Search results for: train schedule

Authors: Murat Erkoc, Kadir Ertogral

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Maintenance, repair and overhauling (MRO) of high cost equipment used in many industries such as transportation, military and construction are typically subject to regulations set by local governments or international agencies. Aircrafts are prime examples for this kind of equipment. Such equipment must be overhauled at certain intervals for continuing permission of use. As such, the overhaul must be completed by strict deadlines, which often times cannot be exceeded. Due to the fact that the overhaul is typically a long process, MRO companies carry so called rotable inventory for exchange of expensive modules in the overhaul process of the equipment so that the equipment continue its services with minimal interruption. The extracted module is overhauled and returned back to the inventory for future exchange, hence the name rotable inventory. However, since the rotable inventory and overhaul capacity are limited, it may be necessary to carry out some of the exchanges earlier than their deadlines in order to produce a feasible overhaul schedule. An early exchange results with a decrease in the equipment’s cycle time in between overhauls and as such, is not desired by the equipment operators. This study introduces an integer programming model for the optimal overhaul and exchange scheduling. We assume that there is certain number of rotables at hand at the beginning of the planning horizon for a single type module and there are multiple demands with known deadlines for the exchange of the modules. We consider an MRO system with identical parallel processing lines. The model minimizes total earliness by generating optimal overhaul start times for rotables on parallel processing lines and exchange timetables for orders. We develop a fast exact solution algorithm for the model. The algorithm employs full-delay scheduling approach with backward allocation and can easily be used for overhaul scheduling problems in various MRO settings with modular rotable items. The proposed procedure is demonstrated by a case study from the aerospace industry.

Keywords: rotable inventory, full-delay scheduling, maintenance, overhaul, total earliness

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Authors: Yue Huang, Hongcheng Gan

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The new urbanization pattern has led to a rapid growth in demand for short-distance intercity travel, and the emergence of new travel modes has also increased the variety of intercity travel options. In previous studies on intercity travel mode choice behavior, the impact of functional amenities of travel mode and travelers’ long-term personality characteristics has rarely been considered, and empirical results have typically been calibrated using revealed preference (RP) or stated preference (SP) data. This study designed a questionnaire that combines the RP and SP experiment from the perspective of a trip chain combining inner-city and intercity mobility, with consideration for the actual condition of the Huainan-Hefei traffic corridor. On the basis of RP/SP fusion data, a hybrid choice model considering both random taste heterogeneity and psychological characteristics was established to investigate travelers’ mode choice behavior for traditional train, high-speed rail, intercity bus, private car, and intercity online car-hailing. The findings show that intercity time and cost exert the greatest influence on mode choice, with significant heterogeneity across the population. Although inner-city cost does not demonstrate a significant influence, inner-city time plays an important role. Service attributes of travel mode, such as catering and hygiene services, as well as free wireless network supply, only play a minor role in mode selection. Finally, our study demonstrates that safety-seeking tendency, hedonism, and introversion all have differential and significant effects on intercity travel mode choice.

Keywords: intercity travel mode choice, stated preference survey, hybrid choice model, RP/SP fusion data, psychological latent variable, heterogeneity

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Anjaly Joseph, Elezebeth Mathews

