Search results for: decision of return migration

Authors: Emmanuel Barrantes Chaves, Ernesto Rivera Alvarado

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This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the ‘You Only Look Once’ model in the first layer of the process obtains information from the screen, translating this information into a video game description language known as “Video Game Description Language”; the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared; Monte Carlo Tree Search and Rolling Horizon Evolutionary; in this case, Rolling Horizon Evolutionary shows a better performance. This approach’s main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.

Keywords: AI, MCTS, RHEA, Terraria, VGDL, YOLOv5

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Authors: Razieh Khalafi

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The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.

Keywords: brain, stimuli, partial differential equation, response, EEG signal

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Authors: Nathalie Baeza-Kallee, Raphaël Bergès, Victoria Hein, Stéphanie Cabaret, Jeremy Garcia, Abigaëlle Gros, Emeline Tabouret, Aurélie Tchoghandjian, Carole Colin, Dominique Figarella-Branger

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Glioblastoma (GBM) contains cancer stem cells that are resistant to treatment. GBM cancer stem cell expresses glycolipids recognized by the A2B5 antibody. A2B5, induced by the enzyme ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyl transferase 3 (ST8Sia3), plays a crucial role in the proliferation, migration, clonogenicity, and tumorigenesis of GBM cancer stem cells. Our aim was to characterize the resulting effects of neuraminidase that remove A2B5 in order to target GBM cancer stem cells. To this end, we set up a GBM organotypic slice model; quantified A2B5 expression by flow cytometry in U87-MG, U87-ST8Sia3, and GBM cancer stem cell lines, treated or not by neuraminidase; performed RNAseq and DNA methylation profiling; and analyzed the ganglioside expression by liquid chromatography-mass spectrometry in these cell lines, treated or not with neuraminidase. Results demonstrated that neuraminidase decreased A2B5 expression, tumor size, and regrowth after surgical removal in the organotypic slice model but did not induce a distinct transcriptomic or epigenetic signature in GBM CSC lines. RNAseq analysis revealed that OLIG2, CHI3L1, TIMP3, TNFAIP2, and TNFAIP6 transcripts were significantly overexpressed in U87-ST8Sia3 compared to U87-MG. RT-qPCR confirmed these results and demonstrated that neuraminidase decreased gene expression in GBM cancer stem cell lines. Moreover, neuraminidase drastically reduced ganglioside expression in GBM cancer stem cell lines. Neuraminidase, by its pleiotropic action, is an attractive local treatment against GBM.

Keywords: cancer stem cell, ganglioside, glioblastoma, targeted treatment

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Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle

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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.

Keywords: electric vehicles, fleets, path dependencies, transition pathways

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Nisar Alungal Chungath

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“No human being is illegal" has become a dictum strongly upheld in the context of global immigration and migration, highlighting the ethical and moral dimensions of how societies and governments treat individuals and communities who have crossed political borders or are living in a country without legal authorization. It seeks to shift the focus from categorizing human beings as illegal immigrants to recognizing their inherent human rights and the complexities of their circumstances. As a complex social phenomenon, law has been a crucial instrument in shaping, regulating and governing human societies and vice versa. The law has now become a humongous political project of the modern majoritarian regimes to democratically illegitimize and illegalize the unpopular sections and minorities. Drawing from the theoretical frameworks of dialectics, the paper explores the philosophical underpinnings of the historical evolution and dynamic nature of modern law. The paper employs a phenomenological approach to analyze the dialectical relations between individuals, societies, and legal systems, aiming to shed light on the ethical and political implications of these interactions. By examining the historical essence of law, its relationship with social and cultural norms, and the role of power dynamics, this article argues for constantly maintaining the dialectics of law—the dynamic interplay between legal norms, social practices, cultural values, and historical contexts through a philosophical and phenomenological lens, in order to bridge the gap between universal principles and particular contexts. The paper will shed light to the dialectics of the law in the context of instances of the legal persecutions of the modern secular democracies such as Citizenship Amendment Act-2019, India.

