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Appl. Syst. Innov., Volume 1, Issue 3 (September 2018)

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Open AccessArticle A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers
Appl. Syst. Innov. 2018, 1(3), 36; https://doi.org/10.3390/asi1030036
Received: 8 July 2018 / Revised: 28 August 2018 / Accepted: 7 September 2018 / Published: 12 September 2018
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Abstract
Multimedia teaching materials are widely applied in various disciplines. More resources are provided by authorities to encourage elementary school teachers to use them. The resources provide an opportunity for teachers to share teaching resources for students. In this study, the technology acceptance model
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Multimedia teaching materials are widely applied in various disciplines. More resources are provided by authorities to encourage elementary school teachers to use them. The resources provide an opportunity for teachers to share teaching resources for students. In this study, the technology acceptance model (TAM) was used as the basic model to explore the effects of the information technology (IT) environment on the perceived usefulness, perceived ease of use, and attitude towards using multimedia, and the relevance and influence of these attitudes on behavioral intention. There are 2317 teachers in Chiayi county, and 460 participants were selected by stratified random sampling. The results showed that the ease of use of the multimedia material would enhance the intention to use. The attitude toward use also influences the intention to use. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICICE 2018)
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Open AccessArticle A Composite and Wearable Sensor Kit for Location-Aware Healthcare Monitoring and Real-Time Trauma Scoring for Survival Prediction
Appl. Syst. Innov. 2018, 1(3), 35; https://doi.org/10.3390/asi1030035
Received: 27 June 2018 / Revised: 9 August 2018 / Accepted: 7 September 2018 / Published: 12 September 2018
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Abstract
With the advances in the microfabrication of analogue front-end devices, and embedded and signal processing technology, it has now become possible to devise miniaturized health monitoring kits for non-invasive real time monitoring at any location. The current commonly available kits only measure singleton
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With the advances in the microfabrication of analogue front-end devices, and embedded and signal processing technology, it has now become possible to devise miniaturized health monitoring kits for non-invasive real time monitoring at any location. The current commonly available kits only measure singleton physiological parameters, and a composite analysis that covers all vital signs and trauma scores seems to be missing with these kits. The research aims at using vital signs and other physiological parameters to calculate trauma scores National Early Warning Score (NEWS), Revised Trauma Score (RTS), Trauma Score - Injury Severity Score (TRISS) and Prediction of survival (Ps), and to log the trauma event to electronic health records using standard coding schemes. The signal processing algorithms were implemented in MATLAB and could be ported to TI AM335x using MATLAB/Embedded Coder. Motion artefacts were removed using a level ‘5’ stationary wavelet transform and a ‘sym4’ wavelet, which yielded a signal-to-noise ratio of 27.83 dB. To demonstrate the operation of the device, an existing Physionet, MIMIC II Numerics dataset was used to calculate NEWS and RTS scores, and to generate the correlation and regression models for a clinical class of patients with respiratory failure and admitted to Intensive Care Unit (ICU). Parameters such as age, heart rate, Systolic Blood Pressure (SysBP), respiratory rate, and Oxygen Saturation (SpO2) as predictors to Ps, showed significant positive regressions of 93% at p < 0.001. The NEWS and RTS scores showed no significant correlation (r = 0.25, p < 0.001) amongst themselves; however, the NEWS and RTS together showed significant correlations with Ps (blunt) (r = 0.70, p < 0.001). RTS and Ps (blunt) scores showed some correlations (r = 0.63, p < 0.001), and the NEWS score showed significant correlation (r = 0.79, p < 0.001) with Ps (blunt) scores. Global Positioning System (GPS) system was built into the kit to locate the individual and to calculate the shortest path to the nearest healthcare center using the Quantum Geographical Information System (QGIS) Network Analysis tool. The physiological parameters from the sensors, along with the calculated trauma scores, were encoded according to a standard Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) coding system, and the trauma information was logged to electronic health records using Fast Health Interoperability Resources (FHIR) servers. The FHIR servers provided interoperable web services to log the trauma event information in real time and to prepare for medical emergencies. Full article
