Search results for: decision trees

Authors: Joanna Stawska

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The main objective of this article is to examine the impact of interest rates on investments in Poland in the context of financial crisis. The paper also investigates the dependence of bank loans to enterprises on interbank market rates. The article studies the impact of interbank market rate on the level of investments in Poland. Besides, this article focuses on the research of the correlation between the level of corporate loans and the amount of investments in Poland in order to determine the indirect impact of central bank interest rates through the transmission mechanism of monetary policy on the real economy. To achieve the objective we have used econometric and statistical research methods like: econometric model and Pearson correlation coefficient. This analysis suggests that the central bank reference rate inversely proportionally affects the level of investments in Poland and this dependence is moderate. This is also important issue because it is related to preparing of Poland to accession to euro area. The research is important from both theoretical and empirical points of view. The formulated conclusions and recommendations determine the practical significance of the paper which may be used in the decision making process of monetary and economic authorities of the country.

Keywords: central bank, financial crisis, interest rate, investments

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Authors: Asmae Chraibi, Rachid Lghoul, Nabil Rhiati

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In the era of Industry 4.0, enterprises are increasingly employing digital technologies in order to improve their product development processes. This research focuses on the strategic deployment of Product Lifecycle Management (PLM) solutions during production as a key tracker of traceability and digital transformation activities. The study explores the integration of PLM within a larger organizational framework, examining its impact on product lifecycle efficiency, corporation, and innovation. Through a comprehensive analysis of a real case study from the automotive industry, this project evaluates the critical success factors and challenges associated with implementing PLM solutions for digital transformation. Moreover, it explores the synergic relationship between PLM and emerging technologies such as 3D experience and SOLIDWORKS, elucidating their combined potential in optimizing production workflows and enabling data-driven decision-making. The study's findings provide global approaches for firms looking to embark on a digital transformation journey by implementing PLM technologies. This research contributes to a better understanding of how PLM can be effectively used to foster innovation and competitiveness in the changing landscape of modern industry by shining light on best practices, critical considerations, and potential obstacles.

Keywords: product lifecyle management (PLM), industry 4.0, traceability, digital transformation, solution, innovation, 3D experience, SOLIDWORKS

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Authors: Nadia Adnan, Muhammad Mohsin Raza, Latha Ravindran

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Based on the principles above, the study presents an economic model of food waste for consumers, intermediaries, and producers. We discriminate between purchasing and selling, purchases versus customers consumption, and gross output versus sales for each intermediary. To compensate for waste at each level of the supply chain, agents must charge higher sales prices. The research model can produce more accurate predictions about how actions (public regulations or private efforts) to reduce food waste impact markets, including indirect (cascading) effects. With a formal model, researchers demonstrate the uniqueness of these interaction effects and simulate an empirical model calibrated to market characteristics and waste rates in Saudi Arabia. Researchers demonstrate that the effects of waste reduction differ per commodity, depending on supply and demand elasticities, degree of openness to international commerce, and the beginning rates of food loss and waste at each level of the value chain. Because of the consequential effects related to the supply chain, initiatives to minimize food waste will be strengthened in some circumstances and partially countered in others.

Keywords: food loss, food waste, supply chain management, Saudi Arabia, food supply

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Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang

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Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.

Keywords: mental disorder, diagnosis, occupational stress, IT workplace

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Authors: Antonia Tsaknaki

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There are many and divergent views on how the science of translation should be taught in academic institutions or colleges, meaning as an independent study area or as part of Linguistics, Literature or Foreign Languages Departments. A much more debated issue refers to the question of whether translation theory should be included in syllabuses and study programs or the focus should be solely on practicing the profession, that is translating texts. This dissertation examines prevailing views on the significance of translation theory in translation studies in order to design an open course on moodle. Taking into account that there is a remarkable percentage of translation professionals who are self-taught without having any specific studies, the course aims at helping either translation students or professional translators familiarize with concepts, methods and problem-solving strategies that are considered necessary during the process. It is organized in four modules where the learner is guided through a series of topics (register, equivalence, decision-making, level of naturalness, Skopos theory etc); after completing these topics, they are given assignments (further reading) and texts to work on in order to practice the skills obtained. The course does not focus on a specific language pair and therefore is suitable for every individual who needs a theoretical background to boost their performance or for institutions seeking to save classroom time but not at the expense of learners’ skills.

