Volume 6, Issue 6

This paper describes what can be accomplished by understanding sound environments. Understanding sound environments is achieved by extracting the features of the sound and visualizing the features. The visualization is realized by converting the three features, namely, loudness, continuity, and pitch, into RGB values and expressing the sound with color, where the color is painted in the estimated direction of the sound. The three features can distinguish falling objects within a building and roughly estimate the direction of the generated sounds. The effectiveness of the proposed sound visualization was confirmed using the sounds of cans and stones falling in a building; hence, it is shown that the proposed visualization method will be useful for monitoring the collapse of buildings by sound.

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We propose and analyze new impedance matching schemes to enhance applied voltage to an optical modulator and light modulation for a subcarrier multiplexed light transmitter or a radio-on-fiber transmitter that carries radio-frequency signal through an optical fiber. Our proposal includes two methods using a quarter-wavelength impedance transformer and a tapered microstrip line for impedance matching between a driver circuit and an electro-absorption modulator. Simulation results for both two schemes show that large enhancement is observed for 20 GHz and lower frequency and that some resonant boosts are observed for higher frequency as well. Discussions are described to design a circuit with improved performances. It is shown that our schemes can drive the electro-absorption modulator at a voltage higher than 1 V that is sufficient to drive the modulator.

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Lean Six Sigma (LSS) is a renowned approach for boosting operational excellence and competitive advantage through integrated core objectives of value creation and variation reduction. Despite its proven benefits in many leading companies, LSS implementation in the food sector is still behind compared with other sectors. LSS implementation is costly, and most businesses have failed due to a lack of preparation and an unsupportive organizational culture. Therefore, there is a need to identify LSS readiness factors that suit the food sector to minimize the risk of implementation failure in the industry. The current study concentrates on the LSS pre-implementation phase to determine the competency criteria to adopt LSS customized for the food business. This study will explore the LSS readiness criteria during the pre-implementation stage and critical success factors (CSFs) during the implementation stage in the food sector through Lewin’s Change Theory. Twelve food sector employees who were associated with quality management activities were interviewed using a semi-structured approach. The interview was recorded, transcribed and the transcription was analyzed using content analysis. The results showed six readiness themes in the food manufacturing sector with twenty-nine LSS readiness attributes, while seventeen factors out of thirty-one CSFs for the LSS at the implementation stage. The identified readiness factors are management commitment and leadership (ten attributes), organizational culture (nine attributes), employee involvement (six attributes), process management (four attributes), project management (four attributes) and external factors (three attributes). Through Pareto analysis, the most prioritized CSFs are from top management and leadership and employee involvement themes, with the training program being identified as the most important LSS CSFs (85%). This study will serve as a foundation for a benchmarking tool for managers to improve the effectiveness of an LSS implementation in the food sector.

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In the last decade, South Africa has attracted and attained more investment by means of the Renewable Energy Independent Power Producer Procurement Programme (REI4P), which is, a structured invitation to Independent Power Producers (IPPs) to submit a bid to generate and supply power to the electrical grid. In spite of REI4P’s undeniable triumph, a much-discussed drawback has been the related service lifetime cost of equipment that facilitate the renewable energy technologies. The description of the service lifetime loss method (SLLM) gets more complex in the new dawn of decarbonized electricity market. The SLLM must be modified for determining the total ownership cost of transformers facilitating Sustainable Energy Systems (SES’s) in the decentralized energy market. The main focus of this work is to indicatively formulate a fundamental advancement upon the conventional service lifetime losses evaluation formula to contemplate the service lifetime loss evaluation method for transformers exclusively of service to solar power plants in South Africa. The distinct operational features of a solar plant have been embedded in the formulated service lifetime loss evaluation formula by way of the plants’ Generation (GM) and Non-Generation Mode (NGM). Further, a levelized cost of energy supplied per unit of time by the solar plant is employed to determine the energy cost of the no-load and load losses that will be consumed by the studied transformers during their service life. Ultimately, the premier findings of this study indicate that the annual solar potential has an effect on the transformer service lifetime loss factors and the conventional method is not suitable thereof for this application. This is a characteristic that should be precisely considered, as it may influence the tender adjudication process to purchase a transformer based on the total ownership cost offers of various transformer manufacturers.

