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Information, Volume 10, Issue 1 (January 2019) – 33 articles

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13 pages, 794 KiB  
Article
Architecture of a Dispersed Gamification System for Tourist Attractions
by Jakub Swacha
Information 2019, 10(1), 33; https://doi.org/10.3390/info10010033 - 19 Jan 2019
Cited by 10 | Viewed by 4739
Abstract
The paper addresses the issues of implementing e-guide-based gamification systems for tourist attractions by proposing a dispersed gamification system architecture in which its respective functional aspects are handled by multiple web services with various scopes of responsibility. The features provided by the proposed [...] Read more.
The paper addresses the issues of implementing e-guide-based gamification systems for tourist attractions by proposing a dispersed gamification system architecture in which its respective functional aspects are handled by multiple web services with various scopes of responsibility. The features provided by the proposed architecture are successfully matched to tourist attraction requirements identified during development of an e-guide gamification system for an international consortium of tourist attractions. The key contributions of the paper are: the new definition of gamification system extending beyond the concept of a set of game-based rules and including the information technology components necessary to implement it; mapping the abstract gamification system model into the domain of tourist attraction gamification and the analysis of advantages and disadvantages of various organizations of e-guide gamification systems; the introduction of a new, dispersed architecture of e-guide gamification system that addresses the identified needs of tourist attractions. Full article
(This article belongs to the Special Issue Cloud Gamification)
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16 pages, 2289 KiB  
Article
Towards Personal Virtual Traffic Lights
by Vanessa Martins, João Rufino, Luis Silva, João Almeida, Bruno Miguel Fernandes Silva, Joaquim Ferreira and José Fonseca
Information 2019, 10(1), 32; https://doi.org/10.3390/info10010032 - 17 Jan 2019
Cited by 5 | Viewed by 4255
Abstract
Traffic control management at intersections, a challenging and complex field of study, aims to strike a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, [...] Read more.
Traffic control management at intersections, a challenging and complex field of study, aims to strike a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, such as poor efficiency and real-time adaptability. With the advent of Intelligent Transportation Systems (ITS), vehicles are being equipped with state-of-the-art technology, enabling cooperative decision-making which will certainly overwhelm the available traffic control systems. This solution strongly penalizes users without such capabilities, namely pedestrians, cyclists, and other legacy vehicles. Therefore, in this work, a prototype based on an alternative technology to the standard vehicular communications, Bluetooth Low Energy (BLE), is presented. The proposed framework aims to integrate legacy and modern vehicular communication systems into a cohesive management system. In this framework, the movements of users at intersections are managed by a centralized controller which, through the use of networked retransmitters deployed at intersections, broadcasts alerts and virtual light signalization orders. Users receive the aforementioned information on their own smart devices, discarding the need for dedicated light signalization infrastructures. Field tests, carried out with a real-world implementation, validate the correct operation of the proposed framework. Full article
(This article belongs to the Special Issue Vehicular Networks and Applications)
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6 pages, 177 KiB  
Essay
The Universality of Experiential Consciousness
by Robert K. Logan
Information 2019, 10(1), 31; https://doi.org/10.3390/info10010031 - 17 Jan 2019
Cited by 1 | Viewed by 3002
Abstract
It is argued that of Block’s (On a confusion about a function of consciousness, 1995; The Nature of Consciousness: Philosophical Debates, 1997) two types of consciousness, namely phenomenal consciousness (p-consciousness) and access consciousness (a-consciousness), that p-consciousness applies to all living things but that [...] Read more.
It is argued that of Block’s (On a confusion about a function of consciousness, 1995; The Nature of Consciousness: Philosophical Debates, 1997) two types of consciousness, namely phenomenal consciousness (p-consciousness) and access consciousness (a-consciousness), that p-consciousness applies to all living things but that a-consciousness is uniquely human. This differs from Block’s assertion that a-consciousness also applies to some non-human organisms. It is suggested that p-consciousness, awareness, experience and perception are basically equivalent and that human consciousness has in addition to percept-based p-consciousness, concept-based a-consciousness, a verbal and conceptual form of consciousness that can be utilized to coordinate, organize and plan activities for rational decision-making. This argument is based on Logan’s (The Extended Mind: The Emergence of Language, The Human Mind and Culture, 1997) assertion that humans are uniquely capable of reasoning and rationality because they are uniquely capable of verbal language and hence the ability to conceptualize. Full article
(This article belongs to the Special Issue AI AND THE SINGULARITY: A FALLACY OR A GREAT OPPORTUNITY?)
11 pages, 2858 KiB  
Article
Automatic Diagnosis of Neurodegenerative Diseases: An Evolutionary Approach for Facing the Interpretability Problem
by Rosa Senatore, Antonio Della Cioppa and Angelo Marcelli
Information 2019, 10(1), 30; https://doi.org/10.3390/info10010030 - 17 Jan 2019
Cited by 21 | Viewed by 4008
Abstract
Background: The use of Artificial Intelligence (AI) systems for automatic diagnoses is increasingly in the clinical field, being a useful support for the identification of several diseases. Nonetheless, the acceptance of AI-based diagnoses by the physicians is hampered by the black-box approach implemented [...] Read more.
