Search results for: Consultative Committee for Space Data Systems (CCSDS) standards

Authors: Karim S. Hassan, Hisham M. Hamed, Yassmine A. Fahmy, Ahmed F. Shalash

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The mismatch between in-phase and quadrature signals in Orthogonal frequency division multiplexing (OFDM) systems, such as DVB-T2, results in a severe degradation in performance. Several general solutions have been proposed in the past, but these are largely computationally intensive, leading to complex implementations. In this paper, we propose a relatively simple iterative solution, which provides good results in relatively few iterations, using fixed precision arithmetic. An additional advantage is that complex digital blocks, such as dividers and square root, are not required. Thus, the proposed solution may be implemented in relatively simple hardware.

Keywords: OFDM, DVB-T2, I/Q imbalance, I/Q mismatch, iterative method, fixed point, reduced complexity

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Authors: Pooja Verma, Sumana Ghosh

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There is a growing need for alternative way of power generation worldwide. The reason can be attributed to limited resources of fossil fuels, environmental pollution, increasing cost of conventional fuels, and lower efficiency of conversion of energy in existing systems. In this context, one of the potential alternatives for power generation is wave energy. However, it is difficult to estimate the amount of electrical energy generation in an irregular sea condition by experiment and or analytical methods. Therefore in this work, a numerical wave tank is developed using the computational fluid dynamics software Open FOAM. In this software a specific utility known as waves2Foam utility is being used to carry out the simulation work. The computational domain is a tank of dimension: 5m*1.5m*1m with a floating object of dimension: 0.5m*0.2m*0.2m. Regular waves are generated at the inlet of the wave tank according to Stokes second order theory. The main objective of the present study is to validate the numerical model against existing experimental data. It shows a good matching with the existing experimental data of floater displacement. Later the model is exploited to estimate energy extraction due to the movement of such a point absorber in real sea conditions. Scale down the wave properties like wave height, wave length, etc. are used as input parameters. Seasonal variations are also considered.

Keywords: OpenFOAM, numerical wave tank, regular waves, floating object, point absorber

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Authors: Flavio Araujo, Fabiolla Lima, Julio Lima, Paulo Scalize, Antonio Albuquerque, Heitor Reis

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One of the great environmental problems in the management of water treatment (WTP) is on the disposal of waste generated during the treatment process. The same occurs with the waste generated during rectification of porcelain tiles. Despite environmental laws in Brazil the residues does not have an ecologically balanced destination. Thus, with the purpose to identify an environmentally sustainable disposal, residues were used to replace part of the soil, for production soil-cement bricks. It was used the residues from WTP and coatings industry Cecrisa (Brazil). Consequently, a greater amount of fine aggregate in the two samples of residues was found. The residue affects the quality of bricks produced, compared to the sample without residues. However, the results of compression and water absorption tests were obtained values that meet the standards, respectively 2.0 MPa and 20% absorption.

