Search results for: calibration data requirements

Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

Procedia PDF Downloads 487

Authors: M. Makary

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Indigenous tourism is nowadays one of the fastest growing sections of the tourism industry. Nevertheless, it does not yet receive attention on the agenda of public tourism policies in Egypt; however, there are various tourism initiatives in indigenous areas throughout the country mainly in the Nubia region, which located in Upper Egypt, where most of Egypt's indigenous Nubians are concentrated. Considering indigenous tourism can lead to both positive and negative impacts on the indigenous communities the main aim of this study is to analyze the socio-cultural and economic impacts of the indigenous tourism on the indigenous communities in Egypt: the case study of Nubians. Qualitative and quantitative approaches of data collection were designed and applied in conducting this study. Semi-structured interviews, focus groups, and the observations are the main preliminary data collection techniques used in this study while, the secondary data were sourced from articles, statistics, dissertations, and websites. The research concludes that indigenous tourism offers a strong motivation to save the identity of the indigenous communities and to foster their economic development. However, it also has negative impacts on their society.

Keywords: indigenous tourism, sustainable tourism, Indigenous communities, Nubians

Procedia PDF Downloads 227

Authors: James Kinyua Gitonga, Toshio Fujimi

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Vulnerability assessment and analysis is essential to solving the degree of damage and loss as a result of natural disasters. Urban flooding causes a major economic loss and casualties, at Mathare residential area in Nairobi, Kenya. High population caused by rural-urban migration, Unemployment, and unplanned urban development are among factors that increase flood vulnerability in Mathare area. This study aims to analyse flood risk physical vulnerabilities in Mathare based on scientific data, research data that includes the Rainfall data, River Mathare discharge rate data, Water runoff data, field survey data and questionnaire survey through sampling of the study area have been used to develop the risk curves. Three structural types of building were identified in the study area, vulnerability and risk curves were made for these three structural types by plotting the relationship between flood depth and damage for each structural type. The results indicate that the structural type with mud wall and mud floor is the most vulnerable building to flooding while the structural type with stone walls and concrete floor is least vulnerable. The vulnerability of building contents is mainly determined by the number of floors, where households with two floors are least vulnerable, and households with a one floor are most vulnerable. Therefore more than 80% of the residential buildings including the property in the building are highly vulnerable to floods consequently exposed to high risk. When estimating the potential casualties/injuries we discovered that the structural types of houses were major determinants where the mud/adobe structural type had casualties of 83.7% while the Masonry structural type had casualties of 10.71% of the people living in these houses. This research concludes that flood awareness, warnings and observing the building codes will enable reduce damage to the structural types of building, deaths and reduce damage to the building contents.

Keywords: flood loss, Mathare Nairobi, risk curve analysis, vulnerability

Procedia PDF Downloads 224

Authors: Oluyinka Ojedokun, S. E. Idemudia

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In Nigeria, statistics is a compulsory course required from all social sciences students as part of their academic training. However, a rising number of social sciences undergraduates usually express statistics anxiety. The prevalence of statistics anxiety among undergraduates in social sciences has created a growing concern for educators and researchers in the higher education institutions, mainly because this statistics anxiety adversely affects their performance in statistics and research methods courses. From a societal perspective it is important to reverse this trend. Although scholars and researchers have highlighted some psychosocial factors that influence statistics anxiety in students but few empirical studies exist on the association between personality traits of NEO five factors and statistics anxiety. It is in the light of this situation that this study was designed to assess the extent to which the personality traits of NEO five factors influence statistics anxiety of students in social sciences courses. The participants were 282 undergraduates in the faculty of social sciences at a state owned public university in Nigeria. The findings demonstrate that the personality traits contributing to statistics anxiety include openness to experience, conscientious, extraversion, and neuroticism. These results imply that statistics anxiety is related to individual differences in personality traits and suggest that certain aspects of statistics anxiety may be relatively stable and resistant to change. An effective and simple method to reduce statistics anxiety among social sciences students is to create awareness of the statistical and methodological requirements of the social sciences courses before commencement of their programmes.

