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Proteins interact with each other to regulate their functionality and localization. The accumulated protein interaction evidences are represented by protein interaction network using a graph abstraction. Topological properties of protein interaction networks have been explored to characterize proteins and predict undiscovered interactions. Meanwhile, many researchers have tried to explain how protein...
Drug development using plant sources is an important and fast evolving area. Plants contain valuable phytochemicals that possess a wide variety of curative functions including antibacterial, antifungal, anti-carcinogenic, enzyme stimulating, and many more. The growing prevalence of chronic diseases and rising health care costs have renewed the interests of many researchers to collect, store and retrieve...
Adverse drug reactions (ADRs) represent one of the main health and economic problems in the world. With increasing data on ADRs, there is an increased need for software tools capable of organizing and storing the information on drug-ADR associations in a form that is easy to use and understand. Here we present a step by step computational procedure capable of extracting drug-ADR frequency data from...
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,...
Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated set of APIs (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL APIs provide accelerated kernels for local, global as well as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end...
Identification of the correct medicinal plants that goes in to the preparation of a medicine is very important in ayurvedic medicinal industry. The main features required to identify a medicinal plant is its leaf shape, colour and texture. Colour and texture from both sides of the leaf contain deterministic parameters to identify the species. This paper explores feature vectors from both the front...
This paper presents a Pose Invariant Face Recognition algorithm for pose-variance in face databases, which is one of the toughest challenges of any face recognition based biometrics, using a novel feature extraction technique. The feature extraction of the raw images is based upon a novel patch-wise self-similarity measure within an image. The algorithm has been tested upon a Far-infrared (FIR) imaging...
Recently, the problem of the intrusion detection has been largely studied by the computer and networks security communities. Then, the Intrusion Detection System (IDS) becomes a interest topic in research and in particular in machine learning and data mining. In order to improve the classification accuracy and to reduce high false alarm rate from the classical data base like KDD99 or others. In this...
This paper proposes a password security system that allows the host not to store the passwords of its users at its end. Instead it creates and stores a derivative of the password with the help of a bitmap image uploaded by the user during the user creation process. During the login attempts of users, the user is required to enter the password and upload the same image. the proposed system verifies...
In this paper, we propose a novel framework for expression recognition by using salient landmarks induced shape signature. Detection of effective landmarks is achieved by appearance based models. A grid is formed using the landmark points and accordingly several triangles within the grid on the basis of a nose landmark reference point are formed. Normalized shape signature is derived from grid. Stability...
This paper focuses on open set text independent speaker identification which is one of the most challenging subclass of Speaker recognition. The initial stage is similar to closed set speaker identification, where the distortion for each test voice against all train voices are determined. The distortions after normalization is set as decision criteria which eases the process of thresholding. The threshold...
Copy-move forgery detection is one of the most popular type of forgery in multimedia forensics. The attacks copy and paste desired area in the same images. In this paper, we aim to reduce the false matches of detected area of forgery by using the pre-processing methods, such as histogram equalization, smoothing filter with median and Gaussian filter and sharpening filter, combined with the SIFT algorithm...
Malawi Children's Village (MCV) operates a secondary school of approximately 560 students in Mangochi, Malawi, and its strategic goal is to add computer studies into its curriculum. The first step to achieving this goal is for MCV to establish and sustain a teachers-only computer lab. This case study examines the process by which a team of volunteers identified this as the first step, the team's recommendations...
Mobile devices have been helping to empower underserved communities around the world. From bringing information on health and farming to substituting expensive devices, cellular phones and apps have proved to be powerful tools in poverty alleviation and disaster relief. The Mobile Lab at Santa Clara University focuses on developing mobile solutions for social benefit and, in this paper, we describe...
Image geolocalization, inferring the geographic location of an image, is a challenging computer vision problem with many potential applications. The recent state-of-the-art approach to this problem is a deep image classification approach in which the world is spatially divided into cells and a deep network is trained to predict the correct cell for a given image. We propose to combine this approach...
Due to the geomagnetic abnormality in indoor environment, made by various ferrous structural materials such as pipelines, the magnetic signals of a region are regularly different and sustainable. In this paper, we develop an application based on the Android system to implement the indoor geomagnetic positioning. To estimate the pedestrian's position, the real-time geomagnetic sequence measured by...
In this paper we introduce a novel Depth-Aware Video Saliency approach to predict human focus of attention when viewing videos that contain a depth map (RGBD) on a 2D screen. Saliency estimation in this scenario is highly important since in the near future 3D video content will be easily acquired yet hard to display. Despite considerable progress in 3D display technologies, most are still expensive...
A considerable number of indoor positioning systems have been proposed for large-scale environments that extend over several meters. However, there has been less focus on designing an indoor localization system for confined environments where the requirements of reliability and precision are high. The approach discussed in this paper employs a hybrid technique where Received Signal Strength Indicator...
We present a system prototype aimed at lowering the burden of grocery shopping by recommending products according to those currently in a shopping basket, and supporting users in finding their way from their current position to the location of a determined item within the store. On the backend side, retailers can reflect changes in the location of inventory and shelf distribution in the store. These...
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...
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