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  • A survey of neighborhood construction algorithms for clustering and classifying data points
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-20
    Shahin Pourbahrami; Mohammad Ali Balafar; Leyli Mohammad Khanli; Zana Azeez Kakarash

    Clustering and classifying are overriding techniques in machine learning. Neighborhood construction as a key step in these techniques has been extensively used for modeling local relationships between data samples, and constructing global structures from local information. The goal of the neighborhood construction process is to improve the quality of individual data point categorizing. Many applications

    更新日期:2020-10-20
  • Storage, partitioning, indexing and retrieval in Big RDF frameworks: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-15
    Tanvi Chawla; Girdhari Singh; Emmanuel S. Pilli; M.C. Govil

    Resource Description Framework (RDF) is increasingly being used to model data on the web. RDF model was designed to support easy representation and exchange of information on the web. RDF is queried using SPARQL, a standard query language recommended by W3C. The growth in acceptance of RDF format can be attributed to its flexible and reusable nature. The size of RDF data is steadily increasing as many

    更新日期:2020-10-16
  • A survey on privacy and security of Internet of Things
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-13
    Mark Mbock Ogonji; George Okeyo; Joseph Muliaro Wafula

    Internet of Things (IoT) has fundamentally changed the way information technology and communication environments work, with significant advantages derived from wireless sensors and nanotechnology, among others. While IoT is still a growing and expanding platform, the current research in privacy and security shows there is little integration and unification of security and privacy that may affect user

    更新日期:2020-10-13
  • Machine learning techniques for hate speech classification of twitter data: State-of-the-art, future challenges and research directions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-13
    Femi Emmanuel Ayo; Olusegun Folorunso; Friday Thomas Ibharalu; Idowu Ademola Osinuga

    Twitter is a microblogging tool that allow the creation of big data through short digital contents. This study provides a survey of machine learning techniques for hate speech classification from Twitter data streams. Hate speech classification in Twitter data streams has remain a vibrant research focus, but little research efforts have been devoted to the design of a generic metadata architecture

    更新日期:2020-10-13
  • Moving objects detection with a moving camera: A comprehensive review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-08
    Marie-Neige Chapel; Thierry Bouwmans

    During about 30 years, a lot of research teams have worked on the big challenge of detection of moving objects in various challenging environments. First applications concern static cameras but with the rise of the mobile sensors studies on moving cameras have emerged over time. In this survey, we propose to identify and categorize the different existing methods found in the literature. For this purpose

    更新日期:2020-10-08
  • A critical overview of outlier detection methods
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-05
    Abir Smiti

    One of the opening steps towards obtaining a reasoned analysis is the detection of outlaying observations. Even if outliers are often considered as a miscalculation or noise, they may bring significant information. For that reason, it is important to spot them prior to modeling and analysis. In this paper, we will present a structured and comprehensive review of the research on outlier detection. We

    更新日期:2020-10-05
  • DevOps and software quality: A systematic mapping
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-10-03
    Alok Mishra; Ziadoon Otaiwi

    Quality pressure is one of the factors affecting processes for software development in its various stages. DevOps is one of the proposed solutions to such pressure. The primary focus of DevOps is to increase the deployment speed, frequency and quality. DevOps is a mixture of different developments and operations to its multitudinous ramifications in software development industries, DevOps have attracted

    更新日期:2020-10-04
  • Applicability of mobile contact tracing in fighting pandemic (COVID-19): Issues, challenges and solutions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-23
    Aaqib Bashir Dar; Auqib Hamid Lone; Saniya Zahoor; Afshan Amin Khan; Roohie Naaz

    Contact Tracing is considered as the first and the most effective step towards containing an outbreak, as resources for mass testing and large quantity of vaccines are highly unlikely available for immediate utilization. Effective contact tracing can allow societies to reopen from lock-down even before availability of vaccines. The objective of mobile contact tracing is to speed up the manual interview

    更新日期:2020-09-24
  • mHealth Authentication Approach Based 3D Touchscreen and Microphone Sensors for Real-Time Remote Healthcare Monitoring System: Comprehensive Review, Open Issues and Methodological Aspects
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-21
    Moceheb Lazam Shuwandy; B.B. Zaidan; A.A. Zaidan; A.S. Albahri; A.H. Alamoodi; O.S. Albahri; Mamoun Alazab

