Search results for: train positioning

Authors: Mahshid Asadollahi, Mohammad Akbari Asl

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The restaurant industry is highly competitive, and restaurants are constantly looking for ways to attract new customers and retain their existing ones. Nonverbal communication is an important factor in creating a positive customer experience and can play a significant role in attracting customers to restaurants. Nonverbal communication can include body language, facial expressions, tone of voice, and physical proximity, among other things. The present study aimed to investigate the impact of nonverbal communication between restaurant employees and customers on attracting customers in food courts in Tehran. The research method was descriptive-correlational, and the statistical population of this study included all customers of food court restaurants in Tehran, which was about 30 restaurants. The research sample was selected through probability sampling, and 440 customers completed emotional response, customer satisfaction, and nonverbal communication questionnaires in person. The data obtained were analyzed using multiple regression analysis. The results showed that vocal language, employee proximity, physical appearance, and speech movements, as components of nonverbal communication of restaurant employees, had an impact on attracting customers. Additionally, positive and negative emotions of customers have a significant relationship with customer attraction in Food Court restaurants. The study shows that various nonverbal communication factors can play a significant role in attracting customers, and that positive and negative customer emotions can affect customer satisfaction. Therefore, restaurant owners and managers should pay attention to nonverbal communication and train their employees accordingly to create a positive and welcoming atmosphere for customers.

Keywords: verbal language, proximity of employees, physical appearance, speech gestures, nonverbal communication, customer emotions, customer attraction

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Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Pramoda Karunarathna, Hemamalie Gunatilaka

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This study is based on experiences of Sri Lankan lesbian and gay workers’ career in the corporate sector, which include both manufacturing and service sectors. The study has started with the intention of shedding light on a grey area to observe the negative effects on lesbian and gay workers and their experiences while they are employed in the Sri Lankan corporate sector. In order to understand the experiences of lesbian and gay workers while they are at work within the corporate sector, the study seeks to address four questions. First research question is about the challenges faced by lesbian and gay workers while they are at work, and the second research question looks at their career patterns. Third research question seeks to address the behavior at work, and the fourth research question looks at the influence of class, religion, and cultural aspects on the career of lesbian and gay workers. Methodologically, the research was based on semi-structured interviews with nine participants (five gay men and four lesbian women) having work experience in the corporate sector and residing in Colombo, the capital city of Sri Lanka. The research found that the participants have gone through the process of developing sexual identity; gay men possess more feminine characteristics, while lesbian women possess more masculine characteristics. Further, their identity gets revealed in different ways, such as through the curriculum vitae, at the interviews, through the attire and behavior, and with the use of social media. The study also found that lesbian and gay workers experience discrimination due to violation of hierarchical power difference by other employees and marginalization, verbal and nonverbal abuse by other men at work are common experiences. Another finding is that lesbian and gay workers adopt strategies for survival at work, and they prefer the NGO sector to the corporate sector. In contrast, even within the corporate sector, advertising is preferred by lesbian and gay workers. Some of the Sri Lankan corporate sector organizations, especially multinational organizations, have initiated diversity training, and it might lead to making these organisations lesbian and gay-friendly workplaces in the future. It is also found that nearly 44 percent of the participants do not have a religion, and it is due to the rejection of deviant behaviours by most of the religions. In conclusion, lesbian and gay workers experience discrimination at work in the Sri Lankan corporate sector with an exception to the companies relating to advertising and non-governmental organisations is the sector that these workers prefer the most.

Keywords: lesbian workers, gay workers, Sri Lankan corporate sector, discrimination

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Authors: Benedict O. Muyale, Emmanuel S. Murunga

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Cities have always been the loci for nationals as well as growth of cultural fusion and innovation. Over 50%of global population dwells in cities and urban centers. This means that cities are prolific users of natural resources and generators of waste; hence they produce most of the greenhouse gases which are causing global climate change. The root cause of increase in the transport sector carbon curve is mainly the greater numbers of individually owned cars. Development in these cities is geared towards economic progress while environmental sustainability is ignored. Infrastructure projects focus on road expansion, electrification, and more parking spaces. These lead to more carbon emissions, traffic congestion, and air pollution. Recent development plans for Nairobi city are now on road expansion with little priority for electric train solutions. The Vision 2030, Kenya’s development guide, has shed some light on the city with numerous road expansion projects. This chapter seeks to realize the following objectives; (1) to assess the current transport situation of Nairobi; (2) to review green transport solutions being undertaken in the city; (3) to give an overview of alternative green transportation solutions, and (4) to provide a green transportation framework matrix. This preliminary study will utilize primary and secondary data through mainly desktop research and analysis, literature, books, magazines and on-line information. This forms the basis for formulation of approaches for incorporation into the green transportation framework matrix of the main study report.The main goal is the achievement of a practical green transportation system for implementation by the City County of Nairobi to reduce carbon emissions and congestion and promote environmental sustainability.

