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The shift to 6G communications: vision and requirements Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-12-21 Muhammad Waseem Akhtar, Syed Ali Hassan, Rizwan Ghaffar, Haejoon Jung, Sahil Garg, M. Shamim Hossain
The sixth-generation (6G) wireless communication network is expected to integrate the terrestrial, aerial, and maritime communications into a robust network which would be more reliable, fast, and can support a massive number of devices with ultra-low latency requirements. The researchers around the globe are proposing cutting edge technologies such as artificial intelligence (AI)/machine learning
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Social Internet of Things: vision, challenges, and trends Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-12-18 Mozhgan Malekshahi Rad, Amir Masoud Rahmani, Amir Sahafi, Nooruldeen Nasih Qader
IoT describes a new world of billions of objects that intelligently communicate and interact with each other. One of the important areas in this field is a new paradigm-Social Internet of Things (SIoT), a new concept of combining social networks with IoT. SIoT is an imitation of social networks between humans and objects. Objects like humans are considered intelligent and social. They create their
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A model-driven approach to ensure trust in the IoT Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-12-14 Davide Ferraris, Carmen Fernandez-Gago, Javier Lopez
The Internet of Things (IoT) is a paradigm that permits smart entities to be interconnected anywhere and anyhow. IoT opens new opportunities but also rises new issues. In this dynamic environment, trust is useful to mitigate these issues. In fact, it is important that the smart entities could know and trust the other smart entities in order to collaborate with them. So far, there is a lack of research
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Multiple Kinect based system to monitor and analyze key performance indicators of physical training Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-12-14 Karolis Ryselis, Tautvydas Petkus, Tomas Blažauskas, Rytis Maskeliūnas, Robertas Damaševičius
Using a single Kinect device for human skeleton tracking and motion tracking lacks of reliability required in sports medicine and rehabilitation domains. Human joints reconstructed from non-standard poses such as squatting, sitting and lying are asymmetric and have unnatural lengths while their recognition error exceeds the error of recognizing standard poses. In order to achieve higher accuracy and
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An efficient attribute-based hierarchical data access control scheme in cloud computing Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-12-05 Heng He, Liang-han Zheng, Peng Li, Li Deng, Li Huang, Xiang Chen
Security issues in cloud computing have become a hot topic in academia and industry, and CP-ABE is an effective solution for managing and protecting data. When data is shared in cloud computing, they usually have multiple access structures that have hierarchical relationships. However, existing CP-ABE algorithms do not consider such relationships and just require data owners to generate multiple ciphertexts
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The effect of eye movements and cultural factors on product color selection Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-11-24 Bo Wu, Yishui Zhu, Keping Yu, Shoji Nishimura, Qun Jin
A color is a powerful tool used to attract people’s attention and to entice them to purchase a product. However, the way in which a specific color influences people’s color selection and the role of their eye movements and cultural factors in this process remain unknown. In this study, to delve into this problem, we designed an experiment to determine the influence of specific colors on people’s product
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Collaborative behavior, performance and engagement with visual analytics tasks using mobile devices Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-11-22 Lei Chen, Hai-Ning Liang, Feiyu Lu, Konstantinos Papangelis, Ka Lok Man, Yong Yue
Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visualizations. This research investigates the use of co-located collaborative visualizations in mobile devices, how users working with two different modes of interaction and view (Shared or Non-Shared) and how being placed at
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Facial UV map completion for pose-invariant face recognition: a novel adversarial approach based on coupled attention residual UNets Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-11-10 In Seop Na, Chung Tran, Dung Nguyen, Sang Dinh
Pose-invariant face recognition refers to the problem of identifying or verifying a person by analyzing face images captured from different poses. This problem is challenging due to the large variation of pose, illumination and facial expression. A promising approach to deal with pose variation is to fulfill incomplete UV maps extracted from in-the-wild faces, then attach the completed UV map to a
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Medical image processing with contextual style transfer Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-11-10 Yin Xu, Yan Li, Byeong-Seok Shin
