Information

2381 KiB

Open AccessArticle

TESMA: Requirements and Design of a Tool for Educational Programs ^†

by Nicolas Guelfi, Benjamin Jahic and Benoît Ries

Information 2017, 8(1), 37; https://doi.org/10.3390/info8010037 - 22 Mar 2017

Cited by 3 | Viewed by 7060

Defining and managing teaching programs at universities or other institutions is a complex task for which there is not much support in terms of methods and tools. This task becomes even more critical when the time comes to obtain certifications w.r.t. official standards. [...] Read more.

Defining and managing teaching programs at universities or other institutions is a complex task for which there is not much support in terms of methods and tools. This task becomes even more critical when the time comes to obtain certifications w.r.t. official standards. In this paper, we present an on-going project called TESMA, whose objective is to provide an open-source tool dedicated to the specification and management (including certification) of teaching programs. An in-depth market analysis regarding related tools and conceptual frameworks of the project is presented. This tool has been engineered using a development method called Messir for its requirements elicitation and introduces a domain-specific language dedicated to the teaching domain. This paper presents the current status of this project and the future activities planned. Full article

(This article belongs to the Special Issue Applications in Information Technology)

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2875 KiB

Open AccessArticle

Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing

by Maria Tsiplakidou, Markos G. Tsipouras, Nikolaos Giannakeas, Alexandros T. Tzallas and Pinelopi Manousou

Information 2017, 8(1), 36; https://doi.org/10.3390/info8010036 - 20 Mar 2017

Cited by 11 | Viewed by 4943

Abstract

Hepatic steatosis is the accumulation of fat in the hepatic cells and the liver. Triglycerides and other kinds of molecules are included in the lipids. When there is some defect in the process, hepatic steatosis arise, during which the free fatty acids are [...] Read more.

Hepatic steatosis is the accumulation of fat in the hepatic cells and the liver. Triglycerides and other kinds of molecules are included in the lipids. When there is some defect in the process, hepatic steatosis arise, during which the free fatty acids are taken by the liver and exuded as lipoproteins. Alcohol is the main cause of steatosis when excessive amounts are consumed for a long period of time. In many cases, steatosis can lead to inflammation that is mentioned as steatohepatitis or non-alcoholic steatohepatitis (NASH), which can later lead to fibrosis and finally cirrhosis. For automated detection and quantification of hepatic steatosis, a novel two-stage methodology is developed in this study. Initially, the image is processed in order to become more suitable for the detection of fat regions and steatosis quantification. In the second stage, initial candidate image regions are detected, and then they are either validated or discarded based on a series of criteria. The methodology is based on liver biopsy image analysis, and has been tested using 40 liver biopsy images obtained from patients who suffer from hepatitis C. The obtained results indicate that the proposed methodology can accurately assess liver steatosis. Full article

(This article belongs to the Special Issue Selected Papers from the Workshop on Intelligent Systems and Applications in Healthcare (ISA’Health 2016))

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182 KiB

Open AccessEditorial

Information and Symmetry: Adumbrating the Abstract Core of Complex Systems

by Lin Bi, Abir U. Igamberdiev and Pedro C. Marijuán

Information 2017, 8(1), 35; https://doi.org/10.3390/info8010035 - 14 Mar 2017

Viewed by 4543

Abstract

Information and symmetry are essential theoretical concepts that underlie the scientific explanation of a variety of complex systems. In spite of clear-cut developments around both concepts, their intersection is really problematic, either in fields related to mathematics, physics, and chemistry, or even more [...] Read more.

Information and symmetry are essential theoretical concepts that underlie the scientific explanation of a variety of complex systems. In spite of clear-cut developments around both concepts, their intersection is really problematic, either in fields related to mathematics, physics, and chemistry, or even more in those pertaining to biology, neurosciences, and social sciences. The present Special Issue explores recent developments, both theoretical and applied, in most of these disciplines. Full article

(This article belongs to the Special Issue Symmetry and Information)

2249 KiB

Open AccessArticle

Vertical Handover Algorithm for WBANs in Ubiquitous Healthcare with Quality of Service Guarantees

by Dong Doan Van, Qingsong Ai and Quan Liu

Information 2017, 8(1), 34; https://doi.org/10.3390/info8010034 - 14 Mar 2017

Cited by 10 | Viewed by 7137

Abstract

Recently, Wireless Body Area Networks (WBANs) have become an emerging technology in healthcare, where patients are equipped withwearable and implantable body sensor nodes to gather sensory information for remote monitoring. The increasing development of coordinator devices on patients enables the internetworking of WBANs [...] Read more.