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Open AccessArticle Numerical Simulation of an Aluminum Container including a Phase Change Material for Cooling Energy Storage
Appl. Syst. Innov. 2018, 1(3), 34; https://doi.org/10.3390/asi1030034
Received: 9 August 2018 / Revised: 19 August 2018 / Accepted: 24 August 2018 / Published: 4 September 2018
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Abstract
Thermal energy storage systems can be determinant for an effective use of solar energy, as they allow to decouple the thermal energy production by the solar source from thermal loads, and thus allowing solar energy to be exploited also during nighttime and cloudy
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Thermal energy storage systems can be determinant for an effective use of solar energy, as they allow to decouple the thermal energy production by the solar source from thermal loads, and thus allowing solar energy to be exploited also during nighttime and cloudy periods. The current study deals with the modelling and simulation of a cooling thermal energy storage unit consisting of an aluminum container partially filled with a phase change material (PCM). Two unsteady models are implemented and discussed, namely a conduction-based model and a conduction-convection-based one. The equations systems relative to both the models are solved by means of the Comsol Multiphysics finite element solver, and results are presented in terms of temporal variation of temperature in different points inside the PCM, of the volume average liquid fraction, and of the cooling energy stored and released through the aluminum container external surface during the charge and discharge, respectively. Moreover, the numerical results obtained by the implementation of the above different models are compared with experimental ones obtained with a climatic chamber. The comparison between numerical and experimental results indicate that, for the considered cooling energy storage unit, free convection plays a crucial role in the heat transfer inside the liquid PCM and cannot be neglected. Full article
(This article belongs to the Special Issue Solar Thermal Systems)
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Open AccessArticle An Adaptive Ensemble Approach to Ambient Intelligence Assisted People Search
Appl. Syst. Innov. 2018, 1(3), 33; https://doi.org/10.3390/asi1030033
Received: 13 July 2018 / Revised: 23 August 2018 / Accepted: 28 August 2018 / Published: 3 September 2018
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Abstract
Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algorithms to perform localized people
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Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algorithms to perform localized people search tasks where the recognition must be done in real time, and where only a small face database is accessible. A localized people search is essential to enable robot–human interactions. In this article, we propose a novel adaptive ensemble approach to improve facial recognition rates while maintaining low computational costs, by combining lightweight local binary classifiers with global pre-trained binary classifiers. In this approach, the robot is placed in an ambient intelligence environment that makes it aware of local context changes. Our method addresses the extreme unbalance of false positive results when it is used in local dataset classifications. Furthermore, it reduces the errors caused by affine deformation in face frontalization, and by poor camera focus. Our approach shows a higher recognition rate compared to a pre-trained global classifier using a benchmark database under various resolution images, and demonstrates good efficacy in real-time tasks. Full article
(This article belongs to the Special Issue Healthcare System Innovation)
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Open AccessArticle Effect of Surface Roughness on Early Stage Oxidation Behavior of Ni-Base Superalloy IN 625
Appl. Syst. Innov. 2018, 1(3), 32; https://doi.org/10.3390/asi1030032
Received: 29 June 2018 / Revised: 27 August 2018 / Accepted: 28 August 2018 / Published: 31 August 2018
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Abstract
In the present work the effect of surface roughness on oxidation behavior during the early stages of high temperature exposure of Ni-base superalloy IN 625 is described. The surface roughness was described using standard contact profilometer as well as novel method, fractal analysis.