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The ageing of oil-immersed power transformers triggers several defects and damages in the insulating materials, particularly in the cellulose insulation. The decomposition of the cellulose paper produces dissolved gases into the insulating oil, in which the Dissolved Gas Analysis (DGA) of the oil samples can provide insights to incipient faults sustained by the transformer as well as the status of the insulation. The condition of the cellulose insulation can be established by the measurement of the Degree of Polymerization (DP). In some instances, when the DP is intricate to measure, the estimation can be realized by collating information with respect to oil Furan analysis (2-furfuraldehyde (2FAL)). In this work, regression analysis based on 120 transformer oil samples is developed to establish new formulae by generating an analogy between the DP and 2FAL to indicate the status of the cellulose insulation and percentage of remnant life expectancy. In present study, five different transformers are tested using the proposed formulae to compute the DP based on the 2FAL concentrations. The results, are compared with measurement results and four other existing models. The results indicate an error of estimate of less than 2% and 1% against the measured DP.

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Service robots are applied in many kinds of business fields and its various kinds of data can be collected with service robot in business scenes. Therefore, it becomes more important to utilize such data for business improvement. Additionally, due to limitation of design such as body size and battery life, a service robot cannot prepare much peripheral equipment on its body. In this paper, we will show two research results as for service robot. One is data analysis technology for business improvement as a function of operation and management system for service robot. Another is service extension of service robot by association of external equipment with proper design of utilization condition of external equipment. Through evaluation experiment, we confirmed potential effect of business improvement is 8.1 % by modifying service scenario of robot.

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Serious games are at the forefront of discussions about the future of learning. Research shows that they can help improve student motivation and knowledge transfer by making learning experiences more pleasurable. Teaching practices are increasingly enhanced or complemented by serious games; skills and knowledge are developed by recreating realistic situations allowing learners to enhance their procedural knowledge, all while having fun. Literature is scarce when it comes to identifying factors that influence learners’ satisfaction when using serious games. In this paper, we present empirical results from an ongoing research project. We developed a questionnaire using factors identified in the literature and collected the responses of n = 110 business students from classes using serious games as a tool. Analyses were performed using partial least squares structural equation modeling (PLS-SEM). We used the following predictor variables for our model: performance and status feedback and tracking, ease of use, reliability, perceived control, instructor support, aesthetics, realism entertainment, goal clarity, immersion, and progressive challenge. Results show that sense of control, entertainment and effectiveness have a direct positive influence on learners’ satisfaction while other factors influence satisfaction by mediation or as components of theoretically justified higher-order constructs. The sample size and its composition limit the generalization of results. Further studies are needed.

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The Japanese writing system is unique due to the number of characters employed and the methods used to write words. It consists of three different ’alphabets’, which may result in the methods used to process Latin script not being sufficient to obtain satisfactory results when attempting to apply them to a recognition of the Japanese script. The authors present an algorithm based on minutiae, i.e., feature points, to recognise the hiragana and katakana characters. A method using image processing algorithms is compared with a method using a neural network for the purpose of automating this process. Based on the distribution and type of minutiae, vectors of features have been created to recognise 96 different characters. The authors conducted a study showing the effect of the chosen segmentation method on the accuracy of the character recognition. The proposed solution has achieved a maximum accuracy at the level of 65.2%.

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The SENSORIA Reference Modeling Language (SRML) aims at modelling composite services at a high level. Continuous time SRML extends SRML so that it can model services whose components can perform both discrete processes and continuous processes. In order to show how continuous time SRML is applied, in this paper, we systematically introduce our study on continuous time SRML in the following approach: First we introduce the theoretical foundation of continuous time SRML, the Service-Oriented Hybrid Doubly Labeled Transition Systems. This is the semantic domain over which continuous time SRML is defined and interpreted. Then we design a case study of a traffic control system. In the case study, we illustrate the scenario of the system, explain the continuous time SRML model of the system, and show how to transform the model to a kind of Deterministic Finite Automata that can be used for testing and verification. Finally, we show our idea of testing our model with the IBM WebSphere Process Server. With this approach, we come to a conclusion that continuous time SRML can be used to model certain systems in the real-world, and can be tested with proper tools.

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Considering the importance of addressing innovation issues that impact the development of economic sectors, this document presents the research work aimed at establishing a state of the art related to technology transfer and intermediation issues, which can be adopted in the innovation systems. In this case, the agro-industrial innovation system is taken as a reference from the perspective of a country, Colombia. Likewise, it is proposed to consider the synergy between actors such as the university and the industry, from a holistic vision of the systems. In this sense, and making use of the Scopus, Web of Science and Google Scholar databases, through the implementation of a methodology in which three main phases of search, selection and reading of scientific publications were generated, a set of documents was obtained, and through these it was possible to identify: concepts on innovation systems, aspects that intervene in transfer processes of technology especially related to the articulation of the actors that are part of the innovation systems, as well as the way in which these issues can be adopted, taking the agro-industrial sector as a reference. Thus, through this research, the existence of structural gaps in the networks of actors is highlighted as a key factor, which, when trying to be moderated through the intervention of government actors, also require the participation of intermediary innovation agents, that facilitate the articulation and flow of data, information and communication between those who develop technology and those who require these developments to mitigate a need in the productive sectors.

