Search results for: decision tree forest

Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Pei-Ru Yang, Yu-Chen Lin, Jia-Min Wu

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Background: A 58-year-old man with a history of osteoporosis and diabetes presented with chronic pain in his left knee due to severe knee joint degeneration. The knee replacement surgery was recommended by the doctor. But the patient suffered from low pain tolerance and wondered if virtual reality could relieve acute postoperative wound pain. Methods: We used the PICO (patient, intervention, comparison, and outcome) approach to generate indexed keywords and searched systematic review articles from 2017 to 2021 on the Cochran Library, PubMed, and Clinical Key databases. Results: The initial literature results included 38 articles, including 12 Cochrane library articles and 26 PubMed articles. One article was selected for further analysis after removing duplicates and off-topic articles. The eight trials included in this article were published between 2013 and 2019 and recruited a total of 723 participants. The studies, conducted in India, Lebanon, Iran, South Korea, Spain, and China, included adults who underwent hemorrhoidectomy, dental surgery, craniotomy or spine surgery, episiotomy repair, and knee surgery, with a mean age (24.1 ± 4.1 to 73.3 ± 6.5). Virtual reality is an emerging non-drug postoperative analgesia method. The findings showed that pain control was reduced by a mean of 1.48 points (95% CI: -2.02 to -0.95, p-value < 0.0001) in minor surgery and 0.32 points in major surgery (95% CI: -0.53 to -0.11, p-value < 0.03), and the overall postoperative satisfaction has improved. Discussion: Postoperative pain is a common clinical problem in surgical patients. Research has confirmed that virtual reality can create an immersive interactive environment, communicate with patients, and effectively relieve postoperative pain. However, virtual reality requires the purchase of hardware and software and other related computer equipment, and its high cost is a disadvantage. We selected the best literature based on clinical questions to answer the patient's question and used share decision making (SDM) to help the patient make decisions based on the clinical situation after knee replacement surgery to improve the quality of patient-centered care.

Keywords: knee replacement surgery, postoperative pain, share decision making, virtual reality

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Authors: Inês Amorim Leitão, Loes van Shaick, António Dinis Ferreira, Violette Geissen

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Plastic pollution is a growing concern worldwide: plastics are commercialized in large quantities and it takes a long time for them to degrade. When in the environment, plastic is fragmented into microplastics (<5mm), which have been found in all environmental compartments at different locations. Microplastics contribute to the environmental pollution in water, air and soil and are linked to human health problems. The progressive increase of population living in cities led to the aggravation of the pollution problem worldwide, especially in urban environments. Urban areas represent a strong source of pollution, through the roads, industrial production, wastewater, landfills, etc. It is expected that pollutants such as microplastics are transported diffusely from the sources through different pathways such as wind and rain. Therefore, it is very complex to quantify, control and treat these pollutants, designated current problematic issues by the European Commission. Green areas are pointed out by experts as natural filters for contaminants in cities, through their capacity of retention by vegetation. These spaces have thus the capacity to control the load of pollutants transported. This study investigates the spatial distribution of microplastics in urban soils of different land uses, their transport through atmospheric deposition, wind erosion, runoff and streams, as well as their deposition in vegetation like grass and tree leaves in urban environment. Coimbra, a medium large city located in the central Portugal, is the case-study. All the soil, sediments, water and vegetation samples were collected in Coimbra and were later analyzed in the Wageningen University & Research laboratory. Microplastics were extracted through the density separation using Sodium Phosphate as solution (~1.4 g cm−3) and filtration methods, visualized under a stereo microscope and identified using the u-FTIR method. Microplastic particles were found in all the different samples. In terms of soils, higher concentrations of microplastics were found in green parks, followed by landfills and industrial places, and the lowest concentrations in forests and pasture land-uses. Atmospheric deposition and streams after rainfall events seems to represent the strongest pathways of microplastics. Tree leaves can retain microplastics on their surfaces. Small leaves such as needle leaves seem to present higher amounts of microplastics per leaf area than bigger leaves. Rainfall episodes seem to reduce the concentration of microplastics on leaves surface, which suggests the wash of microplastics down to lower levels of the tree or to the soil. When in soil, different types of microplastics could be transported to the atmosphere through wind erosion. Grass seems to present high concentrations of microplastics, and the enlargement of the grass cover leads to a reduction of the amount of microplastics in soil, but also of the microplastics moved from the ground to the atmosphere by wind erosion. This study proof that vegetation can help to control the transport and dispersion of microplastics. In order to control the entry and the concentration of microplastics in the environment, especially in cities, it is essential to defining and evaluating nature-based land-use scenarios, considering the role of green urban areas in filtering small particles.

