With the constant rise of data volumes in many disciplines, various new Big data management systems have emerged to provide scalable tools for efficient data integration, processing, and analysis. In this article, we provide an overview of biomedical data integration systems focusing on ontology‐based semantic systems and Big data technologies based systems such as Apache Spark. We also propose a new

There has been a huge increase in interest in blockchain technology. However, little is known about the drivers behind the adoption of this technology. In this article we identify and analyze these drivers, using six real‐world and representative scenarios. We confirm in our analysis that blockchain is not an appropriate technology for some scenarios, from a purely technical point of view. The choice

Distributed data‐parallel processing systems like MapReduce, Spark, and Flink are popular for analyzing large datasets using cluster resources. Resource management systems like YARN or Mesos in turn allow multiple data‐parallel processing jobs to share cluster resources in temporary containers. Often, the containers do not isolate resource usage to achieve high degrees of overall resource utilization

To improve time efficiency for structured environment exploration of multi‐robot systems, a novel coordinated strategy based on predicate logic reasoning is proposed in this paper. The strategy assigns the room with maximal utility to the robot with the optimal exploring property, and realizes cooperative exploration by considering the room capacity. A set of predicate logic reasoning formulas is established

Historic landscape islands are a unique landscape phenomenon in the urbanization and modernization process in Shanghai. Shanghai has been fragmented and isolated at the landscape space level because of islanding, and its historic and cultural values have been broken and weakened. Therefore, it is urgent to implement fusion protection planning. Considering the islanding of urban historic landscape,

Smart contracts can be implemented using either centralized or decentralized (blockchain) platforms. However, for a large class of applications, neither of these two alternatives on its own can provide adequate scalability, performance, quality of service, security, and trust requirements. We argue that for many applications, hybrid solutions that combine both on and off‐blockchain components are more

Wearable devices (WDs) adopting advanced microsensors and IoT technology are facing severe security risks in the process of building wearable healthcare monitoring system. In particular, new requirements are proposed for the security of the identity authentication and key agreement protocol as well as the consumption of computing resources for WDs, such as replay attack, modification attack, server‐spoofing

With the continuous increase of the network scale, the structure of the network has also become complicated. The original community discovery algorithm based on small‐scale static networks has been unable to meet our needs. In order to improve the quality of community division, community discovery algorithms based on multiple optimization functions have been proposed. These multiobjective algorithms

In the purpose of analyzing and checking time constraints in business processes, we propose to model and simulate them in the “discrete event system specification” (DEVS) formalism. The proposed model will contain atomic DEVS models representing the activities, supervised by, other DEVS control models, and based on one to one mapping. Hence, guaranteeing a close concordance with the temporal requirements

The switched reluctance motor (SRM) has the high level of vibration and noise, whose application is greatly limited in many fields. In this article, a novel stator for a SRM is designed to reduce torque ripple and is suitable for one‐directional or low‐speed reverse rotation. On the one hand, a shoe is added to the stator pole side in the rotating forward direction from the completely unaligned to

A (σ,τ)‐directed acyclic mixed graph (DAMG) is a mixed graph, which allows both arcs (or directed edges) and (undirected) edges such that there exist exactly σ source nodes and τ sink nodes, but there exists no directed cycle (consisting of only arcs). Each source (resp. sink) node has at least one outgoing (resp. incoming) arc, but no incoming (resp. outgoing) arc. Moreover any other node is neither

SaaS software performance issue diagnosis aims to classify the type of the performance records. Deep classification method has gained much attention as a way to construct hierarchical representations from a small amount of labeled data. However, there are few researches on how to solve the classification problem of performance issues by using the deep classification method. In addition, shallow classification

The energy consumption of virtualized data centers has grown very fast in last several years. Because a large number of hosts are running in an idle state, virtualized data centers waste a large amount of electric energy. To save more energy for virtualized data centers, an energy‐saving mechanism is proposed based on switching operating mode of physical servers and reserving virtual machines (VMs)

Stream processing is a parallel paradigm used in many application domains. With the advance of graphics processing units (GPUs), their usage in stream processing applications has increased as well. The efficient utilization of GPU accelerators in streaming scenarios requires to batch input elements in microbatches, whose computation is offloaded on the GPU leveraging data parallelism within the same

For the dataset with different sample contributions and different feature importance, it is difficult to acquire a proper cluster structure that covers the entire features of the sample set. To improve the clustering result, a novel weighted fuzzy clustering algorithm based on both samples and generalized entropy features, called SGEF‐WFCM, is proposed in this article, among which a new objective function