Background: The use of Artificial Intelligence (AI) systems for automatic diagnoses is increasingly in the clinical field, being a useful support for the identification of several diseases. Nonetheless, the acceptance of AI-based diagnoses by the physicians is hampered by the black-box approach implemented by most performing systems, which do not clearly state the classification rules adopted. Methods: In this framework we propose a classification method based on a Cartesian Genetic Programming (CGP) approach, which allows for the automatic identification of the presence of the disease, and concurrently, provides the explicit classification model used by the system. Results: The proposed approach has been evaluated on the publicly available HandPD dataset, which contains handwriting samples drawn by Parkinson’s disease patients and healthy controls. We show that our approach compares favorably with state-of-the-art methods, and more importantly, allows the physician to identify an explicit model relevant for the diagnosis based on the most informative subset of features. Conclusion: The obtained results suggest that the proposed approach is particularly appealing in that, starting from the explicit model, it allows the physicians to derive a set of guidelines for defining novel testing protocols and intervention strategies. Full article
(This article belongs to the Special Issue eHealth and Artificial Intelligence)
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36 pages, 1217 KiB  
Article
Full Support for Efficiently Mining Multi-Perspective Declarative Constraints from Process Logs
by Christian Sturm, Myriel Fichtner and Stefan Schönig
Information 2019, 10(1), 29; https://doi.org/10.3390/info10010029 - 15 Jan 2019
Cited by 3 | Viewed by 3676
Abstract
Declarative process management has emerged as an alternative solution for describing flexible workflows. In turn, the modelling opportunities with languages such as Declare are less intuitive and hard to implement. The area of process discovery covers the automatic discovery of process models. It [...] Read more.
Declarative process management has emerged as an alternative solution for describing flexible workflows. In turn, the modelling opportunities with languages such as Declare are less intuitive and hard to implement. The area of process discovery covers the automatic discovery of process models. It has been shown that the performance of process mining algorithms, particularly when considering the multi-perspective declarative process models, are not satisfactory. State-of-the-art mining tools do not support multi-perspective declarative models at this moment. We address this open research problem by proposing an efficient mining framework that leverages the latest big data analysis technology and builds upon the distributed processing method MapReduce. The paper at hand further completes the research on multi-perspective declarative process mining by extending our previous work in various ways; in particular, we introduce algorithms and descriptions for the full set of commonly accepted types of MP-Declare constraints. Additionally, we provide a novel implementation concept allowing an easy introduction and discovery of customised constraint templates. We evaluated the mining performance and effectiveness of the presented approach on several real-life event logs. The results highlight that, with our efficient mining technique, multi-perspective declarative process models can be extracted in reasonable time. Full article
(This article belongs to the Special Issue Selected Papers from ICEIS 2018: Advances in Enterprise Information Systems)
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21 pages, 2135 KiB  
Article
Designing and Evaluating a Virtual Patient Simulation—The Journey from Uniprofessional to Interprofessional Learning
by Nataly Martini, Kate Farmer, Shambhavi Patil, Gauis Tan, Cindy Wang, Lucy Wong and Craig S. Webster
Information 2019, 10(1), 28; https://doi.org/10.3390/info10010028 - 14 Jan 2019
Cited by 6 | Viewed by 6870
Abstract
“Ready to Practice?”(R2P) is a virtual patient simulation designed for undergraduate medical and pharmacy students. After initial prototyping, R2P developed into a screen-based virtual patient (VP) simulation with an intuitive interface using photorealistic images of people and places with speech bubbles and decision [...] Read more.
“Ready to Practice?”(R2P) is a virtual patient simulation designed for undergraduate medical and pharmacy students. After initial prototyping, R2P developed into a screen-based virtual patient (VP) simulation with an intuitive interface using photorealistic images of people and places with speech bubbles and decision menus. We describe the design of the VP, findings from student experiences with the software, and the potential of VPs for interprofessional learning. We used a mixed methods study to assess students’ perceptions of the VP as a learning tool. Qualitative data were gathered using semi-structured interviews and observations, and quantitative data through the Readiness for Interprofessional Learning Scale (RIPLS) and an evaluation questionnaire. Overall, participants showed significantly improved RIPLS scores after participation in the simulation (78.78 to 82.25, p < 0.0001), including in the Positive Professional Identify domain (p < 0.001). Students also showed significant improvement in RIPLS scores in the Teamwork and Collaboration domain when pharmacy and medical students were working together in interprofessional pairs (40.75 to 43.00, p < 0.006) but not when working alone (n.s.). Five themes emerged from interviews where participants identified specific interprofessional insights into each other’s roles and skills. Students found the VP engaging and valuable for their learning and their understanding of teamwork. Full article
(This article belongs to the Special Issue Serious Games and Applications for Health (SeGAH 2018))
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22 pages, 739 KiB  
Review
Forecasting Issues of Wireless Communication Networks’ Cyber Resilience for An Intelligent Transportation System: An Overview of Cyber Attacks
by Mikhail Buinevich and Andrei Vladyko
Information 2019, 10(1), 27; https://doi.org/10.3390/info10010027 - 14 Jan 2019
Cited by 19 | Viewed by 6602
Abstract
During the last decade there has been an essential development of wireless communication technologies for intelligent transportation system (ITS) applications for motor transport; these advanced infocommunication technologies are called vehicular ad hoc networks (VANET). VANET/ITS, in particular, inform and warn drivers about possible [...] Read more.