With recent advances in deep learning research, generative models have achieved great achievements and play an increasingly important role in current industrial applications. At the same time, technologies derived from generative methods are also under a wide discussion with researches, such as style transfer, image synthesis and so on. In this work, we treat generative methods as a possible solution
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Newspaper article-based agent control in smart city simulations Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-11-03 Euhee Kim, Sejun Jang, Shuyu Li, Yunsick Sung
The latest research on smart city technologies mainly focuses on utilizing cities’ resources to improve the quality of the lives of citizens. Diverse kinds of control signals from massive systems and devices such as adaptive traffic light systems in smart cities can be collected and utilized. Unfortunately, it is difficult to collect a massive dataset of control signals as doing so in the real-world
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TSME: a trust-based security scheme for message exchange in vehicular Ad hoc networks Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-10-17 Ryma Abassi, Aida Ben Chehida Douss, Damien Sauveron
A Vehicular Ad hoc NETwork (VANET) is a self-organized network formed by connected vehicles, which allows the exchange of useful traffic information in a timely manner. In such a context, evaluating the reliability of transmissions is vital. Trust can be used to promote such healthy collaboration. In fact, trust enables collaborating vehicles to counter uncertainty and suspicion by establishing trustworthy
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TMaR: a two-stage MapReduce scheduler for heterogeneous environments Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-10-07 Neda Maleki, Hamid Reza Faragardi, Amir Masoud Rahmani, Mauro Conti, Jay Lofstead
In the context of MapReduce task scheduling, many algorithms mainly focus on the scheduling of Reduce tasks with the assumption that scheduling of Map tasks is already done. However, in the cloud deployments of MapReduce, the input data is located on remote storage which indicates the importance of the scheduling of Map tasks as well. In this paper, we propose a two-stage Map and Reduce task scheduler
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Deep learning scheme for character prediction with position-free touch screen-based Braille input method Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-09-19 Sana Shokat, Rabia Riaz, Sanam Shahla Rizvi, Abdul Majid Abbasi, Adeel Ahmed Abbasi, Se Jin Kwon
Smart devices are effective in helping people with impairments, overcome their disabilities, and improve their living standards. Braille is a popular method used for communication by visually impaired people. Touch screen smart devices can be used to take Braille input and instantaneously convert it into a natural language. Most of these schemes require location-specific input that is difficult for
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A collaborative healthcare framework for shared healthcare plan with ambient intelligence Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-09-11 Abdul Rehman Javed, Muhammad Usman Sarwar, Mirza Omer Beg, Muhammad Asim, Thar Baker, Hissam Tawfik
The fast propagation of the Internet of Things (IoT) devices has driven to the development of collaborative healthcare frameworks to support the next generation healthcare industry for quality medical healthcare. This paper presents a generalized collaborative framework named collaborative shared healthcare plan (CSHCP) for cognitive health and fitness assessment of people using ambient intelligent
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SD2PA: a fully safe driving and privacy-preserving authentication scheme for VANETs Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-09-02 Saad Ali Alfadhli, Songfeng Lu, Abdulaziz Fatani, Haider Al-Fedhly, Mahmut Ince
The basic idea behind the vehicular ad-hoc network (VANET) is the exchange of traffic information between vehicles and the surrounding environment to offer a better driving experience. Privacy and security are the main concerns for meeting the safety aims of the VANET system. In this paper, we analyse recent VANET schemes that utilise a group authentication technique and found important vulnerabilities
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Modelling email traffic workloads with RNN and LSTM models Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-09-02 Khandu Om, Spyros Boukoros, Anupiya Nugaliyadde, Tanya McGill, Michael Dixon, Polychronis Koutsakis, Kok Wai Wong
Analysis of time series data has been a challenging research subject for decades. Email traffic has recently been modelled as a time series function using a Recurrent Neural Network (RNN) and RNNs were shown to provide higher prediction accuracy than previous probabilistic models from the literature. Given the exponential rise of email workloads which need to be handled by email servers, in this paper
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Robust cooperative car-parking: implications and solutions for selfish inter-vehicular social behaviour Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-08-26 Ali Aliedani, Seng W. Loke, Sebastien Glaser