Recently, Wireless Body Area Networks (WBANs) have become an emerging technology in healthcare, where patients are equipped withwearable and implantable body sensor nodes to gather sensory information for remote monitoring. The increasing development of coordinator devices on patients enables the internetworking of WBANs in heterogeneous wireless networks to deliver physiological information that is collected at remote terminals in a timely fashion. However, in this type of network, providing a seamless handover with a guaranteed Quality of Service (QoS), especially emergency services, is a challenging task. In this paper, we proposed an effective Multi-Attribute Decision-Making (MADM) handover algorithm that guarantees seamless connectivity. A patient’s mobile devices automatically connect to the best network that fulfills the QoS requirements of different types of applications. Additionally, we integrated a Content-Centric Networking (CCN) processing module into different wireless networks to reduce packet loss, enhance QoS and avoid unnecessary handovers by leveraging in-network caching to achieve efficient content dissemination for ubiquitous healthcare. Simulation results proved that our proposed approach forthe model with CCN outperforms the model without CCN and Received Signal Strength Vertical Handoff (RSS-VHD) in terms of the number of handovers, enhancing QoS, packet loss, and energy efficiency. Full article

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Open AccessArticle

Analysis and Modeling for China’s Electricity Demand Forecasting Based on a New Mathematical Hybrid Method

by Jie Liang and Yi Liang

Information 2017, 8(1), 33; https://doi.org/10.3390/info8010033 - 13 Mar 2017

Cited by 18 | Viewed by 6479

Abstract

Electricity demand forecasting can provide the scientific basis for the country to formulate the power industry development strategy and the power-generating target, which further promotes the sustainable, healthy and rapid development of the national economy. In this paper, a new mathematical hybrid method [...] Read more.

Electricity demand forecasting can provide the scientific basis for the country to formulate the power industry development strategy and the power-generating target, which further promotes the sustainable, healthy and rapid development of the national economy. In this paper, a new mathematical hybrid method is proposed to forecast electricity demand. In line with electricity demand feature, the framework of joint-forecasting model is established and divided into two procedures: firstly, the modified GM(1,1) model and the Logistic model are used to make single forecasting. Then, the induced ordered weighted harmonic averaging operator (IOWHA) is applied to combine these two single models and make joint-forecasting. Forecasting results demonstrate that this new hybrid model is superior to both single-forecasting approaches and traditional joint-forecasting methods, thus verifying the high prediction validity and accuracy of mentioned joint-forecasting model. Finally, detailed forecasting-outcomes on electricity demand of China in 2016–2020 are discussed and displayed a slow-growth smoothly over the next five years. Full article

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676 KiB

Open AccessArticle

The Effects of Topology on Throughput Capacity of Large Scale Wireless Networks

by Qiuming Liu, Xuejing Jiang and Xiaohong Qiu

Information 2017, 8(1), 32; https://doi.org/10.3390/info8010032 - 10 Mar 2017

Cited by 3 | Viewed by 4241

Abstract

In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difﬁcult since it is complex to handle the interference caused by simultaneous transmission. [...] Read more.

In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difﬁcult since it is complex to handle the interference caused by simultaneous transmission. To solve this problem, we, according to the inhomogeneity of topology, divide the transmission into intra-cluster transmission and inter-cluster transmission. For the intra-cluster transmission, a spheroidal percolation model is constructed. The spheroidal percolation model guarantees a constant rate when a power control strategy is adopted. We also propose a cube percolation mode for the inter-cluster transmission. Different from the spheroidal percolation model, a constant transmission rate can be achieved without power control. For both transmissions, we propose a routing scheme with ﬁve phases. By comparing the achievable rate of each phase, we get the rate bottleneck, which is the throughput capacity of the network. Full article

(This article belongs to the Section Information Systems)

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Open AccessArticle

Forecasting Monthly Electricity Demands: An Application of Neural Networks Trained by Heuristic Algorithms

by Jeng-Fung Chen, Shih-Kuei Lo and Quang Hung Do

Information 2017, 8(1), 31; https://doi.org/10.3390/info8010031 - 10 Mar 2017

Cited by 24 | Viewed by 6515

Abstract

Electricity demand forecasting plays an important role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate prediction of electricity demands is therefore vital. In this study, artificial neural networks (ANNs) trained by different heuristic algorithms, including Gravitational Search Algorithm [...] Read more.

Electricity demand forecasting plays an important role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate prediction of electricity demands is therefore vital. In this study, artificial neural networks (ANNs) trained by different heuristic algorithms, including Gravitational Search Algorithm (GSA) and Cuckoo Optimization Algorithm (COA), are utilized to estimate monthly electricity demands. The empirical data used in this study are the historical data affecting electricity demand, including rainy time, temperature, humidity, wind speed, etc. The proposed models are applied to Hanoi, Vietnam. Based on the performance indices calculated, the constructed models show high forecasting performances. The obtained results also compare with those of several well-known methods. Our study indicates that the ANN-COA model outperforms the others and provides more accurate forecasting than traditional methods. Full article

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Open AccessArticle

Computer-Aided Identiﬁcation and Validation of Intervenability Requirements

by Rene Meis and Maritta Heisel

Information 2017, 8(1), 30; https://doi.org/10.3390/info8010030 - 9 Mar 2017

Cited by 14 | Viewed by 6108

Abstract

Privacy as a software quality is becoming more important these days and should not be underestimated during the development of software that processes personal data. The privacy goal of intervenability, in contrast to unlinkability (including anonymity and pseudonymity), has so far received little [...] Read more.

