Search results for: intelligent transportation

Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Yu-Ping Chiu, Dung-Ying Lin

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Traditional staff scheduling methods, relying on employee experience, often lead to inefficiencies and resource waste. The challenges of transferring scheduling expertise and adapting to changing labor regulations further complicate this process. Manual approaches become increasingly impractical as companies accumulate complex scheduling rules over time. This study proposes an algorithmic optimization approach to address these issues, aiming to expedite scheduling while ensuring strict compliance with labor regulations and company policies. The method focuses on generating optimal schedules that minimize weighted company objectives within a compressed timeframe. Recognizing the limitations of conventional commercial software in modeling and solving complex real-world scheduling problems efficiently, this research employs Tabu Search with both long-term and short-term memory structures. The study will present numerical results and managerial insights to demonstrate the effectiveness of this approach in achieving intelligent and efficient staff scheduling.

Keywords: intelligent memory structures, mixed integer programming, meta-heuristics, staff scheduling problem, tabu search

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Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: Bayan Bevrani, Robert L. Burdett, Prasad K. D. V. Yarlagadda

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This article focuses upon multi-modal transportation systems (MMTS) and the issues surrounding the determination of system capacity. For that purpose a multi-objective framework is advocated that integrates all the different modes and many different competing capacity objectives. This framework is analytical in nature and facilitates a variety of capacity querying and capacity expansion planning.

Keywords: analytical model, capacity analysis, capacity query, multi-modal transportation system (MMTS)

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Authors: Mahabub Alam, Mohammad Mahmudul Hassan, M. Hasanuzzaman, M. Ahasanul Hoque

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Animals are transported from one place to another for different purposes in Bangladesh. However, the potential effect of long-distance transport on cattle health has not frequently been studied. Therefore, this study was conducted to assess health conditions of cattle transported from a long distance to Chittagong in Bangladesh. A total of 100 adult cattle, regardless of breed and sex, were selected at Benapole live cattle market in Jessore between August and September 2015 for the study. Blood samples were taken from 50 randomly selected cattle at 0 hours before transportation, just after transportation, at 12-16 hours post-conclusion of transportation, and 24 hours after transportation. The external health conditions and injuries of the cattle were assessed by close inspection, and the trader was interviewed using the structured questionnaire. Images of cattle injuries were taken with a camera. The basic internal health of the cattle was evaluated using standard hemato-biochemical tests. Animals were fasted and remained standing within a small space allocation (8-10 sq feet/animal) in the vehicle during transportation. Animals were provided only with paddy straw and water prior to selling at the destination market. The overall frequency of cattle injuries varied significantly (26% before vs. 47% after transportation; p < 0.001). The frequency of different cattle injuries also significantly varied by types such as abrasion (11% vs. 21%; p < 0.05) and barbed wire injury (9% vs. 18%; p < 0.05). Single cattle injury differed significantly (21% vs. 36%; p < 0.001). Cattle health conditions varied significantly (nasal discharge: 15% vs. 28%; p < 0.05; diarrhea: 15% vs. 23%; p < 0.05 and severe dehydration: 8% vs. 20%; p < 0.001). The values of hemoglobin (Hb), total erythrocyte count (TEC), total leukocyte count (TLC), lymphocyte (L), neutrophil (N) and eosinophil (E) varied significantly (p ≤ 0.01) (Hb: 11.1mg/dl vs. 12.3mg/dl; TEC: 4.7 million/ml vs. 5.7million/ml; TLC: 6.2 thousand/ml vs. 7.3 thousand/ml; L: 61.7% vs. 58.1%; N: 29.7% vs. 32.8%; E: 3.8% vs. 4.7%). The values of serum total protein (TP), creatine kinase (CK), triglyceride (TG), calcium (Ca), phosphorus (P) and alkaline phosphatase (ALP) significantly differed (p ≤ 0.05) (TP: 6.8g/dl vs. 8.2g/dl; CK:574.9u/l vs. 1288u/l; TG: 104.7mg/dl vs. 127.7mg/dl; Ca: 11.3mg/dl vs. 13mg/dl; P: 7.3mg/dl vs. 7.6mg/dl; ALP: 303u/l vs. 363u/l). The identified status of external and internal health conditions of the cattle for trading purpose due to long-distance transportation in the present study indicates a high degree of transport stress and poor animal welfare.