Vehicular cooperation mechanisms are known to provide efficiency and scalability benefits but for the mechanisms to be human-centric, there is a need for them to be robust and resilient to anti-social behaviours such as deception. More specifically, decentralised vehicle-to-vehicle cooperation has been shown to be an effective and convenient approach to coordinate the use of dynamically changing common
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Automatic, location-privacy preserving dashcam video sharing using blockchain and deep learning Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-08-26 Taehyoung Kim, Im Y. Jung, Yih-Chun Hu
Today, many people use dashcams, and videos recorded on dashcams are often used as evidence of accident fault. People can upload videos of dashcam recordings with specific accident clips and share the videos with others who request them, by providing the time or location of an accident. However, dashcam videos are erased when the dashcam memory is full, so periodic backup is necessary for video sharing
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CAPHAR: context-aware personalized human activity recognition using associative learning in smart environments Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-08-12 Sunder Ali Khowaja, Bernardo Nugroho Yahya, Seok-Lyong Lee
The existing action recognition systems mainly focus on generalized methods to categorize human actions. However, the generalized systems cannot attain the same level of recognition performance for new users mainly due to the high variance in terms of human behavior and the way of performing actions, i.e. activity handling. The use of personalized models based on similarity was introduced to overcome
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Cloud spot instance price prediction using k NN regression Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-08-09 Wenqiang Liu, Pengwei Wang, Ying Meng, Caihui Zhao, Zhaohui Zhang
Cloud computing can provide users with basic hardware resources, and there are three instance types: reserved instances, on-demand instances and spot instances. The price of spot instance is lower than others on average, but it fluctuates according to market demand and supply. When a user requests a spot instance, he/she needs to give a bid. Only if the bid is not lower than the spot price, user can
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Don’t click: towards an effective anti-phishing training. A comparative literature review Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-08-09 Daniel Jampen, Gürkan Gür, Thomas Sutter, Bernhard Tellenbach
Email is of critical importance as a communication channel for both business and personal matters. Unfortunately, it is also often exploited for phishing attacks. To defend against such threats, many organizations have begun to provide anti-phishing training programs to their employees. A central question in the development of such programs is how they can be designed sustainably and effectively to
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Wi-Fi indoor positioning and navigation: a cloudlet-based cloud computing approach Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-07-16 Tran Trong Khanh, VanDung Nguyen, Xuan-Qui Pham, Eui-Nam Huh
Wi-Fi-based indoor positioning for determining accurate wireless indoor location information has become crucial in meeting increasing demands for location-based services by leveraging the Internet of Things (IoT) and ubiquitous connectivity. Most Wi-Fi-based indoor positioning techniques using wireless received signal strength (RSS)-based methods are affected by the indoor environment and depend on
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Hybrid decentralized PBFT Blockchain Framework for OpenStack message queue Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-07-15 Youngjong Kim, Jinho Park
Cloud computing based on OpenStack is widely used as a distributed computing platform. OpenStack has progressed at a rapid pace, incorporating a variety of service modules; it is supported by many companies, has a community of active developers, and a diverse user base. OpenStack uses message queue to coordinate and exchange operation and status information between services. OpenStack supports various
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Context-aware auction solution of cooperative fish market monitoring system for intelligent user Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-07-14 Yeong-Seok Seo, Jun-Ho Huh
This study proposes a context-aware auction solution suitable for the intelligent user. The solution informs the most reasonable prices for brokers after considering the size of each species of the catch along with other information and their effects on the fish price. This solution is expected to improve the safety of the catch and increase the competitiveness of auction sites by introducing a digitalized
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Parameterized algorithms of fundamental NP-hard problems: a survey Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-07-02 Wenjun Li, Yang Ding, Yongjie Yang, R. Simon Sherratt, Jong Hyuk Park, Jin Wang
Parameterized computation theory has developed rapidly over the last two decades. In theoretical computer science, it has attracted considerable attention for its theoretical value and significant guidance in many practical applications. We give an overview on parameterized algorithms for some fundamental NP-hard problems, including MaxSAT, Maximum Internal Spanning Trees, Maximum Internal Out-Branching