Privacy as a software quality is becoming more important these days and should not be underestimated during the development of software that processes personal data. The privacy goal of intervenability, in contrast to unlinkability (including anonymity and pseudonymity), has so far received little attention in research. Intervenability aims for the empowerment of end-users by keeping their personal data and how it is processed by the software system under their control. Several surveys have pointed out that the lack of intervenability options is a central privacy concern of end-users. In this paper, we systematically assess the privacy goal of intervenability and set up a software requirements taxonomy that relates the identiﬁed intervenability requirements with a taxonomy of transparency requirements. Furthermore, we provide a tool-supported method to identify intervenability requirements from the functional requirements of a software system. This tool-supported method provides the means to elicit and validate intervenability requirements in a computer-aided way. Our combined taxonomy of intervenability and transparency requirements gives a detailed view on the privacy goal of intervenability and its relation to transparency. We validated the completeness of our taxonomy by comparing it to the relevant literature that we derived based on a systematic literature review. The proposed method for the identiﬁcation of intervenability requirements shall support requirements engineers to elicit and document intervenability requirements in compliance with the EU General Data Protection Regulation. Full article

(This article belongs to the Special Issue Trust, Privacy and Security in Digital Business)

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Open AccessArticle

Structural and Functional Modeling of Artificial Bioactive Proteins

by Nikola Štambuk and Paško Konjevoda

Information 2017, 8(1), 29; https://doi.org/10.3390/info8010029 - 5 Mar 2017

Cited by 5 | Viewed by 7141

Abstract

A total of 32 synthetic proteins designed by Michael Hecht and co-workers was investigated using standard bioinformatics tools for the structure and function modeling. The dataset consisted of 15 artificial α-proteins (Hecht_α) designed to fold into 102-residue four-helix bundles and 17 artificial six-stranded [...] Read more.

A total of 32 synthetic proteins designed by Michael Hecht and co-workers was investigated using standard bioinformatics tools for the structure and function modeling. The dataset consisted of 15 artificial α-proteins (Hecht_α) designed to fold into 102-residue four-helix bundles and 17 artificial six-stranded β-sheet proteins (Hecht_β). We compared the experimentally-determined properties of the sequences investigated with the results of computational methods for protein structure and bioactivity prediction. The conclusion reached is that the dataset of Michael Hecht and co-workers could be successfully used both to test current methods and to develop new ones for the characterization of artificially-designed molecules based on the specific binary patterns of amino acid polarity. The comparative investigations of the bioinformatics methods on the datasets of both de novo proteins and natural ones may lead to: (1) improvement of the existing tools for protein structure and function analysis; (2) new algorithms for the construction of de novo protein subsets; and (3) additional information on the complex natural sequence space and its relation to the individual subspaces of de novo sequences. Additional investigations on different and varied datasets are needed to confirm the general applicability of this concept. Full article

(This article belongs to the Special Issue Symmetry and Information)

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121 KiB

Open AccessEditorial

The Necessity of Digital Citizenship and Participation

by Muneo Kaigo

Information 2017, 8(1), 28; https://doi.org/10.3390/info8010028 - 3 Mar 2017

Cited by 2 | Viewed by 4971

Abstract

Many recent developments justify how social and political participation through new media and information and communication technology is an urgent matter for many developed countries [...] Full article

(This article belongs to the Special Issue Digital Citizenship and Participation)

1952 KiB

Open AccessArticle

Effective Image Retrieval Using Texture Elements and Color Fuzzy Correlogram

by Fu-ping Yang and Mei-li Hao

Information 2017, 8(1), 27; https://doi.org/10.3390/info8010027 - 25 Feb 2017

Cited by 8 | Viewed by 5540

Abstract

Image low-level information, such as color, texture, and shape, were generally dealt with separately and combined together gruffly. Their image-describing effect in image retrieval was weakened. This paper determines and extracts one group of texture elements from images to mainly express the image [...] Read more.