Keywords: water treatment residue, porcelain tile residue, WTP, brick

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Authors: Nisa Mohan

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Clinical coding is a feasible method for estimating the national prevalence of adverse drug event (ADE) admissions. However, under-coding of ADE admissions is a limitation of this method. Whilst the under-coding will impact the accurate estimation of the actual burden of ADEs, the feasibility of the coded data in estimating the adverse drug event admissions goes much further compared to the other methods. Therefore, it is necessary to know the reasons for the under-coding in order to improve the clinical coding of ADE admissions. The ability to identify the reasons for the under-coding of ADE admissions rests on understanding the decision-making process of coding ADE admissions. Hence, the current study aimed to explore the decision-making process of clinical coders when coding cases of ADE admissions. Clinical coders from different levels of coding job such as trainee, intermediate and advanced level coders were purposefully selected for the interviews. Thirteen clinical coders were recruited from two Auckland region District Health Board hospitals for the interview study. Semi-structured, one-on-one, face-to-face interviews using open-ended questions were conducted with the selected clinical coders. Interviews were about 20 to 30 minutes long and were audio-recorded with the approval of the participants. The interview data were analysed using a general inductive approach. The interviews with the clinical coders revealed that the coders have targets to meet, and they sometimes hesitate to adhere to the coding standards. Coders deviate from the standard coding processes to make a decision. Coders avoid contacting the doctors for clarifying small doubts such as ADEs and the name of the medications because of the delay in getting a reply from the doctors. They prefer to do some research themselves or take help from their seniors and colleagues for making a decision because they can avoid a long wait to get a reply from the doctors. Coders think of ADE as a small thing. Lack of time for searching for information to confirm an ADE admission, inadequate communication with clinicians, along with coders’ belief that an ADE is a small thing may contribute to the under-coding of the ADE admissions. These findings suggest that further work is needed on interventions to improve the clinical coding of ADE admissions. Providing education to coders about the importance of ADEs, educating clinicians about the importance of clear and confirmed medical records entries, availing pharmacists’ services to improve the detection and clear documentation of ADE admissions, and including a mandatory field in the discharge summary about external causes of diseases may be useful for improving the clinical coding of ADE admissions. The findings of the research will help the policymakers to make informed decisions about the improvements. This study urges the coding policymakers, auditors, and trainers to engage with the unconscious cognitive biases and short-cuts of the clinical coders. This country-specific research conducted in New Zealand may also benefit other countries by providing insight into the clinical coding of ADE admissions and will offer guidance about where to focus changes and improvement initiatives.

Keywords: adverse drug events, clinical coders, decision making, hospital admissions

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Authors: Issam Alnader, Aboubaker Lasebae, Rand Raheem

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Wireless sensor networks (WSNs) are distributed network systems used in a wide range of applications, including safety-critical systems. The latter provide critical services, often concerned with human life or assets. Therefore, ensuring the dependability requirements of Safety critical systems is of paramount importance. The purpose of this paper is to utilize the Hidden Markov Model (HMM) to elongate the service availability of WSNs by increasing the time it takes a node to become obsolete via optimal load balancing. We propose an HMM algorithm that, given a WSN, analyses and predicts undesirable situations, notably, nodes dying unexpectedly or prematurely. We apply this technique to improve on C. Lius’ algorithm, a scheduling-based algorithm which has served to improve the lifetime of WSNs. Our experiments show that our HMM technique improves the lifetime of the network, achieved by detecting nodes that die early and rebalancing their load. Our technique can also be used for diagnosis and provide maintenance warnings to WSN system administrators. Finally, our technique can be used to improve algorithms other than C. Liu’s.

Keywords: wireless sensor networks, IoT, dependability of safety WSNs, energy conservation, sleep awake schedule

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Authors: Fitri D. Jaswar, Tharek A. Rahman, Yasser A. Ahmad

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CubeSat in low earth orbit (LEO) mainly uses ultra high frequency (UHF) transmitter with fixed radio frequency (RF) output power to download the telemetry and the payload data. The transmitter consumes large amount of electrical energy during the transmission considering the limited satellite size of a CubeSat. A transmitter with power control ability is designed to achieve optimize the signal to noise ratio (SNR) and efficient power consumption. In this paper, the thermal vacuum chamber (TVAC) test is performed to validate the performance of the UHF band transmitter with power control capability. The TVAC is used to simulate the satellite condition in the outer space environment. The TVAC test was conducted at the Laboratory of Spacecraft Environment Interaction Engineering, Kyushu Institute of Technology, Japan. The TVAC test used 4 thermal cycles starting from +60°C to -20°C for the temperature setting. The pressure condition inside chamber was less than 10-5Pa. During the test, the UHF transmitter is integrated in a CubeSat configuration with other CubeSat subsystem such as on board computer (OBC), power module, and satellite structure. The system is validated and verified through its performance in terms of its frequency stability and the RF output power. The UHF band transmitter output power is tested from 0.5W to 2W according the satellite mode of operations and the satellite power limitations. The frequency stability is measured and the performance obtained is less than 2 ppm in the tested operating temperature range. The test demonstrates the RF output power is adjustable in a thermal vacuum condition.