    Patient authentication acquires superior attention as a necessary security requirement in a remote health monitoring system. From a usability perspective, credential-based authentication techniques that use sensors, such as orientation, finger and camera, are not exceedingly well-convenient for medical applications. Moreover, patients could entrust credentials to someone else, thus violating the privacy

    更新日期:2020-09-21
  • Arabic Machine Translation: A survey of the latest trends and challenges
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-15
    Mohamed Seghir Hadj Ameur, Farid Meziane, Ahmed Guessoum

    Given that Arabic is one of the most widely used languages in the world, the task of Arabic Machine Translation (MT) has recently received a great deal of attention from the research community. Indeed, the amount of research that has been devoted to this task has led to some important achievements and improvements. However, the current state of Arabic MT systems has not reached the quality achieved

    更新日期:2020-09-15
  • A comprehensive and systematic look up into deep learning based object detection techniques: A review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-11
    Vipul Sharma, Roohie Naaz Mir

    Object detection can be regarded as one of the most fundamental and challenging visual recognition task in computer vision and it has received great attention over the past few decades. Object detection techniques find their application in almost all the spheres of life, most prominent ones being surveillance, autonomous driving, pedestrian detection and so on. The primary focus of visual object detection

    更新日期:2020-09-11
  • A survey of live Virtual Machine migration techniques
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-11
    Tuan Le

    Live Virtual Machine migration is the process of moving a running VM from one physical host to another with minimal disruption to ongoing services. It is a powerful tool that facilitates hardware maintenance, load balancing, fault tolerance, and power saving in clusters and data centers. A key challenge with live migration is that it is difficult to simultaneously meet the goals of minimizing downtime

    更新日期:2020-09-11
  • Offline recognition of handwritten Indic scripts: A state-of-the-art survey and future perspectives
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-11
    Reya Sharma, Baijnath Kaushik

    The handwritten script recognition is one of the most interesting and challenging areas of pattern recognition due to numerous variations in writing styles. Extensive in-depth research work is reported on the recognition of handwritten text in scripts such as Latin, Chinese, Arabic and Japanese. However, the work reported on handwritten Indic scripts is still in its infancy, so significant research

    更新日期:2020-09-11
  • Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-11
    Safa Ben Atitallah, Maha Driss, Wadii Boulila, Henda Ben Ghézala

    The rapid growth of urban populations worldwide imposes new challenges on citizens’ daily lives, including environmental pollution, public security, road congestion, etc. New technologies have been developed to manage this rapid growth by developing smarter cities. Integrating the Internet of Things (IoT) in citizens’ lives enables the innovation of new intelligent services and applications that serve

    更新日期:2020-09-11
  • A comprehensive survey of service function chain provisioning approaches in SDN and NFV architecture
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-08
    Karamjeet Kaur, Veenu Mangat, Krishan Kumar

    Network Function Virtualization (NFV) has emerged as an innovative network architecture paradigm that uses IT virtualization technology to abstract the network node functions from hardware. The virtualized network services hosted on Virtual Machines (VMs) are called Virtual Network Functions (VNFs). The sequence of multiple VNFs required by network operators to perform traffic steering is called a

    更新日期:2020-09-08
  • A survey of Konkani NLP resources
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-03
    Annie Rajan, Ambuja Salgaonkar, Ramprasad Joshi

    The first comprehensive survey is presented of natural language processing (NLP) research in Konkani, a low-resource regional Indian language with a small population of native speakers. The combined challenges of complex linguistic phenomena, paucity of documented resources and the presence of neighboring dominant languages are elaborated. The possibilities of crowdsourcing as a means for creating

    更新日期:2020-09-03
  • Intelligent food processing: Journey from artificial neural network to deep learning
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-09-02
    Janmenjoy Nayak, Kanithi Vakula, Paidi Dinesh, Bighnaraj Naik, Danilo Pelusi

    Since its initiation, ANN became popular and also plays a key role in enhancing the latest technology. With an increase in industrial automation and the Internet of Things, now it is easier than ever to collect data and monitor food drying, extrusion, and sterilization, etc. In this industrial revolution, the uses of ANN are found successful in food processing tasks like food grading, safety, and quality

    更新日期:2020-09-02
  • Network embedding: Taxonomies, frameworks and applications
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-08-26
    Mingliang Hou, Jing Ren, Da Zhang, Xiangjie Kong, Dongyu Zhang, Feng Xia

