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In this paper, we propose a new approach to zone identification based on considering features with high semantic richness such as specialized names and mode of verbs belonging to a text's domain of interest and besides that mode of verbs, while taking into account features with less computational cost compared to those of conventional methods. Out of the scenarios of selecting features for identifying...
Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building...
These days, a lot number of elderly people need health care which may cause huge financial costs, especially in formal case. Machine Learning and the profound achievements in sensing technology provide the opportunities to monitor people living independently at home and can detect a distress situation affordably. Although there are some approaches to do recognize activities for this purpose, but there...
Stereotypic behaviours are present in both human and nonhuman primates. Usually, these behaviours are a welfare indicator. However, the stereotypic behaviours may be also a symptom of some mental disorder in the humans. A specific case is Autism Spectrum Disorder (ASD). The individuals with ASD may exhibit stereotypic behaviours through some gestures. The classic stereotyped gestures of autism are:...
Many classification techniques can automatically summarize text into topics and accordingly identify topic terms from the online reviews. Among these techniques Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) are some of the most often employed approaches. LDA is a probability generated model that projects a document into the topic space using Dirichlet Distribution, and each...
Currently, one of the most interesting and quickly growing issues is biometrics. Among many techniques of behavioural biometrics, the human gait recognition deserves special attention. The aim of this work is to check how the quality of a biometrics system based on ground reaction forces will change in the case of women walking in two types of footwear: sports shoes and high heels. The research was...
The paper is devoted to presentation of Unified Process Metamodel as a tool to describe both structural and behavioral aspects of processes identified in a real world. The complexity of the description of the reality urges the use of sophisticated tool for modeling. Therefore Association-Oriented Database Metamodel was used to prepare database model that comply with the needs of proposed system. Since...
Statistical inference has been usually used for medical data analysis, however in many cases it appears not to be efficient enough. Cluster analysis enables finding out groups of similar instances, for which statistical models can be built more effectively. In the paper a feature selection method for finding clustering attributes, which are supposed to improve performance of statistical analysis,...
The aim of this paper was to discover what combination of audio features gives the best performance with music emotion detection. In our approach, emotion recognition was treated as a regression problem and a two-dimensional valence-arousal model was used to measure emotions in music. We used features extracted by Essentia and Marsyas, tools for audio analysis and audio-based music information retrieval...
Big data term refers to different variations of large datasets to complex to be processed by traditional computing methods. The paper presents a system for retrieving images in relational databases in a distributed environment. Content of the query image and images in the database is compared using global color information and local image keypoints. Image keypoints are indexed by fuzzy sets directly...
In deep learning, data augmentation is important to increase the amount of training images to obtain higher classification accuracies. Most data-augmentation methods adopt the use of the following techniques: cropping, mirroring, color casting, scaling and rotation for creating additional training images. In this paper, we propose a novel data-augmentation method that transforms an image into a new...
We propose a new semantic segmentation method and the necessity of certainty for practical use of semantic segmentation in scene understanding. We implement a deep fully convolutional encoder-decoder neural network for semantic segmentation. This network architecture makes the segmentation accuracy improve by retaining boundary details in the extracted image representation. This accuracy means how...
The paper presents an approach to solve some problems arising in the management process of IT security. Our motivation of this research is to study in every detail the context of service oriented systems, which can be defined as considerable heterogeneous, dynamic and flexible configuration of the hardware and software system resources. The fundamental difference between security management systems...
The Underwater Acoustic Communication (UAC) systems work in communication channels characterized by a large variety of multipath propagation conditions that can additionally change over time. Designing a reliable communication system requires knowledge of the transmission parameters of the channel. There is a need for the development of adaptive signaling schemes that would dynamically optimize the...
In this paper, an approach has been proposed for compositional adaptation of the cases based on the semantic relations between the components in each case. Within this scope, a problem situation comprising some components with semantic nature operates over the stored cases to make a reasonable use of the related components and the corresponding similarities with its own components. In this regard...
Internet's mature has changed the behavior of consumers. Most of consumers before purchase will queries opinion on the Internet. Vehicle is high priced and durable merchandise, so consumer would be more prudent to view Internet opinion before they buy. Past research has pointed out eWOM (electronic Word-of-Mouth) and customer satisfaction will influence purchasing decision, 70% of consumers believe...
Demand forecasting for replenishment is one of the main issue for retail industry in terms of optimizing stocks, minimizing costs and also for reducing stock out problem. Better forecasting for demands, means maximizing sales and result with more revenue and profit for retailers. An other critical result of the stock out problem is of course dissatisfied customers and customer churn effect to retailers...
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