Keywords: microplastics, cities, sources, pathways, vegetation

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Authors: Hecson Christian, Joel Macwan

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Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Susanna Menis

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‘Unconscious’ bias is widespread, affecting society on all levels of decision-making and beyond. Placed in the law context, this study will explore the direct effect of the psycho-social and cultural evolution of unconscious bias on how a judicial decision was made. The aim of this study is to contribute to socio-legal scholarship by examining the formation of unconscious bias and its influence on the creation of legal rules that judges believe reflect social solidarity and protect against violence. The study seeks to understand how concepts like criminalization and unlawfulness are constructed by the common law. The study methodology follows two theoretical approaches: historical genealogy and emotions as sociocultural phenomena. Both methods have the ‘tracing back’ of the original formation of a social way of seeing and doing things in common. The significance of this study lies in the importance of reflecting on the ways unconscious bias may be formed; placing judges’ decisions under this spotlight forces us to challenge the status quo, interrogate justice, and seek refinement of the law.

Keywords: legal geneology, emotions, disgust, criminal law

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Authors: Rui Zhang

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Translation has been elevated to one of the key notions in contemporary cultural discourse for a wide range of fields. It focuses not only on communication or transmission of meaning between different languages, but also on ways in which the very act of translation can be understood as a metaphor for cultural process. In recent years, the notion of translation is employed by some contemporary Chinese artists in a conceptual way, whose works contribute to constructing/deconstructing global/local cultural discourse and their own cultural identities. This study examines two artworks by contemporary Chinese artist Gu Wenda from a translational perspective, namely Forest of Stone Steles - Retranslation & Rewriting of Tang Poetry and United Nations - China Monument: Temple of Heaven, aiming to broaden the scope of Translation Studies to investigate visual culture and enrich methodological approach to contemporary Chinese art. Focusing on the relationship between translation, visuality and materiality in these two works, this study explores the nature of translation as part of the production of cultural discourse in the age of globalization as well as a way of establishing cultural identity. Gu Wenda, one of the most prestigious artists in contemporary China, is considered a pioneer in ‘85 Art Movement of China, and thereafter he went abroad for his artistic pursuits. His transnational experience enriches his cultural identity and the underlying discourse constructed/deconstructed in many of his works. In the two works already mentioned, the concept of translation is deployed by Gu Wenda on both linguistic level and metaphorical level for artistic expression. These two works produce discourses in which the artist’s perception of cultural identity in a transnational context is articulated by the tension between source text and target text. Based on the conceptual framework of cultural identity proposed by Stuart Hall, analyses of Gu Wenda’s cultural identity revealed through translation in these two works are centred on two axes, i.e., the axis of similarity and continuity with Chinese intellectual culture and the axis of difference and rupture with it, and the dialogic relationship between these two vectors. It argues that besides serving as a means of constructing visuality in the two works, translation metaphorizes Gu Wenda’s journey from overcoming his cultural identity anxiety to re-establishing a transcultural identity embedded in the underlying discourse.

Keywords: contemporary Chinese art, cultural identity, transculturality, translation

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Authors: Anocha Rojanapanich

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The purpose of this research is to develop and design an accounting management information system for convenient shop in Bangkok Thailand. The study applied the System Development Life Cycle (SDLC) for development which began with study and analysis of current data, including the existing system. Then, the system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Product diversity, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management and importance of cost information for decision making also as well as.

Keywords: accounting management information system, convenient shop, cost information for decision making system, development life cycle

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Zahra Abdolkarimi, Naser Zouri

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The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. There is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidentally.