The cloud computing paradigm has emerged as the backbone of modern price‐aware scalable computing systems. Many cloud service models are competing to become the leading doorway to access the computational power of cloud providers. Recently, a novel service model, called function‐as‐a‐service (FaaS), has been proposed, which enables users to exploit the cloud computational scalability, left out the

Social question and answer (Q&A) communities or websites, such as Quora, StackOverflow, become popular from the last decade. They provide collected answers in a crowdsourcing way by encouraging the interactive between users. The ranking of answers in such Q&A websites depends on many factors, such as received upvotes, downvotes, publishing time, and so on. When there exist malicious users, they can

Green finance represents a new trend and new direction for future financial development, and it is an innovation and change in the financial field. The role of the financial market in environmental protection has gradually become the consensus of the financial community. Although the total amount of environmental protection investment in China shows a growing trend, the actual environmental protection

In case of sharp road illumination changes, bad weather such as rain, snow or fog, wear or missing of the lane marking, the reflective water stain on the road surface, the shadow obstruction of the tree, and mixed lane markings and other signs, missing detection or wrong detection will occur for the traditional lane marking detection algorithm. In this manuscript, a lane marking detection algorithm

As more and more electronic devices get connected together, whole systems get more complicated in terms of development, maintenance and usage. New principles in design are needed to cope with this complexity. That is why we developed the artificial hormone system (AHS). The AHS enables an autonomous and decentralized task‐allocation among a set of processing elements (PEs). The AHS works good in small‐scaled

While the social network services (SNS) have dominate the ways that people communicate with each other on the Internet, identity impersonation remains to be a serious issue that needs to be solved due to the anonymity in the cyber network. Currently, the potential solution to the problem relies heavily on the administration from the central server, which requires intensive workload of the identity

The precise named entity recognition (NER) is a key component in Chinese clinical natural language processing. Although clinical NER systems have attracted widespread attention and been studied for decades, the latest NER research usually relies on a shallow text representation with one‐layer neural encoding, which fails to capture deep features and limits its performance improvement. To capture more

Intrusion detection is essential to prevent damage to computer systems. However, in recent years, with the development of the network, many complex attack types have appeared, and it has become increasingly difficult to obtain high detection rates and low false alarm rates. In addition, traditional heavily hand‐crafted evaluation datasets for network intrusion detection have not been practical. This

In this article, we proposed an improved region‐based active contour model based on curve evolution theory and variational level set method. Our method can be used to segment image with intensity inhomogeneity, such as medical computed tomography images. Our model contains a local intensity fitting term that makes the evolution curve stop at boundaries of the object and a global expansion term that

Image quality can be measured visually. In the human visual system, a compressed image can be judged by the human eye. Image quality may not be perceived to decline in a region with low compression. However, image quality clearly declines in a region with high compression. As image compression increases, image quality gradually transitions from visually lossless to lossy. In this study, we aim to explain

The current cloud market is dominated by a few providers, which offer cloud services in a take‐it‐or‐leave‐it manner. However, the dynamism and uncertainty of cloud environments may require the change over time of both application requirements and service capabilities. The current service‐level agreement (SLA) management solutions cannot easily guarantee a trustworthy, distributed SLA adaptation due

The performance of biomolecular molecular dynamics simulations has steadily increased on modern high‐performance computing resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations is becoming a bottleneck. To close this gap, we studied the performance of trajectory analysis with message passing interface (MPI) parallelization and the Python

Traditional Chinese medicine (TCM) is found on a long‐term medical practice in China. Rare human brains can fully grasp the deep TCM knowledge derived from a tremendous amount of experience. In this big data era, a big electronic brain might be competent via deep learning techniques. For this prospect, the electronic brain needs to process various heterogeneous data, such as images, texts, audio signals

Distributed denial of service (DDoS) attacks are the most common and harmful attack in the field of network security, the purpose of this paper is to predict the occurrence of DDoS attacks quickly, accurately and effectively. In this paper, the characteristics of DDoS attacks are analyzed in detail, graph model is used to express the structural characteristics of traffic data between the victims and

Uncertain data is widely used in many practical applications, such as data cleaning, location‐based services, privacy protection, and so on. With the development of technology, data has a tendency to high‐dimensionality. The most common indexes for nearest neighbor search on uncertain data are the R‐Tree and the KD‐Tree. These indexes will inevitably bring about “curse of dimension.” Focus on this

Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs) that refer to the same real‐world object (eg, the same person in two different KBs). Several approaches in the literature were developed to perform this process using different algorithmic techniques and search strategies. In this article, we aim to provide the rationale for IM and to survey the existing algorithms

No abstract is available for this article.