Keywords: animal welfare, cattle, external and internal health conditions, transportation

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Authors: Gabriele Borg, Alexei De Bono, Charlie Abela

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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.

Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns

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Authors: D. Tappi

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In the past decades, the idea of innovation moved from being considered the result of development to being seen as its means. Innovation and its diffusion are indeed keys to the development and economic catch-up of a country. However, the process of diffusing existing innovation in low income countries has demonstrated dependent on inadequate infrastructures and institutions. The paper examines the role of disruptive innovation in bridging the technology gap between high- and low-income countries, overcoming the lack in infrastructures and institutions. In particular, the focus of this paper goes to the role of disruptive innovation in people transportation in Nigeria. Uber, Taxify, and Smartcab are covering a small and interesting market that was underserved, between the high-end private driver markets, the personal car owners and the low-priced traditional cab and the Keke (tricycle). Indeed the small Nigerian middle class and international community have found in the sharing people transportation market a safe, reasonably priced means of transportation in Nigerian big cities. This study uses mainly qualitative data collection methods in the form of semi-structured interviews with major players and users and quantitative data analysis in the form of a survey among users in order to assess the role of these new transportation modes in shaping the market and even creating a new niche. This paper shows how the new sharing economy in people transportation is creating new solutions to old problems as well as creating new challenges for both the existing market players and institutions. By doing so, the paper shows how disruptive innovations applied to low income countries, not only can overcome the lacking infrastructure problem but could also help bridge the technology gap between those and high income countries. This contribution proves that it is indeed exactly because the market presents these obstacles that disruptive innovations can succeed in countries such as Nigeria.

Keywords: development, disruptive innovation, sharing economy, technology gap

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Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

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The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

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Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Muzaffar Ali, Burhan Ali, Juntakan Taweekun

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Globally transportation sector accounts for around 25% of energy demand and nearly 62% of oil consumed. Therefore, new energy sources are required to introduce for this huge demand replenishment of depleting conventional energy sources. Currently, biofuels such as Jatropha trees as an energy carrier for transportation sector are being utilized effectively round the globe. However, climate conditions at low altitudes with an average annual temperature above 20 degrees Celsius and rainfall of 300-1000mm are considered the most suitable environment for the efficient growth of Jatropha trees. The current study is providing a theoretical survey-based analysis to investigate the effect of rate of cultivation of jatropha trees on the reduction of fuel prices and its environmental benefits. The resulted study shows that jatropha tree’s 100 kg seeds give 80kg oil and the conversion process cost is very small as 890 PKR. Moreover, the extraction of oil from Jatropha tree is tax-free compared to other fuels. The analysis proved very essential for potential assessment of Jatropha regarding future energy fuel for transportation sector at global level. Additionally, it can be very beneficial for increment in the total amount of transportation fuel in Pakistan.

Keywords: jatropha tree, environmental impact, energy contents, theoretical survey

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: P. Vanichkobchinda

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The Logistics Transportation techniques, Open Vehicle Routing (OVR) is an approach toward transportation cost reduction, especially for long distance pickup and delivery nodes. The outstanding characteristic of OVR is that the route starting node and ending node are not necessary the same as in typical vehicle routing problems. This advantage enables the routing to flow continuously and the vehicle does not always return to its home base. This research aims to develop a heuristic for the open vehicle routing problem with pickup and delivery under time window and loading capacity constraints to minimize the total distance. The proposed heuristic is developed based on the Insertion method, which is a simple method and suitable for the rapid calculation that allows insertion of the new additional transportation requirements along the original paths. According to the heuristic analysis, cost comparisons between the proposed heuristic and companies are using method, nearest neighbor method show that the insertion heuristic. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing. The research indicates that the improvement of new transport's calculation and the open vehicle routing with "Insertion Heuristic" represent a better outcome with 34.3 percent in average. in cost savings. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing.