Keywords: cities, transport, Nairobi, green technologies

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Authors: Kamila Troper, Pedro Mestre, Maria Lurdes Menano, Joana Mendonça, Maria João Costa, Sandra Demel

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Introduction: Visual impairment is a problem that has an influence on hundreds of thousands of people all over the world. Although it is possible for a Visually Impaired person to do most jobs, the right training, technological assistance, and emotional support are essential. Ergonomics be able to solve many of the problems/issues with the relative ease of positioning, lighting and design of the workplace. A little forethought can make a tremendous difference to the ease with which a person with an impairment function. Objectives: Review the main ergonomic adaptation measures reported in the literature in order to promote better working conditions and safety measures for the visually impaired. Methodology: This was an exploratory-descriptive, qualitative literature systematic review study. The main databases used were: PubMed, BIREME, LILACS, with articles and studies published between 2000 and 2021. Results: Based on the principles of the theoretical references of ergonomic analysis of work, the main restructuring of the physical space of the workstations were: Accessibility facilities and assistive technologies; A screen reader that captures information from a computer and sends it in real-time to a speech synthesizer or Braille terminal; Installations of software with voice recognition, Monitors with enlarged screens; Magnification software; Adequate lighting, magnifying lenses in addition to recommendations regarding signage and clearance of the places where the visually impaired pass through. Conclusions: Employability rates for people with visual impairments(both those who are blind and those who have low vision)are low and continue to be a concern to the world and for researchers as a topic of international interest. Although numerous authors have identified barriers to employment and proposed strategies to remediate or circumvent those barriers, people with visual impairments continue to experience high rates of unemployment.

Keywords: ergonomic adaptations, visual impairments, ergonomic analysis of work, systematic review

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Authors: Laura Florez

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The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Shazia Anwer

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The current TV Talk Shows, especially on domestic politics in Pakistan are following the Aristotelian techniques, including deductive reasoning, three modes of persuasion, and guidelines for communication. The application of “Approximate Truth is also seen when Talk Show presenters create doubts against political personalities or national issues. Mainstream media of Pakistan, being a key carrier of narrative construction for the sake of the primary function of national consensus on regional and extended public diplomacy, is failing the purpose. This paper has highlighted the Aristotelian communication methodology, its purposes and its limitations for a serious discussion, and its connection to the mistrust among the Pakistani population regarding fake or embedded, funded Information. Data has been collected from 3 Pakistani TV Talk Shows and their analysis has been made by applying the Aristotelian communication method to highlight the core issues. Paper has also elaborated that current media education is impaired in providing transparent techniques to train the future journalist for a meaningful, thought-provoking discussion. For this reason, this paper has given an overview of HEC’s (Higher Education Commission) graduate-level Mass Com Syllabus for Pakistani Universities. The idea of ethos, logos, and pathos are the main components of TV Talk Shows and as a result, the educated audience is lacking trust in the mainstream media, which eventually generating feelings of distrust and betrayal in the society because productions look like the genre of Drama instead of facts and analysis thus the line between Current Affairs shows and Infotainment has become blurred. In the last section, practical implication to improve meaningfulness and transparency in the TV Talk shows has been suggested by replacing the Aristotelian communication method with the cognitive semiotic communication approach.

