Search results for: supervised decision tree
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4989

Search results for: supervised decision tree

3399 The Missing Link in Holistic Health Care: Value-Based Medicine in Entrustable Professional Activities for Doctor-Patient Relationship

Authors: Ling-Lang Huang

Abstract:

Background: The holistic health care should ideally cover physical, mental, spiritual, and social aspects of a patient. With very constrained time in current clinical practice system, medical decisions often tip the balance in favor of evidence-based medicine (EBM) in comparison to patient's personal values. Even in the era of competence-based medical education (CBME), when scrutinizing the items of entrustable professional activities (EPAs), we found that EPAs of establishing doctor-patient relationship remained incomplete or even missing. This phenomenon prompted us to raise this project aiming at advocating value-based medicine (VBM), which emphasizes the importance of patient’s values in medical decisions. A true and effective doctor-patient communication and relationship should be a well-balanced harmony of EBM and VBM. By constructing VBM into current EPAs, we can further promote genuine shared decision making (SDM) and fix the missing link in holistic health care. Methods: In this project, we are going to find out EPA elements crucial for establishing an ideal doctor-patient relationship through three distinct pairs of doctor-patient relationships: patients with pulmonary arterial hypertension (relatively young but with grave disease), patients undergoing surgery (facing critical medical decisions), and patients with terminal diseases (facing forthcoming death). We’ll search for important EPA elements through the following steps: 1. Narrative approach to delineate patients’ values among 2. distinct groups. 3.Hermeneutics-based interview: semi-structured interview will be conducted for both patients and physicians, followed by qualitative analysis of collected information by compiling, disassembling, reassembling, interpreting, and concluding. 4. Preliminarily construct those VBM elements into EPAs for doctor-patient relationships in 3 groups. Expected Outcomes: The results of this project are going to give us invaluable information regarding the impact of patients’ values, while facing different medical situations, on the final medical decision. The competence of well-blending and -balanced both values from patients and evidence from clinical sciences is the missing link in holistic health care and should be established in future EPAs to enhance an effective SDM.

Keywords: value-based medicine, shared decision making, entrustable professional activities, holistic health care

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3398 Predicting the Compressive Strength of Geopolymer Concrete Using Machine Learning Algorithms: Impact of Chemical Composition and Curing Conditions

Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

Abstract:

Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

Procedia PDF Downloads 88
3397 Joint Optimal Pricing and Lot-Sizing Decisions for an Advance Sales System under Stochastic Conditions

Authors: Maryam Ghoreishi, Christian Larsen

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In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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3396 Wireless Sensor Anomaly Detection Using Soft Computing

Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

Abstract:

We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

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3395 Development of an Intelligent Decision Support System for Smart Viticulture

Authors: C. M. Balaceanu, G. Suciu, C. S. Bosoc, O. Orza, C. Fernandez, Z. Viniczay

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The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.

Keywords: blockchain, IoT, smart agriculture, vineyard

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3394 Systematic Examination of Methods Supporting the Social Innovation Process

Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

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Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: factors of social innovation, methodological combination, social innovation process, supporting decision-making

Procedia PDF Downloads 155
3393 How to Perform Proper Indexing?

Authors: Watheq Mansour, Waleed Bin Owais, Mohammad Basheer Kotit, Khaled Khan

Abstract:

Efficient query processing is one of the utmost requisites in any business environment to satisfy consumer needs. This paper investigates the various types of indexing models, viz. primary, secondary, and multi-level. The investigation is done under the ambit of various types of queries to which each indexing model performs with efficacy. This study also discusses the inherent advantages and disadvantages of each indexing model and how indexing models can be chosen based on a particular environment. This paper also draws parallels between various indexing models and provides recommendations that would help a Database administrator to zero-in on a particular indexing model attributed to the needs and requirements of the production environment. In addition, to satisfy industry and consumer needs attributed to the colossal data generation nowadays, this study has proposed two novel indexing techniques that can be used to index highly unstructured and structured Big Data with efficacy. The study also briefly discusses some best practices that the industry should follow in order to choose an indexing model that is apposite to their prerequisites and requirements.

