Search results for: data driven decision making

Authors: Fleura Shkëmbi, Valbona Treska

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In elementary school, we discover that a metaphor is a decorative linguistic device just for poets. But now that we know, it's also a crucial tactic that individuals employ to understand the universe, from fundamental ideas like time and causation to the most pressing societal challenges today. Metaphor is the use of language to refer to something other than what it was originally intended for or what it "literally" means in order to suggest a similarity or establish a connection between the two. People do not identify metaphors as relevant in their decisions, according to a study on metaphor and its effect on decision-making; instead, they refer to more "substantive" (typically numerical) facts as the basis for their problem-solving decision. Every day, metaphors saturate our lives via language, cognition, and action. They argue that our conceptions shape our views and interactions with others and that concepts define our reality. Metaphor is thus a highly helpful tool for both describing our experiences to others and forming notions for ourselves. In therapeutic contexts, their shared goal appears to be twofold. The cognitivist approach to metaphor regards it as one of the fundamental foundations of human communication. The benefits and disadvantages of utilizing the metaphor differ depending on the target domain that the metaphor portrays. The challenge of creating messages and surroundings that affect customers' notions of abstract ideas in a variety of industries, including health, hospitality, romance, and money, has been studied for decades in marketing and consumer psychology. The aim of this study is to examine, through a systematic literature review, the role of the metaphor in communication and in advertising. This study offers a selected analysis of this literature, concentrating on research on customer attitudes and product appraisal. The analysis of the data identifies potential research questions. With theoretical and applied implications for marketing, design, and persuasion, this study sheds light on how, when, and for whom metaphoric communications are powerful.

Keywords: metaphor, communication, advertising, cognition, action

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Authors: Innocent Uzougbo Onwuegbuzie, Siene Elizabeth Eke

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This study investigates cybersecurity challenges and solutions in managing Information and Communication Technology (ICT) at the Federal Polytechnic, Ado-Ekiti, South-West Nigeria. The rapid evolution of ICT has revolutionized organizational operations and impacted various sectors, including education, healthcare, and finance. While ICT advancements facilitate seamless communication, complex data analytics, and strategic decision-making, they also introduce significant cybersecurity risks such as data breaches, ransomware, and other malicious attacks. These threats jeopardize the confidentiality, integrity, and availability of information systems, necessitating robust cybersecurity measures. The primary aim of this research is to identify prevalent cybersecurity challenges in ICT management, evaluate their impact on the institution's operations, and assess the effectiveness of current cybersecurity solutions. Adopting a quantitative research approach, data was collected through surveys and structured questionnaires from students, staff, and IT professionals at the Federal Polytechnic, Ado-Ekiti. The findings underscore the critical need for continuous investment in cybersecurity technologies, employee and student training, and regulatory compliance to mitigate evolving cyber threats. This research contributes to bridging the knowledge gap in cybersecurity management and provides valuable insights into effective strategies and technologies for safeguarding ICT systems in educational institutions. The study's objectives are to enhance the security posture of the Federal Polytechnic, Ado-Ekiti, in an increasingly digital world by identifying and addressing the cybersecurity challenges faced by its ICT management.

Keywords: cybersecurity challenges, cyber threat mitigation, federal polytechnic Ado-Ekiti, ICT management

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

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Authors: Ahcene Boucied

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In this paper, a case study is conducted to analyze the effectiveness of web pages designed in Barbados for the tourism and hospitality industry. The assessment is made from two perspectives: to understand how the Barbados’ tourism industry is using the web, and to identify the effect of information technology on economic issues. In return, this is used: (a) to provide interested parties with accurate information and marketing insight necessary for decision making for electronic commerce/e-commerce, and (b) to demonstrate pragmatic difficulties in searching and designing web pages.