Keywords: MOOCs, moodle, online learning, open courses, translation, translation theory

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Authors: Jennifer E. Lynette

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This study describes the development process of a methodological framework for quality standards used to measure the efficiency and quality of response efforts of trained personnel at emergency events. This paper describes the techniques used to develop the initial framework and its potential application to professions under the broader field of emergency management. The example described in detail in this paper applies the framework specifically to fire response activities by firefighters. Within the quality standards framework, the fire response process is chronologically mapped. Individual variables within the sequence of events are identified. Through in-person data collection, questionnaires, interviews, and the expansion of the incident reporting system, this study identifies and categorizes previously unrecorded variables involved in the response phase of a fire. Following a data analysis of each variable using a quantitative or qualitative assessment, the variables are ranked pertaining to the magnitude of their impact to the event outcome. Among others, key indicators of quality performance in the analysis involve decision communication, resource utilization, response techniques, and response time. Through the application of this framework and subsequent utilization of quality standards indicators, there is potential to increase efficiency in the response phase of an emergency event; thereby saving additional lives, property, and resources.

Keywords: emergency management, fire, quality standards, response

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Jirawan Jitthavech, Vichit Lorchirachoonkul

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A statistical procedure using multiple comparisons test for proportions is proposed for variable selection in a data envelopment analysis (DEA) model. The test statistic in the multiple comparisons is the proportion of efficient decision making units (DMUs) in a DEA model. Three methods of multiple comparisons test for proportions: multiple Z tests with Bonferroni correction, multiple tests in 2Xc crosstabulation and the Marascuilo procedure, are used in the proposed statistical procedure of iteratively eliminating the variables in a backward manner. Two simulation populations of moderately and lowly correlated variables are used to compare the results of the statistical procedure using three methods of multiple comparisons test for proportions with the hypothesis testing of the efficiency contribution measure. From the simulation results, it can be concluded that the proposed statistical procedure using multiple Z tests for proportions with Bonferroni correction clearly outperforms the proposed statistical procedure using the remaining two methods of multiple comparisons and the hypothesis testing of the efficiency contribution measure.

Keywords: Bonferroni correction, efficient DMUs, Marascuilo procedure, Pastor et al. method, 2xc crosstabulation

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Authors: Besik Goginava

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Several days later after the end of 2008 Russo-Georgian War, Venezuela and Nicaragua formally recognized the independence of Abkhazia and South Ossetia. In 2009-10 both countries established diplomatic relations with self-declared republics. It is a paradoxical fact that after neighboring Russia-Georgian conflict territories were internationally recognized by two Latin American states with ongoing territorial disputes. The Venezuela-Guyana territorial dispute which officially began in the early XIX century became conflict-ridden again in the late 1990s and 2000s. Venezuela has long claimed the land which comprises 40% of Guyana’s current territory. Territorial disputes of Nicaragua include dispute with Colombia over Caribbean Islands, with Costa Rica over the San Juan River and maritime dispute with Honduras. Based on historical and analytical research methods the purpose of this paper is to establish the relationship between the recognition of Abkhazia and South Ossetia by Venezuela and Nicaragua and Venezuela’s territorial dispute with Guyana, as well as Nicaragua’s with Colombia, Costa Rica and Honduras. The objective of the study is to investigate the factors that led Venezuela and Nicaragua to formally recognize Georgian conflict territories and how could their own territorial disputes affect on their decision.