During the last decade there has been an essential development of wireless communication technologies for intelligent transportation system (ITS) applications for motor transport; these advanced infocommunication technologies are called vehicular ad hoc networks (VANET). VANET/ITS, in particular, inform and warn drivers about possible obstacles, and also the possibility of how to organize coordinated actions. Therefore, any violation of its functioning by cyber attacks automatically influences the safety of people and automotive engineering on the road. The purpose of this article is to provide an analytical overview of cyber attacks on VANET/ITS, presented in state-of-the-art publications on this topic by the prediction of its cyber resistance. We start with an analysis of the top 10 cyber threats, considered according to the following schemes: attack mechanism, vulnerability, damage, object of attack, and a counter measure. We then set out a synergistic approach for assessing the cyber resistance of the forward-looking VANET/ITS conceptual model, formed by the merger of the internet of vehicles and software-defined networking technology. Finally, we identify open issues and associated research opportunities, the main ones being the formalization of threats, vulnerability stratification, the choice of the level of network management centralization and, last but not least, the modeling and prediction of VANET/ITS cyber resistance. Full article
(This article belongs to the Special Issue Vehicular Networks and Applications)
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12 pages, 2626 KiB  
Article
Visual Object Tracking Robust to Illumination Variation Based on Hyperline Clustering
by Senquan Yang, Yuan Xie, Pu Li, Haoxiang Wen, Huan Luo and Zhaoshui He
Information 2019, 10(1), 26; https://doi.org/10.3390/info10010026 - 14 Jan 2019
Cited by 4 | Viewed by 3088
Abstract
Color histogram-based trackers have obtained excellent performance against many challenging situations. However, since the appearance of color is sensitive to illumination, they tend to achieve lower accuracy when illumination is severely variant throughout a sequence. To overcome this limitation, we propose a novel [...] Read more.
Color histogram-based trackers have obtained excellent performance against many challenging situations. However, since the appearance of color is sensitive to illumination, they tend to achieve lower accuracy when illumination is severely variant throughout a sequence. To overcome this limitation, we propose a novel hyperline clustering based discriminant model, an illumination invariant model that is able to distinguish the object from its surrounding background. Furthermore, we exploit this model and propose an anchor based scale estimation to cope with shape deformation and scale variation. Numerous experiments on recent online tracking benchmark datasets demonstrate that our approach achieve favorable performance compared with several state-of-the-art tracking algorithms. In particular, our approach achieves higher accuracy than comparative methods in the illumination variant and shape deformation challenging situations. Full article
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14 pages, 486 KiB  
Article
Identifying a Medical Department Based on Unstructured Data: A Big Data Application in Healthcare
by Veena Bansal, Abhishek Poddar and R. Ghosh-Roy
Information 2019, 10(1), 25; https://doi.org/10.3390/info10010025 - 11 Jan 2019
Cited by 3 | Viewed by 6121
Abstract
Health is an individual’s most precious asset and healthcare is one of the vehicles for preserving it. The Indian government’s spend on healthcare system is relatively low (1.2% of GDP). Consequently, Secondary and Tertiary government healthcare centers in India (that are presumed to [...] Read more.
Health is an individual’s most precious asset and healthcare is one of the vehicles for preserving it. The Indian government’s spend on healthcare system is relatively low (1.2% of GDP). Consequently, Secondary and Tertiary government healthcare centers in India (that are presumed to be of above average ratings) are always crowded. In Tertiary healthcare centers, like the All India Institute of Medical Science (AIIMS), patients are often unable to articulate their problems correctly to the healthcare center’s reception staff, so that these patients to be directed to the correct healthcare department. In this paper, we propose a system that will scan prescriptions, referral letters and medical diagnostic reports of a patient, process the input using OCR (Optical Character Recognition) engines, coupled with image processing tools, to direct the patient to the most relevant department. We have implemented and tested parts of this system wherein a patient enters his symptoms and/or provisional diagnosis; the system suggests a department based on this user input. Our system suggests the correct department 70.19% of the time. On further investigation, we found that one particular department of the hospital was over-represented. We eliminated the department from the data and performance of the system improved to 92.7%. Our system presently makes its suggestions using random forest algorithm that has been trained using two information repositories-symptoms and disease data, functional description of each medical department. It is our informed assumption that, once we have incorporated medicine information and diagnostics imaging data to train the system; and the complete medical history of the patient, performance of the system will improve further. Full article
(This article belongs to the Special Issue Selected Papers from ICEIS 2018: Advances in Enterprise Information Systems)
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12 pages, 1737 KiB  
Article
A Signal Period Detection Algorithm Based on Morphological Self-Complementary Top-Hat Transform and AMDF
by Zhao Han and Xiaoli Wang
Information 2019, 10(1), 24; https://doi.org/10.3390/info10010024 - 11 Jan 2019
Cited by 4 | Viewed by 6741
Abstract
Period detection technology for weak characteristic signals is very important in the fields of speech signal processing, mechanical engineering, etc. Average magnitude difference function (AMDF) is a widely used method to extract the period of periodic signal for its low computational complexity and [...] Read more.