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Transportation and urban planning is the least recognised area for physical activity promotion in India, unlike developed regions. Identifying the preferred transportation modalities and factors associated with it is essential to address these lacunae. The objective of the study was to assess the prevalence of modes of transportation to work, and its correlates among working adults in Ernakulam District, Kerala. A cross sectional study was conducted among 350 working individuals in the age group of 18-60 years, selected through multi-staged stratified random sampling in Ernakulam district of Kerala. The inclusion criteria were working individuals 18-60 years, workplace at a distance of more than 1 km from the home and who worked five or more days a week. Pregnant women/women on maternity leave and drivers (taxi drivers, autorickshaw drivers, and lorry drivers) were excluded. An interview schedule was used to capture the modes of transportation namely, public, private and active transportation, socio demographic details, travel behaviour, anthropometric measurements and health status. Nearly two-thirds (64 percent) of them used private transportation to work, while active commuters were only 6.6 percent. The correlates identified for active commuting compared to other modes were low socio-economic status (OR=0.22, CI=0.5-0.85) and presence of a driving license (OR=4.95, CI= 1.59-15.45). The correlates identified for public transportation compared to private transportation were female gender (OR= 17.79, CI= 6.26-50.31), low income (OR=0.33, CI= 0.11-0.93), being unmarried (OR=5.19, CI=1.46-8.37), presence of no or only one private vehicle in the house (OR=4.23, CI=1.24-20.54) and presence of convenient public transportation facility to workplace (OR=3.97, CI= 1.66-9.47). The association between body mass index (BMI) and public transportation were explored and found that public transport users had lesser BMI than private commuters (OR=2.30, CI=1.23-4.29). Policies that encourage active and public transportation needs to be introduced such as discouraging private vehicle through taxes, introduction of convenient and safe public transportation facility, walking/cycling paths, and paid parking facility.

Keywords: active transportation, correlates, India, public transportation, transportation modes

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Authors: Bhavishya Ramchandani

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A little electronic device that is worn on the finger is called a smart ring. It incorporates mobile technology and has features that make it simple to use the device. These gadgets, which resemble conventional rings and are usually made to fit on the finger, are outfitted with features including access management, gesture control, mobile payment processing, and activity tracking. A poor sleep pattern, an irregular schedule, and bad eating habits are all part of the problems with health that a lot of people today are facing. Diets lacking fruits, vegetables, legumes, nuts, and whole grains are common. Individuals in India also experience metabolic issues. In the medical field, smart rings will help patients with problems relating to stomach illnesses and the incapacity to consume meals that are tailored to their bodies' needs. The smart ring tracks all bodily functions, including blood sugar and glucose levels, and presents the information instantly. Based on this data, the ring generates what the body will find to be perfect insights and a workable site layout. In addition, we conducted focus groups and individual interviews as part of our core approach and discussed the difficulties they're having maintaining the right diet, as well as whether or not the smart ring will be beneficial to them. However, everyone was very enthusiastic about and supportive of the concept of using smart rings in healthcare, and they believed that these rings may assist them in maintaining their health and having a well-balanced diet plan. This response came from the primary data, and also working on the Emerging Technology Canvas Analysis of smart rings in healthcare has led to a significant improvement in our understanding of the technology's application in the medical field. It is believed that there will be a growing demand for smart health care as people become more conscious of their health. The majority of individuals will finally utilize this ring after three to four years when demand for it will have increased. Their daily lives will be significantly impacted by it.

Keywords: smart ring, healthcare, electronic wearable, emerging technology

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Authors: Jonathan A. Akinwale, Ibukun J. Agotola

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There is a need to rethink how technology is being disseminated to end users in order to ensure wide adoption and utilisation. Aflasafe bio-control was developed to combat aflatoxin in maize to ensure food safety for the end users. This study was designed to assess how the pull mechanism is enhancing the utilisation of this proven technology among maize farmers in Oyo State, Nigeria. The study determines the awareness of farmers on Aflasafe, sources of purchase of Aflasafe, incentives towards the usage of Aflasafe, constraints to farmers’ utilisation and factors influencing farmers’ utilisation of Aflasafe bio-control measures. Respondents were selected using a multi-stage sampling procedure. Data were collected from respondents through interview schedule and analyzed using descriptive statistics (means, frequencies, and percentages) and inferential statistics (Pearson Product Moment Correlation and regression analysis). The result showed that 89% of the farmers indicated implementers as the outlet for the purchase of Aflasafe. Also, premium payment and provision of technical assistance were the highly ranked incentives to the utilisation of Aflasafe among the farmers. The study also revealed that the major constraints face by respondents were low access to credit facility, inadequate sources of purchase, and lack of storage facilities. A little above half (54%) of the farmers were found to have fully utilized Aflasafe in maize production. Pearson Product Moment Correlation (PPMC) analysis revealed that there was a significant correlation between incentives and utilisation of Aflasafe (r-value=0.274; p ≤ 0.01). The result of the regression analysis indicated maize production experience (β=0.572), output (β=0.531), years of formal education (β=0.404) and household size (β=0.391) as the leading factors influencing farmers utilisation of Aflasafe bio-control in maize production. The study, therefore, recommends that governments and non-governmental organisations should be interested in making Aflasafe available to the maize farmers either through loan provision or price subsidy.