Keywords: indexing, hashing, latent semantic indexing, B-tree

Procedia PDF Downloads 156
3392 Factors that Predict Pre-Service Teachers' Decision to Integrate E-Learning: A Structural Equation Modeling (SEM) Approach

Authors: Mohd Khairezan Rahmat

Abstract:

Since the impetus of becoming a develop country by the year 2020, the Malaysian government have been proactive in strengthening the integration of ICT into the national educational system. Teacher-education programs have the responsibility to prepare the nation future teachers by instilling in them the desire, confidence, and ability to fully utilized the potential of ICT into their instruction process. In an effort to fulfill this responsibility, teacher-education program are beginning to create alternatives means for preparing cutting-edge teachers. One of the alternatives is the student’s learning portal. In line with this mission, this study investigates the Faculty of Education, University Teknologi MARA (UiTM) pre-service teachers’ perception of usefulness, attitude, and ability toward the usage of the university learning portal, known as iLearn. The study also aimed to predict factors that might hinder the pre-service teachers’ decision to used iLearn as their platform in learning. The Structural Equation Modeling (SEM), was employed in analyzed the survey data. The suggested findings informed that pre-service teacher’s successful integration of the iLearn was highly influenced by their perception of usefulness of the system. The findings also suggested that the more familiar the pre-service teacher with the iLearn, the more possibility they will use the system. In light of similar study, the present findings hope to highlight the important to understand the user’s perception toward any proposed technology.

Keywords: e-learning, prediction factors, pre-service teacher, structural equation modeling (SEM)

Procedia PDF Downloads 339
3391 Human Gesture Recognition for Real-Time Control of Humanoid Robot

Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

Abstract:

There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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3390 Row Detection and Graph-Based Localization in Tree Nurseries Using a 3D LiDAR

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

Abstract:

Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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3389 Automatic Adult Age Estimation Using Deep Learning of the ResNeXt Model Based on CT Reconstruction Images of the Costal Cartilage

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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3388 Dynamic Analysis of the Heat Transfer in the Magnetically Assisted Reactor

Authors: Tomasz Borowski, Dawid Sołoducha, Rafał Rakoczy, Marian Kordas

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The application of magnetic field is essential for a wide range of technologies or processes (i.e., magnetic hyperthermia, bioprocessing). From the practical point of view, bioprocess control is often limited to the regulation of temperature at constant values favourable to microbial growth. The main aim of this study is to determine the effect of various types of electromagnetic fields (i.e., static or alternating) on the heat transfer in a self-designed magnetically assisted reactor. The experimental set-up is equipped with a measuring instrument which controlled the temperature of the liquid inside the container and supervised the real-time acquisition of all the experimental data coming from the sensors. Temperature signals are also sampled from generator of magnetic field. The obtained temperature profiles were mathematically described and analyzed. The parameters characterizing the response to a step input of a first-order dynamic system were obtained and discussed. For example, the higher values of the time constant means slow signal (in this case, temperature) increase. After the period equal to about five-time constants, the sample temperature nearly reached the asymptotic value. This dynamical analysis allowed us to understand the heating effect under the action of various types of electromagnetic fields. Moreover, the proposed mathematical description can be used to compare the influence of different types of magnetic fields on heat transfer operations.

Keywords: heat transfer, magnetically assisted reactor, dynamical analysis, transient function

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3387 Decision-making in the provision of Accessible Veterinary Care

Authors: Ellen Bryant, Virginia Behmer, Rebecca Garbed, Jeanette O’Quin, Dana Howard

Abstract:

As it currently stands, veterinary care in the United States is not accessible to everyone, and veterinarians regularly face cases of clients who are unable to provide necessary care to their animals regardless of the client’s desire to do so. There is currently limited research into how veterinarians address these issues of access to care. It is apparent that veterinarians regularly utilize funding or offer discounted services to treat cases that otherwise would go without care. With need currently exceeding the amount of funds and services available, veterinarians are tasked with deciding which cases are most deserving of assistance. This mixed methods study distributed a survey to companion animal veterinarians practicing in the United States to identify current trends in how these professionals apply principles of distributive justice in the scope of veterinary medicine. Ethical frameworks identified in human bioethics research into distributive justice were presented, along with demographic questions, to identify relationships between veterinarian priorities and the scope of their practice/respective roles/geographic region. By surveying veterinarians across a wide range of specialties, practice types, and clientele this study was able to assess how priorities and opinions shift based on external factors as well as among the respondents themselves. Participants were asked not only to choose how to distribute aid between different clients and case scenarios, but also asked directly which is the best way to distribute aid when need exceeds the resources available.