Keywords: communication system, CubeSat, SNR, UHF transmitter

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Authors: Azusa Katsumata

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Where there is collaboration between universities and companies in the educational context, companies seek ‘knowledge’ from universities and provide a ‘place of practice’ to them. Several universities have introduced activities aimed at the mutual enlightenment of a diversity of people in career education. However, several programs emphasize on delivering results, and on practicing the prepared materials as planned. Few programs focus on unexpected failures and setbacks. This way of learning is important in career education so that classmates can help each other, overcome difficulties, draw out each other’s strengths, and learn from them. Seijo University in Tokyo offered Tokyo Tourism, a Project-Based Learning course, as a first-year career education course until 2016. In cooperation with a travel agency, students participate in planning actual tourism products for foreigners visiting Japan, undertake tours serving as guides. This paper aims to study the 'learning platform' created by a series of processes such as the fieldwork, planning tours, the presentation, selling the tourism products, and guiding the tourists. We conducted a questionnaire to measure the development of work-related skills in class. From the results of the questionnaire, we can see, in the example of this class, that students demonstrated an increased desire to be pro-active and an improved motivation to learn. Students have not, however, acquired policy or business skills. This is appropriate for first-year careers education, but we need to consider how this can be incorporated into future courses. In the questionnaire filled out by the students after the class, the following results were found. Planning and implementing travel products while learning from each other, and helping the teams has led to improvements in the student workforce. This course is a collaborative project between Japanese universities and the 2020 Tokyo Olympics and Paralympic Games committee.

Keywords: university career education, platform of learning, project-based learning, collaboration between university and company

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Samiah H. Ghounaim

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The topic of this paper is significant because of the increasing need for intercultural training for foreign language teachers due to the continuous challenges they face in their diverse classrooms. First, the structure of the intercultural training program designed will be briefly described, and the structure of a 3D vignette and its intended purposes will be elaborated on. This was the first stage where the program was designed and implemented on the period of three months with a group of local and expatriate foreign language teachers/practitioners at a university in the Middle East. After that, a set of primary data collected during the first stage of this research on the design and co-construction process of a 3D vignette will be reviewed and analysed in depth. Each practitioner designed a personal incident into a 3D vignette where each dimension of the vignette viewed the same incident from a totally different perspective. Finally, the results and the implications of having participant construct their personal incidents into a 3D vignette as a reflective practice will be discussed in detail as well as possible extensions for the research. This process proved itself to be an effective reflective practice where the participants were stimulated to view their incidents in a different light. Co-constructing one’s own critical incidents –be it a positive experience or not– into a structured 3D vignette encouraged participants to decentralise themselves from the incidents and, thus, creating a personal reflective space where they had the opportunity to see different potential outcomes for each incident, as well as prepare for the reflective discussion of their vignette with their peers. This provides implications for future developments in reflective writing practices and possibilities for educators’ continuous professional development (CPD).

Keywords: 3D vignettes, intercultural competence training, reflective practice, teacher training

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Ahmed Rashad Harb Riad Ismail

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The purpose of this research is to study the potential of Dynamic Pricing if deployed by mobile operators and analyse its effects from both operators and consumers side. Furthermore, to conclude, throughout the research study, the recommended conditions for successful Dynamic Pricing deployment, recommended factors identifying the type of markets where Dynamic Pricing can be effective, and proposal for a Dynamic Pricing stakeholders’ framework were presented. Currently, the mobile telecommunications industry is witnessing a dramatic growth rate in the data consumption, being fostered mainly by higher data speed technology as the 4G LTE and by the smart devices penetration rates. However, operators’ revenue from data services lags behind and is decupled from this data consumption growth. Pricing strategy is a key factor affecting this ecosystem. Since the introduction of the 4G LTE technology will increase the pace of data growth in multiples, consequently, if pricing strategies remain constant, then the revenue and usage gap will grow wider, risking the sustainability of the ecosystem. Therefore, this research study is focused on Dynamic Pricing for 4G LTE data services, researching the drivers, benefits and challenges of 4G LTE Dynamic Pricing and the feasibility of its deployment in practice from different perspectives including operators, regulators, consumers, and telecommunications equipment manufacturers point of views.