Keywords: Aflasafe bio-control, maize production, production incentives, pull mechanism, utilisation

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Authors: Iwuchukwu J. C., Ekeh G. Madukwe, M. C., Asadu A. N.

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Melon has significant importance of easy to plant, early maturing, low nutrient requirement and high yielding. Yet many melon farmers in the study area are either diversifying or abandoning this enterprise probably because of lack of agricultural knowledge/information and consequent reduction in output and income. The study was therefore carried out to asses effects of agricultural information on income of melon farmers in Enugu-Ezike Agricultural zone of Enugu state, Nigeria. Three blocks, nine circles and ninety melon farmers who were purposively selected constituted the sample for the study..Data were collected with interview schedule. Percentage and chart were used to present some of the data while some were analysed with mean score and correlation. The findings reveal that. average annual income of these respondents from melon was about seven thousand and five hundred Naira (approximately forty five Dollars). while their total average monthly income (income from melon and other sources) was about one thousand and two hundred Naira (approximately seven Dollars). About 42.% and 62% of the respondents in their respective order did not receive information on agricultural matters and melon production. Among the minority that received information on melon production, most of them sourced it from neighbours/friends/relatives. Majority of the respondents needed information on how to plant melon through interpersonal contact (face to face) using Igbo language as medium of communication and extension agent as teacher or resource person. The study also reveal a significant and positive relationship between number of times respondents received information on agriculture and their total monthly income. There was also a strong, positive and significant relationship between number of times respondents received information on melon and their annual income on melon production. The study therefore recommends that governmental and non-governmental organizations/ institutions should strengthen these farmers access to information on agriculture and melon specifically so as to boost their output and income.

Keywords: farmers, income, information, melon

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Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

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Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

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Authors: Gloria Chen

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When offering conventional level-appropriate ESL classes for adults is not feasible, a multilevel adult ESL class can be formed to benefit those who need to learn English for daily function. This paper examines the rationale, the process, the contents, and the outcomes of a multilevel ESL class for adults. The action research discusses a variety of assessments, lesson plans, teaching strategies that facilitate lifelong language learning. In small towns where adult ESL learners are only a handful, often advanced students and inexperienced students have to be placed in one class. Such class might not be viewed as desirable, but with on-going assessments, careful lesson plans, and purposeful strategies, a multilevel ESL class for adults can overcome the obstacles and help learners to reach a higher level of English proficiency. This research explores some hand-on strategies, such as group rotating, cooperative learning, and modifying textbook contents for practical purpose, and evaluate their effectiveness. The data collected in this research include Needs Assessment (beginning of class term), Mid-term Self-Assessment (5 months into class term), End-of-term Student Reflection (10 months into class), and End-of-term Assessment from the Instructor (10 months into class). A descriptive analysis of the data explains the practice of this particular learning community, and reveal the areas for improvement and enrichment. This research answers the following questions: (1) How do the assessments positively help both learners and instructors? (2) How do the learning strategies prepare students to become independent, life-long English learners? (3) How do materials, grouping, and class schedule enhance the learning? The result of the research contributes to the field of teaching and learning in language, not limited in English, by (a) examining strategies of conducting a multilevel adult class, (b) involving adult language learners with various backgrounds and learning styles for reflection and feedback, and (c) improving teaching and learning strategies upon research methods and results. One unique feature of this research is how students can work together with the instructor to form a learning community, seeking and exploring resources available to them, to become lifelong language learners.

