Search results for: decision tree model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20216

Search results for: decision tree model

18926 Construction of a Dynamic Migration Model of Extracellular Fluid in Brain for Future Integrated Control of Brain State

Authors: Tomohiko Utsuki, Kyoka Sato

Abstract:

In emergency medicine, it is recognized that brain resuscitation is very important for the reduction of mortality rate and neurological sequelae. Especially, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) are most required for stabilizing brain’s physiological state in the treatment for such as brain injury, stroke, and encephalopathy. However, the manual control of BT, ICP, and CBF frequently requires the decision and operation of medical staff, relevant to medication and the setting of therapeutic apparatus. Thus, the integration and the automation of the control of those is very effective for not only improving therapeutic effect but also reducing staff burden and medical cost. For realizing such integration and automation, a mathematical model of brain physiological state is necessary as the controlled object in simulations, because the performance test of a prototype of the control system using patients is not ethically allowed. A model of cerebral blood circulation has already been constructed, which is the most basic part of brain physiological state. Also, a migration model of extracellular fluid in brain has been constructed, however the condition that the total volume of intracranial cavity is almost changeless due to the hardness of cranial bone has not been considered in that model. Therefore, in this research, the dynamic migration model of extracellular fluid in brain was constructed on the consideration of the changelessness of intracranial cavity’s total volume. This model is connectable to the cerebral blood circulation model. The constructed model consists of fourteen compartments, twelve of which corresponds to perfused area of bilateral anterior, middle and posterior cerebral arteries, the others corresponds to cerebral ventricles and subarachnoid space. This model enable to calculate the migration of tissue fluid from capillaries to gray matter and white matter, the flow of tissue fluid between compartments, the production and absorption of cerebrospinal fluid at choroid plexus and arachnoid granulation, and the production of metabolic water. Further, the volume, the colloid concentration, and the tissue pressure of/in each compartment are also calculable by solving 40-dimensional non-linear simultaneous differential equations. In this research, the obtained model was analyzed for its validation under the four condition of a normal adult, an adult with higher cerebral capillary pressure, an adult with lower cerebral capillary pressure, and an adult with lower colloid concentration in cerebral capillary. In the result, calculated fluid flow, tissue volume, colloid concentration, and tissue pressure were all converged to suitable value for the set condition within 60 minutes at a maximum. Also, because these results were not conflict with prior knowledge, it is certain that the model can enough represent physiological state of brain under such limited conditions at least. One of next challenges is to integrate this model and the already constructed cerebral blood circulation model. This modification enable to simulate CBF and ICP more precisely due to calculating the effect of blood pressure change to extracellular fluid migration and that of ICP change to CBF.

Keywords: dynamic model, cerebral extracellular migration, brain resuscitation, automatic control

Procedia PDF Downloads 157
18925 Fuzzy Set Qualitative Comparative Analysis in Business Models' Study

Authors: K. Debkowska

Abstract:

The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

Procedia PDF Downloads 173
18924 Examining the Role of Tree Species in Absorption of Heavy Metals; Case Study: Abidar Forest Park

Authors: Jahede Tekeykhah, Seyed Mohsen Hossini, Gholamali Jalali

Abstract:

Industrial and traffic activities cause large amounts of heavy metals enter into the atmosphere and the use of plant species can be effective in assessing and reducing air pollution by metals. This study aimed to investigate the adsorption level of heavy metals in leaves of Fraxinus rotundifolia, Robinia, Platanus orientalis, Platycladus orientalis and Pinus eldarica trees in Abidar forest park. For this purpose, samples leaves of the trees were prepared from the contaminated and control areas in each region in 3 stations with 3 replicates in mid-August and finally 90 samples were sent to the laboratory. Then, the concentrations of heavy metals were measured by graphite furnace. To do this, factorial experiment based on a completely randomized design with two factors of location on two levels (contaminated area and control area) and the factor of species on five levels (Fraxinus rotundifolia, Robinia, Platanus orientalis, Platycladus orientalis and Pinus eldarica) with three replications was used. The analysis of collected data was performed by SPSS software and Duncan's multiple range test was used to compare the means. The results showed that the accumulation of all metals in the leaves of most species in the infected area with a significant difference at 95% level was higher than the control area. In the contaminated area, with a significant difference at 5% level, the highest accumulations of metals were observed as the following: lead, cadmium, zinc and manganese in Platanus orientalis, nickel in Fraxinus rotundifolia and copper in Platycladus orientalis.