Keywords: Aristotelian techniques of communication, current affairs talk shows, drama, Pakistan

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Authors: Chukwu Fidelis Ndubuisi, Madufor Michael Ozims, Asogwa Vivian Ndidiamaka, Egenamba Juliet Ngozi, Okonkwo Stephen C., Kamah Chukwudi David

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Deflection of the vertical is a quantity used in reducing geodetic measurements related to geoidal networks to the ellipsoidal plane; and it is essential in Geoid modeling processes. Computing the deflection of the vertical component of a point in a given area is necessary in evaluating the standard errors along north-south and east-west direction. Using combined approach for the determination of deflection of the vertical component provides improved result but labor intensive without appropriate method. Least square method is a method that makes use of redundant observation in modeling a given sets of problem that obeys certain geometric condition. This research work is aimed to computing the deflection of vertical component of Owerri West local government area of Imo State using geometric method as field technique. In this method combination of Global Positioning System on static mode and precise leveling observation were utilized in determination of geodetic coordinate of points established within the study area by GPS observation and the orthometric heights through precise leveling. By least square using Matlab programme; the estimated deflections of vertical component parameters for the common station were -0.0286 and -0.0001 arc seconds for the north-south and east-west components respectively. The associated standard errors of the processed vectors of the network were computed. The computed standard errors of the North-south and East-west components were 5.5911e-005 and 1.4965e-004 arc seconds, respectively. Therefore, including the derived component of deflection of the vertical to the ellipsoidal model will yield high observational accuracy since an ellipsoidal model is not tenable due to its far observational error in the determination of high quality job. It is important to include the determined deflection of the vertical component for Owerri West Local Government in Imo State, Nigeria.

Keywords: deflection of vertical, ellipsoidal height, least square, orthometric height

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Authors: Atnafu Ashenef Wondim

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In today’s highly competitive business environment, employees are considered a source of competitive advantage. Researchers have looked into job autonomy's effect on organizational commitment and declared superior organizational performance strongly depends on the effort and commitment of employees. The purpose of this study was to explore the relationship between job autonomy and organizational commitment from newcomer’s point of view. The mediation role of employee engagement (physical, emotional, and cognitive) was also examined in the case of Ethiopian Commercial Banks. An exploratory survey research design with mixed-method approach that included partial least squares structural equation modeling and Fuzzy-Set Qualitative Comparative Analysis technique were using to address the sample size of 348 new employees. In-depth interviews with purposive and convenientsampling techniques are conducted with new employees (n=43). The results confirmed that job autonomy had positive, significant direct effects on physical engagement, emotional engagement, and cognitive engagement (path coeffs. = 0.874, 0.931, and 0.893).The results showed thatthe employee engagement driver, physical engagement, had a positive significant influence on affective commitment (path coeff. = 0.187) and normative commitment (path coeff. = 0.512) but no significant effect on continuance commitment. Employee engagement partially mediates the relationship between job autonomy and organizational commitment, which means supporting the indirect effects of job autonomy on affective, continuance, and normative commitment through physical engagement. The findings of this study add new perspectives by positioning it within a complex organizational African setting and by expanding the job autonomy and organizational commitment literature, which will benefit future research. Much of the literature on job autonomy and organizational commitment has been conducted within a well-established organizational business context in Western developed countries.The findings lead to fresh information on job autonomy and organizational commitment implementation enablers that can assist in the formulation of a better policy/strategy to efficiently adopt job autonomy and organizational commitment.

Keywords: employee engagement, job autonomy, organizational commitment, social exchange theory

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Authors: Manar Al-Ateeq

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The building construction industry plays a major role in the economy of the word and the state of Kuwait. This paper evaluates existing new civil site engineers, describes a new system for improvement and insures the importance of prequalifying and developing for new engineers. In order to have a strong base in engineering, educational institutes and workplaces should be responsible to continuously train engineers and update them with new methods and techniques in engineering. As to achieve that, school of engineering should constantly update computational resources to be used in the professions. A survey was prepared for graduated Engineers based on stated objectives to understand the status of graduate engineers in both the public and private sector. Interviews were made with different sectors in Kuwait, and several visits were made to different training centers within different workplaces in Kuwait to evaluate training process and try to improve it. Virtual Reality (VR) technology could be applied as a complement to three-dimensional (3D) modeling, leading to better communication whether in job training, in education or in professional practice. Techniques of 3D modeling and VR can be applied to develop the models related to the construction process. The 3D models can support rehabilitation design as it can be considered as a great tool for monitoring failure and defaults in structures; also it can support decisions based on the visual analyses of alternative solutions. Therefore, teaching computer-aided design (CAD) and VR techniques in school will help engineering students in order to prepare them to site work and also will assist them to consider these technologies as important supports in their later professional practice. This teaching technique will show how the construction works developed, allow the visual simulation of progression of each type of work and help them to know more about the necessary equipment needed for tasks and how it works on site.