Keywords: phenomenology, dialectic, modern law, politics, resistance, margins

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Authors: Luciano Oliveira, Elsa Vásquez-Alvarez

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The increase in rail freight transport in Brazil in recent years requires new railway lines and the maintenance of existing ones, which generates high costs for concessionaires. It is in this context that this work is inserted, whose objective is to propose a method that uses Binary Linear Programming for the choice of sleeper and rail fastening, from various options, including the way to apply these materials, with focus to minimize costs. Unit value information, the life cycle each of material type, and service expenses are considered. The model was implemented in commercial software using real data for its validation. The formulated model can be replicated to support decision-making for other railway projects in the choice of sleepers and rail fastening with lowest cost.

Keywords: linear programming, rail fastening, rail sleeper, railway

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Authors: Wei-Chia Huang, Jane Wang

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Damage to nerves is considered one of the most irreversible injuries. The regeneration of nerves has always been an important topic in regenerative medicine. In general, damage to human tissue will naturally repair overtime. However, when the nerves are damaged, healed flesh wound cannot guarantee full restoration to its original function, as truncated nerves are often irreversible. Therefore, the development of treatment methods to successfully guide and accelerate the regeneration of nerves has been highly sought after. In order to induce nerve tissue growth, nerve conduits are commonly used to help reconnect broken nerve bundles to provide protection to the location of the fracture while guiding the growth of the nerve bundles. To prevent the protected tissue from becoming necrotic and to ensure the growth rate, the conduits used are often modified with microstructures or blended with neuron growth factors that may facilitate nerve regeneration. Electrical stimulation is another attempted treatment for medical rehabilitation. With appropriate range of voltages and stimulation frequencies, it has been demonstrated to promote cell proliferation and migration. Biodegradability are critical for medical devices like nerve conduits, while conductive polymers pose great potential toward the differentiation and growth of nerve cells. In this work, biodegradability and conductivity were combined into a novel biodegradable, photocurable, conductive polymer composite materials by embedding conductive nanoparticles in poly(glycerol sebacate) acrylate (PGSA) and 3D-printed into nerve conduits. Rat pheochromocytoma cells and rat neuronal Schwann cells were chosen for the in vitro tests of the conduits and had demonstrate selective growth upon culture in the conductive conduits with built-in microchannels and electrical stimulation.

Keywords: biodegradable polymer, 3d printing, neural regeneration, electrical stimulation

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

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Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

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Authors: Hira Jabbar, Tanzeel-Ur Rehman

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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.

Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)

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Authors: Soufiane Fal, Abderahim Aasfar, Ali Ouhssain, Hasnae Choukri, Abelaziz Smouni, Hicham El Arroussi

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Heavy metals contamination is a major environmental concern around the world. It has a harmful impact on plant productivity and poses a serious risk to humans and animals health. In the present study, the effect of Microalgae Crude Extract (MCE) on tomato growth and nutrients uptake exposed to 2 mM Pb2+ and Cd2+ was investigated. In results, 2 mM Pb2+ and Cd2+ showed a significant reduction of tomatobiomass and perturbation in nutrients absorption. Moreover, MCE application in tomato plant exposed to Pb2+ and Cd2+ showed a significant enhancement of biomass compared to tomato plants under Pb2+ and Cd2+. On the other hand, MCE application favoured heavy metals accumulation in root and inhibited their translocation to shoot as phytostabilisation mechanism. Tomato plants showed biochemical responses to Pb2+ and Cd2+ stress with elevation of scavenging enzymes and molecules such as POD, CAT, SOD, Proline, and polyphenols, etc. In addition, the treatment by MCE showed a significant reduction level of the majority of these parameters. Furthermore, the metabolomic analysis revealed a significant change in important metabolites. Pb2+ and Cd2+ showed decrease in SFA and increase of UFA, VLFA, alkanes, alkenes, sterols, which known accumulated as tolerance and resistance mechanism to heavy metal (H.M) stress. However, MCE treatment showed the inverse of these response to return tomato plants to normal state and enhanced tolerance and resistance to heavy metal stress. In the present study, we emphasized that MCE can alleviate H.M stress, enhance tomato plant growth nutrients absorption and improve biochemical responses.