Keywords: adult language learning, assessment, multilevel, teaching strategies

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Authors: Kanu Priya Mohan

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Innovation in education is one of the essential pathways to achieve both educational, and development goals in today’s dynamically changing world. Over the last decade, coaching and mentoring have been applied in the field of education as positive intervention techniques for fostering teaching and learning reforms in the developed countries. The context of this research was Thailand’s educational reform process, wherein a project on coaching and mentoring (C&M) was launched in 2014. The C&M project endeavored to support the professional development of the school teachers in the various provinces of Thailand, and to also enable them to apply C&M for teaching innovative instructional techniques. This research aimed to empirically investigate the learning outcomes for the master trainers, who trained for coaching and mentoring as the first step in the process to train the school teachers. A mixed method study was used for evaluating the learning outcomes of training in terms of cognitive- behavioral-affective dimensions. In the first part of the research a quantitative research design was incorporated to evaluate the effects of learner characteristics and instructional techniques, on the learning outcomes. In the second phase, a qualitative method of in-depth interviews was used to find details about the training outcomes, as well as the perceived barriers and enablers of the training process. Sample size constraints were there, yet these exploratory results, integrated from both methods indicated the significance of evaluating training outcomes from the three dimensions, and the perceived role of other factors in the training. Findings are discussed in terms of their implications for the training of C&M, and also their impact in fostering positive education through innovative educational techniques in the developing countries.

Keywords: cognitive-behavioral-affective learning outcomes, mixed method research, teachers in Thailand, training evaluation

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Authors: Li Hui, Riyadh Hindi

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In the United States, bridge construction often employs overhang brackets to support the deck overhang, the weight of fresh concrete, and loads from construction equipment. This approach, however, can lead to significant torsional moments on the exterior girders, potentially causing excessive girder rotation. Such rotations can result in various safety and maintenance issues, including thinning of the deck, reduced concrete cover, and cracking during service. Traditionally, these issues are addressed by installing temporary lateral bracing systems and conducting comprehensive torsional analysis through detailed finite element analysis for the construction of bridge deck overhang. However, this process is often intricate and time-intensive, with the spacing between temporary lateral bracing systems usually relying on the field engineers’ expertise. In this study, a deep neural network model is introduced to limit exterior girder rotation during bridge deck construction. The model predicts the optimal spacing between temporary bracing systems. To train this model, over 10,000 finite element models were generated in SAP2000, incorporating varying parameters such as girder dimensions, span length, and types and spacing of lateral bracing systems. The findings demonstrate that the deep neural network provides an effective and efficient alternative for limiting the exterior girder rotation for bridge deck construction. By reducing dependence on extensive finite element analyses, this approach stands out as a significant advancement in improving safety and maintenance effectiveness in the construction of bridge decks.

Keywords: bridge deck construction, exterior girder rotation, deep learning, finite element analysis

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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: Sedigheh Abbasnasab Sardareh

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The current study investigates ESL teachers' voices in order to formulate further research on the effectiveness of the SBOA practices. It is an attempt to find out (1) what are ESL experienced teachers’ perceptions, experiences, attitudes, and beliefs of SBOA; (2) what teaching and learning aspects of SBOA needs focus to enhance its effectiveness; (3) external issues related to the implementation of SBOA; (4) internal issues related to the implementation of SBOA; and also (5) perceived recommendations on SBOA. The study utilized focus group discussion sessions. 9 experienced ESL (5 females and 4 males) teachers were selected based on the consent letters sent to them. These teachers had over 20 years experience in both traditional and SBOA-type assessment and the train-the-trainer experts recommended by the Ministry of Education. Respondents were guided with open-ended questions to extracts their perceived experiences implementing SBOA guided structurally by the author as the moderator. Data were first discussed with the respondents for further clarifications and then only analyzed and re-confirmed with some recommendations before the final presentation of this preliminary results were presented here. The focus group discussions yielded some important perceived views on the SBOA implementation. Some of the themes were discussed and some recommendations were proposed for further in-depth study by the Ministry of Education. Some of the future directions based on the results were also put forward. Some external and internal variables were important in order for successful implementation of SBOA. Mere implementing a policy should be taken into consideration because this might impede some of the teaching and learning processes both by the classroom stakeholders such as teachers and student. More research methods such as the use of questionnaires could be utilized to further investigate to large populations of teacher educators in Malaysia.