Image low-level information, such as color, texture, and shape, were generally dealt with separately and combined together gruffly. Their image-describing effect in image retrieval was weakened. This paper determines and extracts one group of texture elements from images to mainly express the image texture information and, during this procedure, the quantized HSV color information is added to develop the feature, Color Layer-Based Texture Elements Histogram (CLBTEH). Furthermore, Color Fuzzy Correlogram (CFC) is put forward and employed for further extraction of color features. The performance of the proposed approach is evaluated on different image databases, including Corel-1k, Corel-10k, and USPTex1.0, and it was found that the experimental results of the proposed approach are encouraging in comparison with similar algorithms. Full article

(This article belongs to the Section Information Processes)

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Open AccessArticle

An Image Compression Scheme in Wireless Multimedia Sensor Networks Based on NMF

by Shikang Kong, Lijuan Sun, Chong Han and Jian Guo

Information 2017, 8(1), 26; https://doi.org/10.3390/info8010026 - 24 Feb 2017

Cited by 14 | Viewed by 5370

Abstract

With the goal of addressing the issue of image compression in wireless multimedia sensor networks with high recovered quality and low energy consumption, an image compression and transmission scheme based on non-negative matrix factorization (NMF) is proposed in this paper. First, the NMF [...] Read more.

With the goal of addressing the issue of image compression in wireless multimedia sensor networks with high recovered quality and low energy consumption, an image compression and transmission scheme based on non-negative matrix factorization (NMF) is proposed in this paper. First, the NMF algorithm theory is studied. Then, a collaborative mechanism of image capture, block, compression and transmission is completed. Camera nodes capture images and send them to ordinary nodes which use an NMF algorithm for image compression. Compressed images are transmitted to the station by the cluster head node and received from ordinary nodes. The station takes on the image restoration. Simulation results show that, compared with the JPEG2000 and singular value decomposition (SVD) compression schemes, the proposed scheme has a higher quality of recovered images and lower total node energy consumption. It is beneficial to reduce the burden of energy consumption and prolong the life of the whole network system, which has great significance for practical applications of WMSNs. Full article

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Open AccessArticle

Improved FIFO Scheduling Algorithm Based on Fuzzy Clustering in Cloud Computing

by Jian Li, Tinghuai Ma, Meili Tang, Wenhai Shen and Yuanfeng Jin

Information 2017, 8(1), 25; https://doi.org/10.3390/info8010025 - 24 Feb 2017

Cited by 23 | Viewed by 8188

Abstract

In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks’ waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. [...] Read more.

In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks’ waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. We construct a task model, resource model, and analyze tasks’ preference, then classify resources with fuzzy clustering algorithms. Based on the parameters of cloud tasks, the algorithm will calculate resource expectation and assign tasks to different resource clusters, so the complexity of resource selection will be decreased. As a result, the algorithm will reduce tasks’ waiting time and improve the resource utilization. The experiment results show that the proposed algorithm shortens the execution time of tasks and increases the resource utilization. Full article

(This article belongs to the Section Information Systems)

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Open AccessArticle

Waves as the Symmetry Principle Underlying Cosmic, Cell, and Human Languages

by Sungchul Ji

Information 2017, 8(1), 24; https://doi.org/10.3390/info8010024 - 20 Feb 2017

Cited by 7 | Viewed by 12273

Abstract

In 1997, the author concluded that living cells use a molecular language (cellese) that is isomorphic with the human language (humanese) based on his finding that the former shared 10 out of the 13 design features of the latter. In 2012, the author [...] Read more.

In 1997, the author concluded that living cells use a molecular language (cellese) that is isomorphic with the human language (humanese) based on his finding that the former shared 10 out of the 13 design features of the latter. In 2012, the author postulated that cellese and humanese derived from a third language called the cosmic language (or cosmese) and that what was common among these three kinds of languages was waves—i.e., sound waves for humanese, concentration waves for cellese, and quantum waves for cosmese. These waves were suggested to be the symmetry principle underlying cosmese, cellese, and humanese. We can recognize at least five varieties of waves—(i) electromagnetic; (ii) mechanical; (iii) chemical concentration; (iv) gravitational; and (v) probability waves, the last being non-material, in contrast to the first four, which are all material. The study of waves is called “cymatics” and the invention of CymaScope by J. S. Reid of the United Kingdom in 2002 is expected to accelerate the study of waves in general. CymaScope has been used to visualize not only human sounds (i.e., humanese) but also sounds made by individual cells (cellese) in conjunction with Atomic Force Microscopy (AFM) (unpublished observations of J. Gimzewski of UCLA and J. Reid). It can be predicted that the gravitational waves recently detected by the Interferometer Gravitational-Wave Observatory (LIGO) will be visualized with CymaScope one day, thereby transforming gravitational waves into CymaGlyphs. Since cellese in part depends on RNA concentration waves (or RNA glyphs) and humanese includes hieroglyphs that were decoded by Champollion in 1822, it seems reasonable to use cymaglyphs, RNA glyphs, and hieroglyphs as symbols of cosmese, cellese, and humanese, respectively, all based on the principle of waves as the medium of communication. Full article

(This article belongs to the Special Issue Symmetry and Information)

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Open AccessArticle

Patients’ Admissions in Intensive Care Units: A Clustering Overview

by Ana Ribeiro, Filipe Portela, Manuel Santos, António Abelha, José Machado and Fernando Rua

Information 2017, 8(1), 23; https://doi.org/10.3390/info8010023 - 17 Feb 2017

Cited by 6 | Viewed by 5624

Abstract

Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU [...] Read more.

Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU management is evident. It is proven that unplanned and prolonged admission to the ICU is not only prejudicial to a patient's health, but also such a situation implies a readjustment of ICU resources, including beds, doctors, nurses, financial resources, among others. By discovering the common characteristics of the admitted patients, it is possible to improve these outcomes. In this study clustering techniques were applied to data collected from admitted patients in an intensive care unit. The best results presented a silhouette of 1, with a distance to centroids of 6.2 × 10⁻¹⁷ and a Davies–Bouldin index of −0.652. Full article

(This article belongs to the Special Issue Selected Papers from the Workshop on Intelligent Systems and Applications in Healthcare (ISA’Health 2016))

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185 KiB

Open AccessReview

Information Flow in the Brain: Ordered Sequences of Metastable States

by Andrew A. Fingelkurts and Alexander A. Fingelkurts

Information 2017, 8(1), 22; https://doi.org/10.3390/info8010022 - 13 Feb 2017

Cited by 26 | Viewed by 7078

Abstract

In this brief overview paper, we analyse information flow in the brain. Although Shannon’s information concept, in its pure algebraic form, has made a number of valuable contributions to neuroscience, information dynamics within the brain is not fully captured by its classical description. [...] Read more.

In this brief overview paper, we analyse information flow in the brain. Although Shannon’s information concept, in its pure algebraic form, has made a number of valuable contributions to neuroscience, information dynamics within the brain is not fully captured by its classical description. These additional dynamics consist of self-organisation, interplay of stability/instability, timing of sequential processing, coordination of multiple sequential streams, circular causality between bottom-up and top-down operations, and information creation. Importantly, all of these processes are dynamic, hierarchically nested and correspond to continuous brain state change, even if the external environment remains constant. This is where metastable coordination comes into play. In a metastable regime of brain functioning, as a result of the simultaneous co-existence of tendencies for independence and cooperation, information is continuously created, preserved for some time and then dissipated through the formation of dynamical and nested spatio-temporal coalitions among simple neuronal assemblies and larger coupled conglomerates of them—so-called delocalised operational modules. Full article

(This article belongs to the Special Issue Symmetry and Information)

135 KiB

Open AccessEssay

A Conjecture on the Nature of Information, with a “Simple” Example

by Stanley N. Salthe

Information 2017, 8(1), 21; https://doi.org/10.3390/info8010021 - 8 Feb 2017

Viewed by 4415

Abstract

Here, I take the position that information is a result of interactions between observers. In order to proceed with this, I construct a simple physical example, with forces standing in for observers. That example leads me to consider the relation between investigative work [...] Read more.

Here, I take the position that information is a result of interactions between observers. In order to proceed with this, I construct a simple physical example, with forces standing in for observers. That example leads me to consider the relation between investigative work and energy constraints, which in turn leads toward a surprising suggestion concerning the most general motivation for work. Full article

(This article belongs to the Special Issue Symmetry and Information)

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Open AccessArticle

Learning to Recommend Point-of-Interest with the Weighted Bayesian Personalized Ranking Method in LBSNs

by Lei Guo, Haoran Jiang, Xinhua Wang and Fangai Liu

Information 2017, 8(1), 20; https://doi.org/10.3390/info8010020 - 6 Feb 2017

Cited by 15 | Viewed by 6434

Abstract

Point-of-interest (POI) recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but implicit. For example, we can only [...] Read more.

Point-of-interest (POI) recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but implicit. For example, we can only get a user’s check-in behaviors from the history of what POIs she/he has visited, but never know how much she/he likes and why she/he does not like them. Recently, some researchers have noticed this problem and began to learn the user preferences from the partial order of POIs. However, these works give equal weight to each POI pair and cannot distinguish the contributions from different POI pairs. Intuitively, for the two POIs in a POI pair, the larger the frequency difference of being visited and the farther the geographical distance between them, the higher the contribution of this POI pair to the ranking function. Based on the above observations, we propose a weighted ranking method for POI recommendation. Specifically, we first introduce a Bayesian personalized ranking criterion designed for implicit feedback to POI recommendation. To fully utilize the partial order of POIs, we then treat the cost function in a weighted way, that is give each POI pair a different weight according to their frequency of being visited and the geographical distance between them. Data analysis and experimental results on two real-world datasets demonstrate the existence of user preference on different POI pairs and the effectiveness of our weighted ranking method. Full article

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Open AccessArticle

A Frequency-Based Assignment Model under Day-to-Day Information Evolution of Oversaturated Conditions on a Feeder Bus Service

by Silin Zhang, Zhenzhou Yuan and Zhichao Cao

Information 2017, 8(1), 19; https://doi.org/10.3390/info8010019 - 4 Feb 2017

Cited by 6 | Viewed by 5264

Abstract

Day-to-day information is increasingly being implemented in transit networks worldwide. Feeder bus service (FBS) plays a vital role in a public transit network by providing feeder access to hubs and rails. As a feeder service, a space-time path for frequent passengers is decided [...] Read more.