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In the present work the effect of surface roughness on oxidation behavior during the early stages of high temperature exposure of Ni-base superalloy IN 625 is described. The surface roughness was described using standard contact profilometer as well as novel method, fractal analysis. It was found that the different surface preparation resulted in a difference in roughness with a parameter increase of at least one order of magnitude for the ground sample as compared with the polished sample. The oxidation test was performed in a horizontal tube furnace. Post-exposure analyses including glow discharge optical emission spectrometry (GD-OES) and scanning electron microscopy (SEM), which revealed that grinding lowers the oxidation kinetics of IN 625 from 1.76 × 10−12 cm2·s−1, obtained for polished sample, to 9.04 × 10−13 cm2·s−1. It was found that surface preparation influences the oxide scale composition and morphology. The hypothesis explaining the mechanism responsible for the changes in oxidation behavior is proposed as well. Full article
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Open AccessArticle Modeling the 2013 Zika Outbreak in French Polynesia: Intervention Strategies
Appl. Syst. Innov. 2018, 1(3), 31; https://doi.org/10.3390/asi1030031
Received: 28 June 2018 / Revised: 4 August 2018 / Accepted: 20 August 2018 / Published: 24 August 2018
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Abstract
The ongoing Zika virus (ZIKV) in the Americas has been a serious public health emergency since 2015. Since Zika is a vector-borne disease, the size of the vector population in the affected area plays a key role in controlling the scale of the
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The ongoing Zika virus (ZIKV) in the Americas has been a serious public health emergency since 2015. Since Zika is a vector-borne disease, the size of the vector population in the affected area plays a key role in controlling the scale of the outbreak. The primary vectors for Zika, the Aedes Agypti and Aedes Albopictus species of mosquitoes, are highly sensitive to climatic conditions for survival and reproduction. Additionally, increased international travel over the years has caused the disease outbreak to turn into a pandemic affecting five continents. The mosquito population and the human travel patterns are the two main driving forces affecting the persistence and resurgence of Zika and other vector-borne diseases. This paper presents an enhanced dynamic model that simulates the 2013–2014 French Polynesia Zika outbreak incorporating the temperature dependent mosquito ecology and the local transit network (flights and ferries). The study highlights the importance of human travel patterns and mosquito population dynamics in a disease outbreak. The results predict that more than 85% of the population was infected by the end of the outbreak and it lasted for more than five months across the islands. The basic reproduction number ( R 0 ) for the outbreak is also calculated using the next-generation-matrix for validation purposes. Additionally, this study is focused on measuring the impact of intervention strategies like reducing the mosquito population, preventing mosquito bites and imposing travel bans. French Polynesia was chosen as the region of interest for the study because of available demographic, climate and transit data. Additionally, results from similar studies for the region are available for validation and comparison. However, the proposed system can be used to study the transmission dynamics of any vector-borne disease in any geographic region by altering the climatic and demographic data, and the transit network. Full article
(This article belongs to the Special Issue Healthcare System Innovation)
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Open AccessArticle New Approximation Methods Based on Fuzzy Transform for Solving SODEs: II
Appl. Syst. Innov. 2018, 1(3), 30; https://doi.org/10.3390/asi1030030
Received: 17 June 2018 / Revised: 11 August 2018 / Accepted: 14 August 2018 / Published: 23 August 2018
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Abstract
In this research, three approximation methods are used in the new generalized uniform fuzzy partition to solve the system of differential equations (SODEs) based on fuzzy transform (FzT). New representations of basic functions are proposed based on the new types of a uniform
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In this research, three approximation methods are used in the new generalized uniform fuzzy partition to solve the system of differential equations (SODEs) based on fuzzy transform (FzT). New representations of basic functions are proposed based on the new types of a uniform fuzzy partition and a subnormal generating function. The main properties of a new uniform fuzzy partition are examined. Further, the simpler form of the fuzzy transform is given alongside some of its fundamental results. New theorems and lemmas are proved. In accordance with the three conventional numerical methods: Trapezoidal rule (one step) and Adams Moulton method (two and three step modifications), new iterative methods (NIM) based on the fuzzy transform are proposed. These new fuzzy approximation methods yield more accurate results in comparison with the above-mentioned conventional methods. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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Open AccessArticle New Approximation Methods Based on Fuzzy Transform for Solving SODEs: I
Appl. Syst. Innov. 2018, 1(3), 29; https://doi.org/10.3390/asi1030029
Received: 17 June 2018 / Revised: 11 August 2018 / Accepted: 14 August 2018 / Published: 23 August 2018
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Abstract
In this paper, new approximation methods for solving systems of ordinary differential equations (SODEs) by fuzzy transform (FzT) are introduced and discussed. In particular, we propose two modified numerical schemes to solve SODEs where the technique of FzT is combined with one-stage and