Keywords: microalgae crude extract, heavy metal stress, nutrient uptake, metabolomic analysis, solanum lycopersicum (Tomato), phytostabilisation

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Authors: Amando A. Radomes Jr., LLoyd Jun Benjamin T. Embernatre, Cherssy Kaye F. Eviota, Krizia Allyn L. Nunez, Jose Thaddeus B. Roble III

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Sitio Kantaling is one of the 34 villages in Danao City, Cebu, in the central Philippines. As of 2015, the eight households in the mountainous village extending over 40 hectares of land area, including 12 hectares of arable land, are the source of over a fifth of the agricultural products that go into the city. Over the years, however, the local government had been concerned with the decline in agricultural productivity because increasing number of residents are migrating into the urban areas of the region to look for better employment opportunities. One of the major reasons for the agricultural productivity decline is underdeveloped irrigation infrastructure. The local government had partnered with the University of San Carlos to conduct research on developing an irrigation system that could sustainably meet both agricultural and household consumption needs. From a macro-perspective, a dynamic simulation model was developed to understand the long-term behavior of the status quo and proposed the system. Data on population, water supply and demand, household income, and urban migration were incorporated in the 20-year horizon model. The study also developed a smart irrigation system design. Instead of using electricity to pump water, a network of aqueducts with three main nodes had been designed and strategically located to take advantage of gravity to transport water from a spring. Simulation results showed that implementing a sustainable irrigation system would be able to significantly contribute to the socio-economic progress of the local community.

Keywords: agriculture, aqueduct, simulation, sustainable irrigation system

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Authors: Tizian Matschak, Ilja Nastjuk, Stephan Kühnel, Simon Trang

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We argue that besides well-known primary effects of information security controls (ISCs), namely confidentiality, integrity, and availability, ISCs can also have secondary effects. For example, while IT can add business value through impacts on business processes, ISCs can be a barrier and distort the relationship between IT and organizational value through the impact on business processes. By applying the Delphi method with 28 experts, we derived 27 business process influence dimensions of ISCs. Defining and understanding these mechanisms can change the common understanding of the cost-benefit valuation of IT security investments and support managers' effective and efficient decision-making.

Keywords: business process dimensions, dark side of information security, Delphi study, IT security controls

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Authors: Susana Marques

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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.

Keywords: store choice, store patronage, structural equation modelling, retailing

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Authors: Ebru Nergiz

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The world is facing one of the biggest refugee crisis’ in history as hundred thousands of refugees who run away from the battle and genocide in the Middle East are travelling illegally to reach Europe over the Mediterranean and Aegean Sea. The number of refugees has reached huge numbers due to the civil war that was caused by the Arab Spring. The number of asylum applications to the European Union has also increased in parallel with the increase in the number of refugees. The conflict in Syria between the government of Bashar Al-Assad and various other forces, which started in the spring of 2011, continues to cause displacement within the country and across the region. The refugee situation caused by the Syrian conflict has placed enormous strain on neighboring countries Lebanon, Jordan, Iraq, Egypt, and especially Turkey. Turkey hosts massive numbers of Syrian refugees, almost 3 million and Syrians have been seeking protection in increasing numbers. The refugee crisis has affected the relationships between Turkey and the European Union deeply. President of the European Council Donald Tusk chaired a meeting of EU heads of state or government with Turkey on 29 November 2015. The meeting opened a new era in the relationships between Turkey and the European Union in terms of the migration crisis. The EU and Turkey agreed to negotiate Turkey's accession process to the European Union and to hold regular summits on Turkey-EU relations and discuss these issues. This paper looks at the reasons and consequences of the European refugee crisis and its effects on Turkey- European Union relationships. This paper also argues that the European Union has not sufficiently contributed toward alleviating the burden caused by the refugee influx, in terms of both financial assistance and refugee resettlement. The European Union’s priority is to guarantee that the lowest possible number of refugees reach Europe rather than to ensure the security of the refugees.