Keywords: three dimensional modeling (3DM), civil engineers (CE), professional practice (PP), virtual reality (VR)

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Authors: Recep Gundogan, Turgay Dindaroglu, Hikmet Gunal, Mustafa Ulukavak, Ron Bingner

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A majority of total soil losses in agricultural areas could be attributed to ephemeral gullies caused by heavy rains in conventionally tilled fields; however, ephemeral gully erosion is often ignored in conventional soil erosion assessments. Ephemeral gullies are often easily filled from normal soil tillage operations, which makes capturing the existing ephemeral gullies in croplands difficult. This study was carried out to determine topographic features, including slope and aspect composite topographic index (CTI) and initiation points of gully channels, using images obtained from unmanned aerial vehicle (UAV) images. The study area was located in Topcu stream watershed in the eastern Mediterranean Region, where intense rainfall events occur over very short time periods. The slope varied between 0.7 and 99.5%, and the average slope was 24.7%. The UAV (multi-propeller hexacopter) was used as the carrier platform, and images were obtained with the RGB camera mounted on the UAV. The digital terrain models (DTM) of Topçu stream micro catchment produced using UAV images and manual field Global Positioning System (GPS) measurements were compared to assess the accuracy of UAV based measurements. Eighty-one gully channels were detected in the study area. The mean slope and CTI values in the micro-catchment obtained from DTMs generated using UAV images were 19.2% and 3.64, respectively, and both slope and CTI values were lower than those obtained using GPS measurements. The total length and volume of the gully channels were 868.2 m and 5.52 m³, respectively. Topographic characteristics and information on ephemeral gully channels (location of initial point, volume, and length) were estimated with high accuracy using the UAV images. The results reveal that UAV-based measuring techniques can be used in lieu of existing GPS and total station techniques by using images obtained with high-resolution UAVs.

Keywords: aspect, compound topographic index, digital terrain model, initial gully point, slope, unmanned aerial vehicle

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Authors: Hao Min Chuah, Tatsuya Yamazaki, Ryosui Iwasawa, Tatsumi Suto

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In recent years, with the advancement of digital technology, the movement to introduce so-called ICT (Information and Communication Technology), such as computer technology and network technology, to civil engineering construction sites and construction sites is accelerating. As part of this movement, attempts are being made in various situations to reproduce actual sites inside computers and use them for designing and construction planning, as well as for training inexperienced engineers. The installation of wave-dissipating blocks on coasts, etc., is a type of work that has been carried out by skilled workers based on their years of experience and is one of the tasks that is difficult for inexperienced workers to carry out on site. Wave-dissipating blocks are structures that are designed to protect coasts, beaches, and so on from erosion by reducing the energy of ocean waves. Wave-dissipating blocks usually weigh more than 1 t and are installed by being suspended by a crane, so it would be time-consuming and costly for inexperienced workers to train on-site. In this paper, therefore, a block installation simulator is developed based on Unity 3D, a game development engine. The simulator computes porosity. Porosity is defined as the ratio of the total volume of the wave breaker blocks inside the structure to the final shape of the ideal structure. Using the evaluation of porosity, the simulator can determine how well the user is able to install the blocks. The voxelization technique is used to calculate the porosity of the structure, simplifying the calculations. Other techniques, such as raycasting and box overlapping, are employed for accurate simulation. In the near future, the simulator will install an automatic block installation algorithm based on combinatorial optimization solutions and compare the user-demonstrated block installation and the appropriate installation solved by the algorithm.

Keywords: 3D simulator, porosity, user interface, voxelization, wave-dissipating blocks

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Barbara Covarrubias Venegas, Sabine Groblschegg, Bernhard Klaus, Julia Domnanovich