    Networks are a general language for describing complex systems of interacting entities. In the real world, a network always contains massive nodes, edges and additional complex information which leads to high complexity in computing and analyzing tasks. Network embedding aims at transforming one network into a low dimensional vector space which benefits the downstream network analysis tasks. In this

    更新日期:2020-08-26
  • Advancement from neural networks to deep learning in software effort estimation: Perspective of two decades
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-08-14
    P. Suresh Kumar, H.S. Behera, Anisha Kumari K, Janmenjoy Nayak, Bighnaraj Naik

    In the software engineering, estimation of the effort, time and cost required for the development of software projects is an important issue. It is a very difficult task for project managers to predict the cost and effort needed in the premature stages of planning. Software estimation ahead of development can reduce the risk and increase the success rate of the project. Many traditional and machine

    更新日期:2020-08-14
  • Deep Learning Methods for Multi-Species Animal Re-identification and Tracking – a Survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-08-07
    Prashanth C. Ravoor, Sudarshan T.S.B.

    Technology has an important part to play in wildlife and ecosystem conservation, and can vastly reduce time and effort spent in the associated tasks. Deep learning methods for computer vision in particular show good performance on a variety of tasks; animal detection and classification using deep learning networks are widely used to assist ecological studies. A related challenge is tracking animal

    更新日期:2020-08-07
  • A comprehensive survey and analysis of generative models in machine learning
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-07-30
    Harshvardhan GM, Mahendra Kumar Gourisaria, Manjusha Pandey, Siddharth Swarup Rautaray

    Generative models have been in existence for many decades. In the field of machine learning, we come across many scenarios when directly learning a target is intractable through discriminative models, and in such cases the joint distribution of the target and the training data is approximated and generated. These generative models help us better represent or model a set of data by generating data in

    更新日期:2020-07-30
  • Community detection in node-attributed social networks: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-07-21
    Petr Chunaev

    Community detection is a fundamental problem in social network analysis consisting, roughly speaking, in unsupervised dividing social actors (modeled as nodes in a social graph) with certain social connections (modeled as edges in the social graph) into densely knitted and highly related groups with each group well separated from the others. Classical approaches for community detection usually deal

    更新日期:2020-07-21
  • Development of improved whale optimization-based FCM clustering for image watermarking
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-07-18
    Kavitha Soppari, N. Subhash Chandra

    With the growing interest in copyright protection of multimedia, digital watermarking has been introduced and widely researched. The digital image watermarking approaches are generally adopted in the spatial or transform domain. Most of the transform-domain watermarking approaches are based on Discrete Cosine Transforms (DCT) and robust to JPEG lossy compression. Few contributions have been done using

    更新日期:2020-07-18
  • Improved node localization using K-means clustering for Wireless Sensor Networks
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-25
    Salim El Khediri, Walid Fakhet, Tarek Moulahi, Rehanullah Khan, Adel Thaljaoui, Abdennaceur Kachouri

    A power-efficient K-means clustering algorithm for Wireless Sensor Networks (WSN) is proposed. This algorithm aims to manage the consumption of energy by WS nodes and enhance the running time for WSN given space constraints. WS node cluster formation is structured as a sample space partition in k-means for the reason that the radio channel is unstable and the distribution of the nodes is coarse. After

    更新日期:2020-06-25
  • A review of using object-orientation properties of C++ for designing expert system in strategic planning
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-23
    Mohsen Ahmadi, Moein Qaisari Hasan Abadi

    Using intelligent expert systems is a necessity for improving the situation of organizations. Since the process of identifying strategy in a strategic plan is time-consuming and costly, the role of expert systems in strategic planning is considerable. Managers utilize expert system to maintain and disseminate knowledge, training, and competition in the organization. Complicated expert system with long

    更新日期:2020-06-23
  • Detection and mitigation of DDoS attacks in SDN: A comprehensive review, research challenges and future directions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-20
    Jagdeep Singh, Sunny Behal

    Many security solutions have been proposed in the past to protect Internet architecture from a diversity of malware. However, the security of the Internet and its applications is still an open research challenge. Researchers continuously working on novel network architectures such as HTTP as the narrow waist, Named Data Networking (NDN), programmable networks and Software-Defined Networking (SDN) for