Keywords: Latin America, Georgia, Venezuela, Nicaragua, Abkhazia, South Ossetia

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Authors: Rajendra Kumar Isaac, Monisha Isaac

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Climate variability and changes are the emerging challenges for Indian agriculture with the growing population to ensure national food security. A study was conducted to assess the Climatic Change effects in medium to low altitude areas of the Himalayan region causing changes in land use and cereal crop productivity with the various climatic parameters. The rainfall and temperature changes from 1951 to 2013 were studied at four locations of varying altitudes, namely Hardwar, Rudra Prayag, Uttar Kashi and Tehri Garwal. It was observed that there is noticeable increment in temperature on all the four locations. It was surprisingly observed that the mean rainfall intensity of 30 minutes duration has increased at the rate of 0.1 mm/hours since 2000. The study shows that the combined effect of increasing temperature, rainfall, runoff and urbanization at the mid-Himalayan region is causing an increase in various climatic disasters and changes in agriculture patterns. A noticeable change in cropping patterns, crop productivity and land use change was observed. Appropriate adaptation and mitigation strategies are necessary to ensure that sustainable and climate-resilient agriculture. Appropriate information is necessary for farmers, as well as planners and decision makers for developing, disseminating and adopting climate-smart technologies.

Keywords: climate variability, agriculture, land use, mitigation strategies

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Authors: Ahmed Hamzi, Bryan Norman

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Having scribes help document patient records in electronic health record systems can improve hospitalists’ productivity. But hospitals need to determine the optimum number of scribes to hire to maximize scribe cost effectiveness. Scribe attendance uncertainty due to planned and unplanned absences is a primary challenge. This paper presents simulation and analytical models to determine the optimum number of scribes for a hospital to hire. Scribe staffing practices vary from one context to another; different staffing scenarios are considered where having extra attending scribes provides or does not provide additional value and utilizing on-call scribes to fill in for potentially absent scribes. These staffing scenarios are assessed for different scribe revenue ratios (ratio of the value of the scribe relative to scribe costs) ranging from 100% to 300%. The optimum solution depends on the absenteeism rate, revenue ratio, and desired service level. The analytical model obtains solutions easier and faster than the simulation model, but the simulation model is more accurate. Therefore, the analytical model’s solutions are compared with the simulation model’s solutions regarding both the number of scribes hired and cost-effectiveness. Additionally, an Excel tool has been developed to facilitate decision-makers in easily obtaining solutions using the analytical model.

Keywords: hospitalists, workload, optimization cost, economic analysis

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Harry Burton, Alexios Dimitrios Iliadis, Neil Jones, Aaron Saini, Nicola Bystrzonowski, Alexandros Vris, Georgios Pafitanis

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This article portrays the authors’ experience with a complex lower limb bone and soft tissue defect, following chronic osteomyelitis and pathological fracture, which was managed by the multidisciplinary orthoplastic team. The decision for functional amputation versus limb salvage was deemed necessary, enhanced by the principles of “spares parts” in reconstructive microsurgery. This case describes a successful use of the osteocutaneous distal tibia turn-over fillet flap that allowed ‘lowering the level of the amputation’ from a through knee to the conventional level of a below-knee amputation to preserve the knee joint function. This case demonstrates the value of ‘spare-parts’ surgery principles and how these concepts refine complex orthoplastic approaches when limb salvage is not possible to enhance function. The osteocutaneous distal tibia turn-over fillet flap is a robust technique for modified BKA reconstructions that provides sufficient bone length to achieve a tough, sensate stump and functional knee joint.

Keywords: osteocutaneous flap, fillet flap, spare-parts surgery, Below knee amputation

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Authors: Xiaosheng Chen, Jingjing Chen, Phil Reed, Dan Zhang

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Conscious intention can be a promising point cut to grasp consciousness and orient voluntary action. The current study adopted a random ratio (RR), yoked random interval (RI) reinforcement learning schedule instead of the previous highly repeatable and single decision point paradigms, aimed to induce voluntary action with the conscious intention that evolves from the interaction between short-range-intention and long-range-intention. Readiness potential (RP) -like-EEG amplitude and inter-trial-EEG variability decreased significantly prior to voluntary action compared to cued action for inter-trial-EEG variability, mainly featured during the earlier stage of neural activities. Notably, (RP) -like-EEG amplitudes decreased significantly prior to higher RI-reward rates responses in which participants formed a higher plane of conscious intention. The present study suggests the possible contribution of conscious intention-based processes to the neural activities from the earlier stage prior to voluntary action on reinforcement leanring schedule.