Keywords: European Union, human rights, refugee crisis, Turkey-European union relationships

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

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Authors: Berrin Şentürk

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In this study, due to the recurrence of bovine tuberculosis, in the same areas, the risk factors for the disease were determined and evaluated at the local level. This study was carried out in 32 farms where the disease was detected in the district and center of Samsun province in 2014. Predetermined risk factors, such as farm, environmental and economic risks, were investigated with the survey method. It was predetermined that risks in the three groups are similar to the risk variables of the disease on the global scale. These risk factors that increase the susceptibility of the infection must be understood by the herd owners. The risk-based contagious disease management system approach should be applied for bovine tuberculosis by farmers, animal health professionals and public and private sector decision makers.

Keywords: bovine tuberculosis, disease management, control, outbreak, risk analysis

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Authors: Hashini E. Mohottala

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We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS.

Keywords: group problem solving (GPS), wikispace (WikiS), physics education, learning

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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Authors: Ida Bagus Made Putra Jandhana, Teuku Yuri M. Zagloel, Rahmat Nurchayo

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Having several crises that affect industrial sector performance in the past decades, decision makers should utilize measurement application that enables them to measure industrial resiliency more precisely. It provides not only a framework for the development of resilience measurement application, but also several theories for the concept building blocks, such as performance measurement management, and resilience engineering in real world environment. This research is a continuation of previously published paper on performance measurement in the industrial sector. Finally, this paper contributes an alternative performance measurement method in industrial sector based on resilience concept. Moreover, this research demonstrates how applicable the concept of resilience engineering is and its method of measurement.

Keywords: industrial, measurement, resilience, sector

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Norma Kok, Diemo Masuko, Thandokazi Dlongwana, Komala Pillay

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CONTEXT: While many school principals have been outstanding teachers and have inherent leadership potential, many have not had access to the quality of leadership development or support that empowers them to produce high-quality education outcomes in extremely challenging circumstances. Further, school leaders in under-served communities face formidable challenges arising from insufficient infrastructure, overcrowded classrooms, socio-economic challenges within the community, and insufficient parental involvement, all of which put a strain on principals’ ability to lead their schools effectively. In addition few school leaders have access to other supportive networks, and many do not know how to build and leverage social capital to create opportunities for their schools and learners. Moreover, we know that fostering parental involvement in their children’s learning improves a child’s morale, attitude, and academic achievement across all subject areas, and promotes better behaviour and social adjustment. Citizen Leader Lab facilitates the Partners for Possibility (PfP) programme to provide leadership development and support to school leaders serving under-resourced communities in South Africa to create effective environments of learning. This is done by creating partnerships between school leaders and private-sector business leaders over a 12-month period. (185) OBJECTIVES: To explore school leaders’ perceptions of their leadership capacities and changes at their schools after being exposed to a year-long leadership development training programme. METHODS: School leaders gained new leadership capacities e.g. resilience, improved confidence, communication and conflict resolution skills - catalysing into improved cultures of collaborative decision-making and environments for enhanced teaching and learningprogramme based on the 70:20:10 model whereby: 10% of learning comes from workshops, 20% of learning takes place through peer learning and 70% of learning occurs through experiential learning as partnerships work together to identify and tackle challenges in targeted schools. Participants completed a post-programme questionnaire consisting of structured and unstructured questions and semi-structured interviews were conducted with them and their business leader. The interviews were audio-recorded, transcribed and thematic content analysis was undertaken. The analysis was inductive and emerging themes were identified. A code list was generated after coding was undertaken using computer software (Dedoose). Quantitative data gathered from surveys was aggregated and analysed. RESULTS: School leadership found the programme interesting and rewarding. They gained new leadership capacities such as resilience, improved confidence, communication and conflict resolution skills - catalyzing into improved cultures of collaborative decision-making and environments for enhanced teaching and learning. New networks resulted in tangible outcomes such as upgrades to school infrastructure, water and sanitation, vegetable gardens at schools resulting in nutrition for learners and/or intangible outcomes such as skills for members of school management teams (SMTs). Collaborative leadership led to SMTs being more aligned, efficient, and cohesive; and teachers being more engaged and motivated. Notable positive changes at the school inspired parents and community members to become more actively involved in the school and in their children’s education. CONCLUSION: The PfP programme leads to improved leadership capacities and improved school culture which leads to improved teaching and learning and new resources for schools.