Keywords: particle swarm optimization, chaos theory, inference fuzzy system, simulation environment rational fuzzy system, mamdani and assilian, deffuzify

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

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We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

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Authors: Alaa Abdullah Altaee

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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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Authors: M. A. T. AlSudairi, T. G. K. Vasista

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The concept of social media is becoming the top of the agenda for many business executives and public sector executives today. Decision makers as well as consultants, try to identify ways in which firms and enterprises can make profitable use of social media and network related applications such as Wikipedia, Face book, YouTube, Google+, Twitter. While it is fun and useful to participating in this media and network for achieving the communication effectively and efficiently, semantic and sentiment analysis and interpretation becomes a crucial issue. So, the objective of this paper is to provide literature review on social media, network and related technology related to semantics and sentiment or opinion analysis covering business and governance perspectives. In this regard, a case study on the use and adoption of Social media in Saudi Arabia has been discussed. It is concluded that semantic web technology play a significant role in analyzing the social networks and social media content for extracting the interpretational knowledge towards strategic decision support.

Keywords: CRASP methodology, formative assessment, literature review, semantic web services, social media, social networks

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Muhammad Saad, AzherBaig, Anwar Maqsood, Muhammad Waseem

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The grey wolf has been ranked endangered and Asiatic jackal as near threatened in Pakistan. Scientific data on population and threats to these species are not available in Pakistan, which is required for their proper management and conservation. The present study was conducted to collect data on distribution range, population status and threats to both of these Canis species in Lehri Nature Park. The data were collected using direct observations and indirect signs in the field. The population of grey wolf and Asiatic jackal were scattered into pocket of the study area and its surroundings. The current population of grey wolf was estimated 06 individuals and that of Asiatic jackal 28 individuals in the study area. The present study showed that grey wolf and Asiatic jackal were distributed in the northern and southern part of the study area having dense vegetation cover of tress and shrub between the altitudes of 330 m and 515 m. The research finding revealed that the scrub forest is the most preferred habitat of both the species but due to anthropogenic pressure the scrub forest is under severe threat. The dominant trees species were Acacia modesta, Zizyphus nummularia, and Prosopis juliflora and shrubs species of Dodonea-viscosa, Calotropis procera and Adhatoda vasica. Urial is one of the natural prey species: their population is low due to a number of reasons and therefore the maximum dependence of the wolves was on the livestock of the local and nomadic shepherds. The main prey species in the livestock was goats and sheep. The interviews were conducted with the eye witnesses of wolf attacks including livestock being killed by 5-6 numbers of wolves in different hamlets in the study area. The killing rate of the livestock by the wolves was greater when the nomadic shepherds were present in the area and decreased when they left the area. Presence of nomadic shepherds and killing rate has relation with the shifting of the wolves from the study area. It is further concluded that the population of the grey wolf and Asiatic jackal has decreased over time due to less availability of the natural prey species and habitat destruction.

Keywords: wildlife ecology, population conservation, rehabilitation, conservation

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Fatih Iscan, Ceren Yagci

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Rapid population growth, urbanization and industrialization are known as the most important factors of environment problems. Elimination and management of solid wastes are also within the most important environment problems. One of the main problems in solid waste management is the selection of the best site for elimination of solid wastes. Lately, Geographical Information System (GIS) has been used for easing selection of landfill area. GIS has the ability of imitating necessary economical, environmental and political limitations. They play an important role for the site selection of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of environmental, social and cultural factors and maximum effect for engineering/economical factors for site selection of landfill areas and using GIS for an decision support mechanism in solid waste landfill areas site selection will be presented in Aksaray/TURKEY city, Güzelyurt district practice.

Keywords: GIS, landfill, solid waste, spatial analysis

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Authors: Chen Chih-Cheng, Chen I-Cheng, Lee Yung-Tan, Kuo Yen-Whea, Yu Chin-Hung

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The purpose of this study is to construct a model for best spike player selection in a top volleyball tournament of the world. Data consisted of the records of 2013 World Grand Prix declared by International Volleyball Federation (FIVB). Simple Multiple-Attribute Rating Technique (SMART) was used for optimal decision-making model on the best spike player selection. The research results showed that the best spike player ranking by SMART is different than the ranking by FIVB. The results demonstrated the effectiveness and feasibility of the proposed model.

