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Discovering similar diseases is very helpful for revealing the pathogenesis of diseases and making direction in drug use. And related diseases are often triggered by disease-related genes. Therefore, function interaction networks structured by disease-related genes are suitable for measurement of disease similarity, and some methods have utilized the advantage of function interaction of disease-related...
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...
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...
The library remote information services of higher educational establishments of America are analysed. The study is based on benchmarking and weights of alternatives methods that allow to identify the group of library leaders in providing quality information services.
Early design-space evaluation of computer-systems is usually performed using performance models such as detailed simulators, RTL-based models etc. Unfortunately, it is very challenging (often impossible) to run many emerging applications on detailed performance models owing to their complex application software-stacks, significantly long run times, system dependencies and the limited speed/potential...
Agricultural textures are in the interest of classification in image processing. Natural images have unique textural shapes inside which cause a tough problem for classification. This paper tests different feature extraction and classification approaches to serve a benchmarking on several agricultural databases like seeds and leaves. Features are obtained using Local Binary Pattern (LBP), Gray Level...
Searching persons in large-scale image databases with the query of natural language description has important applications in video surveillance. Existing methods mainly focused on searching persons with image-based or attribute-based queries, which have major limitations for a practical usage. In this paper, we study the problem of person search with natural language description. Given the textual...
Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicle. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. In this paper, we attempt to fill this research gap to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based...
Dynamically controlling processor frequency to save power while meeting customer Service-Level Objectives (SLOs) can reduce the cost of goods sold for cloud service providers. However, resource governance for Online Transaction Processing (OLTP) workloads in the cloud is complicated by throughput constraints, latency constraints, shallow sleep states that lower processor utilization, and (often) isolation...
In this paper, we present a new benchmark (Menpo benchmark) for facial landmark localisation and summarise the results of the recent competition, so-called Menpo Challenge, run in conjunction to CVPR 2017. The Menpo benchmark, contrary to the previous benchmarks such as 300-W and 300-VW, contains facial images both in (nearly) frontal, as well as in profile pose (annotated with a different markup...
Leveraging Virtual Machine (VM) technologies to host multiple Web applications on the same physical machine can improve the resource utilization and thus save a cloud provider's provisioning cost. By allocating and scheduling virtual CPU (vCPU) resources for running VMs, a hosted Web application may achieve varying performances. Thus, when facing an end user with a specific SLA (Service Level Agreement)...
Hadoop is now the de facto standard for storing and processing big data, not only for unstructured data but also for some structured data. As a result, providing SQL analysis functionality to the big data resided in HDFS becomes more and more important. Hive is a pioneer system that supports SQL-like analysis to the data in HDFS. However, the performance of the early-version of Hive is not satisfactory...
Data security has become an issue of increasing importance, especially for Web applications and distributed databases. One solution is using cryptographic algorithms whose improvement has become a constant concern. The increasing complexity of these algorithms involves higher execution times, leading to an application performance decrease. This paper presents a comparison of execution times for three...
The MNIST dataset has become a standard benchmark for learning, classification and computer vision systems. Contributing to its widespread adoption are the understandable and intuitive nature of the task, the relatively small size and storage requirements and the accessibility and ease-of-use of the database itself. The MNIST database was derived from a larger dataset known as the NIST Special Database...
Text in natural scenes provides many information for peoples and presents an essential tool to interact with their environment. Therefore, recognizing text existing in camera-captured images has become an important issue for many researches in the last decades. Currently, there isn't any available dataset of Arabic script text images in the wild. Since our aim is to help the research community in...
Early design space evaluation of computer systems is usually performed using performance models (e.g., detailed simulators, RTL-based models, etc.). However, it is very challenging (often impossible) to run many emerging applications on detailed performance models owing to their complex software-stacks and long run times. To overcome such challenges in benchmarking these complex applications, we propose...
Key-value stores are an important component of cloud applications. These NoSQL databases typically do not support ACID transactions, hence, their applications have diverged from traditional database workloads and are not well represented by benchmarks like TPC-C. In this context, YCSB emerged as the de facto benchmark for cloud serving stores, supporting a wide variety of synthetic workloads. However,...
Blockchain is an emerging technology for sharing transactional data and computation without using a central trusted third party. It is an architectural choice to use a blockchain instead of traditional databases or protocols, and this creates trade-offs between non-functional requirements such as performance, cost, and security. However, little is known about predicting the behaviour of blockchain-based...
Two open source distributed machine learning/deep learning platforms, namely H2O and Apache SINGA, compared their deep learning performances using multilayer perceptron on the classic MNIST database for hand written digits recognition. However, the results reported by both parties differ and neither of them can repeat the results reported by the other side. This paper is an independent study of the...
The CloudMdsQL polystore provides integrated access to multiple heterogeneous data stores, such as RDBMS, NoSQL or even HDFS through a big data analytics framework such as MapReduce or Spark. The CloudMdsQL language is a functional SQL-like query language with a flexible nested data model. A major capability is to exploit the full power of each of the underlying data stores by allowing native queries...
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