Period detection technology for weak characteristic signals is very important in the fields of speech signal processing, mechanical engineering, etc. Average magnitude difference function (AMDF) is a widely used method to extract the period of periodic signal for its low computational complexity and high accuracy. However, this method has low detection accuracy when the background noise is strong. In order to improve this method, this paper proposes a new method of period detection of the signal with single period based on the morphological self-complementary Top-Hat (STH) transform and AMDF. Firstly, the signal is de-noised by the morphological self-complementary Top-Hat transform. Secondly, the average magnitude difference function of the noise reduction sequence is calculated, and the falling trend is suppressed. Finally, a calculating adaptive threshold is used to extract the peaks at the position equal to the period of periodic signal. The experimental results show that the accuracy of periodic extraction of AMDF after Top-Hat filtering is better than that of AMDF directly. In summary, the proposed method is reliable and stable for detecting the periodic signal with weak characteristics. Full article
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11 pages, 235 KiB  
Editorial
Acknowledgement to Reviewers of Information in 2018
by Information Editorial Office
Information 2019, 10(1), 23; https://doi.org/10.3390/info10010023 - 11 Jan 2019
Viewed by 2641
Abstract
Rigorous peer-review is the corner-stone of high-quality academic publishing [...] Full article
17 pages, 1479 KiB  
Article
Quantum-Behaved Particle Swarm Optimization with Weighted Mean Personal Best Position and Adaptive Local Attractor
by Shouwen Chen
Information 2019, 10(1), 22; https://doi.org/10.3390/info10010022 - 10 Jan 2019
Cited by 9 | Viewed by 3058
Abstract
Motivated by concepts in quantum mechanics and particle swarm optimization (PSO), quantum-behaved particle swarm optimization (QPSO) was proposed as a variant of PSO with better global search ability. In this paper, a QPSO with weighted mean personal best position and adaptive local attractor [...] Read more.
Motivated by concepts in quantum mechanics and particle swarm optimization (PSO), quantum-behaved particle swarm optimization (QPSO) was proposed as a variant of PSO with better global search ability. In this paper, a QPSO with weighted mean personal best position and adaptive local attractor (ALA-QPSO) is proposed to simultaneously enhance the search performance of QPSO and acquire good global optimal ability. In ALA-QPSO, the weighted mean personal best position is obtained by distinguishing the difference of the effect of the particles with different fitness, and the adaptive local attractor is calculated using the sum of squares of deviations of the particles’ fitness values as the coefficient of the linear combination of the particle best known position and the entire swarm’s best known position. The proposed ALA-QPSO algorithm is tested on twelve benchmark functions, and compared with the basic Artificial Bee Colony and the other four QPSO variants. Experimental results show that ALA-QPSO performs better than those compared method in all of the benchmark functions in terms of better global search capability and faster convergence rate. Full article
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14 pages, 396 KiB  
Article
The g-Good-Neighbor Diagnosability of Bubble-Sort Graphs under Preparata, Metze, and Chien’s (PMC) Model and Maeng and Malek’s (MM)* Model
by Shiying Wang and Zhenhua Wang
Information 2019, 10(1), 21; https://doi.org/10.3390/info10010021 - 10 Jan 2019
Cited by 2 | Viewed by 3151
Abstract
Diagnosability of a multiprocessor system is an important topic of study. A measure for fault diagnosis of the system restrains that every fault-free node has at least g fault-free neighbor vertices, which is called the g-good-neighbor diagnosability of the system. As a [...] Read more.
Diagnosability of a multiprocessor system is an important topic of study. A measure for fault diagnosis of the system restrains that every fault-free node has at least g fault-free neighbor vertices, which is called the g-good-neighbor diagnosability of the system. As a famous topology structure of interconnection networks, the n-dimensional bubble-sort graph B n has many good properties. In this paper, we prove that (1) the 1-good-neighbor diagnosability of B n is 2 n − 3 under Preparata, Metze, and Chien’s (PMC) model for n ≥ 4 and Maeng and Malek’s (MM) ∗ model for n ≥ 5 ; (2) the 2-good-neighbor diagnosability of B n is 4 n − 9 under the PMC model and the MM ∗ model for n ≥ 4 ; (3) the 3-good-neighbor diagnosability of B n is 8 n − 25 under the PMC model and the MM ∗ model for n ≥ 7 . Full article
(This article belongs to the Special Issue Graphs for Smart Communications Systems)
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11 pages, 1675 KiB  
Article
Generalized RDP Code Based Concurrent Repair Scheme in Cloud Storage Nodes
by Guojun Xie, Jiquan Shen and Huanhuan Yang
Information 2019, 10(1), 20; https://doi.org/10.3390/info10010020 - 09 Jan 2019
Viewed by 3059
Abstract
With the development and popularization of cloud storage technology, cloud storage has become a main method of data storage. Aiming at the problem of large delay and low availability incurred by multiple invalid nodes in cloud storage, a new type of concurrent nodes [...] Read more.