Keywords: personality traits, statistics anxiety, social sciences, students

Procedia PDF Downloads 519

Authors: Kivilcim Ersoy, Cansu Yazganarikan

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In recent years, composite materials are more frequently utilized not only in aviation but also in automotive industry due to its high strength to weight ratio, fatigue and corrosion resistances as well as better performances in specific environments. The market demand also favors lightweight design for wheeled and tracked armored vehicles due to the increased demand for land and amphibious mobility features. This study represents the current application areas and trends in automotive, bus and armored land vehicles industries. In addition, potential utilization areas of fiber composite and hybrid material concepts are being addressed. This work starts with a survey of current applications and patent trends of composite materials in automotive and land vehicle industries. An intensive investigation is conducted to determine the potential of these materials for application in land vehicle industry, where small series production dominates and challenging requirements are concerned. In the end, potential utilization areas for combat land vehicle systems are offered. By implementing these light weight solutions with alternative materials and design concepts, it is possible to achieve drastic weight reduction, which will enable both land and amphibious mobility without unyielding stiffness and survivability capabilities.

Keywords: land vehicle, composite, light-weight design, armored vehicle

Procedia PDF Downloads 446

Authors: Rosemary Hiscock, Clive Sabel, David Manley, Sam Wren-Lewis

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As part of the Happy City Index Project, Happy City have developed a survey instrument to measure experienced wellbeing: how people are feeling and functioning in their everyday lives. The survey instrument, called the Happiness Pulse, was developed in partnership with the New Economics Foundation (NEF) with the dual aim of collecting citywide wellbeing data and engaging individuals and communities in the measurement and promotion of their own wellbeing. The survey domains and items were selected through a review of the academic literature and a stakeholder engagement process, including local policymakers, community organisations and individuals. The Happiness Pulse was included in the Bristol pilot of the Happy City Index (n=722). The experienced wellbeing items were subjected to factor analysis. A reduced number of items to be included in a revised scale for future data collection were again entered into a factor analysis. These revised factors were tested for reliability and validity. Among items to be included in a revised scale for future data collection three factors emerged: Be, Do and Connect. The Be factor had good reliability, convergent and criterion validity. The Do factor had good discriminant validity. The Connect factor had adequate reliability and good discriminant and criterion validity. Some age, gender and socioeconomic differentiation was found. The properties of a new scale to measure experienced wellbeing, intended for use by municipal authorities, are described. Happiness Pulse data can be combined with local data on wellbeing conditions to determine what matters for peoples wellbeing across a city and why.

Keywords: city wellbeing , community wellbeing, engaging individuals and communities, measuring wellbeing and happiness

Procedia PDF Downloads 241

Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

Procedia PDF Downloads 164

Authors: A. Prajapati, K. L. Koo, F. Ghassemi, M. Mulimakwenda

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In the UK, as the volume of non-linear loads connected to transmission grid continues to rise steeply, the harmonic distortion levels on transmission network are becoming a serious concern for the network owners and system operators. This paper outlines the findings of the study conducted to verify the proposal that the harmonic mitigation could be optimized and can be managed economically and effectively at the transmission network level by the Transmission Owner (TO) instead of the individual polluter connected to the grid. Harmonic mitigation studies were conducted on selected regions of the transmission network in England for recently connected offshore wind power plants to strategize and optimize selected harmonic filter options. The results – filter volume and capacity – were then compared against the mitigation measures adopted by the individual connections. Estimation ratios were developed based on the actual installed and optimal proposed filters. These estimation ratios were then used to derive harmonic filter requirements for future contracted connections. The study has concluded that a saving of 37% in the filter volume/capacity could be achieved if the TO is to centrally manage the harmonic mitigation instead of individual polluter installing their own mitigation solution.

Keywords: C-type filter, harmonics, optimization, offshore wind farms, interconnectors, HVDC, renewable energy, transmission owner

Procedia PDF Downloads 148

Authors: Elfatih M. Abdel-Rahman, Tobias Landmann, Richard Kyalo, George Ong’amo, Bruno Le Ru

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Maize (Zea mays L.) is a major staple food crop in Africa, particularly in the eastern region of the continent. The maize growing area in Africa spans over 25 million ha and 84% of rural households in Africa cultivate maize mainly as a means to generate food and income. Average maize yields in Sub Saharan Africa are 1.4 t/ha as compared to global average of 2.5–3.9 t/ha due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In East Africa, yield losses due to stem borers are currently estimated between 12% to 40% of the total production. The objective of the present study was therefore to predict stem borer larvae density in maize fields using RapidEye reflectance data and generalized linear models (GLMs). RapidEye images were captured for a test site in Kenya (Machakos) in January and in February 2015. Stem borer larva numbers were modeled using GLMs assuming Poisson (Po) and negative binomial (NB) distributions with error with log arithmetic link. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were employed to assess the models performance using a leave one-out cross-validation approach. Results showed that NB models outperformed Po ones in all study sites. RMSE and RPD ranged between 0.95 and 2.70, and between 2.39 and 6.81, respectively. Overall, all models performed similar when used the January and the February image data. We conclude that reflectance data from RapidEye data can be used to estimate stem borer larvae density. The developed models could to improve decision making regarding controlling maize stem borers using various integrated pest management (IPM) protocols.