    更新日期:2020-06-20
  • When machine learning meets medical world: Current status and future challenges
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-20
    Abir Smiti

    Imagine the enormous amounts of data that can be generated in the medical field. Each patient has his own medical record which contains valuable information like patient allergy, chronic diseases and vaccinations. Healthcare can profit from this data when it is properly analyzed. The more data gathered, the more complicated data analytics become, therefore, machine learning can be a very useful solution

    更新日期:2020-06-20
  • A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-17
    Xiaowei Huang, Daniel Kroening, Wenjie Ruan, James Sharp, Youcheng Sun, Emese Thamo, Min Wu, Xinping Yi

    In the past few years, significant progress has been made on deep neural networks (DNNs) in achieving human-level performance on several long-standing tasks. With the broader deployment of DNNs on various applications, the concerns over their safety and trustworthiness have been raised in public, especially after the widely reported fatal incidents involving self-driving cars. Research to address these

    更新日期:2020-06-17
  • Integrating blockchain technology into the energy sector — from theory of blockchain to research and application of energy blockchain
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-09
    Qiang Wang, Min Su

    Blockchain technology has been ushering in nothing short of a decentralized revolution. Distributed/decentralized energy is recognized the best way to ensure energy sustainability in the future. An open question is what promise the integration of blockchain and energy hold for energy future. This paper systematically reviews the theory of blockchain and explores the current status of energy blockchain

    更新日期:2020-06-09
  • Multidisciplinary Pattern Recognition applications: A review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-08
    Marina Paolanti, Emanuele Frontoni

    Pattern recognition (PR) is the study of how machines can examine the environment, learn to distinguish patterns of interest from their background, and make reliable and feasible decisions regarding the categories of the patterns. However, even after almost 70 years of research, the design of an application based on pattern recognizer remains an ambiguous goal. Moreover, currently, there are huge volumes

    更新日期:2020-06-08
  • A systematic mapping study of clone visualization
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-05
    Muhammad Hammad, Hamid Abdul Basit, Stan Jarzabek, Rainer Koschke

    Knowing code clones (similar code fragments) is helpful in software maintenance and re-engineering. As clone detectors return huge numbers of clones, visualization techniques have been proposed to make cloning information more comprehensible and useful for programmers. We present a mapping study of clone visualization techniques, classifying visualizations in respect to the user goals to be achieved

    更新日期:2020-06-05
  • Motif discovery in networks: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-06-05
    Shuo Yu, Yufan Feng, Da Zhang, Hayat Dino Bedru, Bo Xu, Feng Xia

    Motifs are regarded as network blocks because motifs can be used to present fundamental patterns in networks. Motif discovery is well applied in various scientific problems, including subgraph mining and graph isomorphism tasks. This paper analyzes and summarizes current motif discovery algorithms in the field of network science with both efficiency and accuracy perspectives. In this paper, we present

    更新日期:2020-06-05
  • Indoor environment propagation review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-29
    H. Obeidat, A. Alabdullah, E. Elkhazmi, W. Suhaib, O. Obeidat, M. Alkhambashi, M. Mosleh, N. Ali, Y. Dama, Z. Abidin, R. Abd-Alhameed, P. Excell

    A survey of indoor propagation characteristics is presented, including different models for path loss, shadowing and fast fading mechanisms, different channel parameters including signal strength, power delay, coherence bandwidth, Doppler spread and angle of arrival. The concepts of MIMO channels are also covered. The study also explores many types of deterministic channel modelling, such as Finite

    更新日期:2020-05-29
  • Graph spanners: A tutorial review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-26
    Reyan Ahmed, Greg Bodwin, Faryad Darabi Sahneh, Keaton Hamm, Mohammad Javad Latifi Jebelli, Stephen Kobourov, Richard Spence

    This survey provides a guiding reference to researchers seeking an overview of the large body of literature about graph spanners. It surveys the current literature covering various research streams about graph spanners, such as different formulations, sparsity and lightness results, computational complexity, dynamic algorithms, and applications. As an additional contribution, we offer a list of open

    更新日期:2020-05-26
  • Current trends in consumption of multimedia content using online streaming platforms: A user-centric survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-26
    Przemysław Falkowski-Gilski, Tadeus Uhl