With the development and popularization of cloud storage technology, cloud storage has become a main method of data storage. Aiming at the problem of large delay and low availability incurred by multiple invalid nodes in cloud storage, a new type of concurrent nodes repair scheme called Distributed-Cross Repair Solution (DCRS) is proposed. In this scheme, system repair operation is performed in replacement nodes, and all of the replacement nodes cooperatively and crossly repair data to ensure that the data blocks that are required for repairing are only transmitted once within the system. This will solve the system repair bottleneck in the traditional repair scheme and resolve the problem of large internal network throughput and other problems, which can effectively reduce the repair delay of the system. At the same time, the repair trigger mechanism is adopted in order to avoid the repair failure problem caused by the coming of additional damaged nodes during the system reparation, which increases the system’s reliability. The simulation results show that the DCRS has obvious effects in reducing system repair delay and increasing system availability. Full article
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7 pages, 192 KiB  
Editorial
No More Privacy Any More?
by Vic Grout
Information 2019, 10(1), 19; https://doi.org/10.3390/info10010019 - 09 Jan 2019
Viewed by 3774
Abstract
The embodiment of the potential loss of privacy through a combination of artificial intelligence algorithms, big data analytics and Internet of Things technology might be something as simple, yet potentially terrifying, as an integrated app capable of recognising anyone, anytime, anywhere: effectively a [...] Read more.
The embodiment of the potential loss of privacy through a combination of artificial intelligence algorithms, big data analytics and Internet of Things technology might be something as simple, yet potentially terrifying, as an integrated app capable of recognising anyone, anytime, anywhere: effectively a global ‘Shazam for People’; but one additionally capable of returning extremely personal material about the individual. How credible is such a system? How many years away? And what might stop it? Full article
(This article belongs to the Special Issue The End of Privacy?)
18 pages, 2918 KiB  
Article
A Recommendation Model Based on Multi-Emotion Similarity in the Social Networks
by Jun Long, Yulou Wang, Xinpan Yuan, Ting Li and Qunfeng Liu
Information 2019, 10(1), 18; https://doi.org/10.3390/info10010018 - 06 Jan 2019
Cited by 3 | Viewed by 3494
Abstract
This paper proposed a recommendation model called RM-SA, which is based on multi-emotional analysis in networks. In the RM-MES scheme, the recommendation values of goods are primarily derived from the probabilities calculated by a similar existing recommendation system during the initiation stage of [...] Read more.
This paper proposed a recommendation model called RM-SA, which is based on multi-emotional analysis in networks. In the RM-MES scheme, the recommendation values of goods are primarily derived from the probabilities calculated by a similar existing recommendation system during the initiation stage of the recommendation system. First, the behaviors of those users can be divided into three aspects, including browsing goods, buying goods only, and purchasing–evaluating goods. Then, the characteristics of goods and the emotional information of user are considered to determine similarities between users and stores. We chose the most similar shop as the reference existing shop in the experiment. Then, the recommendation probability matrix of both the existing store and the new store is computed based on the similarities between users and target user, who are randomly selected. Finally, we used co-purchasing metadata from Amazon and a certain kind of comments to verify the effectiveness and performance of the RM-MES scheme proposed in this paper through comprehensive experiments. The final results showed that the precision, recall, and F1-measure were increased by 19.07%, 20.73% and 21.02% respectively. Full article
(This article belongs to the Special Issue Social Networks and Recommender Systems)
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16 pages, 5002 KiB  
Article
An Improved Reversible Image Transformation Using K-Means Clustering and Block Patching
by Haidong Zhong, Xianyi Chen and Qinglong Tian
Information 2019, 10(1), 17; https://doi.org/10.3390/info10010017 - 05 Jan 2019
Cited by 2 | Viewed by 4243
Abstract
Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in [...] Read more.
Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in image privacy protection and reversible data hiding in encrypted images. However, the amount of accessorial information, for recording the transformation parameters, is very large in the traditional RIT method, which results in an abrupt degradation of the stego-image quality. In this paper, an improved RIT method for reducing the auxiliary information is proposed. Firstly, we divide secret and target images into non-overlapping blocks, and classify these blocks into K classes by using the K-means clustering method. Secondly, we match blocks in the last (K-T)-classes using the traditional RIT method for a threshold T, in which the secret and target blocks are paired with the same compound index. Thirdly, the accessorial information (AI) produced by the matching can be represented as a secret segment, and the secret segment can be hided by patching blocks in the first T-classes. Experimental results show that the proposed strategy can reduce the AI and improve the stego-image quality effectively. Full article
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15 pages, 342 KiB  
Article
Comparing Supervised Machine Learning Strategies and Linguistic Features to Search for Very Negative Opinions
by Sattam Almatarneh and Pablo Gamallo
Information 2019, 10(1), 16; https://doi.org/10.3390/info10010016 - 04 Jan 2019
Cited by 7 | Viewed by 4038
Abstract
In this paper, we examine the performance of several classifiers in the process of searching for very negative opinions. More precisely, we do an empirical study that analyzes the influence of three types of linguistic features (n-grams, word embeddings, and polarity lexicons) and [...] Read more.