Keywords: airborne, tree species, heavy metals, absorption, Abidar Forest Park

Procedia PDF Downloads 312
18923 A Qualitative Research of Online Fraud Decision-Making Process

Authors: Semire Yekta

Abstract:

Many online retailers set up manual review teams to overcome the limitations of automated online fraud detection systems. This study critically examines the strategies they adapt in their decision-making process to set apart fraudulent individuals from non-fraudulent online shoppers. The study uses a mix method research approach. 32 in-depth interviews have been conducted alongside with participant observation and auto-ethnography. The study found out that all steps of the decision-making process are significantly affected by a level of subjectivity, personal understandings of online fraud, preferences and judgments and not necessarily by objectively identifiable facts. Rather clearly knowing who the fraudulent individuals are, the team members have to predict whether they think the customer might be a fraudster. Common strategies used are relying on the classification and fraud scorings in the automated fraud detection systems, weighing up arguments for and against the customer and making a decision, using cancellation to test customers’ reaction and making use of personal experiences and “the sixth sense”. The interaction in the team also plays a significant role given that some decisions turn into a group discussion. While customer data represent the basis for the decision-making, fraud management teams frequently make use of Google search and Google Maps to find out additional information about the customer and verify whether the customer is the person they claim to be. While this, on the one hand, raises ethical concerns, on the other hand, Google Street View on the address and area of the customer puts customers living in less privileged housing and areas at a higher risk of being classified as fraudsters. Phone validation is used as a final measurement to make decisions for or against the customer when previous strategies and Google Search do not suffice. However, phone validation is also characterized by individuals’ subjectivity, personal views and judgment on customer’s reaction on the phone that results in a final classification as genuine or fraudulent.

Keywords: online fraud, data mining, manual review, social construction

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18922 A Geospatial Consumer Marketing Campaign Optimization Strategy: Case of Fuzzy Approach in Nigeria Mobile Market

Authors: Adeolu O. Dairo

Abstract:

Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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18921 COVID_ICU_BERT: A Fine-Tuned Language Model for COVID-19 Intensive Care Unit Clinical Notes

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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18920 Evaluation of a Hybrid Knowledge-Based System Using Fuzzy Approach

Authors: Kamalendu Pal

Abstract:

This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

Procedia PDF Downloads 367
18919 Mitigating the Cost of Empty Container Repositioning through the Virtual Container Yard: An Appraisal of Carriers’ Perceptions

Authors: L. Edirisinghe, Z. Jin, A. W. Wijeratne, R. Mudunkotuwa

Abstract:

Empty container repositioning is a fundamental problem faced by the shipping industry. The virtual container yard is a novel strategy underpinning the container interchange between carriers that could substantially reduce this ever-increasing shipping cost. This paper evaluates the shipping industry perception of the virtual container yard using chi-square tests. It examines if the carriers perceive that the selected independent variables, namely culture, organization, decision, marketing, attitudes, legal, independent, complexity, and stakeholders of carriers, impact the efficiency and benefits of the virtual container yard. There are two major findings of the research. Firstly, carriers view that complexity, attitudes, and stakeholders may impact the effectiveness of container interchange and may influence the perceived benefits of the virtual container yard. Secondly, the three factors of legal, organization, and decision influence only the perceived benefits of the virtual container yard. Accordingly, the implementation of the virtual container yard will be influenced by six key factors, namely complexity, attitudes, stakeholders, legal, organization and decision. Since the virtual container yard could reduce overall shipping costs, it is vital to examine the carriers’ perception of this concept.

