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Modern drug discovery organizations generate large volumes of SAR data. A promising methodology that can be used to mine this chemical data to identify novel structure-activity relationships is the matched molecular pair (MMP) methodology. However, before the full potential of the MMP methodology can be utilized, a MMP identification method that is capable of identifying all MMPs in large chemical...
Most of the available robot programming by demonstration (PbD) approaches focus on learning a single task, in a given environmental situation. In this paper, we propose to learn multiple tasks together, within a common environment, using one of the available PbD approaches. Task-parameterized Gaussian mixture model (TP-GMM) is used at the core of the proposed approach. A database of TP-GMMs will be...
Host based Intrusion Detection Systems (HIDSs) analyze the sequence of system calls in the trace and audit log files to identify intrusive system processes. HIDSs use the frequency analysis of n-gram terms in the system call traces to identify intrusive processes. However, they are computation and resource intensive as they need to analyze a large number of n-gram input features to differentiate between...
Recent studies show that drug-disease associations provide important information for drug discovery and drug repositioning. Wet experimental identification of drug-disease associations is time-consuming and labor-intensive. Therefore, the development of computational methods that predict drug-disease associations is an urgent task. In this paper, we propose a novel computational method named NTSIM,...
The aim of this paper is to introduce a semantic methodology using ontology in order to improve results of data mining in judicial decisions database. An intelligent and automatic method to search for sentences in lawsuits related to the one in trial is presented. A judicial ontology is built with and without rules from experts. The method can provide judiciary celerity, seeking to solve the yearning...
In this paper we present a reference architecture for ETL stages of EDM and LA that works with different data formats and different extraction sites, ensuring privacy and making easier for new participants to enter into the process without demanding more computing power. Considering scenarios with a multitude of virtual environments hosting educational activities, accessible through a common infrastructure,...
Security is a major challenge in Cloud Computing. Attacks exploiting resource virtualization vulnerabilities such as cross-VM side-channel, VM escape, and VM hopping constitute significant threats. Hosted VMs may act as a potential attack-source against neighboring VMs or cloud infrastructure. Inspired by the sea-chameleons camouflaging process to evade predators, in this paper we propose an Online...
SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
In this paper, we explore the use of recent conditional generative adversarial network framework for image to image translation applied to the domain of heterogeneous face sketch synthesis. Since the inception of the adversarial framework in 2014, great success has been noted with several variants till date. Further, we introduce a new dataset for composite sketch images. In particular we explore...
Overhead distribution lines are usually subject to voltage transients during thunderstorms. Lightning flashes, whether direct or indirect, are one of the main causes of power quality disturbances on the electric grid. In this paper, a methodology to establish a correlation between the incidence point of a lightning flash, the stroke current amplitude and polarity and its effects on the electric distribution...
Industrial use of Model Driven Engineering techniques has emphasized the need for efficiently store, access, and transform very large models. While scalable persistence frameworks, typically based on some kind of NoSQL database, have been proposed to solve the model storage issue, the same level of performance improvement has not been achieved for the model transformation problem. Existing model transformation...
This paper discusses the semantic network approach to identify affects in natural language input and focusses on representing spatio-temporal affect information. It has been observed that this approach performs better in analysis of affect information that can be effectively utilized for the prognosis of human cognitive behavior. The research work in this paper describes a new approach towards simple...
Timely and robust diagnosis of plant diseases and nutrient deficiencies play a major role in management of crop yield. Automation is a low cost alternative to human experts and can help to detect early onset of crop diseases which aids faster decision making and in giving recommendations to farmers to curb yield loss. We have developed a smart-phone based participatory sensing application for agriculture...
Mobile device features such as camera and other sensors are evolving rapidly nowadays. Supported by a reliable communications network, it raises new methods in information retrieval. Mobile devices can capture an image with its camera and pass it to the retrieval systems to get the information needed. This system, called Mobile Content-Based Image Retrieval (MCBIR), generally consists of two parts:...
Despite increasing accessibility of the 3D scanning devices, acquisition of the 2D photographs is still more widely used method to capture human faces. However, many virtual scenarios require 3D representation of the human face. We present an automatic method of the human face reconstruction from a single frontal photograph. Our approach utilizes a database of the precomputed depth images, which we...
The human immune system is incredibly efficient at identifying self- and non-self entities in our bodies. A non-self entity (malicious), once identified, is attacked by particular types of cells to remove the intruder before it can cause damage. Our immune system has components that identify not only non-self entities but also recall old entities that may not have been encountered for a very long...
Some areas in computer science are characterized by a shared base structure for data artifacts (e.g., list, table, tree, graph, model), and dedicated languages for transforming this structure. We observe that in several of these languages it is possible to identify a clear correspondence between some elements in the transformation code and the output they generate. Conversely given an element in an...
The purpose of this research study is to investigate the problems of design and requirements to diagnostic automated systems based on image processing. To realize the research purpose, the authors designed a conceptual model, a use case diagram, and a prototype of automated system object model.
The code behind dynamic webpages often includes calls to database libraries, with queries formed using a combination of static text and values computed at runtime. In this paper, we describe our work on a program analysis for extracting models of database queries that can compactly represent all queries that could be used in a specific database library call. We also describe our work on parsing partial...
Distributed system for sampling and analysis of electroencephalograms is proposed and implemented in alpha state. The system is based on the previously developed database for archiving of the electroencephalograms in Ukrainian National Grid infrastructure. The new components of the system include EEG sensors for laboratory animals, simulations software and data procession algorithms. The first application...
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