当前期刊: Computing Go to current issue    加入关注   
显示样式:        排序: IF: - GO 导出
我的关注
我的收藏
您暂时未登录!
登录
  • A framework for Model-Driven Engineering of resilient software-controlled systems
    Computing (IF 2.044) Pub Date : 2020-09-02
    Jacopo Parri, Fulvio Patara, Samuele Sampietro, Enrico Vicario

    Emergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting

    更新日期:2020-09-02
  • Towards a holistic semantic support for context-aware network monitoring
    Computing (IF 2.044) Pub Date : 2020-08-25
    Paulo Carvalho, Solange Rito Lima, Luis Álvarez Sabucedo, Juan M. Santos-Gago, João Marco C. Silva

    Monitoring current communication networks and services is an increasingly complex task as a result of a growth in the number and variety of components involved. Moreover, different perspectives on network monitoring and optimisation policies must be considered to meet context-dependent monitoring requirements. To face these demanding expectations, this article proposes a semantic-based approach to

    更新日期:2020-08-26
  • Ubiquitous Health Profile (UHPr): a big data curation platform for supporting health data interoperability
    Computing (IF 2.044) Pub Date : 2020-08-19
    Fahad Ahmed Satti, Taqdir Ali, Jamil Hussain, Wajahat Ali Khan, Asad Masood Khattak, Sungyoung Lee

    The lack of Interoperable healthcare data presents a major challenge, towards achieving ubiquitous health care. The plethora of diverse medical standards, rather than common standards, is widening the gap of interoperability. While many organizations are working towards a standardized solution, there is a need for an alternate strategy, which can intelligently mediate amongst a variety of medical systems

    更新日期:2020-08-19
  • Influence ranking of road segments in urban road traffic networks
    Computing (IF 2.044) Pub Date : 2020-08-12
    Tarique Anwar, Chengfei Liu, Hai L. Vu, Md. Saiful Islam, Dongjin Yu, Nam Hoang

    Traffic congestions in urban road traffic networks originate from some crowded road segments with crucial locations, and diffuse towards other parts of the urban road network creating further congestions. This behavior of road networks motivates the need to understand the influence of individual road segments on others in terms of congestion. In this paper, we investigate the problems of global influence

    更新日期:2020-08-12
  • Constraint aware profit maximization scheduling of tasks in heterogeneous datacenters
    Computing (IF 2.044) Pub Date : 2020-08-10
    Chinmaya Kumar Swain, Bhawana Gupta, Aryabartta Sahu

    The extensive use of cloud services in different domains triggers the efficient use of cloud resources to achieve maximum profit. The heterogeneous nature of data centers and the heterogeneous resource requirement of user applications create a scope of improvement in task scheduling. The resource requirements in terms of task constraints must be fulfilled for the tasks to be admitted to the system

    更新日期:2020-08-11
  • Lightweight edge authentication for software defined networks
    Computing (IF 2.044) Pub Date : 2020-08-08
    Amar Almaini, Ahmed Al-Dubai, Imed Romdhani, Martin Schramm, Ayoub Alsarhan

    OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network operators to apply new packet encapsulations. While SDN’s logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects

    更新日期:2020-08-09
  • Improved label propagation algorithm for overlapping community detection
    Computing (IF 2.044) Pub Date : 2020-08-07
    Shi Dong

    Community detection plays an important role in the analysis of complex networks. However, overlapping community detection in real networks is still a challenge. To address the problems of pre-input parameters and label redundancy, an improved label propagation algorithm (ILPA) that adopts a method based on the influence factor is proposed in this paper. Theoretical analysis and experimental results

    更新日期:2020-08-08
  • Exploring and optimizing partitioning of large designs for multi-FPGA based prototyping platforms
    Computing (IF 2.044) Pub Date : 2020-07-21
    Umer Farooq, Bander A. Alzahrani

    Recently, multi-FPGA platforms have become a popular choice to prototype complex digital systems. This is because of unique advantages such as high frequency and real world testing experience that are offered when compared to other pre-silicon testing techniques. However, one of several challenges faced by multi-FPGA prototyping is the requirement of an efficient back end flow. Partitioning is a key

