Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
There are many examples in the literature of scorecards derived from clinical data. These scorecards are proposed for use by health professionals to stratify patients into risk categories and are often compared using receiver operating characteristic (ROC) curves and their associated areas (AUC). This paper analyses random scorecards and shows that the underlying distributions and therefore statistical...
Wrapper based gene selection methods tend to obtain better classification accuracy than filter methods, while it is much more time consuming. Accelerating this process without degrading the high accuracy is of great value for researchers to better analyze gene expression profiles. In this paper, we explore to reduce the time complexity of wrapper based gene selection method with K-Nearest-Neighbor...
There is an important relationship between the stability of protein complex and hot region. Research has shown that in protein-protein interaction (PPI), residues are denser around the hot region. Therefore, this paper proposed an algorithm based on Gi statistics, regional division rule and regional amplification principle to form residue dense region (RDR); Then, according to the results of cascade...
Existing personalized recommendation systems are facing many problems such as cold start, data sparseness and high complexity. Users' interests exist more widely and are more personalized compared with purchasing history in traditional recommendation systems. Thus, applying the interest graph in the recommendation process can make up certain shortages. This paper builds the mechanism of a user-interest-goods...
This paper describes SPICE-compatible macromodels to model the nonlinear behavior of operational amplifiers (Op Amp) and current feedback operational amplifiers (CFOA). The proposed macro-models include not only those performance parameters more important of the Op Amp and CFOA like the dynamic range, slew-rate, DC gain and gain-bandwidth product, but parasitic resistors and capacitors associated...
The Texture Feature Extraction (TFE) plays an important role in satellite image processing application. This paper proposes a novel method for Satellite Imagery Classification. Our proposed method is a combination of Local Binary Pattern (LBP) and Fuzzy c-means classification algorithm. Local Binary Pattern is calculated by thresholding a 3 × 3 neighborhood of each pixel by the center pixel value...
Texas A&M University Corpus-Christi is undergoing a major university expansion on its island campus. The university's Conrad Blucher Institute for Surveying and Science was tasked with providing the spatial information needs related to this expansion. To meet this objective, a small-scale Unmanned Aircraft System (UAS) equipped with a small-format digital camera is utilized to acquire aerial imagery...
Big data is a set of very large and complex data that is hard to load on computers. The main challenge in big data world is related to their search, categorize and analyze specially, when they are unbalanced. Despite, there are a lot of works in the field of big data but analyzing unbalanced big data is still a fundamental challenge in this area. In this paper we try to solve the problem of RSIO-LFCM...
The objective of the present paper is to demonstrate the potential of Computational Intelligence in applications pertaining to the automatic identification - categorisation of Cardiotocograms using Machine Learning Algorithms and Artificial Neural Networks whose purpose is to distinguish between healthy or pathological cases leading to mortality during birth or fetal cerebral palsy. Interest is also...
In this paper, an algorithm is presented for extracting fuzzy rules from the Breast Cancer dataset. To extract fuzzy rules, an imitation based evolutionary algorithm is used called Krill Herd (KH). The KH algorithm is converted to a binary algorithm here, and is used for the classification problem with innovation, named Binary Krill Herd-based Fuzzy Rule Miner (BKH-FRM). Choosing the best krill and...
Malicious program or malware is a computer program which was written intentionally to harm computing system. Malware protection involves several sub-tasks namely Monitoring, Prevention, Analysis, Detection, Removal and Recovery. This paper proposes a static heuristic based scoring system that gives a maliciousness score to portable executable files. Malicious score can be used at different stage of...
Sentence similarity measures play an increasingly important role in text-related research and applications in areas such as text mining, Web page retrieval, and dialogue systems. Existing methods for computing sentence similarity have been adopted from approaches used for long text documents. These methods process sentences in a very high-dimensional space and are consequently inefficient, require...
An improved classification method based on KMeans using HSV color feature is introduced in this paper. It is implemented by extracting three color features (hue, saturation, value) for K-Means clustering. Compared with the traditional K-Means clustering, the experimental results turn out that our proposed method is better than K-Means in classification accuracy and performance.
A novel image recognition method based on the improved BDBN (Bilinear Deep Belief Network) model is presented, optimized with a MKL (Multiple Kernel Learning) strategy. All kernel functions in MKL are replaced by hierarchical feature representations, and the number of kernels is set to the number of layers of BDBN. The method is performed on the standard Caltech101 image dataset. The experiments show...
Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. The former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically,...
Automatic extraction of hyponymy relations between concepts in an ontology is significant for ontology learning and knowledge organization. In this paper, we propose a fusion approach of hyponymy relation extraction in patent domain, using Relative Decoration Degree (RDEG) to extract high precision relations, and then Association Rule (AR) to enrich those relations. We use Cilin to extend a word to...
Sentence similarity compute is an important part in question answering system based on frequency asking questions. The accuracy of the existing sentence similarity algorithm needs to be improved, so this paper presents a revised question similarity compute method. We combine the word order feature with vector space model algorithm. When we use the VSM to compute the question similarity, we propose...
In modern distributed measure and control systems, transmission and processing of real-time data requires each communication node to work in a unified time base in order to ensure the timeliness of data transmission. IEEE1588 precision clock synchronization protocol (PTP) is aimed to solve the high-precision clock synchronization, which supports software or hardware implementation. This paper analyzes...
Along with the increasing popularity of social web sites, users rely more on the trustworthiness information for many online activities among users. However, such social network data often suffers from severe data sparsity and aren't able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Nowadays, trust prediction is...
Query expansion methods based on search logs could improve the quality of search results to some extends. But when the search logs are sparse, this kind of query expansion methods will have poor quality of search results and are unable to meet the user's search request, etc. This paper presents the search log sparseness oriented query extension method. By introducing the determination rule of data...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.