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Research Objectives: The roles and activities of human resource management (HRM) have changed a lot in the past years. Driven by a changing environment and therefore, new business requirements, the scope of human resource (HR) activities has widened. The extent to which these activities should focus on strategic issues to support the long-term success of a company has been discussed in science for many years. As many economies of Central and Eastern Europe (CEE) experienced a phase of transition after the socialist era and are now recovering from the 2008 global crisis it is needed to examine the current state of HR positioning. Furthermore, a trend in HR work developing from rather administrative units to being strategic partners of management can be noticed. This leads to the question of better understanding the underlying competencies which are necessary to support organisations. This topic was addressed by the international study “HR Competencies in international comparison”. The quantitative survey was conducted by the Institute for Human Resources & Organisation of FHWien University of Applied Science of WKW (A) in cooperation with partner universities in the countries Bosnia-Herzegovina, Croatia, Serbia and Slovenia. Methodology: Using the questionnaire developed by Dave Ulrich we tested whether the HR Competency model can be used for Austria, Bosnia and Herzegovina, Croatia, Serbia and Slovenia. After performing confirmatory and exploratory factor analysis for the whole data set containing all five countries we could clearly distinguish between four competencies. In a further step, our analysis focused on median and average comparisons between the HR competency dimensions. Conclusion: Our literature review, in alignment with other studies, shows a relatively rapid pace of development of HR Roles and HR Competencies in BCSS in the past decades. Comparing data from BCSS and Austria we still can notice that regards strategic orientation there is a lack in BCSS countries, thus competencies are not as developed as in Austria. This leads us to the tentative conclusion that HR has undergone a rapid change but is still in a State of Transition from being a rather administrative unit to performing the role of a strategic partner.

Keywords: comparative study, HR competencies, HRM, HR roles

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Authors: U.-B. Schaer, M. Wehr, R. Hodler

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Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

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Authors: Alicia Greenbank, Efrat Bengio

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The aim of this research was to examine the efficacy of the first course in Israel, whose objective is to train student teachers in the special education department to work cooperatively with parents of children with special needs. Studies often highlight the importance of cooperation between teachers and parents of students with special needs. Israel’s Special Education Law defines parents as complete partners, and the Ministry of Education encourages and even requires that partnership be present. Yet this partnership is difficult to achieve many kindergarten teachers, and teachers have a lot of difficulties establishing and managing a pattern of cooperation with their students’ parents. Often we see different perspectives on the child's development and needs, distrust, lack of appreciation, and communication difficulties on both sides – parents & teachers. The course describes a method of instilling the need for cooperation at an early stage of teacher training-in the teacher training program. 22 students in the special education program for early childhood education in the fourth year of learning took part in the course. The fourth-year is the experiential training year and the first time that students have worked in a school. The course consisted of 14 sessions. Seven parents of students with different disabilities participated at 6 of the sessions. The changes in the students' attitudes towards partnership and their ability to manage this partnership were carried out by examining the reports written by the students before the meetings with the parents and the reflections they wrote after each meeting with the parents and at the end of the course. Three themes emerged from the narrative analysis, corresponding to the three preconditions for joint activities with parents — Approach, Attitude, Appropriate Atmosphere, according to the Four A’s Model. The findings showed that a course combining meetings with parents of children with special needs offers many benefits for teacher training. The course raised student awareness of the question partnership, changed students’ approaches and attitudes towards the parents, stressed the importance of partnership, and provided students with tools for working with parents through the school. Based on the findings of this study, courses in this format can be applied in order to cooperate between teachers and parents, for example, parents of gifted children with special needs.

Keywords: Partnership with parents in special education, parents of children with disabilities, parents of children with special needs, parents’ involvement in special education

Procedia PDF Downloads 188

Authors: Ramiz Kuliev, Fuad Kuliev-Smirnov

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The 'Shadow Sparring' training exercise is widely used in the training of boxers and martial artists. The main disadvantage of the usual shadow sparring is that the trainer cannot fully control such training and evaluate its results. During the competition, the athlete, preparing for the upcoming fight, imagines the Shadow (upcoming opponent) in accordance with his own imagination. A ‘Smart-Shadow Sparring’ (SSS) is an innovative version of the ‘Shadow Sparring’. During SSS, the fighter will see the Shadow (virtual opponent that moves, defends, and punches) and understand when he misses the punches from the Shadow. The task of a real athlete is to spar with a virtual one, move around, punch in the direction of unprotected areas of the Shadow and dodge his punches. Moves and punches of Shadow are set up before each training. The system will give the coach full information about virtual sparring: (i) how many and what type of punches has the fighter landed, (ii) accuracy of these punches, (iii) how many and what type of virtual punches (punches of Smart-Shadow) has the fighter missed, etc. SSS will be recorded as animated fighting of two fighters and will help the coach to analyze past training. SSS can be configured to fit the physical and technical characteristics of the next real opponent (size, techniques, speed, missed and landed punches, etc.). This will allow to simulate and rehearse the upcoming fight and improve readiness for the next opponent. For amateur fighters, SSS will be reconfigured several times during a tournament, when the real opponent becomes known. SSS can be used in three versions: (1) Digital Shadow: the athlete will see a Shadow on a monitor (2) VR-Shadow: the athlete will see a Shadow in a VR-glasses (3) Smart Shadow: a Shadow will be controlled by artificial intelligence. These technologies are based on the ‘semi-real simulation’ method. The technology allows coaches to train athletes remotely. Simulation of different opponents will help the athletes better prepare for competition. Repeat rehearsals of the upcoming fight will help improve results. SSS can improve results in Boxing, Taekwondo, Karate, and Fencing. 41 sets of medals will be awarded in these sports at the 2020 Olympic Games.