    更新日期:2020-07-21
  • A method of chained recommendation for charging piles in internet of vehicles
    Computing (IF 2.044) Pub Date : 2020-07-14
    Tianle Zhang, Liwen Zheng, Yu Jiang, Zhihong Tian, Xiaojiang Du, Mohsen Guizani

    With the popularization of new energy electric vehicles (EVs), the recommendation algorithm is widely used in the relatively new field of charge piles. At the same time, the construction of charging infrastructure is facing increasing demand and more severe challenges. With the ubiquity of Internet of vehicles (IoVs), inter-vehicle communication can share information about the charging experience and

    更新日期:2020-07-14
  • On opportunistic software reuse
    Computing (IF 2.044) Pub Date : 2020-07-10
    Niko Mäkitalo, Antero Taivalsaari, Arto Kiviluoto, Tommi Mikkonen, Rafael Capilla

    The availability of open source assets for almost all imaginable domains has led the software industry to opportunistic design—an approach in which people develop new software systems in an ad hoc fashion by reusing and combining components that were not designed to be used together. In this paper we investigate this emerging approach. We demonstrate the approach with an industrial example in which

    更新日期:2020-07-10
  • IoT streaming data integration from multiple sources
    Computing (IF 2.044) Pub Date : 2020-07-08
    Doan Quang Tu, A. S. M. Kayes, Wenny Rahayu, Kinh Nguyen

    The Internet of Things (IoT) has recently received considerable interest due to the development of smart technologies in today’s interconnected world. With the rapid advancement in Internet technologies and the proliferation of IoT sensors, myriad systems and applications generate data of a massive volume, variety and velocity which traditional databases and systems are unable to manage effectively

    更新日期:2020-07-09
  • Optimized SAT encoding of conformance checking artefacts
    Computing (IF 2.044) Pub Date : 2020-07-08
    Mathilde Boltenhagen, Thomas Chatain, Josep Carmona

    Conformance checking is a growing discipline that aims at assisting organizations in monitoring their processes. On its core, conformance checking relies on the computation of particular artefacts which enable reasoning on the relation between observed and modeled behavior. It is widely acknowledge that the computation of these artifacts is the lion’s share of conformance checking techniques. This

    更新日期:2020-07-08
  • A BBR-based congestion control for delay-sensitive real-time applications
    Computing (IF 2.044) Pub Date : 2020-07-06
    Sayed Najmuddin, Muhammad Asim, Kashif Munir, Thar Baker, Zehua Guo, Rajiv Ranjan

    The current User Datagram Protocol (UDP) causes unfairness and bufferbloats to delay sensitive applications due to the uncontrolled congestion and monopolization of available bandwidth.This causes call drops and frequent communication/connection loss in delay sensitive applications such as VoIP. We present a Responsive Control Protocol using Bottleneck Bandwidth and Round trip propagation time (RCP-BBR)

    更新日期:2020-07-07
  • Gravitational search algorithm based on multiple adaptive constraint strategy
    Computing (IF 2.044) Pub Date : 2020-06-29
    Jingsen Liu, Yuhao Xing, Yixiang Ma, Yu Li

    In order to improve the convergence speed and optimization accuracy of gravitational search algorithm, the improved gravitational algorithm with dynamically adjusting inertia weight and trend factors of speed and position is proposed. This kind of algorithm with dynamic inertia weight improves the updating way of particle mass. Moreover, the mass change has a nonlinear decreasing trend and improves

    更新日期:2020-06-30
  • GPU-based matrix-free finite element solver exploiting symmetry of elemental matrices
    Computing (IF 2.044) Pub Date : 2020-06-24
    Utpal Kiran, Sachin Singh Gautam, Deepak Sharma

    Matrix-free solvers for finite element method (FEM) avoid assembly of elemental matrices and replace sparse matrix-vector multiplication required in iterative solution method by an element level dense matrix-vector product. In this paper, a novel matrix-free strategy for FEM is proposed which computes element level matrix-vector product by using only the symmetric part of the elemental matrices. The

    更新日期:2020-06-25
  • Efficient service discovery in mobile social networks for smart cities
    Computing (IF 2.044) Pub Date : 2020-06-10
    Yonghong Guo, Lu Liu, John Panneerselvam, Rongbo Zhu