Keywords: virtual container yard, imbalance, management, inventory

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18918 Sustainable Approach for Strategic Planning of Construction of Buildings using Multi-Criteria Decision Making Tools

Authors: Kishor Bhagwat, Gayatri Vyas

Abstract:

Construction industry is earmarked with complex processes depending on the nature and scope of the project. In recent years, developments in this sector are remarkable and have resulted in both positive and negative impacts on the environment and human being. Sustainable construction can be looked upon as one of the solution to overcome the negative impacts since sustainable construction is a vast concept, which includes many parameters, and sometimes the use of multi-criteria decision making [MCDM] tools becomes necessary. The main objective of this study is to determine the weightage of sustainable building parameters with the help of MCDM tools. Questionnaire survey was conducted to examine the perspective of respondents on the importance of weights of the criterion, and the respondents were architects, green building consultants, and civil engineers. This paper presents an overview of research related to Indian and international green building rating systems and MCDM. The results depict that economy, environmental health, and safety, site selection, climatic condition, etc., are important parameters in sustainable construction.

Keywords: green building, sustainability, multi-criteria decision making method [MCDM], analytical hierarchy process [AHP], technique for order preference by similarity to an ideal solution [TOPSIS], entropy

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18917 Modeling Driving Distraction Considering Psychological-Physical Constraints

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

Abstract:

Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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18916 Impacts on Marine Ecosystems Using a Multilayer Network Approach

Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

Abstract:

Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

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18915 Comparative Life Cycle Assessment of High Barrier Polymer Packaging for Selecting Resource Efficient and Environmentally Low-Impact Materials

Authors: D. Kliaugaitė, J. K, Staniškis

Abstract:

In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE). All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging. Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH. The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: life cycle assessment, polymer packaging, resource efficiency, materials extraction, polyethylene terephthalate

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18914 The Comparative Analysis on Pre-Trial in Relation to the Reform of Pre-Trial in Indonesian Criminal Procedural Code

Authors: Muhammad Fatahillah Akbar

Abstract:

Criminal Procedural Law is established to protect the society from the abuse of authority. To achieve that purpose, the criminal procedural law shall be established in accordance with the laws of human right and the protection of the society. One of the mechanisms to protect human rights and to ensure the compliance of authorities in criminal procedural law is pre-trial mechanism. In many countries, there are various mechanisms of pre-trial. In the recent cases in Indonesia, pre-trial has been an interesting issue. The issue is also addressed by the Constitutional Court Decision Number 21/PUU-XII/2014 which enhance the competence of pre-trial which includes the suspect determination and the legality of seizure and search. Before that decision, some pre-trial decisions have made landmark decision by enhancing the competence of pre-trial, such as the suspect determination case in Budi Gunawan Case and legality of the investigation in Hadi Purnomo Case. These pre-trial cases occurred because the society needs protection even though it is not provided by written legislations, in this matter, The Indonesian Criminal Procedural Code (KUHAP). For instance, a person can be a suspect for unlimited time because the Criminal Procedural Code does not regulate the limit of investigation, so the suspect enactment shall be able to be challenged to protect human rights. Before the Constitutional Court Decision Suspect Determination cannot be challenged so that the society is not fully protected. The Constitutional Court Decision has provided more protections. Nowadays, investigators shall be more careful in conducting the investigation. However, those decisions, including the Constitutional Court Decision are not sufficient for society to be protected by abuse of authority. For example, on 7 March 2017, a single judge, in a Pre-Trial, at the Surabaya District Court, decided that the investigation was unlawful and shall be terminated. This is not regulated according to the Code and also any decisions in pre-trial. It can be seen that the reform of pre-trial is necessary. Hence, this paper aims to examine how pre-trial shall be developed in the future to provide wide access for society to have social justice in criminal justice system. The question will be answered by normative, historical, and comparative approaches. Firstly, the paper will examine the history of pre-trial in Indonesia and also landmark decisions on pre-trial. Then, the lessons learned from other countries regarding to the pre-trial mechanism will be elaborated to show how pre-trial shall be developed and what the competences of a pre-trial are. The focus of all discussions shall be on how the society is protected and provided access to legally complain to the authority. At the end of the paper, the recommendation to reform the pre-trial mechanism will be suggested.