This article studies mini‐applications—Minisweep, GenASiS, GPP, and FF—that use computational methods commonly encountered in HPC. We have ported these applications to develop OpenACC and OpenMP versions, and evaluated their performance on Titan (Cray XK7 with K20x GPUs), Cori (Cray XC40 with Intel KNL), Summit (IBM AC922 with Volta GPUs), and Cori‐GPU (Cray CS‐Storm 500NX with Intel Skylake and Volta

Age is one of the most important biological characteristics of the human face. The increase of age coincides with the increase of the aging degree of the face. Face aging synthesis is attracting increasingly more attention from domestic and overseas scholars in the computer vision and computer graphics fields, and it can be integrated into the basic research of face correlation, such as cross‐age face

In information retrieval, learning to rank was originally proposed for ranking retrieved documents according to their relevance by machine learning techniques. In general, it can effectively improve the performance of critical ranking tasks, where the listwise approach is one of the most popular approaches adopted for ranking. However, considering that documents with more relevance receive greater

Sentiment analysis can extract information from many text sources such as reviews, news, and blogs; then it classifies them based on their polarity. Moreover, big data is produced via mobile networks and social media. Applications of sentiment analysis on big data are used as a way of classifying the opinions into diverse sentiment. Accordingly, performing sentiment analysis on big data can be helpful

Recently, a new intelligent algorithm called animal migration optimization (AMO) is proposed. The AMO algorithm, which is inspired by the behavior of animal migration, exhibits good performance on a series of benchmark functions whose dimensionality is less than or equal to 30. However, its performance deteriorates evidently when the dimensionality is more than 30. To overcome this drawback, we proposed

In this article, a new quantum social spider optimization (QSSO) algorithm is proposed. In the QSSO algorithm, we introduce an encoding approach based on bits described on social spider optimization (SSO) and serves as the evolution method of the population space. For the encoding of individuals, the probability amplitude expression of quantum bit is applied to describe the position of individuals

In order to improve the assemblability and reduce the cost of the parts, the material requirements can be applied to the toleranced feature and the datum feature of the coaxiality at the same time in the practical application. How to realize the information exchange between different heterogeneous systems and how to read and explain the semantics of this complex tolerance specification automatically

Aiming at accelerating the convergence speed and enhancing relative poor local search ability of the traditional artificial bee colony algorithm (ABC), this article introduces an ABC with a new elite search strategy. First, we propose a strategy of recording individuals with high performance. Then bees have more chances to learn from a real elite. In the onlooked bee phase, its updating equation is

In recent years, with the rapid development of adversarial learning technology, facial attribute editing has made great success in a number of areas. Realistic visual effect, invariant identity information, and accurate editing area are the three key issues of facial attribute editing. Unfortunately, most researches focus on the former two problems. However, lack of awareness of the accurate editing

GPGPU‐powered supercomputers are vital for various science and engineering applications. On each cluster node, the GPU works as a coprocessor of the CPU, and the computing task runs alternatively on CPU and GPU. Due to this characteristic, traditional task scheduling strategy tends to result in significant workload imbalance and underutilization of GPUs. We design an adaptive scheduling strategy to

Social media networks have revolutionized the way users interact and express their opinion. Obviously, identifying opinion leaders has a widespread applicability. For instance, by detecting leaders, companies can manipulate the public opinion. However, this task is challenging due to the complexity and the ceaseless change of the social networks structure. Yet, existing opinion leaders 'detection methods

Blockchain sharding is a promising approach to solving the dilemma between decentralization and high performance (transaction throughput) for blockchain. The main challenge of blockchain sharding systems is how to reach a decision on a statement among a subgroup (shard) of people while ensuring the whole population recognizes this statement. Namely, the challenge is to prevent an adversary who does

The increasing amount of solid waste is becoming a significant problem that needs to be addressed urgently. The reliable and accurate classification method is a crucial step in waste disposal because different types of wastes have different disposal ways. The existing waste classification models driven by deep learning are not easy to achieve accurate results and still need to be improved due to the

In virtualized environments, such as Clouds, allocating a fixed amount of resources to a job a priori, may result in underutilization of the shared host. Meanwhile, vertical elasticity can be adopted to reduce the impact by resizing virtual machines (VMs) dynamically, in conjunction with suspension and/or migration before the host had been overloaded. In order to reduce the number of such events, but