Keywords: boxing, combat sports, fight simulation, shadow sparring

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Authors: Akram Rasheed

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Background: Simulation in the health care field has been increasingly used over the last years in the training of resuscitation and life support practices. It has shown the advantage of improving the decision-making and technical skills through deliberate practice and return demonstration. Local Problem: This article reports on the integration of simulation-based training (SBT) in the training program about proper team dynamics and leadership skills during cardiopulmonary resuscitation (CPR) in the intensive care unit (ICU). Method and Intervention: Training of 180 critical care nurses was conducted using SBT between 1st January and 30th 2020. We had conducted 15 workshops, with the integration of SBT using high fidelity manikins and using demonstration and return-demonstration approach to train the nursing staff about proper team dynamics and leadership skills during CPR. Results: After completing the SBT session, all 180 nurses completed the evaluation form. The majority of evaluation items were rated over 95% for the effectiveness of the education; four items were less than 95% (88–94%). Lower rated items considered training and practice time, improved competency, and commitment to apply to learn. The team dynamics SBT was evaluated as an effective means to improve team dynamics and leadership skills during CPR in the intensive care unit (ICU). Conclusion: The use of simulation-based training to improve team dynamics and leadership skills is an effective method for better patient management during CPR. Besides skills competency, closed-loop communication, clear messages, clear roles, and assignments, knowing one’s limitations, knowledge sharing, constructive interventions, re-evaluating and summarizing, and mutual respect are all important concepts that should be considered during team dynamics training. However, participants reported the need for a repeated practice opportunity to build competency.

Keywords: cardiopulmonary resuscitation, high fidelity manikins, simulation-based training, team dynamics

Procedia PDF Downloads 142

Authors: Giulio Nisoli, Jonas Brüngger, Karin Hostettler, Nicole Stoller, Katrin Fischer

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Technical operators in the railway domain are experts responsible for the supervisory control of the railway power grid as well as of the railway tunnels. The technical systems used to master these demanding tasks are constantly increasing in their degree of automation. It becomes therefore difficult for technical operators to maintain the control over the technical systems and the processes of their job. In particular, the operators must have the necessary experience and knowledge in dealing with a malfunction situation or unexpected event. For this reason, it is of growing importance that the skills relevant for the execution of the job are maintained and further developed beyond the basic training they receive, where they are educated in respect of technical knowledge and the work with guidelines. Training methods aimed at improving the cognitive skills needed by technical operators are still missing and must be developed. Goals of the present study were to identify which are the relevant cognitive skills of technical operators in the railway domain and to define which topics should be addressed by the training of these skills. Observational interviews were conducted in order to identify the main tasks and the organization of the work of technical operators as well as the technical systems used for the execution of their job. Based on this analysis, the most demanding tasks of technical operators could be identified and described. The cognitive skills involved in the execution of these tasks are those, which need to be trained. In order to identify and analyze these cognitive skills a cognitive task analysis (CTA) was developed. CTA specifically aims at identifying the cognitive skills that employees implement when performing their own tasks. The identified cognitive skills of technical operators were summarized and grouped in training topics. For every training topic, specific goals were defined. The goals regard the three main categories; knowledge, skills and attitude to be trained in every training topic. Based on the results of this study, it is possible to develop specific training methods to train the relevant cognitive skills of the technical operators.