Day-to-day information is increasingly being implemented in transit networks worldwide. Feeder bus service (FBS) plays a vital role in a public transit network by providing feeder access to hubs and rails. As a feeder service, a space-time path for frequent passengers is decided by its dynamic strategy procedure, in which a day-to-day information self-learning mechanism is identified and analyzed from our survey data. We formulate a frequency-based assignment model considering day-to-day evolution under oversaturated conditions, which takes into account the residual capacity of bus and the comfort feelings of sitting or standing. The core of our proposed model is to allocate the passengers on each segment belonging to their own paths according to multi-utilities transformed from the time values and parametric demands, such as frequency, bus capacity, seat comfort, and stop layout. The assignment method, albeit general, allows us to formulate an equivalent optimization problem in terms of interaction between the FBS’ operation and frequent passengers’ rational behaviors. Finally, a real application case is generated to test the ability of the modeling framework capturing the theoretical consequents, serving the passengers’ dynamic externalities. Full article

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Open AccessArticle

An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators

by Jiuyuan Huo and Liqun Liu

Information 2017, 8(1), 18; https://doi.org/10.3390/info8010018 - 3 Feb 2017

Cited by 8 | Viewed by 6412

Abstract

To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC) inspired by the intelligent foraging behavior of honey bees was proposed in this paper. The proposed algorithm utilizes the Pareto dominance theory and [...] Read more.

To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC) inspired by the intelligent foraging behavior of honey bees was proposed in this paper. The proposed algorithm utilizes the Pareto dominance theory and takes advantage of adaptive grid and regulation operator mechanisms. The adaptive grid technique is used to adaptively assess the Pareto front maintained in an external archive and the regulation operator is used to balance the weights of the local search and the global search in the evolution of the algorithm. The performance of RMOABC was evaluated in comparison with other nature inspired algorithms includes NSGA-II and MOEA/D. The experiments results demonstrated that the RMOABC approach has better accuracy and minimal execution time. Full article

(This article belongs to the Section Artificial Intelligence)

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Open AccessArticle

Exact Solution Analysis of Strongly Convex Programming for Principal Component Pursuit

by Qingshan You and Qun Wan

Information 2017, 8(1), 17; https://doi.org/10.3390/info8010017 - 2 Feb 2017

Viewed by 4141

Abstract

In this paper, we address strongly convex programming for principal component analysis, which recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. In this paper, we ﬁrstly provide sufﬁcient conditions under which the strongly [...] Read more.

In this paper, we address strongly convex programming for principal component analysis, which recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. In this paper, we ﬁrstly provide sufﬁcient conditions under which the strongly convex models lead to the exact low-rank matrix recovery. Secondly, we also give suggestions that will guide us how to choose suitable parameters in practical algorithms. Finally, the proposed result is extended to the principal component pursuit with reduced linear measurements and we provide numerical experiments. Full article

(This article belongs to the Section Information Theory and Methodology)

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Open AccessArticle

A Quick Artificial Bee Colony Algorithm for Image Thresholding

by Linguo Li, Lijuan Sun, Jian Guo, Chong Han, Jian Zhou and Shujing Li

Information 2017, 8(1), 16; https://doi.org/10.3390/info8010016 - 28 Jan 2017

Cited by 24 | Viewed by 5507

Abstract

The computational complexity grows exponentially for multi-level thresholding (MT) with the increase of the number of thresholds. Taking Kapur’s entropy as the optimized objective function, the paper puts forward the modified quick artificial bee colony algorithm (MQABC), which employs a new distance strategy [...] Read more.

The computational complexity grows exponentially for multi-level thresholding (MT) with the increase of the number of thresholds. Taking Kapur’s entropy as the optimized objective function, the paper puts forward the modified quick artificial bee colony algorithm (MQABC), which employs a new distance strategy for neighborhood searches. The experimental results show that MQABC can search out the optimal thresholds efficiently, precisely, and speedily, and the thresholds are very close to the results examined by exhaustive searches. In comparison to the EMO (Electro-Magnetism optimization), which is based on Kapur’s entropy, the classical ABC algorithm, and MDGWO (modified discrete grey wolf optimizer) respectively, the experimental results demonstrate that MQABC has exciting advantages over the latter three in terms of the running time in image thesholding, while maintaining the efficient segmentation quality. Full article

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Open AccessArticle

An Introduction to the Foundations of Chemical Information Theory. Tarski–Lesniewski Logical Structures and the Organization of Natural Sorts and Kinds

by Jerry L. R. Chandler

Information 2017, 8(1), 15; https://doi.org/10.3390/info8010015 - 25 Jan 2017

Cited by 2 | Viewed by 5117

Abstract

Organic mathematics is an applied mathematics of philosophical atomism. The order of the chemical elements in the table of elements is the source of order for the logical operations of addition and subtraction of atomic numbers. The inverse square laws of physics are [...] Read more.