Keywords: LTE, dynamic pricing, EPC, research

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: Ana Paula Esteves, Diego S. Caetano, Louise L. B. Lomardo

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This paper presents an approach to the performance of the natural lighting, when the use of appropriated solar lighting systems on the roof is applied in cultural buildings such as museums and foundations. The roofs, as a part of contact between the building and the external environment, require special attention in projects that aim at energy efficiency, being an important element for the capture of natural light in greater quantity, but also for being the most important point of generation of photovoltaic solar energy, even semitransparent, allowing the partial passage of light. Transparent elements in roofs, as well as superior protection of the building, can also play other roles, such as: meeting the needs of natural light for the accomplishment of the internal tasks, attending to the visual comfort; to bring benefits to the human perception and about the interior experience in a building. When these resources are well dimensioned, they also contribute to the energy efficiency and consequent character of sustainability of the building. Therefore, when properly designed and executed, a roof light system can bring higher quality natural light to the interior of the building, which is related to the human health and well-being dimension. Furthermore, it can meet the technologic, economic and environmental yearnings, making possible the more efficient use of that primordial resource, which is the light of the Sun. The article presents the analysis of buildings that used zenith light systems in search of better lighting performance in museums and foundations: the Solomon R. Guggenheim Museum in the United States, the Iberê Camargo Foundation in Brazil, the Museum of Fine Arts in Castellón in Spain and the Pinacoteca of São Paulo.

Keywords: natural lighting, roof lighting systems, natural lighting in museums, comfort lighting

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Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari

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This study aims to examine, analyze and explain the impacts of compensation, career development and employee engagement to employee’s performance partially and simultaneously (Case Study at PT Bank XYZ). The research design used is quantitative descriptive research causality involving 30 respondents. Sources of data are from primary and secondary data, primary data obtained from questionnaires distribution and secondary data obtained from journals and books. Data analysis used model test using smart application PLS 3 that consists of test outer model and inner model. The results showed that compensation, career development and employee engagement partially have a positive impact on employee performance, while they have a positive and significant impact on employee performance simultaneously. The independent variable has the greatest impact is the employee engagement.

Keywords: compensation, career development, employee engagement, employee performance

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal

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The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP

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Authors: Patricia P. M. C. Lourenço

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South Korean Entertainment Industry has reversed the gender binary through Beast and Beauty Korean dramas that perpetuate Korean unrealistic beauty standards by emphasizing freckles, acne, pimples, excessive weight, fizzy hair, glasses, and braces as ugly and unattractive, therefore in need of correction to fit into society’s pre-established beauty mould. This pursuit of physical beauty as a happiness goal only detracts singularity in favour of mundaneness, sustaining the illusion that unsightly women need to undergo a physical transformation to improve their lives while handsome, wealthy men need not do anything more than altruistically accept them for who they really are inside. Five Beast and Beauty dramas were analysed for this paper. The assessment revealed that there is standardization and typecasting of Beast and Beauty roles in K-Dramas, a reflection of South Korean’s patriarchal society where women and men are continuously expected to fulfil their pre-established gender binary roles and stereotypes.

Keywords: K-dramas, beauty, low self-esteem, plastic surgery, South Korean stereotypes

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Authors: S. Abeysekera, M. Bazghaleh, M. P. L. Ooi, Y. C. Kuang, V. Kalavally

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Smart LED-based lighting systems have significant advantages over traditional lighting systems due to their capability of producing tunable light spectrums on demand. The main challenge in the design of smart lighting systems is to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area. This paper outlines the programmable LED lighting system design principles of design to achieve the two aims. In this paper, a seven-channel design using low-cost discrete LEDs is presented. Optimization algorithms are used to calculate the number of required LEDs, LEDs arrangements and optimum LED separation distance. The results show the illumination uniformity for each channel. The results also show that the maximum color error is below 0.0808 on the CIE1976 chromaticity scale. In conclusion, this paper considered the simulation and design of a seven-channel programmable lighting system using low-cost discrete LEDs to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area.