    Mobile social networks (MSNs) play an important role in the process of the development of smart cities. Citizens can interact and engage with services provided by MSNs. Smart city services enhance their quality of life. With the popularity of smart phones, mobile social activities have become an important component of citizens’ daily life. People can post their social contents to their remote friends

    更新日期:2020-06-10
  • Uniform reliable broadcast in anonymous distributed systems with fair lossy channels
    Computing (IF 2.044) Pub Date : 2020-06-08
    Jian Tang, Mikel Larrea, Sergio Arévalo, Ernesto Jiménez

    Uniform reliable broadcast (URB) is an important abstraction in distributed systems, offering delivery guarantee when spreading messages between processes. Informally, URB guarantees that if a process (correct or not) delivers a message m, then all correct processes deliver m. This abstraction has been extensively investigated in distributed systems where all processes have unique identifiers. Furthermore

    更新日期:2020-06-08
  • Software-driven big data analytics
    Computing (IF 2.044) Pub Date : 2020-06-05
    Rajiv Ranjan, Zheng Li, Massimo Villari, Yan Liu, Dimitrios Georgeakopoulos

    Data analytics is the crucial step to reveal essential values of datasets and complete the value chain of big data. In practice, both the hardware infrastructure and the software stack play a fundamental role in big data analytics (BDA). Unfortunately, it is evident that a disproportionately larger amount of effort is being invested in the hardware infrastructure development over the software stack

    更新日期:2020-06-05
  • An adaptive workload-aware power consumption measuring method for servers in cloud data centers
    Computing (IF 2.044) Pub Date : 2020-05-27
    Weiwei Lin, Yufeng Zhang, Wentai Wu, Simon Fong, Ligang He, Jia Chang

    As cloud computing technologies and applications develop rapidly in recent years, the quantity and size of cloud datacenters have been ever-increasing, making the overconsumption of energy in datacenters become a widespread concern. To reduce the energy cost by servers, we must first build an accurate power model to achieve flexible, device-free power consumption measuring. However, most of the previous

    更新日期:2020-05-27
  • An approach to dynamically assigning cloud resource considering user demand and benefit of cloud platform
    Computing (IF 2.044) Pub Date : 2020-05-26
    Zhongsheng Qian, Xiaojin Wang, Xiangyu Liu, Xiaoxin Xie, Tao Song

    Cloud computing, with the features of flexible resource assignment, timely on-demand service and transparent by-quantity pricing, has been widely applied recently. As a new business service model, cloud platform must be capable of satisfying user demand and enhancing quality of service. Therefore, an excellent resource scheduling scheme is requisite to improve the working efficiency of cloud platform

    更新日期:2020-05-26
  • A novel blockchain based framework to secure IoT-LLNs against routing attacks
    Computing (IF 2.044) Pub Date : 2020-05-25
    Rashmi Sahay, G. Geethakumari, Barsha Mitra

    Routing attacks in the Internet of Things environment (IoT) can result in degraded network performance and often denial of service. Low Power and Lossy Network (LLN) is that segment in IoT which comprises constrained devices like sensors and RFIDs. IPv6 Routing Protocol over Low Power and Lossy Networks (RPL) is the standard routing protocol proposed by IETF for routing in IoT-LLNs. RPL efficiently

    更新日期:2020-05-25
  • QoS evaluation model based on intelligent fuzzy system for vehicular ad hoc networks
    Computing (IF 2.044) Pub Date : 2020-05-19
    Abir Mchergui, Tarek Moulahi, Salem Nasri

    Supporting the Quality of Service (QoS) for broadcasting techniques in Vehicular Ad hoc NETetworks (VANETs) is a primordial concern. Qualitatively, QoS is an aspect reflecting the network performance, but quantitatively, it is a function of multiple parameters such as end-to-end delay, packet loss ratio and overhead. These parameters are changing over time and according to adopted protocols. Therefore

    更新日期:2020-05-19
  • LSTM based link quality confidence interval boundary prediction for wireless communication in smart grid
    Computing (IF 2.044) Pub Date : 2020-05-18
    Wei Sun, Pengyu Li, Zhi Liu, Xue Xue, Qiyue Li, Haiyan Zhang, Junbo Wang

    The smart grid will play an important role in the future city to support the diversified energy supply. Wireless communication, the most cost-effective alternative to the traditional wire-lines, promises to provide ubiquitous bi-direction information channel for smart grid devices. However, due to the complex environment that smart grid devices located in, the wireless link is easily been interfered