Keywords: pre-trial, criminal procedural law, society

Procedia PDF Downloads 168
18913 Decision Support System in Air Pollution Using Data Mining

Authors: E. Fathallahi Aghdam, V. Hosseini

Abstract:

Environmental pollution is not limited to a specific region or country; that is why sustainable development, as a necessary process for improvement, pays attention to issues such as destruction of natural resources, degradation of biological system, global pollution, and climate change in the world, especially in the developing countries. According to the World Health Organization, as a developing city, Tehran (capital of Iran) is one of the most polluted cities in the world in terms of air pollution. In this study, three pollutants including particulate matter less than 10 microns, nitrogen oxides, and sulfur dioxide were evaluated in Tehran using data mining techniques and through Crisp approach. The data from 21 air pollution measuring stations in different areas of Tehran were collected from 1999 to 2013. Commercial softwares Clementine was selected for this study. Tehran was divided into distinct clusters in terms of the mentioned pollutants using the software. As a data mining technique, clustering is usually used as a prologue for other analyses, therefore, the similarity of clusters was evaluated in this study through analyzing local conditions, traffic behavior, and industrial activities. In fact, the results of this research can support decision-making system, help managers improve the performance and decision making, and assist in urban studies.

Keywords: data mining, clustering, air pollution, crisp approach

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18912 CFD Simulation of a Large Scale Unconfined Hydrogen Deflagration

Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

Abstract:

In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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18911 Robot Navigation and Localization Based on the Rat’s Brain Signals

Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: brain-machine interface, decision-making, mobile robot, neural network

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18910 Conceptualizing IoT Based Framework for Enhancing Environmental Accounting By ERP Systems

Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

Abstract:

This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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18909 A Framework for Consumer Selection on Travel Destinations

Authors: J. Rhodes, V. Cheng, P. Lok

Abstract:

The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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18908 Intercultural Intelligence: How to Turn Cultural Difference into a Key Added Value with Tree Lighting Design Project Examples

Authors: Fanny Soulard

Abstract:

Today work environment is more multicultural than ever: spatial limits have been blown out, encouraging people and ideas mobility all around the globe. Indeed, opportunities to design with culturally diverse team workers, clients, or end-users, have become within everyone's reach. We enjoy traveling to discover other civilizations, but when it comes to business, we often take for granted that our own work methodology will be generic enough to federate each party and cover the project needs. This paper aims to explore why, by skipping cultural awareness, we often create misunderstandings, frustration, and even counterproductive design. Tree lighting projects successively developed by a French lighting studio, a Vietnamese lighting studio, and an Australian Engineering company will be assessed from their concept stage to completion. All these study cases are based in Vietnam, where the construction market is equally led by local and international consultants. Core criteria such as lighting standard reference, service scope, communication tools, internal team organization, delivery package content, key priorities, and client relationship will help to spot and list when and how cultural diversity has impacted the design output and effectiveness. On the second hand, we will demonstrate through the same selected projects how intercultural intelligence tools and mindset can not only respond positively to previous situations and avoid major clashes but also turn cultural differences into a key added value to generate significant benefits for individuals, teams, and companies. By understanding the major importance of including a cultural factor within any design, intercultural intelligence will quickly turn out as a “must have” skill to be developed and acquired by any designer.

Keywords: intercultural intelligence, lighting design, work methodology, multicultural diversity

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18907 Exploring Framing Effect and Repetition Effect of the Persuasive Message on Moral Decision Making in Conflict of Interests

Authors: Sae-Yeon Seong, EunSun Chung, Dongjoo Chin

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Conflict of interest (COI) is one of the dominant circumstantial factors of moral corruption across various fields. Several management strategies have been proposed to prevent self-interested decision making in COIs. Among these strategies, message persuasion has been considered as a practical and effective approach. Framing and repetition are two of the major factors in the persuasion effect of message. Therefore, their effect on moral decision making in COI should be explored systematically. The purpose of this study was to compare the differential effects of positively framed message and negatively framed message, and secondly, to investigate how the effectiveness of persuasive message changes through repetitive exposures. A total of 63 participants were randomly assigned to one of 3 framing conditions: positive framing, negative framing, and no-message condition. Prior to the online experiment involving a consultation task, the differently framed persuasive message was presented to the participants. This process was repeated four times in a row. The results showed that participants with positive-framing message were less likely to provide self-interested consultation than participants in the no-message condition. Also, a U-shaped quadric relation between repetition and self-interest consultation was found. Implications and limitations are further discussed.