Keywords: school based oral assessment, Malaysia, ESL, focus group discussion

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Authors: Molla Tadesse Lakew

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This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

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Authors: Batool Ismaeel, Umair Farooq, Saad Mushtaq

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Construction projects in the oil industry can be very complex, having unknown outcomes and uncertainties that cannot be easily predicted. Each project has its unique risks generated by a number of factors which, if not controlled, will impact the successful completion of the project mainly in terms of schedule, cost, quality, and safety. This paper highlights the historic risks associated with projects in the south and east region of Kuwait Oil Company (KOC) collated from the company’s lessons learned database. Starting from Contract Award through to handover of the project to the Asset owner, the gaps in project execution in terms of managing risk will be brought to discussion and where a well-defined systematic approach in project risk management reflecting many claims, change of scope, exceeding budget, delays in engineering phase as well as in the procurement and fabrication of long lead items should be adopted. This study focuses on a proposed feasible approach in risk management for engineering, procurement and construction (EPC) level projects including the various stakeholders involved in executing the works from International to local contractors and vendors in KOC. The proposed approach covers the areas categorized into organizational, design, procurement, construction, pre-commissioning, commissioning and project management in which the risks are identified and require management and mitigation. With the effective deployment and implementation of the proposed risk management system and the consideration of it as a vital key in achieving the project’s target, the outcomes will be more predictable in the future, and the risk triggers will be managed and controlled. The correct resources can be allocated on a timely basis for the company for avoiding any unpredictable outcomes during the execution of the project. It is recommended in this paper to apply this risk management approach as an integral part of project management and investigate further in the future, the effectiveness of this proposed system for newly awarded projects and compare the same with those projects of similar budget/complexity that have not applied this approach to risk management.

Keywords: construction, project completion, risk management, uncertainties

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Authors: Nadilla Saskia, Octoria Nur, Assegaf Zareeva

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Mass transport infrastructures are essential to enhance the connectivity between regions and regional equity in Indonesia. Indonesia’s capital city, Jakarta, ranked the 10th highest congestion rate in the world based on the 2019 traffic index, contributing to air pollution and energy consumption. Other than that, the World Air Quality Report in 2019 depicted Jakarta’s air pollutant concentration at 49.4 mg, the 5th highest in the world. Issues of severe traffic congestion, lack of sufficient urban infrastructure in Jakarta, and greenhouse gas emissions have to be addressed through mass transportation. Indonesia’s government is currently constructing The Greater Jakarta LRT (Light Rapid Transit) as convenient, efficient, and environmentally friendly transportation connecting Jakarta with Bekasi and Cibubur areas and plans to serve the passengers in August 2023. Greater Jakarta LRT is operated with Grade of Automation (GoA) No.3, Driverless Train Operation (DTO). Hence, the automated technology used in rail infrastructure is anticipated to address these issues with greater results. The paper will be validated and establish the extent to which the automation system would increase energy efficiency, help reduce carbon emissions, and benefit the environment. Based on the calculated CO2 emissions and fuel consumption for the existing condition (2015) during the feasibility study of the LRT Project and the predicted condition in 2030, it is obtained that Greater Jakarta LRT with GoA3 operation will reduce the CO2 emissions and fuel consumption by more than 50% in 2030. In the bigger picture, Greater Jakarta LRT supports the government's goal of achieving Jakarta Net-Zero Emissions (NZE) 2050.

Keywords: LRT, Grade of Automation (GoA), energy efficiency, carbon emissions, railway infrastructure, DKI Jakarta

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Authors: Olorunsanya E. O., Adedeji S. O., Anyanwu A. A.