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SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-07-02 Federico Concone, Giuseppe Lo Re, Marco Morana
The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately
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Recognition of cooking activities through air quality sensor data for supporting food journaling Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-06-17 Federica Gerina, Silvia M. Massa, Francesca Moi, Diego Reforgiato Recupero, Daniele Riboni
Unhealthy behaviors regarding nutrition are a global risk for health. Therefore, the healthiness of an individual’s nutrition should be monitored in the medium and long term. A powerful tool for monitoring nutrition is a food diary; i.e., a daily list of food taken by the individual, together with portion information. Unfortunately, frail people such as the elderly have a hard time filling food diaries
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Improving bug report triage performance using artificial intelligence based document generation model Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-06-16 Dong-Gun Lee, Yeong-Seok Seo
Artificial intelligence is one of the key technologies for progression to the fourth industrial revolution. This technology also has a significant impact on software professionals who are continuously striving to achieve high-quality software development by fixing various types of software bugs. During the software development and maintenance stages, software bugs are the major factor that can affect
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Local differential privacy for unbalanced multivariate nominal attributes Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-06-15 Xuejie Feng, Chiping Zhang
Data with unbalanced multivariate nominal attributes collected from a large number of users provide a wealth of knowledge for our society. However, it also poses an unprecedented privacy threat to participants. Local differential privacy, a variant of differential privacy, is proposed to eliminate the privacy concern by aggregating only randomized values from each user, with the provision of plausible
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A scenario generation pipeline for autonomous vehicle simulators Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-06-03 Mingyun Wen, Jisun Park, Kyungeun Cho
To develop a realistic simulator for autonomous vehicle testing, the simulation of various scenarios that may occur near vehicles in the real world is necessary. In this paper, we propose a new scenario generation pipeline focused on generating scenarios in a specific area near an autonomous vehicle. In this method, a scenario map is generated to define the scenario simulation area. A convolutional
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A crowdsourcing method for online social networks security assessment based on human-centric computing Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-06-02 Zhiyong Zhang, Junchang Jing, Xiaoxue Wang, Kim-Kwang Raymond Choo, Brij B. Gupta
Crowdsourcing and crowd computing are a trend that is likely to be increasingly popular, and there remain a number of research and operational challenges that need to be addressed. The human-centric computational abstraction called situation may be used to cope with these difficulties. In this paper, we focus on one such challenge, which is how to assign crowd assessment tasks about security and privacy
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An anonymous authenticated key-agreement scheme for multi-server infrastructure Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-05-15 Muhammad Arslan Akram, Zahid Ghaffar, Khalid Mahmood, Saru Kumari, Kadambri Agarwal, Chien-Ming Chen
Due to single-time registration, the multi-server authentication provides benefit for getting services from different servers through trusted agent. Generally, users feel hesitation for registering themselves individually with all service providers due to the problem of memorizing the multiple passwords. The multi-server authentication allows a quick access to services by real-time customer validation
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Cyclist detection and tracking based on multi-layer laser scanner Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-05-07 Mingfang Zhang, Rui Fu, Yingshi Guo, Li Wang, Pangwei Wang, Hui Deng
The technology of Artificial Intelligence (AI) brings tremendous possibilities for autonomous vehicle applications. One of the essential tasks of autonomous vehicle is environment perception using machine learning algorithms. Since the cyclists are the vulnerable road users, cyclist detection and tracking are important perception sub-tasks for autonomous vehicles to avoid vehicle-cyclist collision
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CNN-based 3D object classification using Hough space of LiDAR point clouds Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-05-07 Wei Song, Lingfeng Zhang, Yifei Tian, Simon Fong, Jinming Liu, Amanda Gozho
With the wide application of Light Detection and Ranging (LiDAR) in the collection of high-precision environmental point cloud information, three-dimensional (3D) object classification from point clouds has become an important research topic. However, the characteristics of LiDAR point clouds, such as unstructured distribution, disordered arrangement, and large amounts of data, typically result in