Keywords: conflicts of interest, persuasive message, framing effect, repetition effect, self-interested behavior

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18906 Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

Abstract:

The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

Procedia PDF Downloads 149
18905 First Documented Anesthesia with Use of Low Doses of Tiletamine-Zolazepam Combination in Ovoviparous Amazon Tree Boa Undergoing Emergency Coeliotomy-Case Report

Authors: Krzysztof Buczak, Sonia Lachowska, Pawel Kucharski, Agnieszka Antonczyk

Abstract:

Tiletamine - zolazepam combination is increasingly used in veterinary anaesthesiology in wild animals, including snakes. The available literature shows a lack of information about anesthesia in this mixture in ovoviviparous snakes. The studies show the possibility of using the combination at a dose of 20 mg/kg or more for snake immobilization. This paper presents an anesthetic protocol with the use of a combination of tiletamine - zolazepam at the dose of 10 mg/kg intramuscularly and maintenance with inhalant anesthesia with isoflurane in pure oxygen. The objective of this study was to evaluate the usefulness of the anesthetic protocol to proceed with coeliotomy in Amazon Tree Boa. The patient was a five years old bicolor female Amazon Tree Boa (Corallus hortulanus) with dystocia. The clinical examination reveals significant emaciation (bodyweight 520g), high degree of dehydration, heart rate (HR = 60 / min), pale mucous membranes and poor reactivity. Meloxicam (1 mg/kg) and tramadol (10 mg/kg) were administered subcutaneously and the patient was placed in an incubator with access to fresh oxygen. Four hours later, the combination of tiletamine - zolazepam (10 mg/kg) was administered intramuscularly for induction of anesthesia. The snake was intubated and connected to inhalant anesthesia equipment. For maintenance, the anesthesia isoflurane in pure oxygen was used due to apnea, which occurs 30 minutes after the induction semi-closed system was attached and the ventilator was turned on (PCV system, four breaths per minute, 8 cm of H2O). Cardiopulmonary parameters (HR, RR, SPO2, ETCO2, ETISO) were assessed throughout the procedure. During the entire procedure, the operating room was heated to a temperature of 26 degrees Celsius. Additionally, the hose was placed on a heating mat, which maintained a temperature of 30 degrees Celsius. For 15 minutes after induction, the loss of muscle tone was observed from the head to the tail. Induction of general anesthesia was scored as good because of the possibility of intubation. During the whole procedure, the heart rate was at the rate of 58 beats per minute (bpm). Ventilation parameters were stable throughout the procedure. The recovery period lasts for about 4 hours after the end of general anesthesia. The muscle tension returned from tail to head. The snake started to breathe spontaneously within 1,5 hours after the end of general anesthesia. The protocol of general anesthesia with the combination of tiletamine- zolazepam with a dose of 10 mg/kg is useful for proceeding with the emergency coeliotomy in maintenance with isoflurane in oxygen. Further study about the impact of the combination of tiletamine- zolazepam for the recovery period is needed.

Keywords: anesthesia, corallus hortulanus, ovoviparous, snake, tiletamine, zolazepam

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18904 Pediatricians as a Key Channel of Influence for Infant Formula Purchases

Authors: Matthew Heidman, Susan Dallabrida, Analice Costa

Abstract:

For infant caregivers, choosing an infant formula for their child can be a difficult task in an already stressful environment of caring for a newborn. There exist several channels that influence purchasing decision of infant formula such as, friends and family and their experiences, health care professionals, social media influencers, as well as standard media marketing. This study sought to identify the key channels by which caregivers obtain information regarding infant formula and help them make their purchasing decision. A digital survey was issued for 90 days in the US (n=121) and 30 days in Mexico (n=88) targeting respondents with children ≤4 years of age. Respondents were asked two key questions regarding the influences on their purchasing decisions: 1) “When choosing a formula brand, what do you do to help you make your decision?”, and 2) “When choosing a formula brand, what is most important to you?”. A list of potential answers was provided for each question and respondents were asked to select all that apply to them. Lastly, respondents were provided a 5-point Likert scale and asked to respond to the statement 3) “I am more likely to buy a particular formula brand if my pediatrician recommends it to me”. For question 1, in the US and Mexico, 76% and 95% of respondents respectively, selected “I ask my pediatrician” which represented the top selection. For question 2, 52% and 45% of respondents respectively, selected “On package “Pediatrician Recommended” claim…” which also represented the top selection. For statement 3, 82% and 89% of respondents respectively, stated that they either “somewhat agree” or “strongly agree” with the statement. For infant caregivers, the pediatrician is a very important channel of influence when it comes to purchasing decision of infant formula. Caregivers clearly see the pediatrician as the arbiter of their child’s nutrition and seek their recommendations for infant formula use. For infant formula manufacturers, it is important that they see the pediatrician as the gatekeeper to this market, and they put resources into medical marketing communication to this health care professional group to ensure success.

Keywords: infant formula, pediatrician, purchasing driver, caregiver

Procedia PDF Downloads 94
18903 Optimization of the Measure of Compromise as a Version of Sorites Paradox

Authors: Aleksandar Hatzivelkos

Abstract:

The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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18902 AgriFood Model in Ankara Regional Innovation Strategy

Authors: Coskun Serefoglu

Abstract:

The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

Procedia PDF Downloads 152
18901 Decision-Making in Higher Education: Case Studies Demonstrating the Value of Institutional Effectiveness Tools

Authors: Carolinda Douglass

Abstract:

Institutional Effectiveness (IE) is the purposeful integration of functions that foster student success and support institutional performance. IE is growing rapidly within higher education as it is increasingly viewed by higher education administrators as a beneficial approach for promoting data-informed decision-making in campus-wide strategic planning and execution of strategic initiatives. Specific IE tools, including, but not limited to, project management; impactful collaboration and communication; commitment to continuous quality improvement; and accountability through rigorous evaluation; are gaining momentum under the auspices of IE. This research utilizes a case study approach to examine the use of these IE tools, highlight successes of this use, and identify areas for improvement in the implementation of IE tools within higher education. The research includes three case studies: (1) improving upon academic program review processes including the assessment of student learning outcomes as a core component of program quality; (2) revising an institutional vision, mission, and core values; and (3) successfully navigating an institution-wide re-accreditation process. Several methods of data collection are embedded within the case studies, including surveys, focus groups, interviews, and document analyses. Subjects of these methods include higher education administrators, faculty, and staff. Key findings from the research include areas of success and areas for improvement in the use of IE tools associated with specific case studies as well as aggregated results across case studies. For example, the use of case management proved useful in all of the case studies, while rigorous evaluation did not uniformly provide the value-added that was expected by higher education decision-makers. The use of multiple IE tools was shown to be consistently useful in decision-making when applied with appropriate awareness of and sensitivity to core institutional culture (for example, institutional mission, local environments and communities, disciplinary distinctions, and labor relations). As IE gains a stronger foothold in higher education, leaders in higher education can make judicious use of IE tools to promote better decision-making and secure improved outcomes of strategic planning and the execution of strategic initiatives.

Keywords: accreditation, data-informed decision-making, higher education management, institutional effectiveness tools, institutional mission, program review, strategic planning

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18900 Determining Inventory Replenishment Policy for Major Component in Assembly-to-Order of Cooling System Manufacturing

Authors: Tippawan Nasawan

Abstract:

The objective of this study is to find the replenishment policy in Assembly-to-Order manufacturing (ATO) which some of the major components have lead-time longer than customer lead-time. The variety of products, independent component demand, and long component lead-time are the difficulty that has resulted in the overstock problem. In addition, the ordering cost is trivial when compared to the cost of material of the major component. A conceptual design of the Decision Supporting System (DSS) has introduced to assist the replenishment policy. Component replenishment by using the variable which calls Available to Promise (ATP) for making the decision is one of the keys. The Poisson distribution is adopted to realize demand patterns in order to calculate Safety Stock (SS) at the specified Customer Service Level (CSL). When distribution cannot identify, nonparametric will be applied instead. The test result after comparing the ending inventory between the new policy and the old policy, the overstock has significantly reduced by 46.9 percent or about 469,891.51 US-Dollars for the cost of the major component (material cost only). Besides, the number of the major component inventory is also reduced by about 41 percent which helps to mitigate the chance of damage and keeping stock.

