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 increasing adoption of electric vehicles (EVs) presents both challenges and opportunities for the power grid, especially for distribution system operators (DSOs). The demand represented by EVs can be significant, but on the other hand, sojourn times of EVs could be longer than the time required to charge their batteries to the desired level (e.g., to cover the next trip). The latter observation...
Network middleboxes are difficult to manage and troubleshoot, due to their proprietary monolithic design. Moving towards Network Functions Virtualization (NFV), virtualized middlebox appliances can be more flexibly instantiated and dynamically chained, making troubleshooting even more difficult. To guarantee carrier-grade availability and minimize outages, operators need ways to automatically verify...
A physics-based and explicit approximation for surface potential of the amorphous InGaZnO (a-InGaZnO) thin-film transistors (TFTs) with considering both the Gaussian deep and exponential tail distribution of trap states is developed in the case of partial depletion. The analytical calculation of the surface potential is one-piece and suitable for circuit simulations. Based on the surface potential,...
Mozambique has been affected by multiple conflicts since colonial rule. This paper proposes an e-PAZ Early Warning System that helps in identifying potential conflicts. The system filters conflict related news from social media. It also offers geographic and socioeconomic information of the conflict zone. It provides qualitative and quantitative analysis on the past conflicts and gives user an open...
AdLocus is an APP developed by HyXen Company for mobile advertisements. This advertising software can push the message to the target users within specified locations. Based on the real big data provided by AdLocus, we design a dynamic advertisements recommendation system to increase the advertising efficiency. The proposed method uses the regression models and the click probability to recommend the...
Often, remote locations are not within close proximity to a mains power grid. A common solution to providing electricity in remote areas is diesel generation. Historically, it is a type of power generation that is proven reliable, but not without adverse environmental impacts. Diesel generation is not capital intensive. However, it can have long term negative financial impacts as well as producing...
Modeling wind generation for use in many power system applications requires a massive database of historical wind speeds so that the stochastic nature of the wind at a particular site can be accurately analyzed. The alternative is to use reliable estimates of a probability distribution function (PDF) that can preserve the variable characteristics of wind speed and generate the desired synthetic data...
Data-driven respiratory gating was previous developed to extract respiratory information directly from PET listmode data. It was also shown that different regions may contribute differently to the accuracy of the motion signal, affecting the successful rate of this method. The goal of this study is to develop and evaluate methods that automatically determine the optimum regions to acquire respiratory...
For making Mobile ad hoc network (MANET) more energy efficient swarm intelligence is used as a base and the clustered based approach as Bee-Ad Hoc-C which is an evolution from Bee-Ad-Hoc has been chosen as the best method in our previous work along with Stable Cluster Maintenance Scheme. In the proposed method parallel routing has been considered to improve the scalability of the system, reduce the...
The concept of pairing confidential-relevant variables (connected variables) using ridge regression and bootstrap sampling has recently been proposed for developing perturbation models to data privacy in cyber-physical systems. In this approach, a single set of perturbation parameters for all the pairs of connected variables has been used to achieve trade-off between data confidentiality and classification...
While addressing real-world issues, there is a significant quantity of domain knowledge available in prior which helps in yielding different perspectives on various characteristics related to the issue. At the same time, several types of machine learning methods do not depend on such prior explicitly expressed domain information. However, such methods require especially in case of operating learning...
Feature selection is one of the techniques in machine learning for selecting a subset of relevant features namely variables for the construction of models. The feature selection technique aims at removing the redundant or irrelevant features or features which are strongly correlated in the data without much loss of information. It is broadly used for making the model much easier to interpret and increase...
This paper presents a texture evaluation system for nursing-care paste foods with a biomimetic approach. To artificially reproduce human oral processing, an elastic imitation tongue is introduced to the compression test device of paste food. During the compression, the tongue is passively deformed and holds a paste sample. Such a tongue behavior varies with respect to characteristics of paste food...
DFAs (Deterministic Finite Automata) and DTMCs (Discrete Time Markov Chain) have been proposed for modeling Modbus/TCP for intrusion detection in SCADA (Supervisory Control and Data Acquisition) systems. While these models can be used to learn the behavior of the system, they require the designer to know the appropriate amount of training data for building the model, to retrain models when configuration...
In this paper, the parameter λ would be introduced to forecast grey number sequence that was based on the paper with known whitenization weight function published by Bo Zeng. We use variable weight instead of no-preference generation. So the most appropriate parameter to build the DGM (1,1) would be chose by GA. Then an improved grey prediction model for forecasting interval grey number is proposed...
For many industrial production processes obeying certain statistical laws, a new method of establishing a SISO control model is put forward based on pattern recognition technology. Firstly, k-means clustering algorithm is used to partition input and output data collected into several classes respectively. Secondly, the distance between two classes is described by the distance of the two class centers...
A smart home system can provide better services to assist users if it knows what user activities will occur beforehand. Early research in activity prediction has indicated that the result of prediction is unique, but the accuracy remains unsatisfactory if only one result is considered. To solve this problem, this paper proposes a method of leveraging multiple models. In this work, we use a Bayesian...
Data streams are rapidly and constantly growing. Analysis of rapidly changing data streams is quite difficult since the amount of data increases in timely manner. Individual patient records provide a vital resource for health research for the benefit of society, such as understanding the association between human immune system and viruses. As the patient records have been constantly growing, data...
Prior work in statistical crime prediction has not investigated micro-level movement patterns of individuals in the area of interest. Geotagged social media implicitly describe these patterns for many individuals; however, methods of extracting such patterns and integrating them into a statistical model remain undeveloped. This paper presents methods and experiments that begin to fill this gap. We...
Motion data is quickly expanding its application scope, following the recent advancements in smart sensing technology. In particular, it has been shown to be helpful for objective measurement and assessment of surgical dexterity among users at different levels of training. The goal is to allow trainees to evaluate their performance based on a reference set of hand movements. Similar to other multimedia...
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.