Keywords: access to veterinary care, bioethics, decision-making, distributive justice, subsidized care

Procedia PDF Downloads 65
3386 Sign Language Recognition of Static Gestures Using Kinect™ and Convolutional Neural Networks

Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

Abstract:

This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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3385 Cloudburst-Triggered Natural Hazards in Uttarakhand Himalaya: Mechanism, Prevention, and Mitigation

Authors: Vishwambhar Prasad Sati

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This article examines cloudburst-triggered natural hazards mainly flashfloods and landslides in the Uttarakhand Himalaya. It further describes mechanism and implications of natural hazards and illustrates the preventive and mitigation measures. We conducted this study through collection of archival data, case study of cloudburst hit areas, and rapid field visit of the affected regions. In the second week of August 2017, about 50 people died and huge losses to property were noticed due to cloudburst-triggered flashfloods. Our study shows that although cloudburst triggered hazards in the Uttarakhand Himalaya are natural phenomena and unavoidable yet, disasters can be minimized if preventive measures are taken up appropriately. We suggested that construction of human settlements, institutions and infrastructural facilities along the seasonal streams and the perennial rivers should be avoided to prevent disasters. Further, large-scale tree plantation on the degraded land will reduce the magnitude of hazards.

Keywords: cloudburst, flash floods, landslides, fragile landscape

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3384 A Multi-Objective Gate Assignment Model Based on Airport Terminal Configuration

Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Assigning aircrafts’ activities to appropriate gates is one the most challenging issues in airport authorities’ multiple criteria decision making. The potential financial loss due to imbalances of demand and supply in congested airports, higher occupation rates of gates, and the existing restrictions to expand facilities provide further evidence for the need for an optimal supply allocation. Passengers walking distance, towing movements, extra fuel consumption (as a result of awaiting longer to taxi when taxi conflicts happen at the apron area), etc. are the major traditional components involved in GAP models. In particular, the total cost associated with gate assignment problem highly depends on the airport terminal layout. The study herein presents a well-elaborated literature review on the topic focusing on major concerns, applicable variables and objectives, as well as proposing a three-objective mathematical model for the gate assignment problem. The model has been tested under different concourse layouts in order to check its performance in different scenarios. Results revealed that terminal layout pattern is a significant parameter in airport and that the proposed model is capable of dealing with key constraints and objectives, which supports its practical usability for future decision making tools. Potential solution techniques were also suggested in this study for future works.

Keywords: airport management, terminal layout, gate assignment problem, mathematical modeling

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3383 The Evaluation of Event Sport Tourism on Regional Economic Development

Authors: Huei-Wen Lin, Huei-Fu Lu

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Event sport tourism (EST) has become an especially important economic sector around the world. As the magnitude continues to grow, attracting more tourists, media, and investment for the host community, and many local areas/regions and states have identified the expenditures by visitors as a potential source of economic or employment growth. The main purposes of this study are to investigate stakeholders’ insights into the feature of hosting EST and using them as a regional development strategy. Continuing the focus of previous literature on the regional development and economic benefits by hosting EST, a total of fıve semi-structured interview questions are designed and a thematic analysis is employed to conduct with eight key sport and tourism decision makers in Atlanta during July to August 2016. Through the depth interviews, the study will contribute to a better understanding of stakeholders’ decision-making, identifying benefits and constraints as well as leveraging the impacts of hosting EST. These findings have provided stakeholders’ perspectives of hosting EST and using them as a reference of regional development in emerging sport tourism markets in the US. Additionally, this study examines key considerations and issues that affect and are critical to reliable understanding of the economic impacts of hosting EST on the regional development, and it will be able to benefit future management authorities (i.e. governments and communities) in their sport tourism development endeavors in defining and hosting successful EST. Furthermore, the insights gained from the qualitative analysis could help other cities/regions analyzing the economic impacts of hosting EST and using it as an instrument of city development strategy.