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In this paper, new approximation methods for solving systems of ordinary differential equations (SODEs) by fuzzy transform (FzT) are introduced and discussed. In particular, we propose two modified numerical schemes to solve SODEs where the technique of FzT is combined with one-stage and two-stage numerical methods. Moreover, the error analysis of the new approximation methods is discussed. Finally, numerical examples of the proposed approach are confirmed, and applications are presented. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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Open AccessArticle Employing Robust Principal Component Analysis for Noise-Robust Speech Feature Extraction in Automatic Speech Recognition with the Structure of a Deep Neural Network
Appl. Syst. Innov. 2018, 1(3), 28; https://doi.org/10.3390/asi1030028
Received: 6 April 2018 / Revised: 11 August 2018 / Accepted: 12 August 2018 / Published: 15 August 2018
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Abstract
In recent decades, researchers have been focused on developing noise-robust methods in order to compensate for noise effects in automatic speech recognition (ASR) systems and enhance their performance. In this paper, we propose a feature-based noise-robust method that employs a novel data analysis
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In recent decades, researchers have been focused on developing noise-robust methods in order to compensate for noise effects in automatic speech recognition (ASR) systems and enhance their performance. In this paper, we propose a feature-based noise-robust method that employs a novel data analysis technique—robust principal component analysis (RPCA). In the proposed scenario, RPCA is employed to process a noise-corrupted speech feature matrix, and the obtained sparse partition is shown to reveal speech-dominant characteristics. One apparent advantage of using RPCA for enhancing noise robustness is that no prior knowledge about the noise is required. The proposed RPCA-based method is evaluated with the Aurora-4 database and a task using a state-of-the-art deep neural network (DNN) architecture as the acoustic models. The evaluation results indicate that the newly proposed method can provide the original speech feature with significant recognition accuracy improvement, and can be cascaded with mean normalization (MN), mean and variance normalization (MVN), and relative spectral (RASTA)—three well-known and widely used feature robustness algorithms—to achieve better performance compared with the individual component method. Full article
(This article belongs to the Special Issue Selected papers from IEEE ICASI 2018)
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Open AccessFeature PaperArticle Solar Hybrid Micro Gas Turbine Based on Turbocharger
Appl. Syst. Innov. 2018, 1(3), 27; https://doi.org/10.3390/asi1030027
Received: 7 June 2018 / Revised: 27 July 2018 / Accepted: 27 July 2018 / Published: 1 August 2018
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Abstract
The performance of solar hybrid Brayton cycle materialized by a micro-gas turbine based on a turbocharger is studied. The use of a turbocharger is aimed at investment cost reduction and construction simplification. Two configurations are investigated, namely hybrid and solar-only. Design aspects are
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The performance of solar hybrid Brayton cycle materialized by a micro-gas turbine based on a turbocharger is studied. The use of a turbocharger is aimed at investment cost reduction and construction simplification. Two configurations are investigated, namely hybrid and solar-only. Design aspects are discussed, in view of the requirement for minimizing the cost of electricity produced. A key parameter is the turbine inlet temperature and its effect on performance is investigated. The effect of heliostat field size is also investigated. Augmentation of the maximum temperature leads to better performance, as a result of higher cycle efficiency. Solar-only configuration features are compared with hybrid ones and the contribution of different cost components to the final electricity cost is discussed. Full article
(This article belongs to the Special Issue Solar Thermal Systems)
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Open AccessArticle A System for Controlling and Monitoring IoT Applications
Appl. Syst. Innov. 2018, 1(3), 26; https://doi.org/10.3390/asi1030026
Received: 14 June 2018 / Revised: 22 July 2018 / Accepted: 25 July 2018 / Published: 27 July 2018
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Abstract
In this work, the design and implementation of an open source software and hardware system for Internet of Things (IoT) applications is presented. This system permits the remote monitoring of supplied data from sensors and webcams and the control of different devices such
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In this work, the design and implementation of an open source software and hardware system for Internet of Things (IoT) applications is presented. This system permits the remote monitoring of supplied data from sensors and webcams and the control of different devices such as actuators, servomotors and LEDs. The parameters which have been monitored are brightness, temperature and relative humidity all of which constitute possible environmental factors. The control and monitoring of the installation is realised through a server which is managed by an administrator. The device which rules the installation is a Raspberry Pi, a small and powerful micro-computer in a single board with low consumption, low cost and reconfigurability. Full article
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Open AccessArticle Causal Graphs and Concept-Mapping Assumptions
Appl. Syst. Innov. 2018, 1(3), 25; https://doi.org/10.3390/asi1030025