Keywords: business competitiveness, cost reduction, SMEs, logistics transportation, VRP

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Hideo Suzuki, Yuya Kiyonobu, Kotaro Matsushita, Masaki Hanada, Rie Suzuki, Noriko Niijima, Noriko Uosaki, Tadao Nakamura

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People often worry about their elderly family members who are living by themselves or staying alone somewhere. An intelligent watch-over system for such elderly people, using a Raspberry Pi IoT device, has been newly developed to monitor those who live or stay separately from their families and alert them if a problem occurs. The system consists of motion sensors and temperature-humidity combined sensors that are located at seven points within an elderly person's home. The intelligent algorithms of the system detect signs and the possibility of unhealthy situations arising for the elderly relative; e.g., an unusually long bathing time, or a visit to a restroom, too high a room temperature, etc., by using data cached by the sensors above, at seven points within their house. The system gives more consideration to the elderly person's privacy, by using the sensors above, instead of using cameras and microphones placed around the house. The system invented and described here, can send a Twitter direct message to designated family members when an elderly relative is possibly in an unhealthy condition. Thus the system helps decrease family members' anxieties regarding their elderly relatives and increases their sense of security.

Keywords: elderly person, IoT device, Raspberry Pi, watch-over system

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Amir Golalipour

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In recent years, resilience emerged as an important topic in transportation infrastructure practice, planning, and design to address the myriad stressors of future climate facing the Nation. Climate change has increased the frequency of extreme weather events and also causes climate and weather patterns to diverge from historic trends, culminating in circumstances where transportation infrastructure and assets are operating outside the scope of their design. To design and maintain transportation infrastructure that can continue meeting objectives over the infrastructure’s design life, these systems must be made adaptable to the changing climate by incorporating resilience wherever practically and financially feasible. This study is focused on the adaptation strategies and incorporation of resilience in infrastructure construction, maintenance, rehabilitation, and preservation processes. This study will include highlights from some of the recent FHWA activities on resilience. This study describes existing resilience planning and decision-making practices related to transportation infrastructure; mechanisms to identify, analyze, and prioritize adaptation options; and the strain that future climate and extreme weather event pressures place on existing transportation assets and the stressors these systems face for both single and combined stressor scenarios. Results of two case studies from Transportation Engineering Approaches to Climate Resiliency (TEACR) projects with focus on temperature and precipitation impacts on transportation infrastructures will be presented. These case studies looked at the impact of infrastructure performance using future temperature and precipitation compared to traditional climate design parameters. The research team used the adaptation decision making assessment and Coupled Model Intercomparison Project (CMIP) processing tool to determine which solution is best to pursue. The CMIP tool provided project climate data for temperature and precipitation which then could be incorporated into the design procedure to estimate the performance. As a result, using the future climate scenarios would impact the design. These changes were noted to have only a slight increase in costs, however it is acknowledged that network wide these costs could be significant. This study will also focus on what we have learned from recent storms, floods, and climate related events that will help us be better prepared to ensure our communities have a resilient transportation network. It should be highlighted that standardized mechanisms to incorporate resilience practices are required to encourage widespread implementation, mitigate the effects of climate stressors, and ensure the continuance of transportation systems and assets in an evolving climate.

Keywords: adaptation strategies, extreme events, resilience, transportation infrastructure

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Authors: J. Bastos, P. Marques, S. Batterman, F. Freire