    In its early days, consumption of multimedia content was only possible at a stationary terminal device. The music player was located at home, and had to have a physical drive. Over the last decade, there has been an enormous increase in the number of online streaming platforms. These services enable users to consume rich multimedia content on various devices. Thanks to the widespread and availability

    更新日期:2020-05-26
  • Big networks: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-20
    Hayat Dino Bedru, Shuo Yu, Xinru Xiao, Da Zhang, Liangtian Wan, He Guo, Feng Xia

    A network is a typical expressive form of representing complex systems in terms of vertices and links, in which the pattern of interactions amongst components of the network is intricate. The network can be static that does not change over time or dynamic that evolves through time. The complication of network analysis is different under the new circumstance of network size explosive increasing. In

    更新日期:2020-05-20
  • Context Aware Recommendation Systems: A review of the state of the art techniques
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-20
    Saurabh Kulkarni, Sunil F. Rodd

    Recommendation systems are gaining increasing popularity in many application areas like e-commerce, movie and music recommendations, tourism, news, advertisement, stock markets, social networks etc. Conventional recommendation systems either use content based or collaborative filtering based approaches to model user preferences and give recommendations. These systems usually fail to consider evolving

    更新日期:2020-05-20
  • Localization schemes for Underwater Acoustic Sensor Networks - A Review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-18
    Archana Toky, Rishi Pal Singh, Sanjoy Das

    Underwater Acoustic Sensor Networks (UWASNs) connect the resources available in oceans to the rest of the world. The network has a huge amount of sensors which are sparsely deployed and are interconnected to collect information for the applications like target tracking, marine life monitoring, surveillance, and civilian applications. To get meaningful information from the data collected by this network

    更新日期:2020-05-18
  • Julia language in machine learning: Algorithms, applications, and open issues
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-16
    Kaifeng Gao, Gang Mei, Francesco Piccialli, Salvatore Cuomo, Jingzhi Tu, Zenan Huo

    Machine learning is driving development across many fields in science and engineering. A simple and efficient programming language could accelerate applications of machine learning in various fields. Currently, the programming languages most commonly used to develop machine learning algorithms include Python, MATLAB, and C/C ++. However, none of these languages well balance both efficiency and simplicity

    更新日期:2020-05-16
  • Multilayer network simplification: Approaches, models and methods
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-05
    Roberto Interdonato, Matteo Magnani, Diego Perna, Andrea Tagarelli, Davide Vega

    Multilayer networks have been widely used to represent and analyze systems of interconnected entities where both the entities and their connections can be of different types. However, real multilayer networks can be difficult to analyze because of irrelevant information, such as layers not related to the objective of the analysis, because of their size, or because traditional methods defined to analyze

    更新日期:2020-05-05
  • Survey on Visualization and Visual Analytics pipeline-based models: Conceptual aspects, comparative studies and challenges
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-05-04
    Hela Ltifi, Christophe Kolski, Mounir Ben Ayed

    In the last decade, many studies have focused on visualization. The main key to make it practical for research and engineering applications is the suitable definition of a pipeline-based visualization model. It provides effective abstractions for designing visualization tools. In this article, we present a comprehensive survey on pipeline-based models for Information Visualization. The basic principles

    更新日期:2020-05-04
  • Homomorphic encryption systems statement: Trends and challenges
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-04-25
    Bechir Alaya, Lamri Laouamer, Nihel Msilini

    For securing our own systems, encryption got the major interest, especially when talking about homomorphic encryption, which has spread like wildfire. Therefore, in this study, we will be presenting different known cryptosystems based, in a great part of its construction, on the homomorphic encryption, all joined with other techniques to enhance the cryptosystem performance and the privacy ratio. In

    更新日期:2020-04-25
  • Conversational agents in business: A systematic literature review and future research directions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-04-06
    Rodrigo Bavaresco, Diórgenes Silveira, Eduardo Reis, Jorge Barbosa, Rodrigo Righi, Cristiano Costa, Rodolfo Antunes, Marcio Gomes, Clauter Gatti, Mariangela Vanzin, Saint Clair Junior, Elton Silva, Carlos Moreira

    The field of business shows an increasing interest in exploring conversational agents to improve service quality and market competitiveness. Furthermore, the advances in machine learning capabilities leverage the natural language processing towards natural and straightforward dialogue experiences for industries. However, in the best of our knowledge, no literature review outlines conversational agents