    更新日期:2020-05-18
  • POF-SVLM: pareto optimized framework for seamless VM live migration
    Computing (IF 2.044) Pub Date : 2020-05-16
    Chetan Dhule, Urmila Shrawankar

    Live migration helps to achieve resource consolidation and fault tolerance. It transfers VM storage together with VM memory and CPU status. During migration, a dirty page rate also delays the period of live migration, and it affects the performance of migration by increasing migration time, network bandwidth consumption, CPU processing overheads and application downtime. Experimental results after

    更新日期:2020-05-16
  • A cache-based method to improve query performance of linked Open Data cloud
    Computing (IF 2.044) Pub Date : 2020-05-14
    Usman Akhtar, Anita Sant’Anna, Chang-Ho Jihn, Muhammad Asif Razzaq, Jaehun Bang, Sungyoung Lee

    The proliferation of semantic big data has resulted in a large amount of content published over the Linked Open Data (LOD) cloud. Semantic Web applications consume these data by issuing SPARQL queries. One of the main challenges faced by querying the LOD web cloud on account of the inherent distributed nature of LOD is its high search latency and lack of tools to connect the SPARQL endpoints. In this

    更新日期:2020-05-14
  • Efficient offloading schemes using Markovian models: a literature review
    Computing (IF 2.044) Pub Date : 2020-05-10
    Mohammad Masdari, Hemn Khezri

    The increasing demand for new mobile applications puts a heavy demand for more processing power and resources in smart mobile devices (SMD). Offloading is a promising solution for these issues which tries to move data, code, or computation from the SMDs to the remote or nearby resourceful servers. To increase the effectiveness of the offloading process and make better decisions, various stochastic

    更新日期:2020-05-10
  • A multi-objective load balancing algorithm for virtual machine placement in cloud data centers based on machine learning
    Computing (IF 2.044) Pub Date : 2020-05-06
    Arezoo Ghasemi, Abolfazl Toroghi Haghighat

    Cloud computing provides utility computing in which clients pay the cost according to their demands and service use. There are some challenges to this technology. One of these issues in data centers is virtual machine (VM) placement so that mapping of these VMs to hosts is executed for a variety of objectives such as load balancing, reducing energy consumption, increasing resource utilization, shortening

    更新日期:2020-05-06
  • An approach to evaluate trust and reputation of things in a Multi-IoTs scenario
    Computing (IF 2.044) Pub Date : 2020-05-05
    Domenico Ursino, Luca Virgili

    In the past research, trust and reputation have been investigated for communities of people, for organizations and for multi-agent systems. However, in the last few years, things are becoming increasingly relevant in the Internet scenario and, at the same time, increasingly complex. As a matter of fact, the term “Internet of Things” (hereafter, IoT) is becoming more and more common in both the scientific

    更新日期:2020-05-05
  • Feature selection and evaluation for software usability model using modified moth-flame optimization
    Computing (IF 2.044) Pub Date : 2020-05-05
    Deepak Gupta, Anil K. Ahlawat, Arun Sharma, Joel J. P. C. Rodrigues

    This paper introduces a nature-inspired optimized algorithm called modified moth-flame optimization (MMFO) for usability feature selection. To determine quality of software usability plays a significant role. This model contains various usability factors that are divided into several features, which have some characteristics, thus making a hierarchical model. Here, the authors have introduced MMFO

    更新日期:2020-05-05
  • An energy-aware clustering and two-level routing method in wireless sensor networks
    Computing (IF 2.044) Pub Date : 2020-05-05
    Aram Mosavifard, Hamid Barati

    Wireless sensor networks (WSN) are consisted of several sensor nodes scattered in an area to gather data from their ambient environment and send it to base station (BS). The energy of nodes in WSNs is limited. One of the most significant issues in WSNs is reducing the energy consumption of nodes, which leads to increased network lifetime. One method to reduce energy consumption in WSNs is energy-efficient

    更新日期:2020-05-05
  • An energy-efficient power management for heterogeneous servers in data centers
    Computing (IF 2.044) Pub Date : 2020-04-06
    Qiang Wang, Haoran Cai, Qiang Cao, Fang Wang