Keywords: simple multiple-attribute rating technique, World Grand Prix, best spike player, International Volleyball Federation

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Authors: Chih-Hsiang Chang, Fang-Jyun Su

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This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.

Keywords: stock characteristics, herding formation, investment decision, US equity market, lead-lag relationship

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Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

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Authors: Asma Shaheen Hashmi, Omer Riaz, Khalid Mahmood, Fahad Ullah, Tanveer Ahmad

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The urban landscapes are being change with the population growth and advancements in new technologies. The urban sprawl pattern and utilizes are related to the local socioeconomic and physical condition. Urban policy decisions are executed mostly through spatial planning. A decision support system (DSS) is very powerful tool which provides flexible knowledge base method for urban planning. An application was developed using geographical information system (GIS) for urban planning. A scenario based DSS was developed to integrate the hierarchical muti-criteria data of different aspects of urban landscape. These were physical environment, the dumping site, spatial distribution of road network, gas and water supply lines, and urban watershed management, selection criteria for new residential, recreational, commercial and industrial sites. The model provided a framework to incorporate the sustainable future development. The data can be entered dynamically by planners according to the appropriate criteria for the management of urban landscapes.

Keywords: urban, GIS, spatial, criteria

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Authors: A. Abbou, V. Makis, N. Salari

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We study the condition-based maintenance (CBM) problem of a system subject to stochastic deterioration. The system is composed of three units (or modules): (i) Module 1 deterioration follows a Markov process with two operational states and one failure state. The operational states are partially observable through periodic condition monitoring. (ii) Module 2 deterioration follows a Gamma process with a known failure threshold. The deterioration level of this module is fully observable through periodic inspections. (iii) Only the operating age information is available of Module 3. The lifetime of this module has a general distribution. A CBM policy prescribes when to initiate a maintenance intervention and which modules to repair during intervention. Our objective is to determine the optimal CBM policy minimizing the long-run expected average cost of operating the system. This is achieved by formulating a Markov decision process (MDP) and developing the value iteration algorithm for solving the MDP. We provide numerical examples illustrating the cost-effectiveness of the optimal CBM policy through a comparison with heuristic policies commonly found in the literature.

Keywords: reliability, maintenance optimization, Markov decision process, heuristics

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Authors: Mehmet Bulent Topkaya, Mustafa Yildirim

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Wastewater treatment systems are designed and used to minimize adverse impacts of the wastewater on the environment before discharging. Various treatment options for wastewater treatment have been developed, and each of them has different performance characteristics and environmental impacts (e.g. material and land usage, energy consumption, greenhouse gas emission, water and soil emission) during construction, operation or maintenance phases. Assessing the environmental impacts during these phases are essential for the overall evaluation of the treatment systems. In this study, wastewater treatment options, such as vegetated land treatment, constructed wetland, rotating biological contactor, conventional activated sludge treatment, membrane bioreactor, extended aeration and stabilization pond are evaluated. The comparison of the environmental impacts is conducted under the assumption that the effluents will be discharged to sensitive and less sensitive areas respectively. The environmental impacts of each alternative are evaluated by life cycle assessment (LCA) approach. For this purpose, data related to energy usage, land requirement, raw material consumption, and released emissions from the life phases were collected with inventory studies based on field studies and literature. The environmental impacts were assessed by using SimaPro 7.1 LCA software. As the scale of the LCA results is global, an MS-Excel based decision support tool that includes the LCA result is developed in order to meet also the local demands. Using this tool, it is possible to assign weight factors on the LCA results according to local conditions by using Analytical Hierarchy Process and finally the most environmentally appropriate treatment option can be selected.