Keywords: economic impacts, event sport tourism, regional economic development, longitudinal analysis

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3382 Carbon Stock of the Moist Afromontane Forest in Gesha and Sayilem Districts in Kaffa Zone: An Implication for Climate Change Mitigation

Authors: Admassu Addi, Sebesebe Demissew, Teshome Soromessa, Zemede Asfaw

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This study measures the carbon stock of the Moist Afromontane Gesha-Sayilem forest found in Gesha and Sayilem District in southwest Ethiopia. A stratified sampling method was used to identify the number of sampling point through the Global Positioning System. A total of 90 plots having nested plots to collect tree species and soil data were demarcated. The results revealed that the total carbon stock of the forest was 362.4 t/ha whereas the above ground carbon stock was 174.95t/ha, below ground litter, herbs, soil, and dead woods were 34.3,1.27, 0.68, 128 and 23.2 t/ha (up to 30 cm depth) respectively. The Gesha- Sayilem Forest is a reservoir of high carbon and thus acts as a great sink of the atmospheric carbon. Thus conservation of the forest through introduction REDD+ activities is considered an appropriate action for mitigating climate change.

Keywords: carbon sequestration, carbon stock, climate change, allometric, Ethiopia

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3381 Modeling Activity Pattern Using XGBoost for Mining Smart Card Data

Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

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3380 Projections of Climate Change in the Rain Regime of the Ibicui River Basin

Authors: Claudineia Brazil, Elison Eduardo Bierhals, Francisco Pereira, José Leandro Néris, Matheus Rippel, Luciane Salvi

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The global concern about climate change has been increasing, since the emission of gases from human activities contributes to the greenhouse effect in the atmosphere, indicating significant impacts to the planet in the coming years. The study of precipitation regime is fundamental for the development of research in several areas. Among them are hydrology, agriculture, and electric sector. Using the climatic projections of the models belonging to the CMIP5, the main objective of the paper was to present an analysis of the impacts of climate change without rainfall in the Uruguay River basin. After an analysis of the results, it can be observed that for the future climate, there is a tendency, in relation to the present climate, for larger numbers of dry events, mainly in the winter months, changing the pluviometric regime for wet summers and drier winters. Given this projected framework, it is important to note the importance of adequate management of the existing water sources in the river basin, since the value of rainfall is reduced for the next years, it may compromise the dynamics of the ecosystems in the region. Facing climate change is fundamental issue for regions and cities all around the world. Society must improve its resilience to phenomenon impacts, and spreading the knowledge among decision makers and citizens is also essential. So, these research results can be subsidies for the decision-making in planning and management of mitigation measures and/or adaptation in south Brazil.

Keywords: climate change, hydrological potential, precipitation, mitigation

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3379 Use of Dendrochronology in Estimation of Creep Velocity and Its Dependence on the Bulk Density of Soils

Authors: Mohammad Amjad Sabir, Ishtiaq Khan, Shahid Ali, Umar Shabbir, Aneel Ahmad

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Creep, being the main silt contributor to the rivers, is a slow, downhill flow of soils. The creep velocity is measured in millimeters to a couple of centimeters per year and is determined with the help of tilt caused by creep in the vertical objects and needs at least ten years to get a reliable creep velocity. This project was devised to calculate creep velocity using dendrochronology and looking for the difference of creep velocity registered by different trees on the same slope. It was concluded that dendrochronology provides a very reliable procedure of creep velocity estimation if ‘J’ shaped trees are studied for their horizontal movement and age. The age of these trees was measured using tree coring, and the horizontal movement was measured with a conventional tape. Using this procedure it does not require decades and additionally the data reveals the creep velocity for up to 150 years and even more instead of just a decade. It was also concluded that the creep velocity does not only depend on bulk density of soil hence no pronounced effect of bulk density was detected.