Keywords: maize, stem borers, density, RapidEye, GLM

Procedia PDF Downloads 482

Authors: Arshad Ali

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This study aims to highlight the comparative patterns of social construction of gender among bureaucrats and non-bureaucrats. For the purpose of this study purposive sample of 8 respondents, including both male and female bureaucrats and non-bureaucrats, was collected from Gujranwala and Lahore. The measures for collecting data included an indigenous demographic information sheet and interview protocol related to gender roles, social construction of gender and managerial performance. The collected data was analyzed through the Nvivo version 11 and analysis reveals that there are diverse perceptions regarding male and female stereotyping among bureaucrats and non-bureaucrats, as different kinds of social environments lead to the modification of stereotypes. The research contributes to gender studies, specifically in the context of Pakistani society. There are very few studies available, and empirical data about Gender construction is scanty, so the study provides an impetus for future research. It is suggested that future research explore the phenomenon at a larger scale, including more respondents and another dimension, by keeping in view the socio-economic factors and policies of the government regarding the elimination of gender discrimination in Pakistan.

Keywords: social construction, gender, bureaucrats, gender perception

Procedia PDF Downloads 57

Authors: Barkha Ramteke, Sonali Ridhorkar

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An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

Procedia PDF Downloads 120

Authors: Bella Llego

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The purpose of this study was to explain and empirically test the influence of attitude towards work, job satisfaction and organizational commitment of SSRU employee’s evaluation and performance. Data used in this study was primary data which were collected through Organizational Commitment Questionnaire with 1-5 Likert Scale. The respondent of this study was 200 managerial and non-managerial staff of SSRU. The statistics to analyze the data provide the descriptive by the mean, standard deviation and test hypothesis by the use of multiple regression. The result of this study is showed that attitude towards work have positive but not significant effect to job satisfaction and employees evaluation and performance. Different with attitude towards work, the organizations commitment has positive and significant influence on job satisfaction and employee performance at SSRU. It means every improvement in organization’s commitment has a positive effect toward job satisfaction and employee evaluation and performance at SSRU.

Keywords: attitude towards work, employee’s evaluation and performance, jobs satisfaction, organization commitment

Procedia PDF Downloads 437

Authors: Sunmyeng Kim

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IEEE 802.11a/b/g standards provide multiple transmission rates, which can be changed dynamically according to the channel condition.Cooperative communications we reintroduced to improve the overallperformance of wireless LANs with the help of relay nodes with higher transmission rates. The cooperative communications are based on the fact that the transmission is much faster when sending data packets to a destination node through a relay node with higher transmission rate, rather than sending data directly to the destination node at low transmission rate. To apply the cooperative communications in wireless LAN, several MAC protocols have been proposed. Some of them can result in collisions among relay nodes in a dense network. In order to solve this problem, we propose a new protocol. Relay nodes are grouped based on their transmission rates. And then, relay nodes only in the highest group try to get channel access. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and collision probability.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

Procedia PDF Downloads 455

Authors: Fatemeh Norouzi

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Today, financial performance has become one of the important issues in accounting and auditing that companies and their managers have paid attention to this issue and for this reason to the variables that are influential in this field. One of the things that can affect financial performance is corporate governance, which is examined in this research, although some things such as issues related to auditing can also moderate this relationship; Therefore, this research has been conducted with the aim of investigating the relationship between corporate governance and financial performance with regard to the moderating role of feedback and internal control weakness. The research is practical in terms of purpose, and in terms of method, it has been done in a post-event descriptive manner, in which the data has been analyzed using stock market data. Data collection has been done by using stock exchange data which has been extracted from the website of the Iraqi Stock Exchange, the statistical population of this research is all the companies admitted to the Iraqi Stock Exchange. . The statistical sample in this research is considered from 2014 to 2021, which includes 34 companies. Four different models have been considered for the research hypotheses, which are eight hypotheses, in this research, the analysis has been done using EXCEL and STATA15 software. In this article, collinearity test, integration test ,determination of fixed effects and correlation matrix results, have been used. The research results showed that the first four hypotheses were rejected and the second four hypotheses were confirmed.