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Food insecurity is a challenge to many nations Nigeria inclusive. It is increasingly becoming a major problem among farm households due to many factors chief of which is low labour productivity. This study therefore profiles the food security status of a representative randomly selected 90 farming households in Chanchaga area of Nigeria’s Guinea Savana using structured interview schedule Descriptive and inferential statistics were used as analytical tools for the study. The results of the descriptive statistics show that majority (35.56%) of the surveyed household heads fall within the age range of 40 – 49 years and (88.89%) are male while (78.89) are married. More than half of the respondents have formal education. About 43.3% of the household heads have farm experience of 11- 20 years and a modal household size class range of 7 – 12. The results further reveal that majority (68.8%) earned more than N12, 500 (22.73 US Dollar) per month. The result of households’ food expenditure pattern reveals that an average household spends about N3, 644.44 (6.63 US Dollar) on food and food items on a weekly basis. The result of the analysis of food diversity intake in the study area shows that 63.33% of the sampled households fell under the low household food diversity intake, while 33 households, representing 36.67% ranks high in term of household food diversity intake. The result for the food security status shows that the sampled population was food secure (58.89%) while 41.11% falls below the recommended threshold. The result for the logistics regression model shows that age, engagement in off farm employment and household size are significant in determining the food security status of farm household in the study area. The three variables were significant at 10%, 5% and 1% respectively. The study therefore recommends among others, that measures be put in place by stakeholders to make agriculture attractive for youth since age is a significant determinant of food security in the study area. Awareness should also be created by stakeholders on the needs for effective family planning methods to be adopted by farm household in the study area.

Keywords: Niger State, Guinea Savana, food diversity, logit regression model and food security

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Authors: Atiwit Sinyoo, Sekh Thanprasertsuk, Sithiporn Agthong, Pasakorn Watanatada, Shaun Peter Qureshi, Saknan Bongsebandhu-Phubhakdi

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Background: Since the SARS-CoV-2 virus became extensively disseminated throughout the world, online learning has become one of the most hotly debated topics in educational reform. While some studies have already shown the advantage of online learning, there are still questions concerning how online learning affects students’ learning behavior and academic achievement when each student learns in a different way. Hence, we aimed to develop a guide for preclinical medical students to avoid drawbacks and get benefits from online learning that possibly a double-edged sword. Methods: We used a multiple-choice questionnaire to evaluate the learning behavior of second-year Thai medical students in the neuroscience course. All traditional face-to-face lecture classes were video-recorded and promptly posted to the online learning platform throughout this course. Students could pick and choose whatever classes they wanted to attend, and they may use online learning as often as they wished. Academic performance was evaluated as summative score, spot exam score and pre-post-test improvement. Results: More frequently students used online learning platform, the less they attended lecture classes (P = 0.035). High proactive online learners (High PO) who were irregular attendee (IrA) had significantly lower summative scores (P = 0.026), spot exam score (P = 0.012) and pre-post-test improvement (P = 0.036). In the meanwhile, conditional attendees (CoA) who only attended classes with attendance check had significantly higher summative score (P = 0.025) and spot exam score (P = 0.001) if they were in the High PO group. Conclusions: The benefit and drawbacks edges of using an online learning platform were demonstrated in our research. Based on this double-edged sword effect, we believe that online learning is a valuable learning strategy, but students must carefully plan their study schedule to gain the “benefit edge” meanwhile avoiding its “drawback edge”.

Keywords: academic performance, assessment, attendance, online learning, preclinical medical students

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Maria Rodriguez-Gazquez, Sara Chaparro-Hernandez, Jose Rafael Gonzalez-Lopez