Keywords: Assembly-to-Order, Decision Supporting System, Component replenishment , Poisson distribution

Procedia PDF Downloads 128
18899 Stability Analysis of SEIR Epidemic Model with Treatment Function

Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

Abstract:

The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

Procedia PDF Downloads 521
18898 Utilization of Logging Residue to Reduce Soil Disturbance of Timber Harvesting

Authors: Juang R. Matangaran, Qi Adlan

Abstract:

Industrial plantation forest in Indonesia was developed in 1983, and since then, several companies have been successfully planted a total area of concessionaire approximately 10 million hectares. Currently, these plantation forests have their annual harvesting period. In the timber harvesting process, amount part of the trees generally become logging residue. Tree parts such as branches, twigs, defected stem and leaves are unused section of tree on the ground after timber harvesting. The use of heavy machines in timber harvesting area has caused damage to the forest soil. The negative impact of such machines includes loss of topsoil, soil erosion, and soil compaction. Forest soil compaction caused reduction of forest water infiltration, increase runoff and causes difficulty for root penetration. In this study, we used logging residue as soil covers on the passages passed by skidding machines in order to observe the reduction soil compaction. Bulk density of soil was measured and analyzed after several times of skidding machines passage on skid trail. The objective of the research was to analyze the effect of logging residue on reducing soil compaction. The research was taken place at one of the industrial plantation forest area of South Sumatra Indonesia. The result of the study showed that percentage increase of soil compaction bare soil was larger than soil surface covered by logging residue. The maximum soil compaction occurred after 4 to 5 passes on soil without logging residue or bare soil and after 7 to 8 passes on soil cover by logging residue. The use of logging residue coverings could reduce soil compaction from 45% to 60%. The logging residue was effective in decreasing soil disturbance of timber harvesting at the plantation forest area.

Keywords: bulk density, logging residue, plantation forest, soil compaction, timber harvesting

Procedia PDF Downloads 408
18897 Optimization of Water Pipeline Routes Using a GIS-Based Multi-Criteria Decision Analysis and a Geometric Search Algorithm

Authors: Leon Mortari

Abstract:

The Metropolitan East region of Rio de Janeiro state, Brazil, faces a historic water scarcity. Among the alternatives studied to solve this situation, the possibility of adduction of the available water in the reservoir Lagoa de Juturnaíba to supply the region's municipalities stands out. The allocation of a linear engineering project must occur through an evaluation of different aspects, such as altitude, slope, proximity to roads, distance from watercourses, land use and occupation, and physical and chemical features of the soil. This work aims to apply a multi-criteria model that combines geoprocessing techniques, decision-making, and geometric search algorithm to optimize a hypothetical adductor system in the scenario of expanding the water supply system that serves this region, known as Imunana-Laranjal, using the Lagoa de Juturnaíba as the source. It is proposed in this study, the construction of a spatial database related to the presented evaluation criteria, treatment and rasterization of these data, and standardization and reclassification of this information in a Geographic Information System (GIS) platform. The methodology involves the integrated analysis of these criteria, using their relative importance defined by weighting them based on expert consultations and the Analytic Hierarchy Process (AHP) method. Three approaches are defined for weighting the criteria by AHP: the first treats all criteria as equally important, the second considers weighting based on a pairwise comparison matrix, and the third establishes a hierarchy based on the priority of the criteria. For each approach, a distinct group of weightings is defined. In the next step, map algebra tools are used to overlay the layers and generate cost surfaces, that indicates the resistance to the passage of the adductor route, using the three groups of weightings. The Dijkstra algorithm, a geometric search algorithm, is then applied to these cost surfaces to find an optimized path within the geographical space, aiming to minimize resources, time, investment, maintenance, and environmental and social impacts.

Keywords: geometric search algorithm, GIS, pipeline, route optimization, spatial multi-criteria analysis model

Procedia PDF Downloads 35