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 ubiquitous growth of Internet of Things (IoT) and its medical applications has improved the effectiveness in remote health monitoring systems of elderly people or patients who need long-term personal care. Nowadays, chronic illnesses, such as, stroke, heart disease, diabetes, cancer, chronic respiratory diseases are major causes of death, in many parts of the world. In this paper, we propose a...
With the large-scale photovoltaic power plants and centralized network, more and more new energy grid problem arises. Distributed photovoltaic power plants connected to the grid, and can lead to accidents such as power grid voltage instability occurs at a certain probability. The fundamental reason is the unreliability of distributed photovoltaic power generation. Solar irradiance and ambient temperature...
Almost all studies on course recommenders in online platforms target closed online platforms that belong to a University or other provider. Recently, a demand has developed that targets open platforms. Such platforms lack rich user profiles with content metadata. Instead they log user interactions. We report on how user interactions and activities tracked in open online learning platforms may generate...
Plane of array irradiance derived from common measurement sources is not usually directly applicable in modelling the energy yield of photovoltaic systems. Corrections to an effective irradiance value are required due to the differences in the spectral and angular response of irradiance measurement instruments (typically pyronometers or reference cells) when compared to the installed system. Empirical...
Pregnancy complications are a leading cause of maternal deaths in the present era. There is a rising need to protect pregnant women from possible threats posed by abnormalities induced by changing physiological parameters. Pregnancy is a delicate stage and requires acute medical attention and care. Decision tree classification algorithms are popular and powerful methods most suitable for the medical...
The paper presents the results of research related to the efficiency of the so called rule quality measures which are used to evaluate the quality of rules at each stage of the rule induction. The stages of rule growing and pruning were considered along with the issue of conflicts resolution which may occur during the classification. The work is the continuation of research on the efficiency of quality...
There has been growing interest in location-based services and indoor localization in recent years. While several smartphone based indoor localization techniques have been proposed, these techniques have many shortcomings related to accuracy and consistency. These prior efforts also ignore energy consumption analysis which is a crucial quality metric in resource-constrained smartphones. In this work,...
Markets are a medium for information exchange between buyers and sellers. Prediction markets exploit the information transmission property of markets to improve forecasts of future events. Participants in a prediction market buy and sell assets that pay off if the underlying event occurs. Prices in a prediction market can be interpreted as consensus probabilities for the underlying events. Prediction...
The inherent nondeterminism present in reduction operations on an exascale system, coupled with the nonassociativity of floating-point arithmetic, makes achieving reproducible results difficult or impossible. Work investigating the irreproducibility phenomenon has generally proceeded along one of two veins: (1) development of algorithms that produce reproducible numerical results irrespective of nondeterminism...
Effective prediction of unobservable degradation can assist to schedule preventive maintenance and reduce unexpected downtime for realistic industrial systems. In this paper, an extended time-/condition-based framework is proposed for the Probability Density Function (PDF) prediction of unobservable industrial wear. Furthering our earlier work of unobservable degradation estimation, a stage-based...
Genetic changes that may be associated with complex diseases are tried to be determined by means of many genome-wide association studies. Single Nucleotide Polymorphisms (SNPs) are used primarily in these studies since they comprise a large part of these genetic changes. Statistical importance of the genome-wide association study is directly related to the number of individuals and SNPs. However,...
Collaborative filtering algorithm is currently the most widely used and a very efficient technology in personalized recommendation system. To overcome several defects in the research of the traditional Item-based collaborative filtering algorithm, this paper presents a optimized algorithm in two aspects, which are the selection of neighbors and the prediction of ratings. Firstly, different numbers...
In this work a real-time indoor localisation system based on the Viterbi algorithm is developed. This Viterbi principle is used in combination with semantic data to improve the accuracy: i.e., the environment of the object that is being tracked and an adjustable maximum speed. The developed algorithm was verified by simulations and with experiments in a building-wide testbed for sensor and WiFi experiments...
Machine Leaning (ML) plays an important role in the electronic data management. It is always costly and difficult to manage the data manually without adopting ML or with ML using metadata. Many ML algorithms have been proposed to solve different data management issues, but the prediction of the confidential data and non- confidential data in a data file is still a challenging research gap. A file...
Tens of thousands of pictures are taken at different locations throughout the year. People often visit places and take pictures to remember their visits. We believe that the seasonal travel patterns of people to specific locations will create a correlation between a location and the season of the images taken in that location. For example, fewer people visit Bear Valley, California during the summer...
Associative Classification is a recent and rewarding approach which combines associative rule mining and classification. This technique has attracted many researchers as it derives accurate classifier with effective rules. Associative classifiers are useful for application where maximum predictive accuracy is desired. Increasing access to huge datasets and corresponding demands to analyze these data...
Rainfall prediction is an important part of weather prediction. Compared to conventional methods predicting rainfall rate, the approach applying historical records and data mining technology shows obviously advantage in computing cost. Many excellent works have been done attempting to build predicting model with data mining methods, however, most of them just test the predicting accuracy on data set...
Virtualized cloud systems are prone to performance anomalies due to various reasons such as resource contentions, software bugs, and hardware failures. It will be a daunting task for system administrators to manually keep track of the execution status of a large number of virtual machines all the time. Anomaly prediction is an effective approach to enhancing availability and reliability of Cloud infrastructures...
This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR)...
Classification is an important technique in data mining. The K-Nearest neighbor (K-NN) algorithm is a memory based algorithm and is capable of producing satisfactory results when applied on certain data but the distance measures used in this algorithm is not capable of handling the data sets containing the uncertain attribute values. Data uncertainty is common in real word applications. In this paper...
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.