Keywords: segmentation, tourism stakeholders, destination marketing, case study

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Arun Prasad Jaganathan

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In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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Authors: Berna Yaylalı, Isin Can Traunmüller

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This paper explores the emergent bottom-up practices in the fields of architecture and urban design within comparative perspectives of two cities. As a temporary, easily affordable intervention that gives the possibility of transforming neglected spaces into vibrant public spaces, tactical urbanism, together with creative place-making strategies, presents alternative ways of creating sustainable developments in derelict and underused areas. This study examines the potential of social and physical developments through a reading of case studies of two creative spatial practices: a pop-up garden transformed from an unused derelict space in Favoriten, Vienna, and an urban community garden in Kuzguncuk, Istanbul. Two cities are chosen according to their multicultural population and diversity. Istanbul was selected as a design city by UNESCO Creative Cities Network in 2017, and Vienna was declared an open and livable city by its local government. This research will use media archives and reports, interviews with locals and local governments, site observations, and visual recordings as methods to provide a critical reading on creative public spaces from the view of local users in these neighborhoods. Reflecting on these emergent ways, this study aims at discussing the production process of tactile urbanism with the practices of locals and the decision-making process with cases from İstanbul and Vienna. The comparison between their place-making strategies in tactical urbanism will give important insights for future developments.

Keywords: creative city, tactical urbanism, neglected area, public space

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Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

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Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Shawna M. Margesson

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This research study seeks to explore the lived experience of peer support workers (PSWs) in a peer-led non-governmental organization in Denver, Colorado, USA. The Colorado Mental Wellness Network offers supportive wellness recovery services such as wellness recovery action plans (WRAP), advocacy trainings for anti-stigma campaigns, and PSWs to work with and for consumers in the community. This study suggests that a peer-run environment is a unique community setting for PSWs to work given all employees are living in mental wellness recovery. Little has been documented about PSWs' personal accounts of working within a recovery-oriented organization and their first-person accounts to working with consumers. The importance of this study is to provide an ethnographic account of both subjects; the lived experiences of PSWs of both organizational and consumer-driven recovery. This study seeks to add to the literature and the social work profession the personal accounts of PSWs as they provide services to others like themselves. It also will provide an additional lens to view the peer-driven movement in mental health and wellness recovery.

Keywords: peer to peer movement, mental health, ethnography, peer support workers

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Authors: Yuguang Gao, Mingtao Deng

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The integration of independently operating hospitals into a unified healthcare service system has become a strategic imperative in the pursuit of hospitals’ high-quality development. Central to the concept of group governance over such transformation, exemplified by a collaborative medical alliance, is the delineation of shared value, vision, and goals. Given the inherent disparity in capabilities among hospitals within the alliance, particularly in the treatment of different diseases characterized by Disease Related Groups (DRG) in terms of effectiveness, efficiency and resource utilization, this study aims to address the centralized decision-making of intra-hospital patient referral within the medical alliance to enhance the overall production and quality of service provided. We first introduce the notion of production utility, where a higher production utility for a hospital implies better performance in treating patients diagnosed with that specific DRG group of diseases. Then, a Discrete-Event Simulation (DES) framework is established for patient referral among hospitals, where patient flow modeling incorporates a queueing system with fixed capacities for each hospital. The simulation study begins with a two-member alliance. The pivotal strategy examined is a "whether-to-refer" decision triggered when the bed usage rate surpasses a predefined threshold for either hospital. Then, the decision encompasses referring patients to the other hospital based on DRG groups’ production utility differentials as well as bed availability. The objective is to maximize the total production utility of the alliance while minimizing patients’ average length of stay and turnover rate. Thus the parameter under scrutiny is the bed usage rate threshold, influencing the efficacy of the referral strategy. Extending the study to a three-member alliance, which could readily be generalized to multi-member alliances, we maintain the core setup while introducing an additional “which-to-refer" decision that involves referring patients with specific DRG groups to the member hospital according to their respective production utility rankings. The overarching goal remains consistent, for which the bed usage rate threshold is once again a focal point for analysis. For the two-member alliance scenario, our simulation results indicate that the optimal bed usage rate threshold hinges on the discrepancy in the number of beds between member hospitals, the distribution of DRG groups among incoming patients, and variations in production utilities across hospitals. Transitioning to the three-member alliance, we observe similar dependencies on these parameters. Additionally, it becomes evident that an imbalanced distribution of DRG diagnoses and further disparity in production utilities among member hospitals may lead to an increase in the turnover rate. In general, it was found that the intra-hospital referral mechanism enhances the overall production utility of the medical alliance compared to individual hospitals without partnership. Patients’ average length of stay is also reduced, showcasing the positive impact of the collaborative approach. However, the turnover rate exhibits variability based on parameter setups, particularly when patients are redirected within the alliance. In conclusion, the re-structuring of diagnostic disease groups within the medical alliance proves instrumental in improving overall healthcare service outcomes, providing a compelling rationale for the government's promotion of patient referrals within collaborative medical alliances.