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The aim of this research was to prove the effect of online learning on interest and motivation to learn and its effect on student achievement in the Educational Technology Study Program – Ibnu Khaldun University, Bogor. This research method uses descriptive analysis and verification with a quantitative approach. The source of this research uses primary data. Collecting data using a questionnaire. The sample of this study was 40 students at the Education Technology Study Program IK University Bogor by performing both descriptive and path analysis for the random sampling technique.of this study indicate that online learning has a positive and significant effect on interest and motivation to learn. It is known that the total effect of online learning on students’ interest in learning is 79.03%, while the total effect on student learning motivation is 79.74%. Interest in learning has Both interest in learning and learning motivation have contributed on student achievement which are measured by 29.6% and 51.07% respectively, with a total effect of 29.61%. While learning motivation has a positive and significant effect on student achievement, with a total effect of 51.07%.

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The main objective and contribution of the paper is to describe the creation of a model to support recruitment using social media information and its deployment in practice. The model includes the design of an automated solution for downloading social media data and a proposal for the subsequent analysis and creation of a predictive model based on the evaluation of user behavior on a social network. A final assessment of the effectiveness of the proposed model was made through formal validation and a case study. For the case study validation, the proposed model was implemented through use of the recruitment application called Prace Na Miru (PM; Tailored Work) for Facebook data extraction. A Myers Briggs Type Indicator (MBTI) personality test was used to determine the predictors of user social network behavior. Using cluster analysis and machine learning (or decision trees), a stochastic predictive model was developed to determine the personality type of candidates—the accuracy of MBTI personality category prediction ranges between 68% and 84% for individual cases, with a confirmation rate ranging between 43% and 81%. The case study confirmed the model’s usefulness for supporting recruitment in a real-life deployment of the PM model.

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The focus of this work is first to establish the effect of the chip temperature and thermal feedback on the determination of the power loss in a three-phase propulsion inverter, then to demonstrate the possibility of achieving an improved heat spreading through the different layers inside a SiC power module by using graphene assembled films in the packaging of the power module. The power loss analysis has been carried out for two Silicon Carbide (SiC) modules in a vehicle inverter, incorporating the MOSFET’s reverse conduction as well as including the impact of blanking time on the inverter on-state losses. This data for calculating the losses is determined at an operating situation below the field weakening speed with a high torque for a permanent magnet synchronous machine (PMSM). The operating point is found to be the worst operating condition point when looking at the power loss point. First, it can be noted that not accounting for the thermal feedback, the power loss is considerably underrated, i.e.,11-15% on the on-state converter. Following, the analysis of utilizing the graphene layer in the SiC module reveals a reduction of 10°C per SiC chips in the junction temperature of the SiC MOSFET is achievable. The reduction is calculated based on an applied power loss per SiC chips in steady-state simulation. Furthermore, up to 15°C decrease in the transient computation over the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) per SiC chip is noticed. Moreover, a reduction up to 50% for the junction to case thermal resistance (Rth,JC) is observed by adding the graphene layer in the power module.

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The paper describes the control and monitoring systems installed in medium voltage networks by Polish distribution network operators. It also outlines the expected directions of development of these systems, specifies the functions of the individual system components and describes the requirements applicable to them. In particular, attention is paid to the implementation of functions to detect short-circuits and automatic voltage control on the low voltage side of the transformer using the on-load tap changer. It also describes the communication functions implemented by the control and monitoring systems and the methods of ensuring a guaranteed power supply for the above systems.

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To determine the risk factors associated with the development of extensively resistant pulmonary tuberculosis in the DIRIS Lima Sur, 2017. The type of research was observational, quantitative, analytical, retrospective case-control approach. The population consisted of 158 patients with MDR-TB treatment schedule between 2016 and 2017. The sample consisted of 24 cases diagnosed with extensively drug-resistant pulmonary tuberculosis (XDR-TB) and 48 controls with MDR-TB. The survey was used for both groups (cases – controls) as a data collection technique and a questionnaire as an instrument. 5 risk factors associated with XDR-TB were identified. Among the internal factors associated at the bivariate level were: drug use, previous history of MDR-TB/TB treatment, having taken MDR-TB treatment for less than one year, history of failure to primary and individualized scheme for MDR-TB/TB (p<0.05); and the multivariate analysis confirmed the influence of the factor “history of failure to primary and individualized scheme for MDR-TB/TB”. Among the external factors most associated at the multivariate level were: having a history of family contact deceased by XDR-TB/MDR-TB and extra domiciliary contact in the neighborhood deceased by TB (p<0.05) It was concluded that the factors associated with the development of extensively resistant tuberculosis are “failure to follow the primary and individualized MDR-TB regimen” and “history of deceased family contact with XDR-TB-MDR-TB”.