Keywords: Reinforcement leaning schedule, voluntary action, EEG, conscious intention, readiness potential

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Authors: Eisa A. Alsafran, Francis T. Edum-Fotwe, Wayne E. Lord

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The degree to which a public client actively participates in Public Private Partnership (PPP) schemes, is seen as a determinant of the success of the arrangement, and in particular, efficiency in the delivery of the assets of any infrastructure development. The asset delivery is often an early barometer for judging the overall performance of the PPP. Currently, there are no defined descriptors for the degree of such participation. The lack of defined descriptors makes the association between the degree of participation and efficiency of asset delivery, difficult to establish. This is particularly so if an optimum effect is desired. In addition, such an association is important for the strategic decision to embark on any PPP initiative. This paper presents a conceptual model of different levels of participation that characterise PPP schemes. The modelling was achieved by a systematic review of reported sources that address essential aspects and structures of PPP schemes, published from 2001 to 2015. As a precursor to the modelling, the common areas of Public Client Participation (PCP) were investigated. Equity and risk emerged as two dominant factors in the common areas of PCP, and were therefore adopted to form the foundation of the modelling. The resultant conceptual model defines the different states of combined PCP. The defined states provide a more rational basis for establishing how the degree of PCP affects the efficiency of asset delivery in PPP schemes.

Keywords: asset delivery, infrastructure development, public private partnership, public client participation

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Authors: Cihat Aşan

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Istanbul Strait is a crucial and narrow waterway, not only having a role in linking two continents but also has a crossover mission for the petroleum, which is the biggest energy resource, between its supply and demand sources. Besides its substantial features, sensitivities like around 18 million populations in surroundings, military facilities, ports, oil lay down areas etc. also brings the high risk to use of Istanbul Strait. Based on the statistics of Turkish Ministry of Transportation, Maritime and Communication, although the number of vessel passage in Istanbul Strait is declining, tonnage of hazardous and flammable cargo like oil and chemical transportation is increasing and subsequently the risk of oil pollution, loss of life and property is also rising. Based on the mentioned above; it is crucial to be prepared for the initial and subsequent response to eventual ship sourced oil spill which may cause to block the Strait for an unbearable duration. In this study; preconditioned Istanbul Strait sensitive areas studies has been taken into account and possible oil spill scenario is loaded to PISCES 2 (Potential Incident Simulation Control and Evaluation System) decision support system for the determined specific sea area. Consequences of the simulation like oil expanding process, required number and types of assets to response, had in hand and evaluated.

Keywords: Istanbul strait, oil spill, PISCES simulator, initial response

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Authors: Vhuhwavho Gadisi, Rebecca Alowo, German Nkhonjera

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It has been noted that technical programming for handling groundwater resources is not accessible. The lack of these systems hinders groundwater management processes necessary for decision-making through monitoring and evaluation regarding the Jukskei River of the Crocodile River (West) Basin in Johannesburg, South Africa. Several challenges have been identified in South Africa's Jukskei Catchment concerning groundwater management. Some of those challenges will include the following: Gaps in data records; there is a need for training and equipping of monitoring staff; formal accreditation of monitoring capacities and equipment; there is no access to regulation terms (e.g., meters). Taking into consideration necessities and human requirements as per typical densities in various regions of South Africa, there is a need to construct several groundwater level monitoring stations in a particular segment; the available raw data on groundwater level should be converted into consumable products for example, short reports on delicate areas (e.g., Dolomite compartments, wetlands, aquifers, and sole source) and considering the increasing civil unrest there has been vandalism and theft of groundwater monitoring infrastructure. GIS was employed at the catchment level to plot the relationship between those identified groundwater parameters in the catchment area and the identified borehole. GIS-based maps were designed for groundwater monitoring to be pretested on one borehole in the Jukskei catchment. This data will be used to establish changes in the borehole compared to changes in the catchment area according to identified parameters.