Keywords: collaborative medical alliance, disease related group, patient referral, simulation

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Feyi Olorunshola

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Over the last few years, the senior travel market has been noted for its potential in the wider tourism industry. The tourism sector includes the hotel and hospitality, travel, transportation, and several other subdivisions to make it economically viable. In particular, the hotel attracts a substantial part of the expenditure in tourism activities as when people plan to travel, suitable accommodation for relaxation, dining, entertainment and so on is paramount to their decision-making. The global retail value of the hotel as of 2018 was significant for tourism. But, despite indications of the hotel to the tourism industry at large, very few empirical studies are available to establish how this sector can leverage on the senior demographic to achieve competitive advantage. Predominantly, studies on the mature market have focused on destination tourism, with a limited investigation on the hotel which makes a significant contribution to tourism. Also, several scholarly studies have demonstrated the importance of the senior travel market to the hotel, yet there is very little empirical research in the field which has explored the driving factors that will become the accepted new normal for this niche segment post-pandemic. Giving that the hotel already operates in a highly saturated business environment, and on top of this pre-existing challenge, the ongoing global health outbreak has further put the sector in a vulnerable position. Therefore, the hotel especially the full-service luxury category must evolve rapidly for it to survive in the current business environment. The hotel can no longer rely on corporate travelers to generate higher revenue since the unprecedented wake of the pandemic in 2020 many organizations have invented a different approach of conducting their businesses online, therefore, the hotel needs to anticipate a significant drop in business travellers. However, the rooms and the rest of the facilities must be occupied to keep their business operating. The way forward for the hotel lies in the leisure sector, but the question now is to focus on the potential demographics of travelers, in this case, the seniors who have been repeatedly recognized as the lucrative market because of increase discretionary income, availability of time and the global population trends. To achieve the study objectives, a mixed-method approach will be utilized drawing on both qualitative (netnography) and quantitative (survey) methods, cognitive and decision-making theories (means-end chain) and competitive theories to identify the salient drivers explaining senior hotel choice and its influence on their decision-making. The target population are repeated seniors’ age 65 years and over who are UK resident, and from the top tourist market to the UK (USA, Germany, and France). Structural equation modelling will be employed to analyze the datasets. The theoretical implication is the development of new concepts using a robust research design, and as well as advancing existing framework to hotel study. Practically, it will provide the hotel management with the latest information to design a competitive marketing strategy and activities to target the mature market post-pandemic and over a long period.

Keywords: competitive advantage, covid-19, full-service hotel, five-star, luxury hotels

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Authors: F. Gökgöz, M. E. Atmaca

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Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: electricity market, portfolio optimization, risk management in electricity market, sharpe ratio

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Authors: C. Pacheco, A. Cipriano

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A new concept of response system is proposed for filling the gap that exists in reducing vulnerability during immediate response to natural disasters. Real Time Early Response Systems (RTERSs) incorporate real time information as feedback data for closing control loop and for generating real time situation assessment. A review of the state of the art works that fit the concept of RTERS is presented, and it is found that they are mainly focused on manmade disasters. At the same time, in response phase of natural disaster management many works are involved in creating early warning systems, but just few efforts have been put on deciding what to do once an alarm is activated. In this context a RTERS arises as a useful tool for supporting people in their decision making process during natural disasters after an event is detected, and also as an innovative context for applying well-known automation technologies and automatic control concepts and tools.