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Nowadays, LED lights take an important place in our daily lives and they have known a great growth in indoor as well as in outdoor lighting applications. LED (Light Emitting Diode) light sources including their own drivers have excluded many systems fitted with both inefficient light sources. In this paper we present, a LED driver handling a DC input power supply and piloting a series of powered LEDs Some topologies of LED driver supplying a constant voltage or a constant current toward a LED load and their operations are detailed and presented. In this regard, two types of DC-DC converter in occurrence buck and boost converter are analyzed, designed, and simulated. Furthermore, a design of laboratory prototype of constant-current LED drivers based on DC-DC buck converter totally dimed is achieved, and tested. Calculated and experimental results are in good correspondence with very small deviation of LED current in both cases for different levels of dimming.

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Concomitant with the ubiquity of lightweight electronic terminals, such as smartphones and tablets, e-books have increased in popularity. However, studies have shown that their display method and information-presentation efficiency need improvement. We investigated visual information processing during reading to develop a more efficient display method that presents information in an easier to see fashion than conventional methods. Specifically, we focused on the information- processing ability of the brain within the gazing point during reading to clarify various factors that make a book easier to read such as the minimum display time and line length that can be read accurately and the difference in reading time depending on the font. An experimental method using a “window” was utilized that facilitates changing of the display information in the window by moving the window in conjunction with the eye movement. Using this method, it was found that if the number of characters displayed in the window is more than six and the window display time is 56 ms or more, reading can be performed in the same manner as when the window is not displayed. Thus, here we focused on letter size to investigate the relationship between reading time and font size. Experimental results indicate that among sentences in three font sizes 12, 18, and 24 pt normal reading without any restriction of view is possible when the font size is 18 pt or more. These results suggest that normal reading can be performed even with a very short display time of 56 ms by using characters with a font size of 18 pt or more in Japanese, which is useful for proposing a new display method for e-books. In addition, this experimental method can be applied to languages other than Japanese, and can contribute to the development of an optimum display method for each language.

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This work proposes a new unsupervised learning approach to detect and locate the risks “abnormal event” in video scenes using Faster R-CNN and Bidirectional LSTM autoencoder. The approach proposed in this work is carried out in two steps: In the first step, we used a bidirectional LSTM autoencoder to detect the frames containing risks. In the second step, for each frame containing risks, we first used Faster R-CNN to extract all the objects containing in the scene and then for each object detected we check whether it represents a risk or not. In other words, in testing phase, the frames with events deviated from normal features learned in training phase are detected as risk. To locate objects representing risk, only the objects detected by Fast R-CNN deviated from normal feature are classified as risk. Experimental results demonstrate that the proposed method can reliably detect and locate the object representing risk in video sequences.

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Drought has become more common and severe in recent decades due to increased global changes in climatic conditions and anthropogenic activities thereby analyzing drought at both regional and local levels is crucial. And so, this study aims at assessing drought risk in Northern Nigeria using NDVI and SPI. Data used included satellite images (Landsat OLI-TIRS, ETM+, TM, and MSS) meteorological data, and gridded precipitation datasets (1975 – 2016) from the Climate Research Unit (CRU). The drought index was calculated using the Standardized Precipitation Index (SPI) for both short-term and long-term timescales with emphasis on drought magnitude, frequency, duration. The Mann-Kendall trend analysis was utilized on precipitation and SPI to investigate the trend changes. Results indicated that SPI dynamics over the region at varying timescales suggest the unpredictability of drought with longest drought duration were the severe and extreme drought (SPI ≤ − 1.5) was peaked at -3.12 severity that lasted 15months between 2007 and 2008. The worst drought magnitudes were more eminent in the longer timescale (SPI12months) with its peak of -70.8 that lasted 60months (5years) between 1984 and 1986. Similarly, drought intensity was observed between the mildly dry with SPI -0.47(1986 – 1991) and severely dry with SPI − 1.79 (1983 – 1984) this further revealed that spatially drought risk is increasing southward. NDVI values obtained demonstrated a consistent decrease with a better state in 1975 which ranged between – 0.31 and 0.63. 2016 recorded lower values with a range between -0.21 and 0.47. NDVI minimum and maximum values were between -0.48 and 0.63 between 1975 and 2016, while in 2016 highest of 0.47 was observed as the least maximum value with 1975 recording the highest value at 0.63. The results demonstrated that drought conditions within the Guinean-Sudano ecological zone of northern Nigeria are evident due to rapid unpredictable climatic changes and anthropogenic activities.

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