Keywords: light spectrum control, LEDs, smart lighting, programmable LED lighting system

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Rajkumar Ghosh

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Urban flooding is a common occurrence throughout Asia. Almost every city is vulnerable to urban floods in some fashion, and city people are particularly vulnerable. Pluvial and fluvial flooding are the most prominent causes of urban flooding in the Gomti Nagar region of Lucknow, Uttar Pradesh, India. The pluvial flooding is regarded to be less damaging because it is caused by heavy rainfall, Seasonal rainfall fluctuations, water flows off concrete infrastructures, blockages of the drainage system, and insufficient drainage capacity or low infiltration capacity. However, this study considers pluvial flooding in Lucknow to be a significant source of cumulative damage over time, and the risks of such events are increasing as a result of changes in ageing infrastructure, hazard exposure, rapid urbanization, massive water logging and global warming. As a result, urban flooding has emerged as a critical field of study. The popularity of analytical approaches to project the spatial extent of flood dangers has skyrocketed. To address future urban flood resilience, more effort is needed to enhance both hydrodynamic models and analytical tools to simulate risks under present and forecast conditions. Proper urban planning with drainage system and ample space for high infiltration capacity are required to reduce urban flooding. A better India with no urban flooding is a pipe dream that can be realized by putting household rooftop rainwater collection systems in every structure. According to the current study, domestic RTRWHs are strongly recommended as an alternative source of water, as well as to prevent surface runoff and urban floods in this region of Lucknow, urban areas of India.

Keywords: rooftop rainwater harvesting, urban flood, pluvial flooding, fluvial flooding

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Authors: Jing Niu, Jun X. Wang

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Arterial stiffness predicts mortality and morbidity, independently of other cardiovascular risk factors. And it is a major risk factor for age-related morbidity and mortality. The non-invasive industry gold standard measurement system of arterial stiffness utilizes pulse wave velocity method. However, the desktop device is expensive and requires trained professional to operate. The main objective of this research is the proof of concept of the proposed non-invasive method which uses measurement of magnetic flux disturbance and electrocardiogram (ECG) signal for measuring arterial stiffness. The method could enable accurate and easy self-assessment of arterial stiffness at home, and to help doctors in research, diagnostic and prescription in hospitals and clinics. A platform for assessing arterial stiffness through acquisition and analysis of radial artery pulse waveform and ECG signal has been developed based on the proposed method. Radial artery pulse waveform is acquired using the magnetic based sensing technology, while ECG signal is acquired using two dry contact single arm ECG electrodes. The measurement only requires the participant to wear a wrist strap and an arm band. Participants were recruited for data collection using both the developed platform and the industry gold standard system. The results from both systems underwent correlation assessment analysis. A strong positive correlation between the results of the two systems is observed. This study presents the possibility of developing an accurate, easy to use and affordable measurement device for arterial stiffness assessment.

Keywords: arterial stiffness, electrocardiogram, pulse wave velocity, Magnetic Flux Disturbance

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Authors: Richard Joseph, Nerey Mvungi

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An electric power system includes a generating, a transmission, a distribution and consumers subsystems. An electrical power network in Tanzania keeps growing larger by the day and become more complex so that, most utilities have long wished for real-time monitoring and remote control of electrical power system elements such as substations, intelligent devices, power lines, capacitor banks, feeder switches, fault analyzers and other physical facilities. In this paper, the concept of automation of management of power systems from generation level to end user levels was determined by using Power System Simulator for Engineering (PSS/E) version 30.3.2.