Keywords: disaster management, emergency response system, natural disasters, real time

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Authors: Zain Khan, Steve Ahn, Kathy Monypenny, James Fink

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In Australian public hospitals, there were approximately 34,000 reported inpatient falls between 2015 to 2016. The gold standard for diagnosing intracranial injury is non-contrast enhanced brain computed tomography (CTB). Over a three-month timeframe, a total of one hundred and eighty (180) falls were documented between the hours of 4pm and 8am at a large metro hospital. Only three (3) of these scans demonstrated a positive intra-cranial finding. The rationale for scanning varied. The common indications included a fall with head strike, the presence of blood thinning medication, loss of consciousness, reduced Glasgow Coma Scale (GCS), vomiting and new neurological findings. There are several validated tools to aid in decision-making around ordering CTB scans in the acute setting, but no such accepted tool exists for the inpatient space. With further data collection, spanning a greater length of time and through involving multiple centres, work can be done towards generating such a tool that can be utilized for inpatient falls.

Keywords: computed tomography, falls, inpatient, intracranial hemorrhage

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Authors: Xuan Linh Nguyen, Tien Yin Chou, Yao Min Fang, Feng Cheng Lin, Thanh Van Hoang, Yin Min Huang

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In Vietnam, land use planning is the most important and powerful tool of the government for sustainable land use and land management. Nevertheless, many of land use planning locations are facing protests from surrounding households due to environmental impacts. In addition, locations are planned completely based on the subjective decisions of planners who are unsupported by tools or scientific methods. Hence, this research aims to assist the decision-makers in evaluating the rationality of planning locations by developing a Spatial Decision Support System (SDSS) using approaches of Geographic Information System (GIS)-based technology, Analytic Hierarchy Process (AHP) multi-criteria-based technique and Fuzzy set theory. An ArcGIS Desktop add-ins named SDSS-LUPA was developed to support users analyzing data and presenting results in friendly format. The Fuzzy-AHP method has been utilized as analytic model for this SDSS. There are 18 planned locations in Hung Ha district (Thai Binh province, Vietnam) as a case study. The experimental results indicated that the assessment threshold higher than 0.65 while the 18 planned locations were irrational because of close to residential areas or close to water sources. Some potential sites were also proposed to the authorities for consideration of land use planning changes.

Keywords: analytic hierarchy process, fuzzy set theory, land use planning, spatial decision support system

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Authors: Saba Ebrahimi, Hedieh Ashrafi

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Predicting the cover type of forests is a challenge for natural resource managers. In this project, we aim to perform a comprehensive comparative study of two well-known classification methods, support vector machine (SVM) and decision tree (DT). The comparison is first performed among different types of each classifier, and then the best of each classifier will be compared by considering different evaluation metrics. The effect of boosting and bagging for decision trees is also explored. Furthermore, the effect of principal component analysis (PCA) and feature selection is also investigated. During the project, the forest cover-type dataset from the remote sensing and GIS program is used in all computations.

Keywords: classification methods, support vector machine, decision tree, forest cover-type dataset

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Seher Arslankaya, Bahar Uludağ

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Meeting the needs and demands of customers and pleasing the customers are important requirements for companies in food sectors where the growth of competition is significantly unpredictable. Customer satisfaction is also one of the key concepts which is mainly driven by wide range of customer preference and expectation upon products and services introduced and delivered to them. In order to meet the customer demands, the companies that engage in food sectors are expected to have a well-managed set of Total Quality Management (TQM), which sets out to improve quality of products and services; to reduce costs and to increase customer satisfaction by restructuring traditional management practices. It aims to increase customer satisfaction by meeting (their) customer expectations and requirements. The achievement would be determined with the help of customer satisfaction surveys, which is done to obtain immediate feedback and to provide quick responses. In addition, the surveys would also assist the making of strategic planning which helps to anticipate customer future needs and expectations. Meanwhile, periodic measurement of customer satisfaction would be a must because with the better understanding of customers perceptions from the surveys (done by questioners), the companies would have a clear idea to identify their own strengths and weaknesses that help the companies keep their loyal customers; to stand in comparison toward their competitors and map out their future progress and improvement. In this study, we propose a survey based on customer satisfaction measurement method and its statistical analysis for sales and logistic activities of food firms. Customer satisfaction would be discussed in details. Furthermore, after analysing the data derived from the questionnaire that applied to customers by using the SPSS software, various results obtained from the application would be presented. By also applying ANOVA test, the study would analysis the existence of meaningful differences between customer demographic proportion and their perceptions. The purpose of this study is also to find out requirements which help to remove the effects that decrease customer satisfaction and produce loyal customers in food industry. For this purpose, the customer complaints are collected. Additionally, comments and suggestions are done according to the obtained results of surveys, which would be useful for the making-process of strategic planning in food industry.