Keywords: GIS, monitoring, Jukskei, catchment

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Authors: Rhoann Kerh, Chen-Fu Chien, Kuo-Yi Lin

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In the era of rapidly increasing notebook market, consumer electronics manufacturers are facing a highly dynamic and competitive environment. In particular, the product appearance is the first part for user to distinguish the product from the product of other brands. Notebook product should differ in its appearance to engage users and contribute to the user experience (UX). The UX evaluates various product concepts to find the design for user needs; in addition, help the designer to further understand the product appearance preference of different market segment. However, few studies have been done for exploring the relationship between consumer background and the reaction of product appearance. This study aims to propose a data mining framework to capture the user’s information and the important relation between product appearance factors. The proposed framework consists of problem definition and structuring, data preparation, rules generation, and results evaluation and interpretation. An empirical study has been done in Taiwan that recruited 168 subjects from different background to experience the appearance performance of 11 different portable computers. The results assist the designers to develop product strategies based on the characteristics of consumers and the product concept that related to the UX, which help to launch the products to the right customers and increase the market shares. The results have shown the practical feasibility of the proposed framework.

Keywords: consumers decision making, product design, rough set theory, user experience

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Authors: Muhammad Umar

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Safety and Assets management is considering a backbone of every department. GIS in the Railway become very important to Manage Assets and Security through Digital Maps and Web based GIS Maps. It provides a complete frame of work to the organization for the management of assets. Pakistan Railway is the most common and safest mode of traveling in Pakistan. Due to ever-increasing demand of transporting huge amount of information generated from various sources and this information must be accurate. This creates problems for Passengers and Administration that causes finical and time loss. GIS Solve this problem by Digital Maps & Database. It provides you a real time Spatial and Statistical analysis that helps you to communicate and exchange the information in a sophisticated way to the users. GIS Based Web system provides a facility to different end user to make query at a time as per requirements. This GIS System provides an advancement in an organization for a complete Monitoring, Safety and Decision System for tracks, Stations and Junctions that further use for the Analysis of different areas i.e. analysis of tracks, junctions and Stations in case of reconstruction, Rescue for rail accidents and Natural disasters .This Research work helps to reduce the financial loss and reduce human mistakes helps you provide a complete security and Management system of assets.

Keywords: Geographical Information System (GIS) for assets management, geo spatial database, railway assets management, Pakistan

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Authors: Aleksandra Majewska

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The article analyses the impact of Western sanctions on Russian rhythmic gymnastics since the outbreak of war in Ukraine. The chronological presentation of events shows how international political tensions and economic sanctions have affected the organisation of competitions, training and the careers of athletes. The article outlines the key moments and decisions that have changed the landscape of Russian sport, including the decision to change the citizenship made by some gymnasts in order to continue competing in international competitions. Russia strongly opposes participation in competitions without its flag and anthem while maintaining the view that Russian gymnasts are crucial to the prestige of rhythmic gymnastics in the world. In response to the sanctions, Russia created its own rules for rhythmic gymnastics, according to which they now compete domestically. Furthermore, this sport in Russia is strongly linked to politics, which further emphasises its importance in the national and international context. The information collected derives from numerous interviews with Russian athletes, coaches and other people, which are available only in the Russian language. The findings highlight the significant difficulties Russian athletes have faced due to their isolation in the international arena and the adaptive strategies adopted by Russia in the face of these challenges. The article makes an important contribution to understanding the consequences of global politics on the world of sport and the fate of individual athletes.

Keywords: sport, gymnastics, war in Ukraine, sanctions

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Authors: Mohammed Ali Faqeeh

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SCADA System Alarms Optimization Process has been introduced recently and applied accordingly in different implemented stages. First, MODBUS communication protocols between RTU/SCADA were improved at the level of I/O points scanning intervals. Then, some of the technical issues related to manufacturing limitations were resolved. Afterward, another approach was followed to take a decision on the configured alarms database. So, a couple of meetings and workshops were held among all system stakeholders, which resulted in an agreement of disabling unnecessary (Diagnostic) alarms. Moreover, a leap forward step was taken to segregate the SCADA Operator Graphics in a way to show only process-related alarms while some other graphics will ensure the availability of field alarms related to maintenance and engineering purposes. This overall system management and optimization have resulted in a huge effective impact on all operations, maintenance, and engineering. It has reduced unneeded open tickets for maintenance crews which led to reduce the driven mileages accordingly. Also, this practice has shown a good impression on the operation reactions and response to the emergency situations as the SCADA operators can be staying much vigilant on the real alarms rather than gets distracted by noisy ones. SCADA System Alarms Optimization process has been executed utilizing all applicable in-house resources among engineering, maintenance, and operations crews. The methodology of the entire enhanced scopes is performed through various stages.