In this paper, we examine the performance of several classifiers in the process of searching for very negative opinions. More precisely, we do an empirical study that analyzes the influence of three types of linguistic features (n-grams, word embeddings, and polarity lexicons) and their combinations when they are used to feed different supervised machine learning classifiers: Naive Bayes (NB), Decision Tree (DT), and Support Vector Machine (SVM). The experiments we have carried out show that SVM clearly outperforms NB and DT in all datasets by taking into account all features individually as well as their combinations. Full article
(This article belongs to the Special Issue Knowledge Engineering and Semantic Web)
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15 pages, 996 KiB  
Article
Semantic Distance Spreading Across Entities in Linked Open Data
by Sultan Alfarhood, Susan Gauch and Kevin Labille
Information 2019, 10(1), 15; https://doi.org/10.3390/info10010015 - 02 Jan 2019
Cited by 3 | Viewed by 2847
Abstract
Recommender systems can utilize Linked Open Data (LOD) to overcome some challenges, such as the item cold start problem, as well as the problem of explaining the recommendation. There are several techniques in exploiting LOD in recommender systems; one approach, called Linked Data [...] Read more.
Recommender systems can utilize Linked Open Data (LOD) to overcome some challenges, such as the item cold start problem, as well as the problem of explaining the recommendation. There are several techniques in exploiting LOD in recommender systems; one approach, called Linked Data Semantic Distance (LDSD), considers nearby resources to be recommended by calculating a semantic distance between resources. The LDSD approach, however, has some drawbacks such as its inability to measure the semantic distance resources that are not directly linked to each other. In this paper, we first propose another variation of the LDSD approach, called wtLDSD, by extending indirect distance calculations to include the effect of multiple links of differing properties within LOD, while prioritizing link properties. Next, we introduce an approach that broadens the coverage of LDSD-based approaches beyond resources that are more than two links apart. Our experimental results show that approaches we propose improve the accuracy of the LOD-based recommendations over our baselines. Furthermore, the results show that the propagation of semantic distance calculation to reflect resources further away in the LOD graph extends the coverage of LOD-based recommender systems. Full article
(This article belongs to the Special Issue Knowledge Engineering and Semantic Web)
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15 pages, 789 KiB  
Article
Networked Euler-Lagrangian Systems Synchronization under Time-Varying Communicating Delays
by Hongjun Wang, Zhuoqun Zhao and Tao Li
Information 2019, 10(1), 14; https://doi.org/10.3390/info10010014 - 01 Jan 2019
Cited by 1 | Viewed by 2888
Abstract
This paper investigates the problem of the task-space synchronization control for networked Euler-Lagrange systems. In the considered systems, there are time-varying delays existing in the networking links and every subsystem contains uncertainties in both kinematics and dynamics. By adding new time-varying coupling gains, [...] Read more.
This paper investigates the problem of the task-space synchronization control for networked Euler-Lagrange systems. In the considered systems, there are time-varying delays existing in the networking links and every subsystem contains uncertainties in both kinematics and dynamics. By adding new time-varying coupling gains, the negative effects caused by time-varying delays are eliminated. Moreover, to address the difficulties of parametric calibration, an adaptively synchronous protocol and adaptive laws are designed to online estimate kinematics and dynamic uncertainties. Through a Lyapunov candidate and a Lyapunov-Krasovskii functional, the asymptotic convergences of tracking errors and synchronous errors are rigorously proved. The simulation results demonstrate the proposed protocol guaranteeing the cooperative tracking control of the uncalibrated networked Euler-Lagrange systems in the existence of time-varying delays. Full article
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14 pages, 2517 KiB  
Article
Throughput of Wireless-Powered Based Multiuser System with Large-Scale Distributed Antennas
by Qing Wang, Jingbo Wei and Weidong Guo
Information 2019, 10(1), 13; https://doi.org/10.3390/info10010013 - 30 Dec 2018
Cited by 2 | Viewed by 2546
Abstract
This paper investigates energy harvesting based multiuser system with large-scale distributed antennas, where a large number of remote antenna units (RAUs) are evenly separated across multiple circles. An efficient wireless energy and information transmission protocol is proposed. To save the signaling and the [...] Read more.
This paper investigates energy harvesting based multiuser system with large-scale distributed antennas, where a large number of remote antenna units (RAUs) are evenly separated across multiple circles. An efficient wireless energy and information transmission protocol is proposed. To save the signaling and the radio frequency chains overheads, the RAU with the shortest distance towards a user equipment (UE) is employed for the downlink wireless energy transfer (WET). In the uplink phase, we analyze the probability of wireless information transmission (WIT) of UEs. Then, linear zero-forcing detection and minimum-mean-square error are used to separate the data information among all the UEs that satisfy the requirement of WIT. The asymptotic throughput for an arbitrary UE is derived in closed-form. The time fraction used for the WET is optimized through maximizing the asymptotic throughput. Numerical and simulation results are given to verify the theoretical analysis, and bring to light the time fraction planning and the RAUs deployment for the system. Full article
(This article belongs to the Section Information and Communications Technology)
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14 pages, 1530 KiB  
Article
Review of Implementation of Augmented Reality into the Georeferenced Analogue and Digital Maps and Images
by Piotr A. Werner
Information 2019, 10(1), 12; https://doi.org/10.3390/info10010012 - 30 Dec 2018
Cited by 20 | Viewed by 5639
Abstract
Augmented reality (AR) combines information from databases with information derived directly through the human senses or different sensors. AR is the organic, real-time, and dynamically overlaying virtual images created by computers and other information on a real environment that the observer can see. [...] Read more.