Keywords: customer satisfaction measurement and analysis, food industry, SPSS, TQM

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Authors: B. Sudarsan Baskar, S. Pooja Pragati, S. Raj Kumar

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The cost effectiveness in aircraft maintenance is of high privilege in the recent days. The cost effectiveness can be effectively made when line maintenance activities are incorporated at airports during Turn around time (TAT). The present work outcomes the shortcomings that affect the dispatching of the aircrafts, aiming at high fleet operability and low maintenance cost. The operational and cost constraints have been discussed and a suggestive alternative mechanism is proposed. The possible allocation of all deferred maintenance tasks to a set of all deferred maintenance tasks to a set of suitable airport resources have termed as alternative and is discussed in this paper from the data’s collected from the kingfisher airlines.

Keywords: decision support system, aircraft maintenance planning, maintenance-cost, RUL(remaining useful life), logistics, supply chain management

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

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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: Johannes Gantner, Michael Held, Matthias Fischer

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The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Jan Van Uden

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The paper reviews classical agency-theory and its contributions to the analysis of complex business negotiations and gives an approach for the modification of the basic agency-model in order to examine the negotiation specific dimensions of agency-problems. By illustrating fundamental potentials for the modification of agency-theory in context of business negotiations the paper highlights recent empirical research that investigates agent-based negotiations and inter-team constellations. A general theoretical analysis of complex negotiation would be based on a two-level approach. First, the modification of the basic agency-model in order to illustrate the organizational context of business negotiations (i.e., multi-agent issues, common-agencies, multi-period models and the concept of bounded rationality). Second, the application of the modified agency-model on complex business negotiations to identify agency-problems and relating areas of risk in the negotiation process. The paper is placed on the first level of analysis – the modification. The method builds on the one hand on insights from behavior decision research (BRD) and on the other hand on findings from agency-theory as normative directives to the modification of the basic model. Through neoclassical assumptions concerning the fundamental aspects of agency-relationships in business negotiations (i.e., asymmetric information, self-interest, risk preferences and conflict of interests), agency-theory helps to draw solutions on stated worst-case-scenarios taken from the daily negotiation routine. As agency-theory is the only universal approach able to identify trade-offs between certain aspects of economic cooperation, insights obtained provide a deeper understanding of the forces that shape business negotiation complexity. The need for a modification of the basic model is illustrated by highlighting selected issues of business negotiations from agency-theory perspective: Negotiation Teams require a multi-agent approach under the condition that often decision-makers as superior-agents are part of the team. The diversity of competences and decision-making authority is a phenomenon that overrides the assumptions of classical agency-theory and varies greatly in context of certain forms of business negotiations. Further, the basic model is bound to dyadic relationships preceded by the delegation of decision-making authority and builds on a contractual created (vertical) hierarchy. As a result, horizontal dynamics within the negotiation team playing an important role for negotiation success are therefore not considered in the investigation of agency-problems. Also, the trade-off between short-term relationships within the negotiation sphere and the long-term relationships of the corporate sphere calls for a multi-period perspective taking into account the sphere-specific governance-mechanisms already established (i.e., reward and monitoring systems). Within the analysis, the implementation of bounded rationality is closely related to findings from BRD to assess the impact of negotiation behavior on underlying principal-agent-relationships. As empirical findings show, the disclosure and reservation of information to the agent affect his negotiation behavior as well as final negotiation outcomes. Last, in context of business negotiations, asymmetric information is often intended by decision-makers acting as superior-agents or principals which calls for a bilateral risk-approach to agency-relations.