With the development of internet technologies, social media and mobile devices, short texts have become an increasingly popular medium among users to communicate with friends, search information and review products. Measuring the similarity between short texts is a fundamental task due to its importance in many applications, such as text retrieval, topic discovery, and event detection. However, short

Being part of public transportations, the bike sharing system plays an important role in solving the “last mile” problem. With more advantages than traditional bike sharing systems relying on fixed docks, dockless bike sharing systems are rapidly expanding, which generally operated under cloud‐based architectures. Emerging Things‐Edge‐Cloud (TEC) architectures are showing many advantages than cloud‐based

We propose two acceleration methods, namely, Fused and Gram, for reducing out‐of‐core data access when performing randomized singular value decomposition (RSVD) on graphics processing units (GPUs). Out‐of‐core data here are data that are too large to fit into the GPU memory at once. Both methods accelerate GPU‐enabled RSVD using the following three schemes: (1) a highly tuned general matrix‐matrix

Prognostics and health management enables the prediction of future degradation and remaining useful life (RUL) for in‐service systems based on historical and contemporary data, showing promise for many practical applications. One major challenge for prognostics is the common occurrence of missing values in time‐series data, often caused by disruptions in sensor communication or hardware/software failures

Parallel applications executing in contemporary heterogeneous clusters are complex to code and optimize. The task‐based programming model is an alternative to handle the coding complexity. This model consists of splitting the problem domain into tasks with dependencies through a directed acyclic graph, and submit the set of tasks to a runtime scheduler that maps each task dynamically to resources.

Based on the relationship between the Internet of Things (IoT) and mobile payment, this article analyzed the security characteristics of IoT mobile payment. The security system of IoT mobile payment was constructed according to the security demands of mobile payment. Finally, the mobile payment security system was utilized to grade the current level of mobile payment security in China, which verified

With the rapid development of Internet of Things (IoT) information technology, the IoT has become a key infrastructure for telemedicine, smart home, and intelligent transportation. One of the key technologies for these applications is information sharing and interoperation among multiple domains. However, the security and privacy issues of multidomain interaction face severe security challenges. Aiming

This paper proposes a coded modulation scheme based on frequency shift keying (FSK) modulation and a simple binary permutation code. FSK detection is based on the knowledge of the probability density function (PDF) of the noise and the attenuation of the channel, called FSK “Soft‐Decision” (FSK/SD) detection. We introduce an approximation of the FSK/SD, called FSK “Select Largest” (FSK/SL). We compare

Heterogeneous devices are becoming necessary components of high performance computing infrastructures, and the graphics processing unit (GPU) plays an important role in this landscape. Given a problem, the established approach for exploiting the GPU is to design solutions that are parallel, without data dependencies. These solutions are then offloaded to the GPU's massively parallel capability. This

In today's big data environment, we get the Maonan residential information of Maonan Nationality in Huanjiang through the web crawler technology, and further study the protection and renewal of the local architectural culture and environment, in order to promote the social civilization and sustainable development. With the continuous development and improvement of Internet technology, information acquisition

Multidimensional Bayesian network classifier (MBC) has become a popular classification model because of their intuitive graphical representation ability among class variables. But learning MBC and performing multidimensional classification based on the MBC can be very computationally demanding. For the tractability of performing multidimensional classification, a class‐bridge‐decomposable (CB‐decomposable)

Fuzzing is an effective approach to detect software vulnerabilities utilizing changeable generated inputs. However, fuzzing the network protocol on the firmware of IoT devices is limited by inefficiency of test case generation, cross‐architecture instrumentation, and fault detection. In this article, we propose the Fw‐fuzz, a coverage‐guided and crossplatform framework for fuzzing network services

Fast nondominated sorting genetic algorithm II (NSGA‐II) is a popular multiobjective optimization method. However, the tournament selection strategy for crossover operator suffers from the drawback of repetitively selecting the same individuals, resulting in unsatisfying performance. To alleviate this problem, this article first proposes to employ k‐means clustering strategy to divide the candidate

Human emotions can be recognized from facial expressions captured in videos. It is a growing research area in which many have attempted to improve video emotion detection in both lab‐controlled and unconstrained environments. While existing methods show a decent recognition accuracy on lab‐controlled datasets, they deliver much lower accuracy in a real‐world uncontrolled environment, where a variety