Augmented reality (AR) combines information from databases with information derived directly through the human senses or different sensors. AR is the organic, real-time, and dynamically overlaying virtual images created by computers and other information on a real environment that the observer can see. Virtual information changes according to the movement of the observer, as if that virtual information truly exists in the real world. The convergence of geographic information systems (GIS), web mapping, mobile technology, and augmented reality (AR) implies the emergence of location based systems (LBS) and, in turn, the diminishing use of traditional analog maps by smartphone users. The focus and review of current achievements in this subject on the wider trends of the use of AR also prove that coding of some data and metadata on an image or a map (both in digital and analogue form) permits inter alia the inclusion of, for example, a paper map or analogue image into the chain of digital devices use. Some solutions, remarks, and comments concerning functioning of the digitally augmented (printed) map and their digital counterparts within the information society are presented. Full article
(This article belongs to the Special Issue Selected Papers from FIS 2017: Structure, Dynamics, Complexity in the Informational Nature)
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19 pages, 1739 KiB  
Article
Comparative Study of Ant Colony Algorithms for Multi-Objective Optimization
by Jiaxu Ning, Changsheng Zhang, Peng Sun and Yunfei Feng
Information 2019, 10(1), 11; https://doi.org/10.3390/info10010011 - 30 Dec 2018
Cited by 29 | Viewed by 4604
Abstract
In recent years, when solving MOPs, especially discrete path optimization problems, MOACOs concerning other meta-heuristic algorithms have been used and improved often, and they have become a hot research topic. This article will start from the basic process of ant colony algorithms for [...] Read more.
In recent years, when solving MOPs, especially discrete path optimization problems, MOACOs concerning other meta-heuristic algorithms have been used and improved often, and they have become a hot research topic. This article will start from the basic process of ant colony algorithms for solving MOPs to illustrate the differences between each step. Secondly, we provide a relatively complete classification of algorithms from different aspects, in order to more clearly reflect the characteristics of different algorithms. After that, considering the classification result, we have carried out a comparison of some typical algorithms which are from different categories on different sizes TSP (traveling salesman problem) instances and analyzed the results from the perspective of solution quality and convergence rate. Finally, we give some guidance about the selection of these MOACOs to solve problem and some research works for the future. Full article
(This article belongs to the Section Artificial Intelligence)
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17 pages, 2592 KiB  
Article
Contact-Less Real-Time Monitoring of Cardiovascular Risk Using Video Imaging and Fuzzy Inference Rules
by Gabriella Casalino, Giovanna Castellano, Vincenzo Pasquadibisceglie and Gianluca Zaza
Information 2019, 10(1), 9; https://doi.org/10.3390/info10010009 - 29 Dec 2018
Cited by 30 | Viewed by 5780
Abstract
Conventional methods for measuring cardiovascular parameters use skin contact techniques requiring a measuring device to be worn by the user. To avoid discomfort of contact devices, camera-based techniques using photoplethysmography have been recently introduced. Nevertheless, these solutions are typically expensive and difficult to [...] Read more.
Conventional methods for measuring cardiovascular parameters use skin contact techniques requiring a measuring device to be worn by the user. To avoid discomfort of contact devices, camera-based techniques using photoplethysmography have been recently introduced. Nevertheless, these solutions are typically expensive and difficult to be used daily at home. In this work, we propose an innovative solution for monitoring cardiovascular parameters that is low cost and can be easily integrated within any common home environment. The proposed system is a contact-less device composed of a see-through mirror equipped with a camera that detects the person’s face and processes video frames using photoplethysmography in order to estimate the heart rate, the breath rate and the blood oxygen saturation. In addition, the color of lips is automatically detected via clustering-based color quantization. The estimated parameters are used to predict a risk of cardiovascular disease by means of fuzzy inference rules integrated in the mirror-based monitoring system. Comparing our system to a contact device in measuring vital parameters on still or slightly moving subjects, we achieve measurement errors that are within acceptable margins according to the literature. Moreover, in most cases, the response of the fuzzy rule-based system is comparable with that of the clinician in assessing a risk level of cardiovascular disease. Full article
(This article belongs to the Special Issue eHealth and Artificial Intelligence)
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11 pages, 22384 KiB  
Article
Planar UWB Monopole Antenna with Tri-Band Rejection Characteristics at 3.5/5.5/8 GHz
by Jian Dong, Xin Zhuang and Guoqiang Hu
Information 2019, 10(1), 10; https://doi.org/10.3390/info10010010 - 29 Dec 2018
Cited by 4 | Viewed by 3596
Abstract
A triple band-notched ultrawide band (UWB) antenna is presented to avoid the interference of services working in the UWB band, such as WLAN, WiMAX and X-band satellite systems. The arc H-shaped slot on the radiating patch creates a low frequency notched band, while [...] Read more.
A triple band-notched ultrawide band (UWB) antenna is presented to avoid the interference of services working in the UWB band, such as WLAN, WiMAX and X-band satellite systems. The arc H-shaped slot on the radiating patch creates a low frequency notched band, while the other two band-notched bands are formed by cutting narrow slots on the ground plane. The presented antenna can operate on the ultrawide band efficiently and inhibit interference from three different kinds of narrow band communication systems. The simulation and measurement results show that the antenna has excellent band-notched function on the rejectband and almost omnidirectional radiation pattern on the passband. Full article
(This article belongs to the Section Information and Communications Technology)
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2 pages, 165 KiB  
Editorial
Special Issue on Advanced Learning Methods for Complex Data
by Maurizio Atzori and Barbara Pes
Information 2019, 10(1), 8; https://doi.org/10.3390/info10010008 - 27 Dec 2018
Cited by 1 | Viewed by 2558
Abstract
The importance of data mining methods has increased dramatically in recent years, making this research area relevant and challenging to extract actionable knowledge from complex data. Indeed, new algorithms and machine learning methods are constantly being explored to deal with domains that present [...] Read more.