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A secure electronic medical record authorization system for smart device application in cloud computing environments Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-05-07 Chin-Ling Chen, Po-Tsun Huang, Yung-Yuan Deng, Hsing-Chung Chen, Yun-Ciao Wang
As cloud computing technology matures, along with an increased application of distributed networks, increasingly larger amounts of data are being stored in the cloud, and are thus available for pervasive application. At the same time, current independent medical record systems tend to be inefficient, and most previous studies in this field fail to meet the security requirements of anonymity and unlinkability
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Indoor positioning and wayfinding systems: a survey Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-05-02 Jayakanth Kunhoth, AbdelGhani Karkar, Somaya Al-Maadeed, Abdulla Al-Ali
Navigation systems help users access unfamiliar environments. Current technological advancements enable users to encapsulate these systems in handheld devices, which effectively increases the popularity of navigation systems and the number of users. In indoor environments, lack of Global Positioning System (GPS) signals and line of sight with orbiting satellites makes navigation more challenging compared
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Generalization of intensity distribution of medical images using GANs Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-04-25 Dong-Ho Lee, Yan Li, Byeong-Seok Shin
The performance of a CNN based medical-image classification network depends on the intensities of the trained images. Therefore, it is necessary to generalize medical images of various intensities against degradation of performance. For lesion classification, features of generalized images should be carefully maintained. To maintain the performance of the medical image classification network and minimize
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Transient ischemic attack analysis through non-contact approaches Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-04-22 Qing Zhang, Yajun Li, Fadi Al-Turjman, Xihui Zhou, Xiaodong Yang
The transient ischemic attack (TIA) is a kind of sudden disease, which has the characteristics of short duration and high frequency. Since most patients can return to normal after the onset of the disease, it is often neglected. Medical research has proved that patients are prone to stroke in a relatively short time after the transient ischemic attacks. Therefore, it is extremely important to effectively
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Ensuring user authentication and data integrity in multi-cloud environment Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-04-21 Leila Megouache, Abdelhafid Zitouni, Mahieddine Djoudi
The necessity to improve security in a multi-cloud environment has become very urgent in recent years. Although in this topic, many methods using the message authentication code had been realized but, the results of these methods are unsatisfactory and heavy to apply, which, is why the security problem remains unresolved in this environment. This article proposes a new model that provides authentication
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An improved object detection algorithm based on multi-scaled and deformable convolutional neural networks Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-04-11 Danyang Cao, Zhixin Chen, Lei Gao
Object detection methods aim to identify all target objects in the target image and determine the categories and position information in order to achieve machine vision understanding. Numerous approaches have been proposed to solve this problem, mainly inspired by methods of computer vision and deep learning. However, existing approaches always perform poorly for the detection of small, dense objects
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Information cascades prediction with attention neural network Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-04-11 Yun Liu, Zemin Bao, Zhenjiang Zhang, Di Tang, Fei Xiong
Cascade prediction helps us uncover the basic mechanisms that govern collective human behavior in networks, and it also is very important in extensive other applications, such as viral marketing, online advertising, and recommender systems. However, it is not trivial to make predictions due to the myriad factors that influence a user’s decision to reshare content. This paper presents a novel method
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A multilevel features selection framework for skin lesion classification Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-03-31 Tallha Akram, Hafiz M. Junaid Lodhi, Syed Rameez Naqvi, Sidra Naeem, Majed Alhaisoni, Muhammad Ali, Sajjad Ali Haider, Nadia N. Qadri
Melanoma is considered to be one of the deadliest skin cancer types, whose occurring frequency elevated in the last few years; its earlier diagnosis, however, significantly increases the chances of patients’ survival. In the quest for the same, a few computer based methods, capable of diagnosing the skin lesion at initial stages, have been recently proposed. Despite some success, however, margin exists
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Text and phone calls: user behaviour and dual-channel communication prediction Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-03-30 Shamaila Hayat, Aimal Rextin, Adnan Idris, Mehwish Nasim
