Recent developments in computer science enable algorithms previously perceived as too time-consuming to now be efficiently used for applications in bioinformatics and life sciences. This work focuses on proteins and their structures, protein structure similarity searching at main representation levels and various techniques that can be used to accelerate similarity searches. Divided into four parts, the first part provides a formal model of 3D protein structures for functional genomics, comparative bioinformatics and molecular modeling. The second part focuses on the use of multithreading for...
Recent developments in computer science enable algorithms previously perceived as too time-consuming to now be efficiently used for applications in bi...
This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing,...
This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the m...
This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4)...
This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text...
Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for computer-generated images.
Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for comput...
To support smart vehicular services especially in the future driverless era, the vehicular networks are expected to support high-bandwidth content delivery and reliable accessibility of multifarious applications. However, the limited radio spectrum resources, the inflexibility in accommodating dynamic traffic demands, and the geographically constrained fixed infrastructure deployment of current terrestrial networks pose great challenges in ensuring ubiquitous, flexible, and reliable network connectivity. This book investigates mobile edge content caching and delivery in heterogeneous...
To support smart vehicular services especially in the future driverless era, the vehicular networks are expected to support high-bandwidth conten...
This book aims to sort out the clear logic of the development of machine learning-driven privacy preservation in IoTs, including the advantages and disadvantages, as well as the future directions in this under-explored domain. In big data era, an increasingly massive volume of data is generated and transmitted in Internet of Things (IoTs), which poses great threats to privacy protection. Motivated by this, an emerging research topic, machine learning-driven privacy preservation, is fast booming to address various and diverse demands of IoTs. However, there is no existing literature...
This book aims to sort out the clear logic of the development of machine learning-driven privacy preservation in IoTs, including the advantages and...
This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs.
The authors first classify the existing works of CSS over HINs according to the classic cohesiveness metrics such as core, truss, clique, connectivity, density, etc., and then extensively...
This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous informatio...
The remarkable progress in computer vision over the last few years is, by and large, attributed to deep learning, fueled by the availability of huge sets of labeled data, and paired with the explosive growth of the GPU paradigm. While subscribing to this view, this work criticizes the supposed scientific progress in the field, and proposes the investigation of vision within the framework of information-based laws of nature.
This work poses fundamental questions about vision that remain far from understood, leading the reader on a journey populated by novel challenges resonating...
The remarkable progress in computer vision over the last few years is, by and large, attributed to deep learning, fueled by the availability of hug...
The 5G technology has been commercialized worldwide and is expected to provide superior performance with enhanced mobile broadband, ultra-low latency transmission, and massive IoT connections. Meanwhile, the edge computing paradigm gets popular to provide distributed computing and storage resources in proximity to the users. As edge services and applications prosper, 5G and edge computing will be tightly coupled and continuously promote each other forward.
Embracing this trend, however, mobile users, infrastructure providers, and service providers are all faced with the energy...
The 5G technology has been commercialized worldwide and is expected to provide superior performance with enhanced mobile broadband, ultra-low laten...
The volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification, object detection and recognition.
Astronomical study starts with imaging from recorded raw data, followed by image processing, such as image reconstruction, inpainting and generation, to enhance imaging quality. We study deep learning for solar...
The volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte ...