The importance of data mining methods has increased dramatically in recent years, making this research area relevant and challenging to extract actionable knowledge from complex data. Indeed, new algorithms and machine learning methods are constantly being explored to deal with domains that present multiple challenges including high-dimensionality, heterogeneity of features, and complex relationships between data objects. This special issue aims at discussing emerging approaches for learning from complex data, including text data, images, and social media data. Full article
(This article belongs to the Special Issue Advanced Learning Methods for Complex Data)
15 pages, 2213 KiB  
Article
Traveling-Salesman-Problem Algorithm Based on Simulated Annealing and Gene-Expression Programming
by Ai-Hua Zhou, Li-Peng Zhu, Bin Hu, Song Deng, Yan Song, Hongbin Qiu and Sen Pan
Information 2019, 10(1), 7; https://doi.org/10.3390/info10010007 - 25 Dec 2018
Cited by 43 | Viewed by 10193
Abstract
The traveling-salesman problem can be regarded as an NP-hard problem. To better solve the best solution, many heuristic algorithms, such as simulated annealing, ant-colony optimization, tabu search, and genetic algorithm, were used. However, these algorithms either are easy to fall into local optimization [...] Read more.
The traveling-salesman problem can be regarded as an NP-hard problem. To better solve the best solution, many heuristic algorithms, such as simulated annealing, ant-colony optimization, tabu search, and genetic algorithm, were used. However, these algorithms either are easy to fall into local optimization or have low or poor convergence performance. This paper proposes a new algorithm based on simulated annealing and gene-expression programming to better solve the problem. In the algorithm, we use simulated annealing to increase the diversity of the Gene Expression Programming (GEP) population and improve the ability of global search. The comparative experiments results, using six benchmark instances, show that the proposed algorithm outperforms other well-known heuristic algorithms in terms of the best solution, the worst solution, the running time of the algorithm, the rate of difference between the best solution and the known optimal solution, and the convergent speed of algorithms. Full article
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23 pages, 719 KiB  
Article
A Comparison of Word Embeddings and N-gram Models for DBpedia Type and Invalid Entity Detection
by Hanqing Zhou, Amal Zouaq and Diana Inkpen
Information 2019, 10(1), 6; https://doi.org/10.3390/info10010006 - 25 Dec 2018
Cited by 3 | Viewed by 3727
Abstract
This article presents and evaluates a method for the detection of DBpedia types and entities that can be used for knowledge base completion and maintenance. This method compares entity embeddings with traditional N-gram models coupled with clustering and classification. We tackle two challenges: [...] Read more.
This article presents and evaluates a method for the detection of DBpedia types and entities that can be used for knowledge base completion and maintenance. This method compares entity embeddings with traditional N-gram models coupled with clustering and classification. We tackle two challenges: (a) the detection of entity types, which can be used to detect invalid DBpedia types and assign DBpedia types for type-less entities; and (b) the detection of invalid entities in the resource description of a DBpedia entity. Our results show that entity embeddings outperform n-gram models for type and entity detection and can contribute to the improvement of DBpedia’s quality, maintenance, and evolution. Full article
(This article belongs to the Special Issue Knowledge Engineering and Semantic Web)
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22 pages, 9330 KiB  
Article
Linear Offset-Free Model Predictive Control in the Dynamic PLS Framework
by Ligang Hou, Ze Wu, Xin Jin and Yue Wang
Information 2019, 10(1), 5; https://doi.org/10.3390/info10010005 - 24 Dec 2018
Cited by 2 | Viewed by 2920
Abstract
This work addresses the model predictive control (MPC) of the offset-free tracking problem in the dynamic partial least square (DyPLS) framework. Firstly, state space MPC based on the DyPLS is proposed. Then, two methods are proposed to solve the offset-free problem. One is [...] Read more.
This work addresses the model predictive control (MPC) of the offset-free tracking problem in the dynamic partial least square (DyPLS) framework. Firstly, state space MPC based on the DyPLS is proposed. Then, two methods are proposed to solve the offset-free problem. One is to reform the state space model as a velocity form. Another is to augment the state space model with a disturbance model and estimate the mismatch between system output and model output with an estimator. Both methods use the system output as a feedback in the control scheme. Hence, the offset-free tracking is guaranteed, and unmeasured step disturbance can be rejected. The results of two simulations demonstrate the effectiveness of proposed methods. Full article
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7 pages, 604 KiB  
Editorial
Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management
by Edmundas Kazimieras Zavadskas, Jurgita Antucheviciene and Prasenjit Chatterjee
Information 2019, 10(1), 4; https://doi.org/10.3390/info10010004 - 23 Dec 2018
Cited by 61 | Viewed by 7699
Abstract
Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in [...] Read more.
Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community. Full article
(This article belongs to the Special Issue Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management)
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