The contact list size of modern mobile phone users has increased up to hundreds of contacts, making contact retrieval a relatively difficult task. Various algorithms have been designed to predict the contact that a user will call at a given time. These algorithms use historical call data to make this prediction. However, modern mobile users do not just make calls, but also rely on various communication
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Exploring coupled images fusion based on joint tensor decomposition Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-03-27 Liangfu Lu, Xiaoxu Ren, Kuo-Hui Yeh, Zhiyuan Tan, Jocelyn Chanussot
Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the estimation accuracy and explain related latent variables of other coupled datasets. This paper proposes several kinds of coupled images decomposition algorithms
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A blockchain-based smart home gateway architecture for preventing data forgery Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-03-17 Younghun Lee, Shailendra Rathore, Jin Ho Park, Jong Hyuk Park
With the advancement of Information and Communication Technology (ICT) and the proliferation of sensor technologies, the Internet of Things (IoT) is now being widely used in smart home for the purposes of efficient resource management and pervasive sensing. In smart homes, various IoT devices are connected to each other, and these connections are centered on gateways. The role of gateways in the smart
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Designing human-centric software artifacts with future users: a case study Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-03-10 Marco Roccetti, Catia Prandi, Silvia Mirri, Paola Salomoni
The quality and quantity of participation supplied by human beings during the different phases of the design and development of a software artifact are central to studies in human-centered computing. With this paper, we have investigated on what kind of experienced people should be engaged to design a new computational artifact, when a participatory approach is adopted. We compared two approaches:
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Identifying smartphone users based on how they interact with their phones Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-02-28 Mohammed A. Alqarni, Sajjad Hussain Chauhdary, Maryam Naseer Malik, Muhammad Ehatisham-ul-Haq, Muhammad Awais Azam
The continuous advancement in the Internet of Things technology allows people to connect anywhere at any time, thus showing great potential in technology like smart devices (including smartphones and wearable devices). However, there is a possible risk of unauthorized access to these devices and technologies. Unfortunately, frequently used authentication schemes for protecting smart devices (such as
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Low-rate DoS attack detection based on two-step cluster analysis and UTR analysis Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-02-06 Dan Tang, Rui Dai, Liu Tang, Xiong Li
Low-rate denial of service (LDoS) attacks send attacking bursts intermittently to the network which can severely degrade the victim system’s Quality of Service (QoS). The low-rate nature of such attacks complicates attack detection. LDoS attacks repeatedly trigger the congestion control mechanism, which can make TCP traffic extremely unstable. This paper investigates the network traffic’ characteristics
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A deep learning approach for pressure ulcer prevention using wearable computing Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-02-03 Giovanni Cicceri, Fabrizio De Vita, Dario Bruneo, Giovanni Merlino, Antonio Puliafito
In recent years, statistics have confirmed that the number of elderly people is increasing. Aging always has a strong impact on the health of a human being; from a biological of point view, this process usually leads to several types of diseases mainly due to the impairment of the organism. In such a context, healthcare plays an important role in the healing process, trying to address these problems
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Proposal and testing goals-guided interaction for occasional users Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-02-01 Antonio L. Carrillo, Juan A. Falgueras
The latest shifts in technology have brought about new kinds of users who occasionally access unfamiliar systems in new scenarios. This way of use should not request any learning curve. There have been many attempts to help this kind of users: agents, floating help, tooltips, direct video demonstrations, etc., elements that support the appealing direct manipulation style (DM), but add indeed an extra
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Intelligent video interview agent used to predict communication skill and perceived personality traits Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-01-08 Hung-Yue Suen, Kuo-En Hung, Chien-Liang Lin
The prediction of individual interpersonal communication skills and personality traits is a critical issue in both industrial and organizational psychology and affective computing. In this study, we invited 114 participants, including 57 interviewers and 57 interviewees, to collect the ground truth of interviewees’ communication skills and personality traits as perceived by real human interviewers