Keywords: cognitive skills, cognitive task analysis, technical operators in the railway domain, training topics

Procedia PDF Downloads 153

Authors: Christopher Meyer, Laima Gerlitz

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European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

Procedia PDF Downloads 79

Authors: Christophe Spaas, Lies Pottel, Joke De Ceulaer, Johan Abeloos, Philippe Lamoral, Tom De Backer, Calix De Clercq

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We aimed to evaluate the accuracy of an in-house developed low-cost computer-assisted surgery (CAS) protocol for osseous free flap mandibular reconstruction. All patients who underwent primary or secondary mandibular reconstruction with a free (solely or composite) osseous flap, either a fibula free flap or iliac crest free flap, between January 2014 and December 2017 were evaluated. The low-cost protocol consisted out of a virtual surgical planning, a prebend custom reconstruction plate and an individualized free flap positioning guide. The accuracy of the protocol was evaluated through comparison of the postoperative outcome with the 3D virtual planning, based on measurement of the following parameters: intercondylar distance, mandibular angle (axial and sagittal), inner angular distance, anterior-posterior distance, length of the fibular/iliac crest segments and osteotomy angles. A statistical analysis of the obtained values was done. Virtual 3D surgical planning and cutting guide design were performed with Proplan CMF® software (Materialise, Leuven, Belgium) and IPS Gate (KLS Martin, Tuttlingen, Germany). Segmentation of the DICOM data as well as outcome analysis were done with BrainLab iPlan® Software (Brainlab AG, Feldkirchen, Germany). A cost analysis of the protocol was done. Twenty-two patients (11 fibula /11 iliac crest) were included and analyzed. Based on voxel-based registration on the cranial base, 3D virtual planning landmark parameters did not significantly differ from those measured on the actual treatment outcome (p-values >0.05). A cost evaluation of the in-house developed CAS protocol revealed a 1750 euro cost reduction in comparison with a standard CAS protocol with a patient-specific reconstruction plate. Our results indicate that an accurate transfer of the planning with our in-house developed low-cost CAS protocol is feasible at a significant lower cost.

Keywords: CAD/CAM, computer-assisted surgery, low-cost, mandibular reconstruction

Procedia PDF Downloads 140

Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 96

Authors: Sadam Elayah, Yang Li, Bing Shi

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Background: The impact of relaxing incisions on maxillofacial growth during palatoplasty remains a topic of debate, and further research is needed to understand its effects fully. Thus, the current study is the first long-term study that aimed to assess the maxillofacial growth of patients with isolated cleft palate following the Sommerlad-Furlow modified (S.F) technique and to estimate the impact of relaxing incisions on maxillofacial growth following S.F technique in patients with isolated cleft palate. Methods: A total of 85 participants, 55 patients with non-syndromic isolated soft and hard cleft palate underwent primary palatoplasty with our technique (30 patients received the Sommerlad-Furlow modified technique without relaxing incision (S.F+RI group), and 25 received Sommerlad-Furlow modified technique without relaxing (S.F-RI group) with no significant difference found between them regarding the cleft type, cleft width, and age at repair. While the other 30 were normal participants with skeletal class I pattern (C group). The control group was matched with the study group in number, age, and sex. All the study variables were measured using stable landmarks, including 12 linear and 10 angular variants. Results: The mean ages at collection of cephalograms were 6.03±0.80 in the S.F+RI group, 5.96±0.76 in the S.F-RI group, and 5.91±0.87 in the C group. Regarding cranial base, the results showed no statistically significant differences between the three groups in S-N and S-N-Ba. The S.F+R.I group had a significantly shorter S-Ba than the S.F-R.I & C groups (P= 0.01). However, there was no statistically significant difference between the S.F-R.I & C groups (P=0.80). Regarding the skeletal maxilla, there was no significant difference between the S.F+R.I and S.F-R.I groups in all linear measurements (N-ANS, S- PM & SN-PP ) except Co-A, the S.F+R.I group had significantly shorter Co-A than the S.F-R.I & C groups (P= <0.01). While the angular measurement, S.F+R.I group had significantly less SNA angle than the S.F-R.I & C groups (P= <0.01). Regarding mandibular bone, there were no statistically significant differences in all linear and angular mandibular measurements between the S.F+R.I and S.F-R.I groups. Regarding intermaxillary relation, the S.F+R.I group had significant differences in Co-Gn - Co-A and ANB compared to the S.F-R.I & C groups (P= <0.01). There was no statistically significant difference in PP-MP among the three groups. Conclusion: As a preliminary report, the Sommerlad-Furlow modified technique without relaxing incisions was found to have good maxillary positioning in the face and a satisfactory intermaxillary relationship compared to the Sommerlad-Furlow modified technique with relaxing incisions.