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Due to demands of a growing urban population, it is crucial to manage urban development and its associated environmental impacts. While most of the environmental analyses have addressed buildings and transportation separately, both the design and location of a building affect environmental performance and focusing on one or the other can shift impacts and overlook improvement opportunities for more sustainable urban development. Recently, several life-cycle (LC) studies of residential buildings have integrated user transportation, focusing exclusively on primary energy demand and/or greenhouse gas emissions. Additionally, most papers considered only private transportation (mainly car). Although it is likely to have the largest share both in terms of use and associated impacts, exploring the variability associated with mode choice is relevant for comprehensive assessments and, eventually, for supporting decision-makers. This paper presents a life-cycle assessment (LCA) of a residential building in Lisbon (Portugal), addressing building construction, use and user transportation (commuting with private and public transportation). Five environmental indicators or categories are considered: (i) non-renewable primary energy (NRE), (ii) greenhouse gas intensity (GHG), (iii) eutrophication (EUT), (iv) acidification (ACID), and (v) ozone layer depletion (OLD). In a first stage, the analysis addresses the overall life-cycle considering the statistical model mix for commuting in the residence location. Then, a comparative analysis compares different available transportation modes to address the influence mode choice variability has on the results. The results highlight the large contribution of transportation to the overall LC results in all categories. NRE and GHG show strong correlation, as the three LC phases contribute with similar shares to both of them: building construction accounts for 6-9%, building use for 44-45%, and user transportation for 48% of the overall results. However, for other impact categories there is a large variation in the relative contribution of each phase. Transport is the most significant phase in OLD (60%); however, in EUT and ACID building use has the largest contribution to the overall LC (55% and 64%, respectively). In these categories, transportation accounts for 31-38%. A comparative analysis was also performed for four alternative transport modes for the household commuting: car, bus, motorcycle, and company/school collective transport. The car has the largest results in all impact categories. When compared to the overall LC with commuting by car, mode choice accounts for a variability of about 35% in NRE, GHG and OLD (the categories where transportation accounted for the largest share of the LC), 24% in EUT and 16% in ACID. NRE and GHG show a strong correlation because all modes have internal combustion engines. The second largest results for NRE, GHG and OLD are associated with commuting by motorcycle; however, for ACID and EUT this mode has better performance than bus and company/school transport. No single transportation mode performed best in all impact categories. Integrated assessments of buildings are needed to avoid shifts of impacts between life-cycle phases and environmental categories, and ultimately to support decision-makers.

Keywords: environmental impacts, LCA, Lisbon, transport

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Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

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With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

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Authors: Raneem O. Salem, Najwa Al-Mously, Nihal Mohamed Nabil, Abdulmohsen H. Al-Zalabani, Abeer F. Al-Dhawi, Nasser Al-Hamdan

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Objective: There are various demographic and educational factors that affect the academic performance of undergraduate medical students. The objective of this study is to identify these factors and correlate them to the GPA of the students. Methods: A cross-sectional study design utilizing grade point averages (GPAs) of two cohorts of students in both levels of the pre-clinical phase. In addition, self-administered questionnaire was used to evaluate the effect of these factors on students with poor and good cumulative GPA. Results: Among the various factors studied, gender, marital status, and the transportation used to reach the faculty significantly affected academic performance of students. Students with a cumulative GPA of 3.0 or greater significantly differed than those with a GPA of less than 3.0 being higher in female students, in married students, and type of transportation used to reach the college. Factors including age, educational factors, and type of transportation used have shown to create a significant difference in GPA between male and females. Conclusion: Factors such as age, gender, marital status, learning resources, study time, and the transportation used have been shown to significantly affect medical student GPA as a whole batch as well as when they are tested for gender.

Keywords: academic performance, educational factors, learning resources, study time, gender, socio-demographic factors

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Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Xukai Fu

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The concept of circular economy is interdisciplinary, intersecting environmental engineering, information technology, business, and social science domains. Over the course of its 15-year tenure in the sanitation industry, Jinkai has concentrated its efforts in the past five years on integrating artificial intelligence (AI) technology with street sanitation apparatus and systems. This endeavor has led to the development of various innovations, including the Intelligent Identification Sweeper Truck (Intelligent Waste Recognition and Energy-saving Control System), the Intelligent Identification Water Truck (Intelligent Flushing Control System), the intelligent food waste treatment machine, and the Intelligent City Road Sanitation Surveillance Platform. This study will commence with an examination of prevalent global challenges, elucidating how Jinkai effectively addresses each within the framework of circular economy principles. Utilizing a review and analysis of pertinent environmental management data, we will elucidate Jinkai's strategic approach. Following this, we will investigate how Jinkai utilizes the advantages of circular economy principles to guide the design of street sanitation machinery, with a focus on digitalization integration. Moreover, we will scrutinize Jinkai's sustainable practices throughout the invention and operation phases of street sanitation machinery, aligning with the triple bottom line theory. Finally, we will delve into the significance and enduring impact of corporate social responsibility (CSR) and environmental, social, and governance (ESG) initiatives. Special emphasis will be placed on Jinkai's contributions to community stakeholders, with a particular emphasis on human rights. Despite the widespread adoption of circular economy principles across various industries, achieving a harmonious equilibrium between environmental justice and social justice remains a formidable task. Jinkai acknowledges that the mere development of energy-saving technologies is insufficient for authentic circular economy implementation; rather, they serve as instrumental tools. To earnestly promote and embody circular economy principles, companies must consistently prioritize the UN Sustainable Development Goals and adapt their technologies to address the evolving exigencies of our world.

