An Overview of Classification Techniques for Human Activity Recognition

In this paper, both classic and less commonly used classification techniques are evaluated in terms of recognizing human activities recorded in the PAMAP2 dataset that was created using three inertial measurement units. Seven algorithms are compared in terms of their accuracy performance with the best classifier being based on the Orthogonal Matching Pursuit algorithm that has been modified to remove the limitation of the number of training vectors per class present in its original version. The overview shows that human activities as defined by the PAMAP2 dataset can be recognized reliably even without any prior data preprocessing

Parallel Mapper

The construction of Mapper has emerged in the last decade as a powerful and effective topological data analysis tool that approximates and generalizes other topological summaries, such as the Reeb graph, the contour tree, split, and joint trees. In this paper, we study the parallel analysis of the construction of Mapper. We give a provably correct parallel algorithm to execute Mapper on multiple processors and discuss the performance results that compare our approach to a reference sequential Mapper implementation. We report the performance experiments that demonstrate the efficiency of our method

FTKHUIM: A fast and efficient method for mining top-k high-utility itemsets

High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility threshold value. Determining a suitable threshold value to obtain the expected results is not a simple task and requires spending a lot of time. For common users, it is difficult to define a minimum threshold utility for exploring the right number of HUIs. On the one hand, if the threshold is set too high then the number of HUIs would not be enough. On the other hand, if the threshold is set too low, too many HUIs will be mined, thus wasting both time and memory. The top-k HUIs mining problem was proposed to solve this issue, and many effective algorithms have since been introduced by researchers. In this research, a novel approach, namely FTKHUIM (Fast top k HUI Mining), is introduced to explore the top-k HUIs. One new threshold-raising strategy called RTU, a transaction utility (TU)-based threshold-raising strategy, has also been shown to rapidly increase the speed of top-k HUIM. The study also proposes a global structure to store utility values in the process of applying raising-threshold strategies to optimize these strategies. The results of experiments on various datasets prove that the FTKHUIM algorithm achieves better results with regard to both the time and search space needed.Web of Science1110480510478

Content Based Image Search with Vector Quantization

Fast and efficient query of information based on image contents is one of the major challenges in visual information systems. Features pace based the Vector Quantization (VQ). The indexing system extracts VQ features from each image to be inserted in the database. The size of the feature vector is much smaller than the image size but the feature vector accurately represents the image

Modeling of light propagation in head tissues with taking into account anisotropy of scattering for optimization of sources and detectors location in the brain-computer interface baded in near infrared spectroscopy

Описывается применение метода Монте-Карло моделирования для уточнения параметров прохождения излучения ближней инфракрасной области через ткани головы, необходимых для оптимизации работы интерфейсов мозг-компьютер. В работе использовалась четырёхслойная сферическая модель головы, состоящая из слоёв кожи, кости, серого и белого вещества. Получены зависимости параметров регистрируемого излучения от расстояния между источником и детектором.The application of the Monte Carlo simulation method was described to specify the parameters of the near infrared light propagation through the head tissues necessary to optimize the operation of the brain-computer interfaces. Four-layered spherical head model, consisting of layers of skin, bone, gray and white matter, was used. The dependences of the parameters of the detected light on the distance between the source and the detector are obtained.Web of Science67455354

Przewidywana moc wyjściowa elektrowni fotowoltaicznej określona przy użyciu zasad rozmytych

Photovoltaic Power Plants (PVPP) are classified as power energy sources with non-stabile supply of electric energy. It is necessary to back up power energy from PVPP for stabile electric network operation. We can set an optimal value of back up power energy with using a variety of prediction models and methods for PVPP Power output prediction. Fuzzy classi?ers and fuzzy rules can be informally defined as tools that use fuzzy sets or fuzzy logic for their operations. In this paper, we use genetic programming to evolve a fuzzy classi?er in the form of a fuzzy search expression to predict PVPP Power output.Elektrownie fotowoltaiczne (EF) są klasyfikowane jako źródła prądu elektrycznego o niestabilnej dostawie energii elektrycznej. Dla stabilnej pracy sieci elektrycznej konieczne jest wspieranie dostawy prądu z EF. Możemy ustalić optymalną wartość wspierającej dostawy prądu, stosując różne modele przewidywania i metody dla predykcji mocy wyjściowej z EF. Możliwe jest nieformalne określenie rozmytych klasyfikatorów i zasad jako narzędzi do ich działania, opartych na zbiorach rozmytych i logice rozmytej. W tej pracy stosujemy genetyczne programowanie do opracowania klasyfikatora rozmytego wyrażenia poszukiwania mocy wyjściowej EF