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Appl. Syst. Innov., Volume 2, Issue 4 (December 2019)

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Open AccessArticle
The Leaky Feeder, a Reliable Medium for Vehicle to Infrastructure Communications
Appl. Syst. Innov. 2019, 2(4), 36; https://doi.org/10.3390/asi2040036 - 08 Nov 2019
Abstract
Reliable vehicular communications is fast becoming a necessity. Vehicle to infrastructure (V2I) communication, which is critical for safety, is often interrupted when vehicles travel in tunnels. Leaky Feeder (LF) or radiating cable have been the primary solution to provide wireless access in tunnels [...] Read more.
Reliable vehicular communications is fast becoming a necessity. Vehicle to infrastructure (V2I) communication, which is critical for safety, is often interrupted when vehicles travel in tunnels. Leaky Feeder (LF) or radiating cable have been the primary solution to provide wireless access in tunnels and mines, but being overlooked until now. The LF is a natural multi antenna transceiver ideal for broadband short rage access. In this work, we model the LF as a linear antenna array and derive the average bit error rate (BER) in Rayleigh fading channel considering Quadrature Phase Shift Keying (QPSK) and M-Array Quadrature Amplitude (M-QAM) Modulations. We consider maximal ratio transmission (MRT) at the transmission end and coherent detection and maximal ratio combining (MRC) at the receiving end. Analytical expressions are derived for the BER. The effects of slot spacing and carrier frequency on the BER are also studied. Numerical evaluations show that the LF is a strong candidate for tunnels with much lower BER than a single antenna transmitter with the same SNR. Full article
(This article belongs to the Special Issue Transport Systems and Infrastructures)
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Open AccessFeature PaperArticle
Experience Design, Virtual Reality and Media Hybridization for the Digital Communication Inside Museums
Appl. Syst. Innov. 2019, 2(4), 35; https://doi.org/10.3390/asi2040035 - 30 Oct 2019
Abstract
Experience design, both in real and in virtual museums, is very complex to be planned, even more when digital contents are juxtaposed to real collections. Researchers in this field, curators, creatives and software developers must work together in order to evolve towards a [...] Read more.
Experience design, both in real and in virtual museums, is very complex to be planned, even more when digital contents are juxtaposed to real collections. Researchers in this field, curators, creatives and software developers must work together in order to evolve towards a more efficient interconnection among visitors, collections and digital applications. This paper deals with such an interconnection, providing a theoretical background and practical guidelines, on the basis of museum studies and of the author’s research experience in this domain, supported by the results of surveys carried out on European museums visitors dealing with digital technologies. Media hybridization has a long and evolving tradition and it can contribute to transmit culture in engaging way to the public, respecting the scientific plausibility of contents. The choice of narrative structures and styles, as well as of interaction paradigms and technologies, is deeply conditioned by a series of factors that will be examined in detail. A general “direction” is needed to arouse in the visitor a feeling of confidence and trust, expectation and discovery that makes him/her feel at the center of an emotional and creative experience, of a progressive appropriation of meaning. Various typologies of experiences will be discussed and compared. Full article
(This article belongs to the Special Issue Virtual Reality in Product Design)
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Open AccessReview
Developments in Electric and Green Marine Ships
Appl. Syst. Innov. 2019, 2(4), 34; https://doi.org/10.3390/asi2040034 - 28 Oct 2019
Abstract
The maritime industry, among all other industries, is being forced to gradually reduce its emissions. Legislation is one of the tools applying this pressure, and from 1 January 2020, it focuses on the reduction of sulfur percentage in the heavy fuel oil (HFO)-powered [...] Read more.
The maritime industry, among all other industries, is being forced to gradually reduce its emissions. Legislation is one of the tools applying this pressure, and from 1 January 2020, it focuses on the reduction of sulfur percentage in the heavy fuel oil (HFO)-powered vessels to 0.5%. In the beginning of this paper, the harmful environmental contribution of the naval sector is presented, along with the current legislation. The maritime industry is in a transitional stage, diverging from fossil fuels through alternative technologies and fuels, aiming to become over the long term a zero-emission industry. However, there are many implemented technologies, mostly of a mechanical nature, that already improve the efficiency of vessels and indirectly reduce their emissions. Such technologies include shaft generators (SGs), scrubbers, etc. The aim is for alternative fuels and technologies such as solar and wind to be implemented, too. Such technologies, when combined with the advantages of digitalization and automation, can further reduce emissions toward zero-emission vessels (ZEVs) through integrated systems. The present paper serves the purpose of a common point of gathering, addressing, and explaining the latest updates, previous achievements, and future targets of the maritime sector. The very nature of the subject—electric propulsion in the maritime sector—makes it very difficult to find sufficient and trustworthy data. There are two main reasons for this problem. The first one is that electric vehicles became commercial at a large scale (electric cars) very recently, and are still in a transitional stage. The second reason is that the maritime industry is very competitive; therefore, state-of-the-art technologies and data that give each company the lead are rarely published, and when they do, it happens very discreetly. In the quantitative part of the paper, where the photovoltaic (PV) and battery system calculations take place, there is no use of a specific model rather than a simplified approach. The purpose of the calculations is to show that with the present technologies, a purely solar-powered commercial vessel (such as RoRo, passenger, etc.) is technically impossible, and that there could be only a small contribution—of around 7%—to the electricity needs of a roll-on/roll-off (RoRo)-passenger ship. The state of the art finds a very short number of vessels that already use battery propulsion, but is expected to increase in the upcoming years. The present paper not only presents an overview of the state-of-the-art achievements in the electric propulsion of vessels, it also considers the exploitation of the continuous growth that the battery market is facing. As stated before, batteries are on the up, and this is due to the emerging need for energy storage in electricity grids that depend increasingly on renewable energy sources (RES). The paper makes a first consideration about the feasibility and possible benefits of implementing grid-like battery systems on-board vessels. In such a scenario, vessels would acquire significantly bigger energy capacity, allowing greater travel distances, a possible contribution of 44% of the vessel’s total power requirements (propulsion included), and a surplus as far as electricity requirements are concerned. There is also the more futuristic long-term scenario where Green Ports would charge vessels purely from RES dedicated to the port’s needs. The last part of the paper contains a qualitative assessment about the possible impacts that a battery-powered maritime industry could have. Full article
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Open AccessArticle
Business Process Automation: A Workflow Incorporating Optical Character Recognition and Approximate String and Pattern Matching for Solving Practical Industry Problems
Appl. Syst. Innov. 2019, 2(4), 33; https://doi.org/10.3390/asi2040033 - 24 Oct 2019
Abstract
Companies are relying more on artificial intelligence and machine learning in order to enhance and automate existing business processes. While the power of OCR (Optical Character Recognition) technologies can be harnessed for the digitization of image data, the digitalized text still needs to [...] Read more.