Keywords: analytical hierarchy process, decision support system, life cycle assessment, wastewater treatment

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

Abstract:

Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: H. M. B. N Jayasinghe

Abstract:

The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

Procedia PDF Downloads 234

Authors: Hong Nguyen Thi Hai, Ryota Konda, Dat Kieu Tuan, Cao Tran Thanh, Khang Phung Van, Hau Tran Tin, Harry Wu

Abstract:

Melaleuca cajuputi is a moderately fast-growing species and considered as a multi-purpose tree as it provides fuelwood, piles and frame poles in construction, leaf essential oil and honey. It occurs in Australia, Papua New Guinea, and South-East Asia. M. cajuputi plantation can be harvested on 6-7 year rotations for wood products. Its timber can also be used for pulp and paper, fiber and particle board, producing quality charcoal and potentially sawn timber. However, most reported M. cajuputi breeding programs have been focused on oil production rather than wood production. In this study, breeding program of M. cajuputi aimed to improve wood production was examined by estimating genetic parameters for growth (tree height, diameter at breast height (DBH), and volume), stem form, stiffness (modulus of elasticity (MOE)), bark thickness and bark ratio in a half-sib family progeny trial including 80 families in the Mekong Delta of Vietnam. MOE is one of the key wood properties of interest to the wood industry. Non-destructive wood stiffness was measured indirectly by acoustic velocity using FAKOPP Microsecond Timer and especially unaffected by bark mass. Narrow-sense heritability for the seven traits ranged from 0.13 to 0.27 at age 7 years. MOE and stem form had positive genetic correlations with growth while the negative correlation between bark ratio and growth was also favorable. Breeding for simultaneous improvement of multiple traits, faster growth with higher MOE and reduction of bark ratio should be possible in M. cajuputi. Index selection based on volume and MOE showed genetic gains of 31 % in volume, 6 % in MOE and 13 % in stem form. In addition, heritability and age-age genetic correlations for growth traits increased with time and optimal early selection age for growth of M. cajuputi based on DBH alone was 4 years. Selected thinning resulted in an increase of heritability due to considerable reduction of phenotypic variation but little effect on genetic variation.

Keywords: acoustic velocity, age-age correlation, bark thickness, heritability, Melaleuca cajuputi, stiffness, thinning effect

Procedia PDF Downloads 163

Authors: Emad Mohammed Sani

Abstract:

Women encounter exclusion and discrimination in varying degrees, particularly those who marry as minors. The detrimental custom of getting married young is still prevalent worldwide and affects millions of people. It has been less common over time, although it is still widespread in underdeveloped nations. Oromia Regional State is the region in Ethiopia with the highest proportion of child brides. This study aimed at evaluating the effects of early marriage on its survivors’ life conditions – specifically, empowerment and household decision-making – in Eastern Hararghe Zone of Oromia Region. This study employed community-based cross-sectional study design. It adopted mixed method approach – survey, in-depth interview and focus group discussion (FGD) – to collect, analyses and interpret data on early marriage and its effects on household decision-making processes. Narratives and analytical descriptions were integrated to substantiate and/or explain observed quantitative results, or generate contextual themes. According to this study, married women who were married at or after the age of eighteen participated more in household decision-making than child brides. Child brides were more likely to be victims of violence and other types of spousal abuse in their marriages. These changes are mostly caused by an individual's age at first marriage. Delaying marriage had a large positive impact on women's empowerment at the household level, and age at first marriage had a considerable negative impact. In order to advance women's welfare and emancipation, we advise more research to concentrate on the relationship between the home and the social-structural forms that appear at the individual and communal levels.

Keywords: child-bride, early marriage, women, ethiopia

Procedia PDF Downloads 50

Authors: Narong Anurak

Abstract:

The objectives of the study were to determine the factors influencing tourists’ destination decision making for cultural tourism in the southern provinces, to examine the potential for developing cultural tourism and to guideline for marketing strategy for cultural tourism in Nakhon Si Thammarat. Both quantitative and qualitative data were applied in this study. The samples of 400 cases for quantitative analysis were tourists who were interested in cultural tourism in the southern provinces, and traveled to cultural sites in Nakhon Si Thammarat, Surat Thani, and Phuket, and 14 representatives from provincial tourism committee of Nakhon Si Thammarat. The study found that Thai and foreign tourists are influenced by different important marketing mix factors (7Ps) when making decisions for cultural tourism in southern provinces. The important factors for Thai respondents were physical evidence, price, people, and place at high importance level, whereas, product, process, and promotion were moderate importance level as well.

Keywords: marketing mix factors, Nakhon Si Thammarat province, sustainable cultural tourism, tourists decision making

Procedia PDF Downloads 258