Keywords: business negotiations, agency-theory, negotiation analysis, interteam negotiations

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Authors: Katalin Kovacs

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In most forms of violence the perpetrators intend to hide their identities. Terrorism is different. Terrorist groups often take responsibility for their attacks, and consequently they reveal their identities. This unique characteristic of terrorism has been largely overlooked, and scholars are still puzzled as to why terrorist groups claim responsibility for their attacks. Certainly, the claim of responsibility is worth analysing. It would help to have a clearer picture of what terrorist groups try to achieve and how, but also to develop an understanding of the strategic planning of terrorist attacks and the message the terrorists intend to deliver. The research aims to answer the question why terrorist groups choose to claim responsibility for some of their attacks and not for others. In order to do so the claim of responsibility is considered to be a tactical choice, based on the assumption that terrorists weigh the costs and benefits of claiming responsibility. The main argument is that terrorist groups do not claim responsibility in cases when there is no tactical advantage gained from claiming responsibility. The idea that the claim of responsibility has tactical value offers the opportunity to test these assertions using a large scale empirical analysis. The claim of responsibility as a tactical choice depends on other tactical choices, such as the choice of target, the internationality of the attack, the number of victims and whether the group occupies territory or operates as an underground group. The structure of the terrorist groups and the level of decision making also affects the claim of responsibility. Terrorists on the lower level are less disciplined than the leaders. This means that the terrorists on lower levels pay less attention to the strategic objectives and engage easier in indiscriminate violence, and consequently they would less like to claim responsibility. Therefore, the research argues that terrorists, who are on a highest level of decision making would claim responsibility for the attacks as those are who takes into account the strategic objectives. As most studies on terrorism fail to provide definitions; therefore the researches are fragmented and incomparable. Separate, isolated researches do not support comprehensive thinking. It is also very important to note that there are only a few researches using quantitative methods. The aim of the research is to develop a new and comprehensive overview of the claim of responsibility based on strong quantitative evidence. By using well-established definitions and operationalisation the current research focuses on a broad range of attributes that can have tactical values in order to determine circumstances when terrorists are more likely to claim responsibility.

Keywords: claim of responsibility, leadership, tactical choice, terrorist group

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Authors: Umit Duru

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The Soil and Water Assessment Tool (SWAT) was tested for prediction of water balance and sediment yield in the Ankara gauged basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT in this region of Turkey. Thirteen years of monthly stream flow, and suspended sediment, data were used for calibration and validation. This research assessed model performance based on differences between observed and predicted suspended sediment yield during calibration (1987-1996) and validation (1982-1984) periods. Statistical comparisons of suspended sediment produced values for NSE (Nash Sutcliffe efficiency), RE (relative error), and R² (coefficient of determination), of 0.81, -1.55, and 0.93, respectively, during the calibration period, and NSE, RE (%), and R² of 0.77, -2.61, and 0.87, respectively, during the validation period. Based on the analyses, SWAT satisfactorily simulated observed hydrology and sediment yields and can be used as a tool in decision making for water resources planning and management in the basin.

Keywords: calibration, GIS, sediment yield, SWAT, validation

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Safa Kaka

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As more and more students are travelling to different countries to study and, in particular, to study English, the question of what motivates them to make such a large move has come under question. This is particularly pertinent in the case of Arab students who make up nearly 15% of the foreign student body in the UK. Given that the cultural differences between the UK and Arab nations are extremely wide, the decision to come to this country to study English must be driven by strong motivational forces. Numerous previous studies have considered what motivates foreign students to travel to the UK and other countries for their education or language learning but the specific motivators of Arab students have yet to be explored. This study undertakes to close that gap by examining the concepts and theories of motivation, both in general terms and in relation to English learning and foreign study. 70 Arab students currently studying in the UK were asked to participate in an online questionnaire which asked about their motivations for coming to the UK and for studying and learning English. A further six individuals were interviewed on a face to face basis. The outcomes have indicated that the factors which motivate the decision to come to the UK are similar to those that motivate the desire to learn English. In particular a motivation for self-improvement, career advancement and potential future benefits were cited by a number of respondents. Other indications were the ease of accessibility to the UK as an English speaking country, a motivation to experience different cultures and lifestyles and even political freedoms. Overall the motivations of Arab students were not found to be conspicuously different from those of other foreign students, although it was noted that their motivations did change, both positively and negatively following a period of time in the country. These changes were based on the expectations of the students pre-arrival and their actual experience of the country and its teaching approaches and establishments and were, as indicated both good and bad. The implications for the Arab student population and UK educational establishments are reviewed and future research pathways highlighted.

Keywords: motivation, Arab learners of English, language teaching, applied linguistics

Procedia PDF Downloads 350