Companies are relying more on artificial intelligence and machine learning in order to enhance and automate existing business processes. While the power of OCR (Optical Character Recognition) technologies can be harnessed for the digitization of image data, the digitalized text still needs to be validated and enhanced to ensure that data quality standards are met for the data to be usable. This research paper focuses on finding and creating an automated workflow that can follow image digitization and produce a dictionary consisting of the desired information. The workflow introduced consists of a three-step process that is implemented after the OCR output has been generated. With the introduction of each step, the accuracy of key-value matches of field names and values is increased. The first step takes the raw OCR output and identifies field names using exact string matching and field-values using regular expressions from an externally maintained file. The second step introduces index pairing that matches field-values to field names based on the location of the field name and value on the document. Finally, approximate string matching is introduced to the workflow, which increases accuracy. By implementing these steps, the F-measure for key-value pair matches is measured at 60.18% in the first step, 80.61% once index pairing is introduced, and finally 90.06% after approximate string matching is introduced. The research proved that accurate usable data can be obtained automatically from images with the implementation of a workflow after OCR. Full article
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Open AccessArticle
Mathematical Apparatus of Optimal Decision-Making Based on Vector Optimization
Appl. Syst. Innov. 2019, 2(4), 32; https://doi.org/10.3390/asi2040032 - 11 Oct 2019
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Abstract
We present a problem of “acceptance of an optimal solution” as a mathematical model in the form of a vector problem of mathematical programming. For the solution of such a class of problems, we show the theory of vector optimization as a mathematical [...] Read more.
We present a problem of “acceptance of an optimal solution” as a mathematical model in the form of a vector problem of mathematical programming. For the solution of such a class of problems, we show the theory of vector optimization as a mathematical apparatus of acceptance of optimal solutions. Methods of solution of vector problems are directed to problem solving with equivalent criteria and with the given priority of a criterion. Following our research, the analysis and problem definition of decision making under the conditions of certainty and uncertainty are presented. We show the transformation of a mathematical model under the conditions of uncertainty into a model under the conditions of certainty. We present problems of acceptance of an optimal solution under the conditions of uncertainty with data that are represented by up to four parameters, and also show geometrical interpretation of results of the decision. Each numerical example includes input data (requirement specification) for modeling, transformation of a mathematical model under the conditions of uncertainty into a model under the conditions of certainty, making optimal decisions with equivalent criteria (solving a numerical model), and, making an optimal decision with a given priority criterion. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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Open AccessArticle
A Performance Study of the Impact of Different Perturbation Methods on the Efficiency of GVNS for Solving TSP
Appl. Syst. Innov. 2019, 2(4), 31; https://doi.org/10.3390/asi2040031 - 20 Sep 2019
Viewed by 298
Abstract
The purpose of this paper is to assess how three shaking procedures affect the performance of a metaheuristic GVNS algorithm. The first shaking procedure is generally known in the literature as intensified shaking method. The second is a quantum-inspired perturbation method, and the [...] Read more.
The purpose of this paper is to assess how three shaking procedures affect the performance of a metaheuristic GVNS algorithm. The first shaking procedure is generally known in the literature as intensified shaking method. The second is a quantum-inspired perturbation method, and the third is a shuffle method. The GVNS schemes are evaluated using a search strategy for both First and Best improvement and a time limit of one and two minutes. The formed GVNS schemes were applied on Traveling Salesman Problem (sTSP, nTSP) benchmark instances from the well-known TSPLib. To examine the potential advantage of any of the three metaheuristic schemes, extensive statistical analysis was performed on the reported results. The experimental data shows that for aTSP instances the first two methods perform roughly equivalently and, in any case, much better than the shuffle approach. In addition, the first method performs better than the other two when using the First Improvement strategy, while the second method gives results quite similar to the third. However, no significant deviations were observed when different methods of perturbation were used for Symmetric TSP instances (sTSP, nTSP). Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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