Keywords: size of the board of directors, duality of the CEO, financial performance, internal control weakness

Procedia PDF Downloads 75

Authors: Marcin Michalak

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Biclustering is the way of two-dimensional data analysis. For several years it became possible to express such issue in terms of Boolean reasoning, for processing continuous, discrete and binary data. The mathematical backgrounds of such approach — proved ability of induction of exact and inclusion–maximal biclusters fulfilling assumed criteria — are strong advantages of the method. Unfortunately, the core of the method has quite high computational complexity. In the paper the basics of Boolean reasoning approach for biclustering are presented. In such context the problems of computation parallelization are risen.

Keywords: Boolean reasoning, biclustering, parallelization, prime implicant

Procedia PDF Downloads 111

Authors: Huda Aljabi

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The existence of heavy metals similar to cadmium, arsenic, lead and mercury in the drinking water be able to be a threat to public health. The amount of the substances of these heavy metals in drinking water has expected importance. The National Primary Drinking Water Regulations have set limits for the concentrations of these elements in drinking water because of their toxicity. Furthermore, bromate shaped during the disinfection of drinking water by Ozonation can also be a health hazard. The Paper proposed here will concentrate on the compilation of all available data and information on the presence of trace metals and bromate in the drinking water at residential houses distributed over different areas in Kuwait. New data will also be collected through a sampling of drinking water at some of the residential houses present in different areas of Kuwait and their analysis for the contents of trace metals and bromate. The collected data will be presented on maps showing the distribution of these metals and bromate in the drinking water of Kuwait. Correlation among different chemical parameters will also be investigated using the GRAPHER software. This will help both the Ministry of Electricity and Water (MEW) and the Ministry of Health (MOH) in taking corrective measures and also in planning the infrastructure activities for the future.

Keywords: bromate, ozonation, GIS, heavy metals

Procedia PDF Downloads 160

Authors: André Felipe Gimenez, Flávia Alessandra Ribeiro da Silva, Roberto Saverio Souza Costa

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Currently, the rural producer has been facing problems regarding environmental regularization, which is precisely why the CAR (Rural Environmental Registry) was created. CAR is an electronic registry for rural properties with the purpose of assimilating notions about legal reserve areas, permanent preservation areas, areas of limited use, stable areas, forests and remnants of native vegetation, and all rural properties in Brazil. . The objective of this work was to evaluate and compare altimetry and slope data from google Earth with a digital terrain model (MDT) generated by aerophotogrammetry, in three plots of a steep slope, for the purpose of declaration in the CAR (Rural Environmental Registry). The realization of this work is justified in these areas, in which rural landowners have doubts about the reliability of the use of the free software Google Earth to diagnose inclinations greater than 25 degrees, as recommended by federal law 12651/2012. Added to the fact that in the literature, there is a deficiency of this type of study for the purpose of declaration of the CAR. The results showed that when comparing the drone altimetry data with the Google Earth image data, in areas of high slope (above 40% slope), Google underestimated the real values of terrain slope. Thus, it is concluded that Google Earth is not reliable for diagnosing areas with an inclination greater than 25 degrees (46% declivity) for the purpose of declaration in the CAR, being essential to carry out the local topographic survey.

Keywords: MDT, drone, RPA, SiCar, photogrammetry

Procedia PDF Downloads 115

Authors: Sudaporn Arundee

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The purposes of this research were to study in three areas: (1) to study political understanding and participating of the constitutional monarchy, (2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data. The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.

Keywords: political participation, constitutional monarchy, management and social sciences

Procedia PDF Downloads 240

Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: Hebberly Ahatlan

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The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, IT/OT convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: digitalization, IT/OT convergence, semantic interoperability, VPP, energy blockchain