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Introduction: Nurses are models in healthy behaviors for their patients. This is why it is important for these professionals to not only have a good knowledge of healthy behaviors but also practice. Today’s nursing students will be tomorrow’s professionals and to fulfill their role in caring they not only need knowledge, they also must maintain behaviors which enable them to improve and protect both the health of others and their own. This is why the university is a unique environment of opportunities to foster the maximum potential of health. To care for others we first have to take care of ourselves. It is important for these behaviors in Nursing students to be evaluated during the years of their university education in order to design timely interventions which improve the health behaviors of the future professionals. Aim: The objective of this study was to evaluate the lifestyles of first year nursing students of two Universities. Methodology: Cross-sectional study. In 2014, 140 first year Nursing students of two Universities Seville –US- (Spain -Europe, n=37) and Antioquia –UA- (Colombia -South America, n=93) self-reported the FANTASTIC Lifestyle checklist. Results: Findings reveal that (I) UA students doubled the percentage of dangerous or bad lifestyles with respect to the US students, (II) the lifestyles are not appropriate in 1 of 3 of nursing students in both Universities, (II) there are statistically significant differences for family support items (higher in US), positive thinkers (higher in UA), the use of safety belts and alcohol consumption before driving (higher in US). Discussion: The nursing students are mostly young people who are at a stage in which some of the most important behaviors for adult life can still be molded. It is necessary to develop educational interventions in their Nursing curricula to strengthen healthy behaviours during training. Nursing Schools not only have the duty to train professionals, but to also be agents that foster the health, welfare and quality of those who study and work there. It must encourage knowledge and skills oriented to healthy lifestyles.

Keywords: cross-sectional studies, life style, nursing students, questionnaires

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Authors: Rasheed Owolabi Oloyede, Joseph Olusegun Adelusi, Seun Oluwadare

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Sleep has been found to have many recuperative and restorative beneficial effects on athletic recovery. When a person is deprived of sleep this can have many effects on their immune and endocrine systems. Both of these systems are extremely important for the recovery process of any athlete and when we deprive ourselves of sleep, we are depriving ourselves of recovery. This study examined how sleep deprivation can hinder sport performance among selected athletes representing Adeyemi College of Education at Nigeria Colleges of Education Games (NICEGA) competitions at Minna. A total of 32 athletes were sampled for the study. They were exposed to two different activities. Each activity was performed before and after sleep deprivation, the activities were 100m dash, shuttle relay. The athletes were randomly assigned to two groups that are experimental and control groups. Pretest were conducted on both groups before apply treatment to the other group. A day before the activities to be performed the control group was denied of sleep between 10p.m to 5a.m for a period of 6 weeks. The analysis of the data showed that athletes performance in the two selected activities performed on equal basis before the sleep deprivation. After sleep deprivation the performance of experimental group was a little better than the control group that were denied of sleep. It was concluded that sleep allows the body to spend less energy resources on body processes needed while awake, it was concluded that sleep deprivation enables the body system work effectively. The body can expend needed energy, balance and adequate reaction time if it is allowed to have enough rest. Lack of adequate sleep results to dullness of the brain, nervousness and anxiety which all have negative effect on performance of activities by athletes. Based on the findings, it was recommended that extend nightly sleep for several week to reduce your sleep debt before competition. Maintain a low sleep debt by obtaining a sufficient amount of nightly sleep (seven to eight hours for adults, nine or more hours for teens and young adults). Keep a regular sleep-wake schedule, going to bed and waking up at the same times every day.

Keywords: activities, deprivation, performance, sleep

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Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

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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: Chia-Ying Lin

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This paper explains how to enhance doctor-patient communication and nurse-patient communication through multiple intelligence signing methods and user-centered. It is hoped that through the implementation of the "electronic consent", the problems faced by the paper consent can be solved: storage methods, resource utilization, convenience, correctness of information, integrated management, statistical analysis and other related issues. Make better use and allocation of resources to provide better medical quality. First, invite the ｍedical records department to assist in the inventory of paper consent in the hospital: organising, classifying, merging, coding, and setting. Second, plan the electronic consent configuration file: set the form number, consent form group, fields and templates, and the corresponding doctor's order code. Next, Summarize four types of rapid methods of electronic consent: according to the doctor's order, according to the medical behavior, according to the schedule, and manually generate the consent form. Finally, system promotion and adjustment: form an "electronic consent promotion team" to improve, follow five major processes: planning, development, testing, release, and feedback, and invite clinical units to raise the difficulties faced in the promotion, and make improvements to the problems. The electronic signature rate of the whole hospital will increase from 4% in January 2022 to 79% in November 2022. Use the saved resources more effectively, including: reduce paper usage (reduce carbon footprint), reduce the cost of ink cartridges, re-plan and use the space for paper medical records, and save human resources to provide better services. Through the introduction of information technology and technology, the main spirit of "lean management" is implemented. Transforming and reengineering the process to eliminate unnecessary waste is also the highest purpose of this project.

