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Existing Web API search engines allow for only category-based browsing and keyword or tag-based searches for RESTful services without offering the capability of discovering and composing real-world RESTful services from the viewpoint of application developers. Therefore, we propose a novel approach, referred to as TAD (Transformation-Annotation-Discovery), to address the above issue. TAD firstly transforms...
Post-database searching is a key procedure for peptide spectrum matches (PSMs) in protein identification with mass spectrometry-based strategies. Although many machine learning-based approaches have been developed to improve the accuracy of peptide identification, the challenge remains for improvement due to the poor quality of data samples. CRanker has shown its effectiveness and efficiency in terms...
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...
Barter system is an alternative commerce approach where customers meet at a marketplace in order to exchange their goods or services without currency. E-barter systems, also gain attention with the rise of e-commerce. Barterers search databases for goods and services they need. In this paper, the integration of ontology and agent systems is proposed as a solution for searching in diverse barter databases...
Long transactions, high concurrency, and frequent activity situations occur in many areas. The intermediate process of long transactions in the process of execution is more, in the process, therefore, can not avoid frequent access to the data, the system overhead of the data access process is relatively large, which reduces the efficiency of the system and increase the pressure of the server. The...
In order to improve the quality of teaching of Japanese intensive reading courses, improve the quality of higher education, improve the quality of personnel training, and improve the level of scientific research, strengthen the social service ability, optimize the Japanese intensive reading courses in discipline. Put forward the curriculum design of Web network based on the teaching of Japanese intensive...
Warehouse Management Systems (WMS) play a major role in optimizing warehouse logistic processes, archiving merchant trends of supply and demand, and also easen treating of goods which are close to expiring deadline, out of stock, broken or deposited by customers. Since warehouse management systems may be integrated with business intelligence, they may comprise algorithms for optimization of warehouse...
In an iterative and incremental development environment software regression testing plays an important role; it helps to ensure the reliability in the building process of a software product. The optimization of a regression test depends on the size of the test suite to be executed. Regression testing helps to verify existing modifications (fixing bugs) or verify new features added to a software product...
This paper deals with the smart placement of motion sensors in smart homes for Ambient Assisted Living, by considering the sensor technology and cost and respecting specific coverage requirements. The core of the proposed methodology is a decision module that can optimize the sensors placement according to different objectives. More precisely, the main objective is the minimization of costs of the...
Modelling of a database performance depending on numerous factors is the first step towards its optimization. The linear regression model with optional parameters was created. Regression equation coefficients are optimized with the Flower Pollination metaheuristic algorithm. The algorithm is executed with numerous possible execution parameter combinations and results are discussed. Potential obstacles...
Self-organization is critical to enable novel indoor Location-Based Services (LBSs) for users and businesses in large, complex and unstructured buildings. Inspired by high densities of smartphones in public indoor spaces, in this paper we propose a self-organizing indoor localization approach that allows the use of available WiFi Access Points (APs) and iBeacons in the area to improve location accuracy...
With the growth of mobile Internet, online health forums become more accessible for patient to health related discussions, subsequently host rich resources of drug-drug interactions (DDIs). However, traditional methods are not feasible for the large volume online data. They are designed for highly structured data sources such as clinical trials and spontaneous reporting systems, whose inherent limitations...
Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression,...
Demand response (DR) programs have emerged as a potential key enabling ingredient in the context of smart grid (SG). Nevertheless, the rising concerns over privacy issues raised by customers subscribed to these programs constitute a formidable hurdle towards their effective deployment and utilization. This has driven extensive research to resolve the hindrance confronted, resulting in a number of...
In this paper we approach the problem of scene recognition in paintings. We tackle this task with the aid of Convolutional Neural Networks and a large database consisting of around 80,000 paintings. The main purpose is to identify an efficient method to enlarge the database by domain transfer from photographic content to artistic content. Thus, we discuss the practical capabilities of a recent method...
In recent years, video surveillance technology has become ubiquitous in every sphere of our life. But automated video surveillance generates huge quantities of data, which ultimately does rely upon manual inspection at some stage. The present work aims to address this ever increasing gap between the volumes of actual data generated and the volume that can be reasonably inspected manually. It is laborious...
Most existing hashing methods resort to binary codes for similarity search, owing to the high efficiency of computation and storage. However, binary codes lack enough capability in similarity preservation, resulting in less desirable performance. To address this issue, we propose an asymmetric multi-valued hashing method supported by two different non-binary embeddings. (1) A real-valued embedding...
First-person videos (FPVs) in daily living help us to memorize our life experience and information systems to process daily activities. Summarizing FPVs into key frames that represent the entire data would allow us to remember our memory in the past and computers to efficiently process the data. However, most video summarization approaches only use visual information, even though our daily activities...
Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
The users of information systems often have to deal with outliers in their data. Such outliers can have negative (i.e. abnormal observations) or positive (i.e. detection of new features) impact on their work. Despite the fact, that several methods of outlier detection already exist, there is still a need to improve them. In this work we propose a method for evolutionary outlier detection. The novelty...
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