    更新日期:2020-04-06
  • Comparative study for 8 computational intelligence algorithms for human identification
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-04-01
    Shaymaa Adnan Abdulrahman, Wael Khalifa, Mohamed Roushdy, Abdel-Badeeh M. Salem

    The biometric system includes the algorithms, procedures, and devices which are utilized for the purpose of recognizing individuals according to their behavioral and physiological features. The approaches of Computational Intelligence (CI) are utilized extensively to establish biometric-based identities as well as overcoming non-idealities usually exist in samples. The objective of this paper is to

    更新日期:2020-04-01
  • I2CE3: A dedicated and separated attack chain for ransomware offenses as the most infamous cyber extortion
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-02-29
    Masoudeh Keshavarzi, Hamid Reza Ghaffary

    “All of your files have been encrypted!”, “Your device has been locked!”, and so on are the sentences that these days are often seen in the cyber world. Motivated by recent promotions of technology, ransomware attack has soared saliently in terms of volume, versatility, and intricacy. This attack has initiated a lucrative trade by holding users’ resources, whether data or non-data, hostage and demanding

    更新日期:2020-02-29
  • XML data manipulation in conventional and temporal XML databases: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-02-17
    Zouhaier Brahmia, Hind Hamrouni, Rafik Bouaziz

    After more than two decades of its use, XML is not only a standard format for exchanging data between different (Web) applications but also a model for a family of some emerging or NoSQL databases, called XML databases. In addition to its efficiency in the management of conventional data (i.e., data without a temporal reference), XML is also an excellent support for storing, manipulating, and querying

    更新日期:2020-02-17
  • Relational intelligence recognition in online social networks — A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-02-04
    Ji Zhang, Leonard Tan, Xiaohui Tao, Thuan Pham, Bing Chen

    Information networks today play an important, fundamental role in regulating real life activities. However, many methods developed on this framework lack the capacity to adequately represent sophistication contained within the information it carries. As a result, they suffer from problems such as inaccuracies, reliability and performance. We define relational intelligence as a combination of affective

    更新日期:2020-02-04
  • A review of attack graph and attack tree visual syntax in cyber security
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-01-11
    Harjinder Singh Lallie, Kurt Debattista, Jay Bal

    Perceiving and understanding cyber-attacks can be a difficult task, and more effective techniques are needed to aid cyber-attack perception. Attack modelling techniques (AMTs) - such as attack graphs, attack trees and fault trees, are a popular method of mathematically and visually representing the sequence of events that lead to a successful cyber-attack. These methods are useful visual aids that

    更新日期:2020-01-11
  • Combining UML and ontology: An exploratory survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2020-01-08
    Meriem Mejhed Mkhinini, Ouassila Labbani-Narsis, Christophe Nicolle

    UML models and ontologies are two knowledge representations with different strengths and weaknesses. Until recently, they were considered unrelated research domains. However, studies investigating their underlying paradigms and the approaches combining these two are increasingly emerging. Nevertheless, the state of the art research covering the relationship between the two is still under exploration

    更新日期:2020-01-08
  • Application of deep learning for retinal image analysis: A review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-12-18
    Maryam Badar, Muhammad Haris, Anam Fatima

    Retinal image analysis holds an imperative position for the identification and classification of retinal diseases such as Diabetic Retinopathy (DR), Age Related Macular Degeneration (AMD), Macular Bunker, Retinoblastoma, Retinal Detachment, and Retinitis Pigmentosa. Automated identification of retinal diseases is a big step towards early diagnosis and prevention of exacerbation of the disease. A number

    更新日期:2019-12-18
  • Transaction scheduling protocols for controlling priority inversion: A review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-11-19
    Sarvesh Pandey, Udai Shanker

    In advanced real-time distributed computing databases, the main performance criterion is to reduce the ‘deadline miss’ by the transactions; of course, consistency constraints also need to be satisfied. The goal of these applications is not to provide simply real-time transaction execution, but rather to provide a highly predictable, analysable, schedulable and reliable distributed computing platform

    更新日期:2019-11-19
  • Background subtraction in real applications: Challenges, current models and future directions
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-11-18
    Belmar Garcia-Garcia, Thierry Bouwmans, Alberto Jorge Rosales Silva