    Power management for heterogeneous servers has been playing a key role in improving energy efficiency in data centers. Running latency-critical web services on such scenario is still challenging due to the overheads of task transition between such servers. In this paper, we present a runtime power management system, Montgolfier, which is built on a latency-aware feedback control mechanism. It consolidates

    更新日期:2020-04-20
  • Enhanced time-aware QoS prediction in multi-cloud: a hybrid k-medoids and lazy learning approach (QoPC)
    Computing (IF 2.044) Pub Date : 2019-10-10
    Amin Keshavarzi, Abolfazl Toroghi Haghighat, Mahdi Bohlouli

    Cloud service providers should be able to predict the future states of their infrastructure in order to avoid any violation of Service Level Agreement. This becomes more complex when vendors have to deal with services from various providers in multi-clouds. As a result, QoS prediction can significantly support service providers in a better understanding of their resources future states. Users should

    更新日期:2020-04-20
  • Software system design based on patterns for Newton-type methods
    Computing (IF 2.044) Pub Date : 2019-09-10
    Ricardo Serrato-Barrera, Gustavo Rodríguez-Gómez, Julio César Pérez-Sansalvador, Saúl Pomares-Hernández, Leticia Flores-Pulido, Antonio Muñoz

    A wide range of engineering applications use optimization techniques as part of their solution process. The researcher uses specialized software that implements well-known optimization techniques to solve his problem. However, when it comes to develop original optimization techniques that fit a particular problem the researcher has no option but to implement his own new method from scratch. This leads

    更新日期:2020-04-20
  • Deployment of an aerial platform system for rapid restoration of communications links after a disaster: a machine learning approach
    Computing (IF 2.044) Pub Date : 2019-11-21
    Faris A. Almalki, Marios C. Angelides

    Having reliable telecommunication systems in the immediate aftermath of a catastrophic event makes a huge difference in the combined effort by local authorities, local fire and police departments, and rescue teams to save lives. This paper proposes a physical model that links base stations that are still operational with aerial platforms and then uses a machine learning framework to evolve ground-to-air

    更新日期:2020-04-20
  • SVM ensembles for named entity disambiguation
    Computing (IF 2.044) Pub Date : 2019-08-21
    Amal Alokaili, Mohamed El Bachir Menai

    The enormous quantity of digital data necessitates automation, which among other things can help link unstructured to structured data. Such a task requires a systematic approach of mapping entity mentions (e.g., person, location) to corresponding entries in a Knowledge Base. This area of research is rapidly evolving at a breathtaking pace, which has led to the popularization of the Named Entity Disambiguation

    更新日期:2020-04-20
  • Long range dependence in cloud servers: a statistical analysis based on Google workload trace
    Computing (IF 2.044) Pub Date : 2020-01-07
    Shaifu Gupta, A. D. Dileep

    Analysis and characterization of cloud workloads provides crucial information for designing optimal resource management policies. In this work, we propose to analyse long range dependence nature of cloud resource workloads. Long range dependence is a phenomenon widely studied in Ethernet and Internet traffic. But there is a dearth of works that analyse long range dependence in cloud workloads. In this

    更新日期:2020-04-20
  • A probabilistic model for assigning queries at the edge
    Computing (IF 2.044) Pub Date : 2019-11-18
    Kostas Kolomvatsos, Christos Anagnostopoulos

    Data management at the edge of the network can increase the performance of applications as the processing is realized close to end users limiting the observed latency in the provision of responses. A typical data processing involves the execution of queries/tasks defined by users or applications asking for responses in the form of analytics. Query/task execution can be realized at the edge nodes that

    更新日期:2020-04-20
  • A green energy consumption policy of Bluetooth mobile devices for smart cities
    Computing (IF 2.044) Pub Date : 2019-10-30
    Hui Ye, FangMin Li, ZhiXiong Liu, XuDong Deng

    Green computing mode becomes a social concern in recently years. Consequently people have higher demand for Bluetooth device with lower power consumption. In this paper, a green energy consumption policy (ECP) of battery of Bluetooth devices during data transmission was put forward. ECP extracted detail information from four key configuration parameters during Bluetooth data transmission, namely, transmission

    更新日期:2020-04-20
  • A review of CUDA optimization techniques and tools for structured grid computing
    Computing (IF 2.044) Pub Date : 2019-07-26
    Mayez A. Al-Mouhamed, Ayaz H. Khan, Nazeeruddin Mohammad