Keywords: smart signature, electronic consent, electronic medical records, user-centered, doctor-patient communication, nurse-patient communication

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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: Zeynep Yazicioglu

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Project development is a complex process where many stakeholders work together. Employers and main contractors are the base stakeholders, whereas designers, engineers, sub-contractors, suppliers, supervisors, and consultants are other stakeholders. A combination of the complexity of the building process with a large number of stakeholders often leads to time and cost overruns and irregular resource utilization. Failure to comply with the work schedule and inefficient use of resources in the construction processes indicate that it is necessary to accelerate production and increase productivity. The development of computer software called Building Information Modeling, abbreviated as BIM, is a major technological breakthrough in this area. The use of BIM enables architectural, structural, mechanical, and electrical projects to be drawn in coordination. BIM is a tool that should be considered by every stakeholder with the opportunities it offers, such as minimizing construction errors, reducing construction time, forecasting, and determination of the final construction cost. It is a process spreading over the years, enabling all stakeholders associated with the project and construction to use it. The main goal of this paper is to explore the problems associated with the adoption of BIM in multi-stakeholder projects. The paper is a conceptual study, summarizing the author’s practical experience with design offices and construction firms working with BIM. In the transition period to BIM, three of the challenges will be examined in this paper: 1. The compatibility of supplier companies with BIM, 2. The need for two-dimensional drawings, 3. Contractual issues related to BIM. The paper reviews the literature on BIM usage and reviews the challenges in the transition stage to BIM. Even on an international scale, the supplier that can work in harmony with BIM is not very common, which means that BIM's transition is continuing. In parallel, employers, local approval authorities, and material suppliers still need a 2-D drawing. In the BIM environment, different stakeholders can work on the same project simultaneously, giving rise to design ownership issues. Practical applications and problems encountered are also discussed, providing a number of suggestions for the future.

Keywords: BIM opportunities, collaboration, contract issues about BIM, stakeholders of project

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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: 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

Procedia PDF Downloads 117

Authors: Xuewei Li, Jingfeng Yuan, Jianliang Zhou

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The 21st century has been called the century of human exploitation of underground space. Due to the characteristics of large quantity, tight schedule, low safety reserve and high uncertainty of deep foundation pit engineering, accidents frequently occur in deep foundation pit engineering, causing huge economic losses and casualties. With the successful application of information technology in the construction industry, building information modeling has become a research hotspot in the field of architectural engineering. Therefore, the application of building information modeling (BIM) and other information communication technologies (ICTs) in construction safety management is of great significance to improve the level of safety management. This research summed up the mechanism of the deep foundation pit engineering accident through the fault tree analysis to find the control factors of deep foundation pit engineering safety management, the deficiency existing in the traditional deep foundation pit construction site safety management. According to the accident cause mechanism and the specific process of deep foundation pit construction, the hazard information of deep foundation pit engineering construction site was identified, and the hazard list was obtained, including early warning information. After that, the system framework was constructed by analyzing the early warning information demand and early warning function demand of the safety management system of deep foundation pit. Finally, the safety management system of deep foundation pit construction site based on BIM through combing the database and Web-BIM technology was developed, so as to realize the three functions of real-time positioning of construction site personnel, automatic warning of entering a dangerous area, real-time monitoring of deep foundation pit structure deformation and automatic warning. This study can initially improve the current situation of safety management in the construction site of deep foundation pit. Additionally, the active control before the occurrence of deep foundation pit accidents and the whole process dynamic control in the construction process can be realized so as to prevent and control the occurrence of safety accidents in the construction of deep foundation pit engineering.

Keywords: Web-BIM, safety management, deep foundation pit, construction

Procedia PDF Downloads 129

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

Procedia PDF Downloads 112