Keywords: creep velocity, Galiyat, Pakistan, dendrochronology, Nagri Bala

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3378 Behavioral Analysis of Anomalies in Intertemporal Choices Through the Concept of Impatience and Customized Strategies for Four Behavioral Investor Profiles With an Application of the Analytic Hierarchy Process: A Case Study

Authors: Roberta Martino, Viviana Ventre

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The Discounted Utility Model is the essential reference for calculating the utility of intertemporal prospects. According to this model, the value assigned to an outcome is the smaller the greater the distance between the moment in which the choice is made and the instant in which the outcome is perceived. This diminution determines the intertemporal preferences of the individual, the psychological significance of which is encapsulated in the discount rate. The classic model provides a discount rate of linear or exponential nature, necessary for temporally consistent preferences. Empirical evidence, however, has proven that individuals apply discount rates with a hyperbolic nature generating the phenomenon of intemporal inconsistency. What this means is that individuals have difficulty managing their money and future. Behavioral finance, which analyzes the investor's attitude through cognitive psychology, has made it possible to understand that beyond individual financial competence, there are factors that condition choices because they alter the decision-making process: behavioral bias. Since such cognitive biases are inevitable, to improve the quality of choices, research has focused on a personalized approach to strategies that combines behavioral finance with personality theory. From the considerations, it emerges the need to find a procedure to construct the personalized strategies that consider the personal characteristics of the client, such as age or gender, and his personality. The work is developed in three parts. The first part discusses and investigates the weight of the degree of impatience and impatience decrease in the anomalies of the discounted utility model. Specifically, the degree of decrease in impatience quantifies the impact that emotional factors generated by haste and financial market agitation have on decision making. The second part considers the relationship between decision making and personality theory. Specifically, four behavioral categories associated with four categories of behavioral investors are considered. This association allows us to interpret intertemporal choice as a combination of bias and temperament. The third part of the paper presents a method for constructing personalized strategies using Analytic Hierarchy Process. Briefly: the first level of the analytic hierarchy process considers the goal of the strategic plan; the second level considers the four temperaments; the third level compares the temperaments with the anomalies of the discounted utility model; and the fourth level contains the different possible alternatives to be selected. The weights of the hierarchy between level 2 and level 3 are constructed considering the degrees of decrease in impatience derived for each temperament with an experimental phase. The results obtained confirm the relationship between temperaments and anomalies through the degree of decrease in impatience and highlight that the actual impact of emotions in decision making. Moreover, it proposes an original and useful way to improve financial advice. Inclusion of additional levels in the Analytic Hierarchy Process can further improve strategic personalization.

Keywords: analytic hierarchy process, behavioral finance anomalies, intertemporal choice, personalized strategies

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3377 Lunch Hour Concerts as a Strategy for Strengthening Student Performance Skills: University of Port Harcourt Experience

Authors: Rita A. Sunday-Kanu

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This article reports on an evaluation of lunch hour concert and its effectiveness in improving undergraduate performance ability. In particular, it examines the aptitude of students in classroom applied music and their reaction/responses to true life concert situations. It further investigated factors affecting students’ confidence during performances, the relationship between stage fright and confidence building in regular concert participation. The Department of Music, University of Port Harcourt runs monthly lunch our concerts which are coordinated by undergraduates for the university community. Forty music students who have participated in or coordinated lunch hour concerts were chosen for this survey. Eight music lecturers who have supervised the monthly lunch hour concert were also chosen for this study. The attitude and view on the effectiveness of lunch hour concert in enhancing students’ performance skills were gotten through questionnaires survey, in-depth interview and participant observation to determine if classroom based applied music alone is as successful in grooming performance genius as the lunch hour concert. Result indicated that students’ participation in lunch hour concert did indeed broaden and strengthened their performance experiences. This observation led to a recommendation that regular community based concerts be considered as a standard for performance practices in the university curriculum since it serves as a preparatory platform for acquiring professional performance skills before graduation.