Procedia PDF Downloads 155

Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

Procedia PDF Downloads 78

Authors: Jodie Lee, Lorena Chan, Esther Tong

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Hong Kong students face a unique learning environment. Starting from the 2010/2011 school year, The Education Bureau (EDB) of the Government of the Hong Kong Special Administrative Region implemented the fine-tuned Medium of Instruction (MOI) arrangements for secondary schools. Since then, secondary schools in Hong Kong have been given the flexibility to decide the most appropriate MOI arrangements for their schools and under the new academic structure for senior secondary education, particularly on the compulsory part of the mathematics curriculum. In 2019, Hong Kong Diploma of Secondary Education Examination (HKDSE), over 40% of school day candidates attempted the Mathematics Compulsory Part examination in the Chinese version while the rest took the English version. Moreover, only 14.38% of candidates sat for one of the extended Mathematics modules. This results in a serious of intricate issues to students’ learning in post-secondary education programmes. It is worth to note that when students further pursue to an higher education in Hong Kong or even oversea, they may facing substantial difficulties in transiting learning from learning mathematics in their mother tongue in Chinese-medium instruction (CMI) secondary schools to an English-medium learning environment. Some students understood the mathematics concepts were found to fail to fulfill the course requirements at college or university due to their learning experience in secondary study at CMI. They are particularly weak in comprehending the mathematics questions when they are doing their assessment or attempting the test/examination. A government funded project was conducted with the aims of providing integrated learning context and language support to students with a lower level of numeracy and/or with CMI learning experience. By introducing this “integrated concept + language mapping approach”, students can cope with the learning challenges in the compulsory English-medium mathematics and statistics subjects in their tertiary education. Ultimately, in the hope that students can enhance their mathematical ability, analytical skills, and numerical sense for their lifelong learning. The “Concept + Language Mapping “(CLM) approach was adopted and tried out in the bridging courses for students with a lower level of numeracy and/or with CMI learning experiences. At the beginning of each class, a pre-test was conducted, and class time was then devoted to introducing the concepts by CLM approach. For each concept, the key thematic items and their different semantic relations are presented using graphics and animations via the CLM approach. At the end of each class, a post-test was conducted. Quantitative data analysis was performed to study the effect on students’ learning via the CLM approach. Stakeholders' feedbacks were collected to estimate the effectiveness of the CLM approach in facilitating both content and language learning. The results based on both students’ and lecturers’ feedback indicated positive outcomes on adopting the CLM approach to enhance the mathematical ability and analytical skills of CMI students.

Keywords: mathematics, Concept+Language Mapping, level of numeracy, medium of instruction

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Authors: Nihan Gurel Ulusan

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It is obvious that electrical energy, which is an inseparable part of modern day’s human and also the most important power source of our age, should be generated on a level that will suffice the nation’s requirements. The electrical energy used for a sustainable architectural design should be reduced as much as possible. Designing the buildings as energy efficient systems which aim at reducing the artificial illumination loads has been a current subject of our times as a result of concepts gaining importance like conscious consumption of energy sources, environment-friendly designs and sustainability. Reducing the consumption of electrical energy regarding the artificial lighting carries great significance, especially in the volumes which are used all day long like the educational buildings. Starting out with such an aim in this paper, the educational buildings are explored in terms of energy efficient lighting. Firstly, illumination techniques, illumination systems, light sources, luminaries, illumination controls and 'efficient energy' usage in lighting are mentioned. In addition, natural and artificial lighting systems used in educational buildings and also the spaces building up these kind buildings are examined in terms of energy efficient lighting. Lastly, the illumination properties of the school sample chosen for this study, Kağıthane Anadolu Lisesi, a typical high school in Istanbul, is observed. Suggestions are made in order to improve the system by evaluating the illumination properties of the classes with the survey carried out with the users.

Keywords: educational buildings, energy efficient, illumination techniques, lighting

Procedia PDF Downloads 267

Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 79

Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: Kassahun Tilahun

Abstract:

Most of the studies available on adult psychological well-being have been centered on Western countries. However, psychological well-being does not have the same meaning across the world. The Euro-American and African conceptions and experiences of psychological well-being differ systematically. As a result, questions like, how do people living in developing African countries, like Ethiopia, report their psychological well-being; what would the context-specific prominent determinants of their psychological well-being be, needs a definitive answer. This study was, therefore, aimed at developing a new theory that would address these socio-cultural issues of psychological well-being. Consequently, data were obtained through interview and open ended questionnaire. A total of 438 adults, working in governmental and non-governmental organizations situated in Addis Ababa, participated in the study. Appropriate qualitative method of data analysis, i.e. thematic content analysis, was employed for analyzing the data. The thematic analysis involves a type of abductive analysis, driven both by theoretical interest and the nature of the data. Reliability and credibility issues were addressed appropriately. The finding identified five major categories of themes, which are viewed as essential in determining the conceptions and experiences of psychological well-being of Ethiopian adults. These were; socio-cultural harmony, social cohesion, security, competence and accomplishment, and the self. Detailed discussion on the rational for including these themes was made and appropriate positive psychology interventions were proposed. Researchers are also encouraged to expand this qualitative research and in turn develop a suitable instrument taping the psychological well-being of adults with different sociocultural orientations.

Keywords: sociocultural, psychological, well-being Ethiopia, adults

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi

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A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.

Keywords: posture correction, posture training, riding posture, riding simulator

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

Abstract:

A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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