Keywords: automation, distribution subsystem, generating subsystem, PSS/E, TANESCO, transmission subsystem

Procedia PDF Downloads 656

Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

Procedia PDF Downloads 86

Authors: Cheyne Kirkpatrick

Abstract:

In an attempt to make the university intensive English program more worthwhile for students, many English language programs are redesigning curriculum to offer for-credit English for Academic Purposes classes, sometimes marketed as “bridge” courses. These programs are designed to be accredited to national language standards, provide communicative language learning, and give students the opportunity to simultaneously earn university language credit while becoming proficient in academic English. This presentation will discuss the curriculum design of one such program in the United States at a large private university that created its own for-credit “bridge” program. The planning, development, piloting, teaching, and challenges of designing this type of curriculum will be presented along with the aspects of accreditation, communicative language learning, and integration within various university programs. Attendees will learn about how such programs are created and what types of objectives and outcomes are included in American EAP classes.

Keywords: IEP, AEP, Curriculum, CEFR, University Credit, Bridge

Procedia PDF Downloads 468

Authors: Diane H. Dotson, Shari L. Rodriguez

Abstract:

Habitat for predators is on the decline worldwide, which often brings humans and predators into conflict over remaining shared space and common resources. While the direct impacts of human predator conflict on humans (i.e., attacks on livestock or humans resulting in injury or death) are well documented, the indirect impacts of conflict on humans (i.e., downstream effects such as fear, stress, opportunity costs, PTSD) have not been addressed. We interviewed 437 people living in 54 villages on the periphery of Kanha National Park, India, to assess the amount and severity of direct and indirect impacts of predator conflict. ​While 58% of livestock owners believed that predator attacks on livestock guards occurred frequently and 62% of those who collect forest products believed that predator attacks on those collecting occurred frequently, less than 20% of all participants knew of someone who had experienced an attack. Data related to indirect impacts suggest that such impacts are common; 76% of participants indicated they were afraid a predator will physically injure them. Livestock owners reported that livestock guarding took time away from their primary job (61%) and getting enough sleep (73%), and believed that it increased their vulnerability to illnesses (80%). These results suggest that the perceptions of risk of predator attack are likely inflated, yet the costs of human predator impacts may be substantially higher than previously estimated, particularly related to human well-being, making the implementation of appropriate and effective conservation and conflict mitigation strategies and policies increasingly urgent.

Keywords: direct impacts, indirect impacts, human-predator conflict, India

Procedia PDF Downloads 139

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

Procedia PDF Downloads 287

Authors: Mohammad Abbas Nejad

Abstract:

Tuka Sabz service production company (private shares), with more than 30 years of history, is considered as one of the first holding companies of Tuka Foulad, which takes steps in the direction of increasing service quality and customer satisfaction. Manpower supply is one of the most important activities of Tuka Sabz company, in addition to car supply services; light and heavy transportation services; management of entertainment, sports, tourism and accommodation centers; design, creation and maintenance services of land space; preparing, cooking, distributing and serving all kinds of personal and ceremonial foods; design, construction, repair and reconstruction of non-industrial buildings; industrial laundry services; public and industrial cleaning services are also among other activities of Tuka Sabz. This company has a high capacity of specialized and committed human resources as the main pillar of its success and spent most of its years of activity in Mobarakeh steel company as one of the reliable contractors in the field of automotive service contracts, green space, industrial cleaning, management cultural, recreational and tourism places, consulting, maintenance and repair of buildings and facilities, industrial laundry, management of cooking centers and personnel transportation. The final result of this article states that Tuka Sabz company is trying to get the satisfaction of three main groups of stakeholders, i.e., employees, customers, and shareholders, for this purpose, by improving the competence and competence of employees, trying to establish a system of meritocracy and respecting the human status of employees. On the one hand, the implementation of quality management and assurance to employers with the timely and favorable implementation of contracts takes a step in this direction.

Keywords: Mubarakeh steel company, Tuka Sabz company, human resources, industrial laundry services

Procedia PDF Downloads 43

Authors: Xinwen Zhu, Xingguang Li, Sun Yi

Abstract:

Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

Procedia PDF Downloads 201