    Computer vision applications based on videos often require the detection of moving objects in their first step. Background subtraction is then applied in order to separate the background and the foreground. In literature, background subtraction is surely among the most investigated field in computer vision providing a big amount of publications. Most of them concern the application of mathematical

    更新日期:2019-11-18
  • Machine learning and multi-agent systems in oil and gas industry applications: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-11-05
    Khadijah M. Hanga, Yevgeniya Kovalchuk

    The oil and gas industry (OGI) has always been associated with challenges and complexities. It involves many processes and stakeholders, each generating a huge amount of data. Due to the global and distributed nature of the business, processing and managing this information is an arduous task. Many issues such as orchestrating different data sources, owners and formats; verifying, validating and securing

    更新日期:2019-11-05
  • A taxonomy and survey of attacks against machine learning
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-10-23
    Nikolaos Pitropakis, Emmanouil Panaousis, Thanassis Giannetsos, Eleftherios Anastasiadis, George Loukas

    The majority of machine learning methodologies operate with the assumption that their environment is benign. However, this assumption does not always hold, as it is often advantageous to adversaries to maliciously modify the training (poisoning attacks) or test data (evasion attacks). Such attacks can be catastrophic given the growth and the penetration of machine learning applications in society.

    更新日期:2019-10-23
  • A comparative review of Urdu stemmers: Approaches and challenges
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-09-25
    Abdul Jabbar, Saif ul Islam, Shafiq Hussain, Adnan Akhunzada, Manzoor Ilahi

    With the advent of globalization epoch, the Internet-based resources for Urdu are increasing in depth and breadth at a higher pace than ever and thus require a mechanism for computational processing of Urdu text. Information retrieval (IR) systems have now become the major tool for seeking varied information on the web. It uses variant forms of the word transformed through stemmer. Broadly speaking

    更新日期:2019-09-25
  • Prediction methods and applications in the science of science: A survey
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-09-25
    Jie Hou, Hanxiao Pan, Teng Guo, Ivan Lee, Xiangjie Kong, Feng Xia

    Science of science has become a popular topic that attracts great attentions from the research community. The development of data analytics technologies and the readily available scholarly data enable the exploration of data-driven prediction, which plays a pivotal role in finding the trend of scientific impact. In this paper, we analyse methods and applications in data-driven prediction in the science

    更新日期:2019-09-25
  • Data Mining and Information Retrieval in the 21st century: A bibliographic review
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-09-16
    Jiaying Liu, Xiangjie Kong, Xinyu Zhou, Lei Wang, Da Zhang, Ivan Lee, Bo Xu, Feng Xia

    Data Mining and Information Retrieval is an emerging interdisciplinary discipline dealing with Information Retrieval and Data Mining techniques. It has undergone rapid development with the advances in mathematics, statistics, information science, and computer science. In this paper, we present an empirical analysis of publication metadata obtained from 6 top-tier journals and 9 conferences for the

    更新日期:2019-09-16
  • Systematic analysis and review of stock market prediction techniques
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-08-28
    Dattatray P. Gandhmal, K. Kumar

    Prediction of stock market trends is considered as an important task and is of great attention as predicting stock prices successfully may lead to attractive profits by making proper decisions. Stock market prediction is a major challenge owing to non-stationary, blaring, and chaotic data, and thus, the prediction becomes challenging among the investors to invest the money for making profits. Several

    更新日期:2019-08-28
  • Model-based testing using UML activity diagrams: A systematic mapping study
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-07-24
    Tanwir Ahmad, Junaid Iqbal, Adnan Ashraf, Dragos Truscan, Ivan Porres

    Context: The Unified Modeling Language (UML) has become the de facto standard for software modeling. UML models are often used to visualize, understand, and communicate the structure and behavior of a system. UML activity diagrams (ADs) are often used to elaborate and visualize individual use cases. Due to their higher level of abstraction and process-oriented perspective, UML ADs are also highly suitable

    更新日期:2019-07-24
  • A brief survey on probability distribution approximation
    Comput. Sci. Rev. (IF 7.707) Pub Date : 2019-07-01
    Massimo Melucci

    Probability distributions are extensively utilized in many areas of Computer Science such as Machine Learning, Information Retrieval and Databases. The computation of a probability distribution can be a difficult task because of the exponential size of the event space. As a consequence, researchers investigated methods for approximating probability distributions. This article provides a brief survey

    更新日期:2019-07-01
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