Keywords: circular economy, core principles, benefits, the tripple bottom line, CSR, ESG, social justice, human rights, Jinkai

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Ting Gao, Mingyue He

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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: Hyeon-Seung Kim, Bit-Na Cho, Tae-Woon Jeong, Soo-Young Yoon, Leen-Seok Kang

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Recently, a construction project has been large in the size and complicated in the site work. The web-cameras are used to manage the construction site of such a large construction project. They can be used for monitoring the construction schedule as compared to the actual work image of the planned work schedule. Specially, because the 4D CAD system that the construction appearance is continually simulated in a 3D CAD object by work schedule is widely applied to the construction project, the comparison system between the real image of actual work appearance by web-camera and the simulated image of planned work appearance by 3D CAD object can be an intelligent construction schedule management system (ICON). The delayed activities comparing with the planned schedule can be simulated by red color in the ICON as a virtual reality object. This study developed the ICON and it was verified in a real bridge construction project in Korea. To verify the developed system, a web-camera was installed and operated in a case project for a month. Because the angle and zooming of the web-camera can be operated by Internet, a project manager can easily monitor and assume the corrective action.

Keywords: 4D CAD, web-camera, ICON (intelligent construction schedule management system), 3D object image

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Authors: Prakash Singh

Abstract:

For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Keywords: emotional intelligence, teachers' emotions, teachers' job satisfaction, principals' emotionally intelligent behaviours

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Authors: Adedeji W. Oyediran, Yekini N. Asafe

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Mechatronics is synergistic integration of mechanical engineering, with electronics and intelligent computer control in the design and manufacturing of industrial products and processes. Automobile (auto car, motor car or car is a wheeled motor vehicle used for transporting passengers, which also carries its own engine or motor) is a mechatronic system which served as major means of transportation around the world. Virtually all community has a need for automobile. This makes automobile issues as related to diagnostic and repair interesting to all communities. Consequent to the diversification of skill in diagnosing automobile faults and approaches in solving some problems and innovation in automobile industry. It is appropriate to say that repair and diagnostic of automobile will be better enhanced if community has opportunity of sharing knowledge and idea globally. This paper discussed the desirable elements in automobile as mechatronics system and present conceptual framework of virtual community model for automobile users.

Keywords: automobile, automobile users, knowledge sharing, mechatronics system, virtual community

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Authors: Srikanth Pandurangi, Basheer Mohammed, Nezar Al Sayegh

Abstract:

In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.

Keywords: innovative methods in transportation data collection, integrated public transportation system, traffic forecasts, transportation modeling, travel behavior

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Authors: Seyed Habib A. Rahmati, Parsa Fallah Sheikhlari, Morteza Musakhani

Abstract:

This paper studies the structure of financial investment and efficiency on the subway would be created between Hashtgerd and Qazvin in Iran. Regarding ascending rate of transportation between Tehran and Qazvin which directly air pollution, it clearly implies to public transportation requirement between these two cities near Tehran. The railway transportation like subway can help each country to terminate traffic jam which has some advantages such as speed, security, non-pollution, low cost of public transport, etc. This type of transportation needs national infrastructures which require enormous investment. It couldn’t implement without leading and managing funds and investments properly. In order to response 'needs', clear norms or normative targets have to be agreed and obviously it is important to distinguish costs from investment requirements critically. Implementation phase affects investment requirements and financing needs. So recognizing barrier related to investment and the quality of investment (what technologies and services are invested in) is as important as the amounts of investment. Different investment methods have mentioned as follows loan, leasing, equity participation, Line of financing, finance, usance, bay back. Alternatives survey before initiation and analyzing of risk management is one of the most important parts in this project. Observation of similar project cities each country has the own specification to choose investment method.

Keywords: subway project, project investment, project contract, project management

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Authors: V. Reyes, P. Ferreira

Abstract:

In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

Procedia PDF Downloads 118