Organic mathematics is an applied mathematics of philosophical atomism. The order of the chemical elements in the table of elements is the source of order for the logical operations of addition and subtraction of atomic numbers. The inverse square laws of physics are the source of organization of subatomic structures of chemical atoms (atomic and molecular structures). These facts are foundational to the logic of the chemical sciences and are therefore the scientific basis for chemical information theory. The theories and facts of the chemical sciences are so perplex that several forms of symbolic representations are necessary to communicate the broad range of scientific concepts used to inquire into the nature of natural sorts and kinds. The logics proposed by Tarski, Lesniewski and Malatesta are applied to the construction of a numerical “spine” of perplex numbers representing atomic numbers as meta-symbols in meta-languages. The orbital angular momenta of certain collections of electrical particles (also known as “handedness”) are critical components in constructing the logical propositions of the perplex number “spine”. Biological communication channels can function if and only if the natural sorts and kinds are consistent with the matching patterns of the optical isomers. The terms spinners and twisters are introduced to express the electro-mechanical torques necessary for encoding chemical information. This hypothesis can be tested by several categories of experiments, including clinical pharmaco-dynamics and clinical toxico-dynamics of dissymmetric isomers of different sorts and kinds. Full article

(This article belongs to the Special Issue Symmetry and Information)

1270 KiB

Open AccessArticle

Consideration of ERP Effectiveness: From the Perspective of ERP Implementation Policy and Operational Effectiveness

by Haruna Jinno, Hiromichi Abe and Kayo Iizuka

Information 2017, 8(1), 14; https://doi.org/10.3390/info8010014 - 21 Jan 2017

Cited by 11 | Viewed by 11215

Abstract

The aim of this paper is to present the results of an analysis of implementing enterprise resource planning (ERP) effectiveness from the perspective of implementation policy and operational effectiveness. Re-engineering has become increasingly important recently due to the rapid changes in the business [...] Read more.

The aim of this paper is to present the results of an analysis of implementing enterprise resource planning (ERP) effectiveness from the perspective of implementation policy and operational effectiveness. Re-engineering has become increasingly important recently due to the rapid changes in the business environment. By implementing ERP systems, companies can standardize their business processes and thereby manage them more effectively and efficiently. However, it is difficult to achieve that kind of effectiveness and efficiency by just implementing ERP. Companies want to know the suitable way to achieve effectiveness. In Japan, ERP systems started to be implemented in the 1990s, and the installation rate to the whole enterprise system is increasing yearly in Japan. However, there are some companies that cannot achieve effectiveness, though some companies have succeeded. The authors developed a model focusing on implementation policy and customization policy, and analyzed the survey results. Data used for the analysis (182 samples) was from the ERP Users’ Survey (2013). For the analysis method, covariance structure analysis using IBM® SPSS® Amos provided by International Business Machines (IBM) Corporation was conducted. This research aimed to contribute to the successful implementation of ERP in Japan. Full article

(This article belongs to the Section Information Systems)

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995 KiB

Open AccessArticle

Dependency Parsing with Transformed Feature

by Fuxiang Wu

Information 2017, 8(1), 13; https://doi.org/10.3390/info8010013 - 21 Jan 2017

Cited by 1 | Viewed by 5033

Abstract

Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the [...] Read more.

Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser. Full article

(This article belongs to the Section Artificial Intelligence)

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12860 KiB

Open AccessArticle

The Matrix Method of Representation, Analysis and Classification of Long Genetic Sequences

by Ivan V. Stepanyan and Sergey V. Petoukhov

Information 2017, 8(1), 12; https://doi.org/10.3390/info8010012 - 17 Jan 2017

Cited by 12 | Viewed by 8709

Abstract

The article is devoted to a matrix method of comparative analysis of long nucleotide sequences by means of presenting each sequence in the form of three digital binary sequences. This method uses a set of symmetries of biochemical attributes of nucleotides. It also [...] Read more.

The article is devoted to a matrix method of comparative analysis of long nucleotide sequences by means of presenting each sequence in the form of three digital binary sequences. This method uses a set of symmetries of biochemical attributes of nucleotides. It also uses the possibility of presentation of every whole set of N-mers as one of the members of a Kronecker family of genetic matrices. With this method, a long nucleotide sequence can be visually represented as an individual fractal-like mosaic or another regular mosaic of binary type. In contrast to natural nucleotide sequences, artificial random sequences give non-regular patterns. Examples of binary mosaics of long nucleotide sequences are shown, including cases of human chromosomes and penicillins. The obtained results are then discussed. Full article

(This article belongs to the Special Issue Symmetry and Information)

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3658 KiB

Open AccessArticle

Four-Switch Three-Phase PMSM Converter with Output Voltage Balance and DC-Link Voltage Offset Suppression

by Fadil Hicham, Driss Yousfi, Elhafyani Mohamed Larbi and Aite Driss Youness

Information 2017, 8(1), 11; https://doi.org/10.3390/info8010011 - 17 Jan 2017

Cited by 4 | Viewed by 6646

Abstract

High power quality, efficiency, complexity, size, cost effectiveness and switching losses of the direct current to alternating current (DC–AC) conversion system are crucial aspects in industrial applications. Therefore, the four-switch three-phase inverter (4S3P) has been proposed as an innovative inverter design. However, this [...] Read more.