Keywords: lunch hour concert, performance, performing skill, community concert

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3376 Factors Contributing to a Career Choice Abroad Among Rwandan Students in Poland

Authors: Faucal Marie Providence Idufashe, Rafał Katamay

Abstract:

Background: Cases of foreign students who do not return to their home countries after their graduation have been reported. Over the past years, More and more young Rwandans choose to study in Poland, appreciating the high level of education in Polish universities. However, the majority of them tend to stay there after their studies or move to other nearby countries. Therefore, this study aims at identifying factors contributing to a career choice abroad among Rwandan students in Poland. Methods: This was a cross-sectional, observational, survey-based study and targeted the Rwandan community living in Poland. All the analyses were done in SPSS. A total of 219 respondents completed the online survey within two months from July to September 2022. Results: The prevalence of migration intention among Rwandan student in Poland was estimated at 79.91%. Only religion was statistically significant, whereas other social demographic factors such as age, residence, education, and marital status did not contribute to the decision of a career choice in Poland among respondents, Rwandans in Poland. Furthermore, perceived connection to co-workers, employment company's culture and respect were the significant socio-economic factors contributed to the decision of a career choice in Poland among those studied. The level of income did not contribute. Conclusion: A high proportion expressed migration intention in our study. These intentions were attracted by opportunities in Poland in addition to the welcoming culture. Going forward, we recommend exploring those factors using in-depth interviews for more insights.

Keywords: career, choice, abroad, Poland, students, Rwandan

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3375 Simons, Ehrlichs and the Case for Polycentricity – Why Growth-Enthusiasts and Growth-Sceptics Must Embrace Polycentricity

Authors: Justus Enninga

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Enthusiasts and skeptics about economic growth have not much in common in their preference for institutional arrangements that solve ecological conflicts. This paper argues that agreement between both opposing schools can be found in the Bloomington Schools’ concept of polycentricity. Growth-enthusiasts who will be referred to as Simons after the economist Julian Simon and growth-skeptics named Ehrlichs after the ecologist Paul R. Ehrlich both profit from a governance structure where many officials and decision structures are assigned limited and relatively autonomous prerogatives to determine, enforce and alter legal relationships. The paper advances this argument in four steps. First, it will provide clarification of what Simons and Ehrlichs mean when they talk about growth and what the arguments for and against growth-enhancing or degrowth policies are for them and for the other site. Secondly, the paper advances the concept of polycentricity as first introduced by Michael Polanyi and later refined to the study of governance by the Bloomington School of institutional analysis around the Nobel Prize laureate Elinor Ostrom. The Bloomington School defines polycentricity as a non-hierarchical, institutional, and cultural framework that makes possible the coexistence of multiple centers of decision making with different objectives and values, that sets the stage for an evolutionary competition between the complementary ideas and methods of those different decision centers. In the third and fourth parts, it is shown how the concept of polycentricity is of crucial importance for growth-enthusiasts and growth-skeptics alike. The shorter third part demonstrates the literature on growth-enhancing policies and argues that large parts of the literature already accept that polycentric forms of governance like markets, the rule of law and federalism are an important part of economic growth. Part four delves into the more nuanced question of how a stagnant steady-state economy or even an economy that de-grows will still find polycentric governance desirable. While the majority of degrowth proposals follow a top-down approach by requiring direct governmental control, a contrasting bottom-up approach is advanced. A decentralized, polycentric approach is desirable because it allows for the utilization of tacit information dispersed in society and an institutionalized discovery process for new solutions to the problem of ecological collective action – no matter whether you belong to the Simons or Ehrlichs in a green political economy.

Keywords: degrowth, green political theory, polycentricity, institutional robustness

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3374 Prioritizing Temporary Shelter Areas for Disaster Affected People Using Hybrid Decision Support Model

Authors: Ashish Trivedi, Amol Singh

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In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

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3373 Use of Data of the Remote Sensing for Spatiotemporal Analysis Land Use Changes in the Eastern Aurès (Algeria)

Authors: A. Bouzekri, H. Benmassaud

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Aurès region is one of the arid and semi-arid areas that have suffered climate crises and overexploitation of natural resources they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and its spatiotemporal changes in the Aurès between 1987 and 2013, for this work, we adopted a method of analysis based on the exploitation of the images satellite Landsat TM 1987 and Landsat OLI 2013, from the supervised classification likelihood coupled with field surveys of the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover maps from 1987 and 2013, one can extract a spatial map change of different land cover units. The results show that between 1987 and 2013 vegetation has suffered negative changes are the significant degradation of forests and steppe rangelands, and sandy soils and bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013 allows us to understand the extensive or regressive orientation of vegetation and soil, this map shows that dense forests give his place to clear forests and steppe vegetation develops from a degraded forest vegetation and bare, sandy soils earn big steppe surfaces that explain its remarkable extension. The analysis of remote sensing data highlights the profound changes in our environment over time and quantitative monitoring of the risk of desertification.

