trust on the appearance of a site by using webpages that are visually similar to an authentic site. In the past, various research studies have tried to identify and classify the factors contributing towards the detection of phishing websites. The focus of this research is to establish a strong relationship between those identified heuristics (content-based) and the legitimacy...
The accurate short-term traffic flow prediction can provide timely and accurate traffic condition information which can help one to make travel decision and mitigate the traffic jam. Deep learning (DL) provides a new paradigm for the analysis of big data generated by the urban daily traffic. In this paper, we propose a novel end-to-end deep learning architecture which consists of two modules. We combine...
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.