High power quality, efficiency, complexity, size, cost effectiveness and switching losses of the direct current to alternating current (DC–AC) conversion system are crucial aspects in industrial applications. Therefore, the four-switch three-phase inverter (4S3P) has been proposed as an innovative inverter design. However, this topology has been known to have many performance limitations in the low-frequency region, because of the generation of an unbalanced voltage leading to an unbalanced current due to the fluctuation and offset of the centre tap voltage of the DC-link capacitors. Those drawbacks are investigated and solved in this paper in order to provide pure sinusoidal output voltages. The generated output voltages are controlled using proportional-integral (PI) controllers to follow the desired voltages. Furthermore, the DC-link capacitor voltage offset is mitigated by subtracting the direct component from the control reference voltage using low pass filters, where this direct voltage component provides the direct current component which leads to DC-link capacitor voltage divergence. A simulation model and experimental setup are used to validate the proposed concept. Many simulation and experimental results are carried out to show the effectiveness of the proposed control scheme. Full article

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4083 KiB

Open AccessArticle

An Improved Particle Swarm Optimization-Based Feed-Forward Neural Network Combined with RFID Sensors to Indoor Localization

by Changzhi Wang, Zhicai Shi and Fei Wu

Information 2017, 8(1), 9; https://doi.org/10.3390/info8010009 - 11 Jan 2017

Cited by 19 | Viewed by 6145

Abstract

Location-based services (LBS) have long been recognized as a significant component of the emerging information services. However, the localization cost and the performance of algorithm still need to be optimized. In the study, an improved particle swarm optimization algorithm based on a feed-forward [...] Read more.

Location-based services (LBS) have long been recognized as a significant component of the emerging information services. However, the localization cost and the performance of algorithm still need to be optimized. In the study, an improved particle swarm optimization algorithm based on a feed-forward neural network (IMPSO-FNN) combined with RFID sensors is proposed, which can achieve the best indoor positioning location and overcome the problems effectively. In IMPSO-FNN, an improved PSO algorithm (IMPSO) is developed to determine the optimal connecting weights and markedly optimize the network parameters and structural parameters for the FNN, and then an optimal location prediction model is established by the IMPSO-FNN. To avoid the interference of environmental noise for the experimental data, some preprocessing methods are used during the positioning process. The computational results for learning two continuous functions show that the proposed positioning algorithm has a faster convergence rate and higher generalization performance. The model evaluation results also verify that the proposed positioning method really is superior to other algorithms in terms of the learning ability, efficiency, and positioning accuracy. Full article

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180 KiB

Open AccessEditorial

Acknowledgement to Reviewers of Information in 2016

by Information Editorial Office

Information 2017, 8(1), 10; https://doi.org/10.3390/info8010010 - 11 Jan 2017

Viewed by 3717

Abstract

The editors of Information would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article

1222 KiB

Open AccessArticle

Citizen Relationship Management System Users’ Contact Channel Choices: Digital Approach or Call Approach?

by Wei-Ning Wu

Information 2017, 8(1), 8; https://doi.org/10.3390/info8010008 - 5 Jan 2017

Cited by 13 | Viewed by 8125

Abstract

Many municipal governments adopted 311 decades ago and have advocated access equality in citizens’ use of 311. However, the role of citizens in the development and usage of 311 remains limited. Channel choices have been discussed in various types of governmental information and [...] Read more.

Many municipal governments adopted 311 decades ago and have advocated access equality in citizens’ use of 311. However, the role of citizens in the development and usage of 311 remains limited. Channel choices have been discussed in various types of governmental information and communication technologies (ICTs), especially when the innovative technology has just been adopted. Much has supported the idea that 311 is viewed as a method of digital civic engagement that many municipal governments adopt to maintain citizen relationship management and the capacity for government service delivery. However, we are still unclear about how citizens use it. This study applies the theory of channel expansion to examine how San Francisco residents use the 311 system, and how citizens’ technology experiences impact their 311 digital contact channel choices rather than the 311 hotline contact channel choice. In addition, we discuss major issues in citizens’ 311 contact choices, so that 311 municipal governments may draw lessons from the San Francisco experience. Full article

(This article belongs to the Special Issue Digital Citizenship and Participation)

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Information, Volume 8, Issue 1 (March 2017) – 37 articles

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