Keywords: SCADA, RTU Communication, alarm management system, SCADA alarms, Modbus, DNP protocol

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Authors: E. O. Aluta, C. A. Booth, D. G. Proverbs, T. Appleby

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Challenges in the effective management of potable water have attracted global attention in recent years and remain many world regions’ major priorities. Scarcity and unavailability of potable water may potentially escalate poverty, obviate democratic expression of views and militate against inter-sectoral development. These challenges contra-indicate the inherent potentials of the resource. Thus, while creation of poverty may be regarded as a broad-based problem, it is capable of reflecting life-span reduction diseases, the friction of interests manifesting in threats and warfare, the relegation of democratic principles for authoritarian definitions and Human Rights abuse. The challenges may be identified as manifestations of ineffective management of potable water resource and therefore, regarded as major problems in environmental protection. In reaction, some nations have re-examined their laws and policies, while others have developed innovative projects, which seek to ameliorate difficulties of providing sustainable potable water. The problems resonate in Nigeria, where the legal framework supporting the supply and management of potable water has been criticized as ineffective. This has impacted more on rural community members, often regarded as ‘voiceless’. At that level, the participation of non-state actors has been identified as an effective strategy, which can improve water supply. However, there are indications that there is no pragmatic application of this, resulting in over-centralization and top-down management. Thus, this study focuses on how the participatory process may enable the development of participatory water governance framework, for use in Nigeria rural communities. The Rural Advisory Board (RAB) is proposed as a governing body to promote proximal relationships, institute democratisation borne out of participation, while enabling effective accountability and information. The RAB establishes mechanisms for effectiveness, taking into consideration Transparency, Accountability and Participation (TAP), advocated as guiding principles of decision-makers. Other tools, which may be explored in achieving these are, Laws and Policies supporting the water sector, under the direction of the Ministries and Law Courts, which ensure non-violation of laws. Community norms and values, consisting of Nigerian traditional belief system, perceptions, attitude and reality (often undermined in favour of legislations), are relied on to pave the way for enforcement. While the Task Forces consist of community members with specific designation of duties, which ensure compliance and enforceability, a cross-section of community members are assigned duties. Thus, the principle of participation is pragmatically reflected. A review of the literature provided information on the potentials of the participatory process, in potable water governance. Qualitative methodology was explored by using the semi-structured interview as strategy for inquiry. The purposive sampling strategy, consisting of homogeneous, heterogeneous and criterion techniques was applied to enable sampling. The samples, sourced from diverse positions of life, were from the study area of Delta State of Nigeria, involving three local governments of Oshimili South, Uvwie and Warri South. From the findings, there are indications that the application of the participatory process is inhered with empowerment of the rural community members to make legitimate demands for TAP. This includes the obviation of mono-decision making for the supply and management of potable water. This is capable of restructuring the top-down management to a top-down/bottom-up system.

Keywords: participation, participatory process, participatory water governance, rural advisory board

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Authors: Roman Asatryan

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The decision-making processes in Corporate Social Responsibility (CSR) among firms in general and airlines in particular have to do with the benefits that accrue through those investments. The crux of the matter is not whether to invest in CSR or not, but rather, how firms can quantify the benefits derived from such investments. This paper analyzes the cost benefit adjustment strategies for firms in the airline industry in their CSR strategy adoption and implementation. The adjustment strategies identified will enable firms in the airline industry to have a basis for determining the worth of such CSR investments. This paper discusses the cost and benefit analysis model in order to understand the ways airlines can reduce costs and increase returns on CSR, or balance the cost and benefits. The analysis from this study points to the fact that economic concepts especially the CBA are useful, though they are not without challenges. The challenge arises when it is problematic to express the real impact of the externality in monetary terms. The use of rational maximization of the gains may seem to be a rather optimistic goal mainly because of environmental variability, perceptual uncertainty, and imperfect knowledge about the potential externality. This paper concludes that the CBA model gives a basic understanding of the motivations for investing in intangible assets like CSR. Consequently, it sets the tone for formulating relevant hypothesis in empirical studies in investment in CSR in particular and other intangible assets in business operations.