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Indoor acoustic localization: a survey Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-01-06 Manni Liu, Linsong Cheng, Kun Qian, Jiliang Wang, Jin Wang, Yunhao Liu
Applications of localization range from body tracking, gesture capturing, indoor plan construction to mobile health sensing. Technologies such as inertial sensors, radio frequency signals and cameras have been deeply excavated to locate targets. Among all the technologies, the acoustic signal gains enormous favor considering its comparatively high accuracy with common infrastructure and low time latency
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Developing an online hate classifier for multiple social media platforms Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2020-01-02 Joni Salminen, Maximilian Hopf, Shammur A. Chowdhury, Soon-gyo Jung, Hind Almerekhi, Bernard J. Jansen
The proliferation of social media enables people to express their opinions widely online. However, at the same time, this has resulted in the emergence of conflict and hate, making online environments uninviting for users. Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. To address this research
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Intelligent data cache based on content popularity and user location for Content Centric Networks Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-12-26 Hsin-Te Wu, Hsin-Hung Cho, Sheng-Jie Wang, Fan-Hsun Tseng
Content cache as well as data cache is vital to Content Centric Network (CCN). A sophisticated cache scheme is necessary but unsatisfied currently. Existing content cache scheme wastes router’s cache capacity due to redundant replica data in CCN routers. The paper presents an intelligent data cache scheme, viz content popularity and user location (CPUL) scheme. It tackles the cache problem of CCN routers
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Understanding freehand gestures: a study of freehand gestural interaction for immersive VR shopping applications Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-12-10 Huiyue Wu, Weizhou Luo, Neng Pan, Shenghuan Nan, Yanyi Deng, Shengqian Fu, Liuqingqing Yang
Unlike retail stores, in which the user is forced to be physically present and active during restricted opening hours, online shops may be more convenient, functional and efficient. However, traditional online shops often have a narrow bandwidth for product visualizations and interactive techniques and lack a compelling shopping context. In this paper, we report a study on eliciting user-defined gestures
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Emotion classification based on brain wave: a survey Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-12-02 Ting-Mei Li, Han-Chieh Chao, Jianming Zhang
Brain wave emotion analysis is the most novel method of emotion analysis at present. With the progress of brain science, it is found that human emotions are produced by the brain. As a result, many brain-wave emotion related applications appear. However, the analysis of brain wave emotion improves the difficulty of analysis because of the complexity of human emotion. Many researchers used different
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Correction to: Detection and classification of social media-based extremist affiliations using sentiment analysis techniques Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-07-11 Shakeel Ahmad,Muhammad Zubair Asghar,Fahad M. Alotaibi,Irfanullah Awan
In the original publication of this article [1], the Acknowledgements and Funding section in Declarations need to be revised.
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Overlapping community detection for count-value networks Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-11-21 QianCheng Yu, ZhiWen Yu, Zhu Wang, XiaoFeng Wang, YongZhi Wang
Detecting network overlapping community has become a very hot research topic in the literature. However, overlapping community detection for count-value networks that naturally arise and are pervasive in our modern life, has not yet been thoroughly studied. We propose a generative model for count-value networks with overlapping community structure and use the Indian buffet process to model the community
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Human motion recognition based on SVM in VR art media interaction environment Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-11-15 Fuquan Zhang, Tsu-Yang Wu, Jeng-Shyang Pan, Gangyi Ding, Zuoyong Li
In order to solve the problem of human motion recognition in multimedia interaction scenarios in virtual reality environment, a motion classification and recognition algorithm based on linear decision and support vector machine (SVM) is proposed. Firstly, the kernel function is introduced into the linear discriminant analysis for nonlinear projection to map the training samples into a high-dimensional
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Cybersecurity profiles based on human-centric IoT devices Hum. Cent. Comput. Inf. Sci. (IF 6.6) Pub Date : 2019-11-01 Ana Nieto, Ruben Rios
This paper proposes a methodology based on the concept of Human Factors to obtain Cybersecurity profiles. The profiles are determined by a set of parameters that help model the skills of individuals (potential offenders, victims, etc.) during a digital investigation. The definition is flexible enough to allow the cybersecurity profiles to grow when more data is available. A critical part of the solution