Keywords: collaborative decision-making, collaborative leadership, community involvement, confidence

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Authors: Rodrigo Zeidan

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The paper identifies failures of decision making and corporate governance that allow non-financial companies around the world to develop hedging strategies that lead to hefty losses in the aftermath of the financial crisis. The sample is comprised of 346 companies from 10 international markets, of which 49 companies (and a subsample of 13 distressed companies) lose a combined US$18.9 billion. An event study shows that most companies that present losses in derivatives experience negative abnormal returns, including a number of companies in which the effect is persistent after a year. The results of a probit model indicate that the lack of a formal hedging policy, no monitoring to the CFOs, and considerations of hubris and remuneration contribute to the mismanagement of hedging policies.

Keywords: risk management, hedging, derivatives, monitoring, corporate governance structure, event study, hubris

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Authors: Bolawole F. Ogunbodede, Mokolade Johnson, Adetunji Adejumo

Abstract:

High population growth rate, reactive infrastructure provision, inability of physical planning to cope with developmental pace are responsible for waste water crisis in the Lagos Metropolis. Septic tank is still the most prevalent waste-water holding system. Unfortunately, there is a dearth of septage treatment infrastructure. Public waste-water treatment system statistics relative to the 23 million people in Lagos State is worrisome. 1.85 billion Cubic meters of wastewater is generated on daily basis and only 5% of the 26 million population is connected to public sewerage system. This is compounded by inadequate budgetary allocation and erratic power supply in the last two decades. This paper explored community participatory waste-water management alternative at Oworonshoki Municipality in Lagos. The study is underpinned by decentralized Waste-water Management systems in built-up areas. The initiative accommodates 5 step waste-water issue including generation, storage, collection, processing and disposal through participatory decision making in two Oworonshoki Community Development Association (CDA) areas. Drone assisted mapping highlighted building footage. Structured interviews and focused group discussion of land lord associations in the CDA areas provided collaborator platform for decision-making. Water stagnation in primary open drainage channels and natural retention ponds in framing wetlands is traceable to frequent of climate change induced tidal influences in recent decades. Rise in water table resulting in septic-tank leakage and water pollution is reported to be responsible for the increase in the water born infirmities documented in primary health centers. This is in addition to unhealthy dumping of solid wastes in the drainage channels. The effect of uncontrolled disposal system renders surface waters and underground water systems unsafe for human and recreational use; destroys biotic life; and poisons the fragile sand barrier-lagoon urban ecosystems. Cluster decentralized system was conceptualized to service 255 households. Stakeholders agreed on public-private partnership initiative for efficient wastewater service delivery.

Keywords: health, infrastructure, management, septage, well-being

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

Abstract:

This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

Procedia PDF Downloads 118

Authors: Falak Nawaz

Abstract:

The Climate Change Vulnerability and Capacity Assessment carried out in the coastal regions of Thatta and Malir districts underscore the potential risks and challenges associated with climate change affecting water resources. This study was conducted by the author using participatory rural appraisal tools, with a greater focus on conducting focus group discussions, direct observations, key informant interviews, and other PRA tools. The assessment delves into the specific impacts of climate change along the coastal belt, concentrating on aspects such as rising sea levels, depletion of freshwater, alterations in precipitation patterns, fluctuations in water table levels, and the intrusion of saltwater into rivers. These factors have significant consequences for the availability and quality of water resources in coastal areas, manifesting in frequent migration and alterations in agriculture-based livelihood practices. Furthermore, the assessment assesses the adaptive capacity of communities and organizations in these coastal regions to effectively confront and alleviate the effects of climate change on water resources. It considers various measures, including infrastructure enhancements, water management practices, adjustments in agricultural approaches, and disaster preparedness, aiming to bolster adaptive capacity. The study's findings emphasize the necessity for prompt actions to address identified vulnerabilities and fortify the adaptive capacities of Sindh's coastal areas. This calls for comprehensive strategies and policies promoting sustainable water resource management, integrating climate change considerations, and providing essential resources and support to vulnerable communities.

Keywords: climate, climate change adaptation, disaster reselience, vulnerability, capacity, assessment

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

Abstract:

In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

Procedia PDF Downloads 369