Keywords: cost-benefit analysis, corporate social responsibility, airline industry

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Authors: Dina Ziadlou, Anthony Sunjaya, Joyzen Cortez Ramos, Romario Muñoz Ramos, Richard Dasselaar

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This study aimed to evaluate the opinions of users using digital health technologies to prevent, promote, and maintain their health and well-being with or without the support of a healthcare provider to delineate an overview of the future patient journey while considering the strategic initiatives in the digital transformation era. This research collected the opinions of healthcare clients through a structural questionnaire to collect user accessibility, user knowledge, user experience, user engagement, and personalized medicine to investigate the mindset of the users and illustrate their opinions, expectations, needs, and voices about digital self-care expansion. In the realm of digital transformation, the accessibility of users to the internet, digital health platforms, tools, and mobile health applications have revolutionized the healthcare ecosystem toward nurturing informed and empowered patients who are tech-savvy and can take the initiative to be in charge of their health, involved in medical decision-making, and seek digital health innovations to prevent diseases and promote their healthy lifestyles. Therefore, the future of the patient journey is digital self-care intervention in a healthcare ecosystem where the partnership of patients in healthcare services is tied to their health information and action ownership.

Keywords: digital health, patient engagement, self-care intervention, digital self-care intervention, digital transformation

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Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena

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Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.

Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents

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Authors: Alan (Avi) Kirschenbaum, Carmit Rapaport

Abstract:

The behavior of bystanders in emergencies and disasters have been examined for over 50 years. Such acts have been cited as contributing to saving lives in terms of providing first responder help until official emergency units can arrive. Several reasons have been suggested for this type of behavior but most focused on a broad segment of individual psychological decision-making processes. Recent theoretical evidence suggests that the external factors for such bystander decisions, mainly disaster community based social contexts factors, are also important. We aim to test these competing arguments. Specifically, we examine alternative explanatory perspectives by focusing on self-efficacy as a proxy for the accepted individual psychological case and contrast it with potential bystander characteristics of the individual as well factors as embedded in the social context of the disaster community. To do so, we will utilize a random sampling of the population from a field study of an urban community in Israel that experienced five years of continuous terror attacks. The results strongly suggest that self-efficacy, as well as external factors: preparedness and having skills for intervention during emergencies along with gender best, predict potential helping behaviors. These results broaden our view of bystander behavior and open a window for enhancing this phenomenon as another element in disaster and crisis management.

Keywords: bystander behavior, disasters emergencies, psychological motivation to help, social context for helping

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

Abstract:

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

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Authors: N. S. Yen, T. H. Yang, W. H. Huang, Y. F. Fang, H. W. Cho

Abstract:

Ultimatum game is an experimental paradigm to study human decision making. There are two players, a proposer and a responder, to split a fixed amount of money. According to the traditional economic theory on ultimatum game, proposer should propose the selfish offers to responder as much as possible to maximize proposer’s own outcomes. However, most evidences had showed that people chose more fair offers, hence two hypotheses – fairness favoring and strategic concern were proposed. In current study, we induced the motivation in participants to be either selfish or altruistic, and manipulated the task variables, the stake sizes (NT$100, 1000, 10000) and the share sizes (the 40%, 30%, 20%, 10% of the sum as selfish offers, and the 60%, 70%, 80%, 90% of the sum as altruistic offers), to examine the two hypotheses. The results showed that most proposers chose more fair offers with longer reaction times (RTs) no matter in choosing between the fair and selfish offers, or between the fair and altruistic offers. However, the proposers received explicit self-interest instruction chose more selfish offers accompanied with longer RTs in choosing between the fair and selfish offers. Therefore, the results supported the strategic concern hypothesis that previous proposers choosing the fair offers might be resulted from the fear of rejection by responders. Proposers would become more self-interest if the fear of being rejected is eliminated.

Keywords: ultimatum game, proposer, self-interest, fear of rejection

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Authors: Jun Wang, Ge Zhang

Abstract:

Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

Abstract:

Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

Procedia PDF Downloads 237