Received: 11 May 2018 / Revised: 11 July 2018 / Accepted: 20 July 2018 / Published: 24 July 2018
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Abstract
Determining what constitutes a causal relationship between two or more concepts, and how to infer causation, are fundamental concepts in statistics and all the sciences. Causation becomes especially difficult in the social sciences where there is a myriad of different factors that are
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Determining what constitutes a causal relationship between two or more concepts, and how to infer causation, are fundamental concepts in statistics and all the sciences. Causation becomes especially difficult in the social sciences where there is a myriad of different factors that are not always easily observed or measured that directly or indirectly influence the dynamic relationships between independent variables and dependent variables. This paper proposes a procedure for helping researchers explicitly understand what their underlying assumptions are, what kind of data and methodology are needed to understand a given relationship, and how to develop explicit assumptions with clear alternatives, such that researchers can then apply a process of probabilistic elimination. The procedure borrows from Pearl’s concept of “causal diagrams” and concept mapping to create a repeatable, step-by-step process for systematically researching complex relationships and, more generally, complex systems. The significance of this methodology is that it can help researchers determine what is more probably accurate and what is less probably accurate in a comprehensive fashion for complex phenomena. This can help resolve many of our current and future political and policy debates by eliminating that which has no evidence in support of it, and that which has evidence against it, from the pool of what can be permitted in research and debates. By defining and streamlining a process for inferring truth in a way that is graspable by human cognition, we can begin to have more productive and effective discussions around political and policy questions. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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Open AccessArticle An Effect of White Space on Traditional Chinese Text-Reading on Smartphones
Appl. Syst. Innov. 2018, 1(3), 24; https://doi.org/10.3390/asi1030024
Received: 1 April 2018 / Revised: 1 July 2018 / Accepted: 20 July 2018 / Published: 23 July 2018
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Abstract
The study explored the effects of white space on reading performance of Chinese essays on smartphones. The experiment was a 2(Line spacing) × 2(Paragraph spacing) × 3(Page spacing) Latin square design with two replicates. The Line spacing had two levels: two-font leading and
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The study explored the effects of white space on reading performance of Chinese essays on smartphones. The experiment was a 2(Line spacing) × 2(Paragraph spacing) × 3(Page spacing) Latin square design with two replicates. The Line spacing had two levels: two-font leading and three-font leading. The Paragraph spacing included two levels: one-leading space and two-leading space. The Page spacing included three levels: none spacing, one-third spacing, and one-half spacing. The objective performance measure was reading time; and subjective performance measures included ratings of ease, comfort, aesthetic appeal, and preference. Results of analysis of variance indicated that the main effects of Page spacing, Line spacing, and Paragraph spacing were significant on reading time. Additionally, Page spacing was also significant on ratings of ease, comfort, aesthetic appeal and preference; Line spacing was significant on comfort and aesthetic appeal. However, Paragraph spacing was not significant on ratings of effortlessness, comfort, aesthetic appeal, and preference. Full article
(This article belongs to the Special Issue Selected papers from IEEE ICASI 2018)
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Open AccessArticle Motion Sensor Application on Building Lighting Installation for Energy Saving and Carbon Reduction Joint Crediting Mechanism
Appl. Syst. Innov. 2018, 1(3), 23; https://doi.org/10.3390/asi1030023
Received: 7 April 2018 / Revised: 5 July 2018 / Accepted: 6 July 2018 / Published: 23 July 2018
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Abstract
Although common in developed countries such as Japan and Taiwan, the use of lamps coupled with motion sensors are still uncommon and even rare in Indonesia. Our experiment aims to show that simple installation of commercially available motion sensors can contribute to reduce
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Although common in developed countries such as Japan and Taiwan, the use of lamps coupled with motion sensors are still uncommon and even rare in Indonesia. Our experiment aims to show that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency, abundance in availability of energy being the main factor in Indonesian high energy consumption habits. High electricity demand for consumption at current supply level in Indonesia led to the rising cost of electricity bills. This factor is compounded by the fact that many electric generators in Indonesia still use fossil fuels, which contributes to the high basic generation cost. UBL is one of the universities that aim to be a green campus. Our research explores the possibility of installing motion sensors to contribute to the energy efficiency. Although mostly common in developed countries, the use of motion sensors for energy efficiency is still rare, especially in Indonesia. Despite rising cost and supply shortages, Indonesian buildings are still of high energy consumption. Our experiment shows that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency. One of the efforts to lower energy demand on the consumer side is to use the electricity efficiently, such as turning off lights in a room when it is not in use. This method can be simply done by turning the light switches for office and classrooms, but difficult to do in public spaces such as toilets and corridors. Automatic light switches experimentally installed in sample toilet rooms prove that electricity consumption from the lamps can contribute to the reduction of total weekly energy that translates into Greenhouse Gas emission reduction. Full article