Keywords: relaxing incisions, cleft palate, palatoplasty, maxillofacial growth

Procedia PDF Downloads 110

Authors: Rachel Koshy, Nazrila Hairizan Bt. Nasir, Samsiah Bt. Awang, Kamaliah Bt. Mohamad Noh

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Malaysia collaborated as a ‘trailblazer’ country with PHCPI (Primary Health Care Performance Initiative) to populate the Primary Health Care (PHC) Vital Signs Profile (VSP) for the country. The PHC VSP provides an innovative snapshot of the primary health care system's performance. Four domains were assessed: system financing, system capacity, system performance, and system equity, and completed in 2019. There were two phases using a mixed method study design. The first phase involved a quantitative study, utilising existing secondary data from national and international sources. In the case of unavailability of data for any indicators, comparable alternative indicators were used. The second phase was a mixed quantitative-qualitative approach to measure the functional capacity based on governance and leadership, population health needs, inputs, population health management, and facility organisation and management. PHC spending constituted 35% of overall health spending in Malaysia, with a per capita PHC spending of $152. The capacity domain was strong in the three subdomains of governance and leadership, information system, and funds management. The two subdomains of drugs & supplies and facility organisation & management had low scores, but the lowest score was in empanelment of the population under the population health management. The PHC system performed with an access index of 98%, quality index of 84%, and service coverage of 62%. In the equity domain, there was little fluctuation in the coverage of reproductive, maternal, newborn, and child health services by mother’s level of education and under-five child mortality between urban and rural areas. The public sector was stronger in the capacity domain as compared to the private sector. This is due to the different financing, organisational structures, and service delivery mechanism. The VSP has identified areas for improvement in the effort to provide high-quality PHC for the population. The gaps in PHC can be addressed through the system approach and the positioning of public and private primary health care delivery systems.

Keywords: primary health care, health system, system domains, vital signs profile

Procedia PDF Downloads 129

Authors: José Álvarez Pérez, Ramón García Cedeño, Gerardo Fajardo-San Miguel, Jorge H. Chávez Gómez, Franco A. Carpio Santamaría, Milena Mesa Lavista

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The uniaxial compressive strength and modulus of elasticity in hollow concrete block masonry (HCBM) represent key mechanical properties for structural design considerations. These properties are obtained through experimental tests conducted on prisms or wallettes and depend on various factors, with the HCB contributing significantly to overall strength. One influential factor in the compressive behaviour of masonry is the thickness and method of mortar placement. Mexican regulations stipulate mortar placement over the entire net area (full-shell) for strength computation based on the gross area. However, in professional practice, there's a growing trend to place mortar solely on the lateral faces. Conversely, the United States of America standard dictates mortar placement and computation over the net area of HCB. The Canadian standard specifies mortar placement solely on the lateral face (Face-Shell-Bedding), where computation necessitates the use of the effective load area, corresponding to the mortar's placement area. This research aims to evaluate the influence of different mortar placement methods on the axial compression behaviour of HCBM. To achieve this, an experimental campaign was conducted, including: (1) 10 HCB specimens with mortar on the entire net area, (2) 10 HCB specimens with mortar placed on the lateral faces, (3) 10 prisms of 2-course HCB under axial compression with mortar in full-shell, (4) 10 prisms of 2-course HCB under axial compression with mortar in face-shell-bedding, (5) 10 prisms of 3-course HCB under axial compression with mortar in full-shell, (6) 10 prisms of 3-course HCB under axial compression with mortar in face-shell-bedding, (7) 10 prisms of 4-course HCB under axial compression with mortar in full-shell, and, (8) 10 prisms of 4-course HCB under axial compression with mortar in face-shell-bedding. A combination of sulphur and fly ash in a 2:1 ratio was used for the capping material, meeting the average compressive strength requirement of over 35 MPa as per NMX-C-036 standards. Additionally, a mortar with a strength of over 17 MPa was utilized for the prisms. The results indicate that prisms with mortar placed over the full-shell exhibit higher strength compared to those with mortar over the face-shell-bedding. However, the elastic modulus was lower for prisms with mortar placement over the full-shell compared to face-shell bedding.

Keywords: masonry, hollow concrete blocks, mortar placement, prisms tests

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Authors: Kishor T. Zingre, Seshadhri Srinivasan

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Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

Procedia PDF Downloads 114