    Recent advances in GPUs opened a new opportunity in harnessing their computing power for general purpose computing. CUDA, an extension to C programming, is developed for programming NVIDIA GPUs. However, efficiently programming GPUs using CUDA is very tedious and error prone even for the expert programmers. Programmer has to optimize the resource occupancy and manage the data transfers between host

    更新日期:2020-04-20
  • Implementation of an energy saving cloud infrastructure with virtual machine power usage monitoring and live migration on OpenStack
    Computing (IF 2.044) Pub Date : 2020-04-01
    Chao-Tung Yang, Tsung-Yueh Wan

    Cloud computing is Internet-based computing which requires more physical machines and consumes a large amount of power. By this means, that will reduce the profit of the service providers and harm the environment. How to effectively handle the power consumption of cloud computing has been an issue in recent years. When making a large number of operations, and power consumption cannot be underestimated

    更新日期:2020-04-20
  • MDPCluster: a swarm-based community detection algorithm in large-scale graphs
    Computing (IF 2.044) Pub Date : 2020-01-11
    Mahsa Fozuni Shirjini, Saeed Farzi, Amin Nikanjam

    Social network analysis has become an important topic for researchers in sociology and computer science. Similarities among individuals form communities as the basic constitutions of social networks. Regarding the importance of communities, community detection is a fundamental step in the study of social networks typically modeled as large-scale graphs. Detecting communities in such large-scale graphs

    更新日期:2020-04-20
  • An approach to merge collaborating processes of an inter-organizational business process for artifact lifecycle synthesis
    Computing (IF 2.044) Pub Date : 2019-11-30
    Jyothi Kunchala, Jian Yu, Sira Yongchareon, Chengfei Liu

    Artifact-centric approach to business process modeling has received considerable attention for elevating data logic to the same level as the process flow logic. With the emergence of this modeling paradigm, several recent works have focused on synthesizing the indispensable lifecycles of key business entities called artifacts from the standalone activity-centric processes. However, synthesizing artifact

    更新日期:2020-04-20
  • Strategies for array data retrieval from a relational back-end based on access patterns
    Computing (IF 2.044) Pub Date : 2020-03-30
    Andrej Andrejev, Kjell Orsborn, Tore Risch

    Multidimensional numeric arrays are often serialized to binary formats for efficient storage and processing. These representations can be stored as binary objects in existing relational database management systems. To minimize data transfer overhead when arrays are large and only parts of arrays are accessed, it is favorable to split these arrays into separately stored chunks. We process queries expressed

    更新日期:2020-04-20
  • Long-term real time object tracking based on multi-scale local correlation filtering and global re-detection
    Computing (IF 2.044) Pub Date : 2020-03-30
    Qi Zhao, Boxue Zhang, Wenquan Feng, Zhiying Du, Hong Zhang, Daniel Sun

    This paper investigates long-term visual object tracking which is a complex problem in computer vision community and big data analysis, due to the variation of the target and the surrounding environment. A novel tracking algorithm based on local correlation filtering and global keypoint matching is proposed to solve problems occurred during long-term tracking such as occlusion, target-losing, etc.

    更新日期:2020-04-20
  • Performance analysis of the ubiquitous and emergent properties of an autonomic reflective middleware for smart cities
    Computing (IF 2.044) Pub Date : 2020-03-30
    Jose Aguilar, M. Jerez, M. Mendonça, M. Sánchez

    One of the biggest challenges in a Smart City is how to describe and dispose of the enormous and multiple sources of information, and how to share and merge it into a single infrastructure, in a timely and correct manner. A Smart City requires computational platforms, which allow the interconnection of multiple and embedded systems, such that the technology is integrated with people, and can respond

    更新日期:2020-04-20
  • Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents
    Computing (IF 2.044) Pub Date : 2020-03-27
    Tariq Alsboui, Yongrui Qin, Richard Hill, Hussain Al-Aqrabi

    It is estimated that there will be approximately 125 billion Internet of Things (IoT) devices connected to the Internet by 2030, which are expected to generate large amounts of data. This will challenge data processing capability, infrastructure scalability, and privacy. Several studies have demonstrated the benefits of using distributed intelligence (DI) to overcome these challenges. We propose a