(This article belongs to the Special Issue Selected papers from IEEE ICASI 2018)
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Open AccessArticle Building a Taiwan Law Ontology Based on Automatic Legal Definition Extraction
Appl. Syst. Innov. 2018, 1(3), 22; https://doi.org/10.3390/asi1030022
Received: 2 April 2018 / Revised: 22 June 2018 / Accepted: 24 June 2018 / Published: 27 June 2018
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Abstract
Term extraction is an important task that automatically extracts relative terms from the texts in a given domain. A significant number of web applications need to model information for specific topics. In particular, we have explored a Taiwan government website that maintains the
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Term extraction is an important task that automatically extracts relative terms from the texts in a given domain. A significant number of web applications need to model information for specific topics. In particular, we have explored a Taiwan government website that maintains the Laws & Regulations Database of the Republic of China (R.O.C) to provide the current Chinese law text to the public. However, the main issue is that there is no efficient structured method to handle such a large number of law texts. Therefore, in this paper, we propose a novel approach to extract legal as well as domain-relative terms, and then build a law ontology. We used the current Chinese law text from the Laws & Regulations Database as the data source. We then utilized natural language processing tools and data mining techniques to extract legal keywords and their definitions automatically. Subsequently, we constructed a Taiwan law ontology with the legal keywords and relative definitions. We have extracted 1114 legal keywords with definitions. With the characteristics of an ontology, users can view one keyword with its information and the associated keywords. Furthermore, we provide a service, which includes both the graphical and text interfaces to users on the web, such that a user can readily access the legal information on the Internet. Full article
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Open AccessArticle Spinning Reserve Capacity Optimization of a Power System When Considering Wind Speed Correlation
Appl. Syst. Innov. 2018, 1(3), 21; https://doi.org/10.3390/asi1030021
Received: 1 May 2018 / Revised: 21 June 2018 / Accepted: 21 June 2018 / Published: 26 June 2018
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Abstract
Usually, the optimal spinning reserve is studied by considering the balance between the economy and reliability of a power system. However, the uncertainties from the errors of load and wind power output forecasting have seldom been considered. In this paper, the optimal spinning
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Usually, the optimal spinning reserve is studied by considering the balance between the economy and reliability of a power system. However, the uncertainties from the errors of load and wind power output forecasting have seldom been considered. In this paper, the optimal spinning reserve capacity of a power grid considering the wind speed correlation is investigated by Nataf transformation. According to the cost–benefit analysis method, the objective function for describing the optimal spinning reserve capacity is established, which considers the power cost, reserve cost, and expected cost of power outages. The model was solved by the quantum-behaved particle swarm optimization (QPSO) algorithm, based on stochastic simulation. Furthermore, the impact of the related factors on the optimal spinning reserve capacity is analyzed by a test system. From the  simulation results, the model and algorithm are proved to be feasible. The method provided in this paper offers a useful tool for the dispatcher when increasing wind energy is integrated into power systems.
Full article
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Open AccessArticle A Hexapod Robot with Non-Collocated Actuators
Appl. Syst. Innov. 2018, 1(3), 20; https://doi.org/10.3390/asi1030020
Received: 8 April 2018 / Revised: 25 May 2018 / Accepted: 12 June 2018 / Published: 25 June 2018
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Abstract
The primary issue in developing hexapod robots is generating legged motion without tumbling. However, when the hexapod is designed with collocated actuators, where each joint is directly mounted with an actuator, the number of actuators is usually high. The adverse effects of using
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The primary issue in developing hexapod robots is generating legged motion without tumbling. However, when the hexapod is designed with collocated actuators, where each joint is directly mounted with an actuator, the number of actuators is usually high. The adverse effects of using a great number of actuators include the rise in the challenge of algorithms to control legged motion, the decline in loading capacity, and the increase in the cost of construction. In order to alleviate these problems, we propose a hexapod robot design with non-collocated actuators which is achieved through mechanisms. This hexapod robot is reliable and robust which, because of its mechanism-generated (as opposed to computer-generated) tripod gaits, is always is statically stable, even if running out of battery or due to electronic failure. Full article
(This article belongs to the Special Issue Selected papers from IEEE ICASI 2018)
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