Keywords: remote sensing, spatiotemporal, land use, Aurès

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3372 Adopting New Knowledge and Approaches to Sustainable Urban Drainage in Saudi Arabia

Authors: Ali Alahmari

Abstract:

Urban drainage in Saudi Arabia is an increasingly challenging issue due to factors such as climate change and rapid urban expansion. The existing infrastructure, based on traditional drainage systems, is not always able to cope with the increased precipitation, sometimes leading to rainwater runoff and floods causing disturbances and damage to property. Therefore, there is a need to find new ways of managing drainage, such as Sustainable Urban Drainage Systems (SUDS). The research has highlighted the main driving forces behind the need for change, revealed by the participants, to the need to adopt new ideas and approaches for urban drainage. However, while moving towards this, certain factors that may hinder the aim of using the experiences of other countries and taking advantage of innovative solutions. The research illustrates an initial conceptual model for these factors emerging from the analysis. It identifies some of the fundamental issues affecting the resistance to change towards the adoption of the concept of sustainability in Saudi Arabia, with Riyadh city as a case study. This was by using a qualitative approach, whereby, through two phases of fieldwork during 2013 and 2014, twenty-six semi-structured interviews were conducted with a number of representative officials and professionals from key government departments and organisations related to urban drainage management. Grounded Theory approach was followed to analyse the qualitative data obtained. Resistance to change was classified to: firstly: individual inertia (e.g. familiarity with the conventional solutions and approaches, lack of awareness, and considering sustainability as a marginal matter in urban planning). This resulted in not paying the desired attention, and impact on planning and setting priorities for development. Secondly: institutionalised inertia (e.g. lack of technical and design specifications for other unconventional drainage solutions, lack of consideration by decision makers in other disciplines such as contributions from environmental and geographical studies, and routine work and bureaucracy). This contributes to the weakness of decision-making, weakness in the role of research, and a lack of human resources. It seems that attitudes towards change may have reduced the ability to move forward towards sustainable development, in addition to contributing towards difficulties in some aspects of the decision-making process. Thus, the chapter provides insights into the current situation in Saudi Arabia and contributes to understanding the decisions that are made regarding change.

Keywords: climate change, new knowledge and approaches, resistance to change, Saudi Arabia, SUDS, urban drainage, urban expansion

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3371 Phylogenetic Relationships of the Malaysian Primates Cercopithecine Based on COI Gene Sequences

Authors: B. M. Md-Zain, N. A. Rahman, M. A. B. Abdul-Latiff, W. M. R. Idris

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We conducted molecular research to portray phylogenetic relationships of Malaysian primates particularly in the genus of Macaca. We have sequenced cytochrome C oxidase subunit I (COI) of mitochondrial DNA of several individuals from M. fascicularis and M. arctoides. PCR amplifications were performed and COI DNA sequences were aligned using ClustalW. Phylogenetic trees were constructed using distance analyses by employing neighbor-joining algorithm (NJ). We managed to sequence 700 bp of COI DNA sequences. The tree topology showed that M. fascicularis did not clump based on phyleogeography division in Peninsular Malaysia. Individuals from Negeri Sembilan merged together with samples from Perak and Penang into one clade. In addition, phylogenetic analyses indicated that M. arctoides was classified into sinica group instead of fascicularis group supported by genetic distance data. COI gene is an effective locus to clarify phylogenetic position of M. arctoides but not in discriminating M. fascicularis population in Peninsular Malaysia.

Keywords: cercopithecine, long-tailed macaque, Macaca fascicularis, Macaca arctoides

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3370 A Recommender System for Job Seekers to Show up Companies Based on Their Psychometric Preferences and Company Sentiment Scores

Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

Procedia PDF Downloads 106