    更新日期:2020-04-20
  • A novel scalable representative-based forecasting approach of service quality
    Computing (IF 2.044) Pub Date : 2020-03-27
    Hamdi Yahyaoui, Hala S. Own, Ahmed Agwa, Zakaria Maamar

    Several approaches to forecast the service quality based on its quality of service (QoS) properties are reported in the literature. However, their main disadvantage resides in their limited scalability. In fact, they elaborate a forecasting model for each quality attribute per service, which cannot scale well for large or even medium size datasets of services. Accordingly, we propose a novel scalable

    更新日期:2020-04-20
  • Fusing attack detection and severity probabilities: a method for computing minimum-risk war decisions
    Computing (IF 2.044) Pub Date : 2020-03-27
    Vaughn H. Standley, Frank G. Nuño, Jacob W. Sharpe

    State actors can minimize the risk of combat deaths by making decisions consistent with a likelihood ratio test that fuses attack detection data with prior war probabilities. The power-law, which has for decades been used to model the distribution of combat fatalities, is invalid as a probability because the mean is divergent. An investigation of Correlates of War data reveal that combat fatalities

    更新日期:2020-04-20
  • SAT-based models for overlapping community detection in networks
    Computing (IF 2.044) Pub Date : 2020-03-23
    Said Jabbour, Nizar Mhadhbi, Badran Raddaoui, Lakhdar Sais

    Communities in social networks or graphs are sets of well-connected, overlapping vertices. Network community detection is a hot research topic in social, biological and information networks analysis. The effectiveness of a community detection algorithm is determined by accuracy in finding the ground-truth communities. In this article, we present two models to detect overlapping communities in large

    更新日期:2020-03-23
  • Ontology-based discovery of time-series data sources for landslide early warning system
    Computing (IF 2.044) Pub Date : 2019-06-13
    Jedsada Phengsuwan, Tejal Shah, Philip James, Dhavalkumar Thakker, Stuart Barr, Rajiv Ranjan

    Abstract Modern early warning system (EWS) requires sophisticated knowledge of the natural hazards, the urban context and underlying risk factors to enable dynamic and timely decision making (e.g., hazard detection, hazard preparedness). Landslides are a common form of natural hazard with a global impact and closely linked to a variety of other hazards. EWS for landslides prediction and detection relies

    更新日期:2020-03-12
  • Research on statistical machine translation model based on deep neural network
    Computing (IF 2.044) Pub Date : 2019-08-21
    Ying Xia

    Abstract With the increase of translation demand, the advancement of information technology, the development of linguistic theories and the progress of natural language understanding models in artificial intelligence research, machine translation has gradually gained worldwide attention. However, at present, machine translation research still has problems such as insufficient bilingual data and lack

    更新日期:2020-03-12
  • Fast fingerprints construction via GPR of high spatial-temporal resolution with sparse RSS sampling in indoor localization
    Computing (IF 2.044) Pub Date : 2019-05-02
    Haojun Ai, Kaifeng Tang, Weiyi Huang, Sheng Zhang, Taizhou Li

    Abstract Effective indoor localization largely relies on the fingerprint database (model) of Received Signal Strength (RSS) in connection with Radio Frequency sources, such as the most widely used Bluetooth Low Energy (BLE) iBeacons. RSSs exhibit significant random variations in both the spatial and temporal domains. It is a notoriously onerous and challenging task to construct the fingerprint database

    更新日期:2020-03-12
  • Study on text representation method based on deep learning and topic information
    Computing (IF 2.044) Pub Date : 2019-09-06
    Zilong Jiang, Shu Gao, Liangchen Chen

    Abstract Deep learning provides a new modeling method for natural language processing. In recent years, it has been applied in language model, text classification, machine translation, sentiment analysis, question and answer system, word distributed representation, etc., and a series of theoretical research results have been obtained. For the text representation task, this paper studies the strategy

    更新日期:2020-03-12
  • English speech recognition based on deep learning with multiple features
    Computing (IF 2.044) Pub Date : 2019-08-26
    Zhaojuan Song

    Abstract English is one of the widely used languages, with the shrinking of the global village, the smart home, the in-vehicle voice system and voice recognition software with English as the recognition language have gradually entered people’s field of vision, and have obtained the majority of users’ love by the practical accuracy. And deep learning technology in many tasks with its hierarchical feature

    更新日期:2020-03-12
  • Towards emotion-sensitive learning cognitive state analysis of big data in education: deep learning-based facial expression analysis using ordinal information
    Computing (IF 2.044) Pub Date : 2019-05-05
    Ruyi Xu, Jingying Chen, Jiaxu Han, Lei Tan, Luhui Xu

    Abstract The boom of big data in education has provided an unrivalled opportunity for educators to evaluate the learners’ cognitive state. However, most existing cognitive state analysis methods focus on attention, ignoring the roles of emotion in human learning. Therefore, this study proposes an emotion-sensitive learning cognitive state analysis framework, which automatically estimates the learners’

    更新日期:2020-03-12
  • An optimized cognitive-assisted machine translation approach for natural language processing
    Computing (IF 2.044) Pub Date : 2019-07-12
    Abdulaziz Alarifi, Ayed Alwadain

    Abstract Currently, computer-aided machine translation (MT) processes play a significant role in natural language processing used to translate a specified language into another language like English to Spanish, Latin to French. During the translation process, and particularly during phrase composition, MT systems may exhibit several issues, including failure to produce high quality translations, increased

    更新日期:2020-03-12
  • RNN-based signal classification for hybrid audio data compression
    Computing (IF 2.044) Pub Date : 2019-03-26
    Weiping Tu, Yuhong Yang, Bo Du, Wanzhao Yang, Xiong Zhang, Jiaxi Zheng

    Abstract Audio data are a fundamental component of multimedia big data. Switched audio codec has been proved to be efficient for compressing a large range of audio signals at low bit rates. However, coding quality strongly relies on an exact classification of the input signals. Two coding mode selection methods are adopted in AMR-WB+, the state-of-the-art switched audio coder. The closed-loop method

    更新日期:2020-03-12
  • A mosaic method for multi-temporal data registration by using convolutional neural networks for forestry remote sensing applications
    Computing (IF 2.044) Pub Date : 2019-04-11
    Yi Zeng, Zihan Ning, Peng Liu, Peilei Luo, Yi Zhang, Guojin He

    Abstract Image registration is one of the most important processes for the generation of remote sensing image mosaics. This paper focuses on the special problems related to remote sensing data registration, and multi-temporal data mosaic applications in the domain of forestry. It proposes an image registration method based on hierarchical convolutional features, and applies it to improve the efficiency

    更新日期:2020-03-12
  • Reusing artifact-centric business process models: a behavioral consistent specialization approach
    Computing (IF 2.044) Pub Date : 2020-02-22
    Sira Yongchareon, Chengfei Liu, Xiaohui Zhao

    Process reuse is one of the important research areas that address efficiency issues in business process modeling. Similar to software reuse, business processes should be able to be componentized and specialized in order to enable flexible process expansion and customization. Current activity/control-flow centric workflow modeling approaches face difficulty in supporting highly flexible process reuse

    更新日期:2020-02-22
  • Failure prediction of tasks in the cloud at an earlier stage: a solution based on domain information mining
    Computing (IF 2.044) Pub Date : 2020-02-19
    Chunhong Liu, Liping Dai, Yi Lai, Guibing Lai, Wentao Mao

    In a large-scale data center, it is vital to precisely recognize the termination statuses of applications at an early stage. In recent years, many machine learning techniques have been applied to this issue, which is beneficial for optimizing the scheduling policy and improving the efficiency of resource utilization. However, if the application’s dynamic information is insufficient at the early stage

    更新日期:2020-02-19
Contents have been reproduced by permission of the publishers.
导出
全部期刊列表>>
物理学研究前沿热点精选期刊推荐
chemistry
《自然》编辑与您分享如何成为优质审稿人-信息流
欢迎报名注册2020量子在线大会
化学领域亟待解决的问题
材料学研究精选新
GIANT
自然职场线上招聘会
ACS ES&T Engineering
ACS ES&T Water
ACS Publications填问卷
屿渡论文,编辑服务
阿拉丁试剂right
南昌大学
王辉
南方科技大学
刘天飞
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
天合科研
x-mol收录
X-MOL
苏州大学
廖矿标
深圳湾
试剂库存
down
wechat
bug