Search results for: predictive decision

Authors: Claudio D'Alonzo

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According to recent tendencies, progress on resource efficiency is possible and it will lead to economic, environmental, and social benefits. The passage to a circular economy system, in which all the materials and energy will maintain their value for as long as possible, waste is reduced and only a few resources are used, is one of the most relevant parts of the European Union's environmental policy to develop a sustainable, competitive and low-carbon economy. A definition of circular economy can be found in Decision 1386/2013/EU of the European Parliament and of the Council on a General Union Environment Action Programme to 2020 named “Living well, within the limits of our planet”. The purpose of renewing waste management systems in the UE and making the European model one of the most effective in the world, a revised waste legislative framework entered into force in July 2018. Regarding the Italian legislation, the laws to be modified are the Legislative Decree 3 April 2006, n. 152 and the laws ruling waste management, end-of-waste, by-products and, the regulatory principles regarding circular economy. European rules on end-of-waste are not fully harmonised and so there are legal challenges. The target to be achieved is full consistency between the laws implementing waste and chemicals policies. Only in this way, materials will be safe, fit-for-purpose and designed for durability; additionally, they will have a low environmental impact.

Keywords: circular economy, end-of-waste, legislation, secondary raw materials

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: S. N. S. Thein, H. L. Yang, Z. B. Liu

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There are many modes of transport. Among them, maritime transport is a major transportation mode of international trade. In the Republic of the Union of Myanmar (Burma), water transportation served as one of the most important modes of transport for country's exports and imports. Getting the accurate information and data-gathering activity are the most important aspects for any study field. Therefore, in this research, a historical review of the development of ports in Myanmar and how they have changed had been carried out. All the relevant literature and documents have also been reviewed, studied, and organized. The sources of collected data are from reports, journals, internet, as well as from the publications of authorized organizations and international associations. To get better understanding about real situation of maritime transport and logistics in Myanmar; current condition of existing ports, expansion and on-going projects, and future port development plans are described successively. Hence, the main purpose of this study is to build up a comprehensive picture of maritime transport and logistics, in addition to border trade within ASEAN and Myanmar. It will help for academic researchers, decision makers, and stakeholders for national planning as well as for the local and foreign investors to recognize current situation of maritime transport and logistics in Myanmar.

Keywords: ASEAN, border trade, logistics, maritime transport, ports of Myanmar

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Authors: Zixuan Yang

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This paper presents an analysis of the necessary consideration culture in distributed design through a thorough literature review and case study. The literature review has identified that the need for understanding cultural differences in product design and user evaluations is highlighted by analyzing cross-cultural influences; culture plays a significant role in distributed work, particularly in establishing team cohesion, trust, and credibility early in the project. By applying approaches of Geert Hofstede's dimensions and Fukuyama's trust analysis, a case study of a global design project, i.e., multicultural distributed teamwork solving the problem in terms of reducing the risk of deep vein thrombosis, showcases cultural dynamics, emphasizing trust-building and decision-making. The lessons learned emphasized the importance of cultural awareness, adaptability, and the utilization of scientific theories to enable effective cross-cultural collaborations in global design, providing valuable insights into navigating cultural diversity within design practices.

Keywords: culture, distributed design, global design, Geert Hofstede's dimensions, Fukuyama's trust analysis

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Authors: Mohamed Bin Alhaj, Hexu Liu, Mohammed Sulaiman, Osama Abudayyeh

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An effective facility maintenance management (FMM) system plays a crucial role in improving the quality of services and maintaining the facility in good condition. Current FMM heavily relies on the quality of the data collection function of the FMM systems, at times resulting in inefficient FMM decision-making. The new technology-based crowdsourcing provides great potential to improve the current FMM practices, especially in terms of timeliness and quality of data. This research aims to investigate the feasibility of using new technology-driven crowdsourcing for FMM and highlight its opportunities and challenges. A survey was carried out to understand the human, data, system, geospatial, and automation characteristics of crowdsourcing for an educational campus FMM via social networks. The survey results were analyzed to reveal the challenges and recommendations for the implementation of crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges and opportunities of using crowdsourcing for facility maintenance and providing a road map for applying crowdsourcing technology in FMM. In future work, a conceptual framework will be proposed to support data-driven FMM using social networks.

Keywords: crowdsourcing, facility maintenance management, social networks

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Authors: Effort M. Magoso

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This study analyses urban institutional arrangements and their implications on allocation of wetlands for development purposes in Zimbabwe using a case study of Harare. It was driven by the need to get to the root of the current urban assault on wetlands. The study sought to analyse institutions that influence wetlands governance in Harare, to ascertain level of wetlands loss and to determine the adequacy of the legal and regulatory framework for governing wetlands. Theories of common property resources and of institutions are the paradigms that undergird this study. A qualitative research methodology was employed, while in-depth interviews, observations and document review were used to gather data. The study found out that unchecked infrastructure developments are taking place in the city’s wetlands. Urban institutional arrangements in Harare were exposed as having negative implications on the protection of wetlands. It is the key argument of this study that good institutional arrangements are priceless in the protection of commons such as wetlands. This study also recommends a new framework that has environmentalists and technocrats as the final decision maker in land allocation as the solution to protect wetlands from undue anthropogenic activities.

Keywords: institutional arrangements, common property resources, wetlands, institutions

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Authors: Taha Benarbia, Kay W. Axhausen, Anugrah Ilahi

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Electric car sharing system as ecologic transportation increasing in the world. The complexity of managing electric car sharing systems, especially one-way trips and battery autonomy have direct influence to on supply and demand of system. One must be able to precisely model the demand and supply of these systems to better operate electric car sharing and estimate its effect on mobility management and the accessibility that it provides in urban areas. In this context, our work focus to develop performances optimization model of the system based on discrete event simulation and stochastic Petri net. The objective is to search optimal decisions and management parameters of the system in order to fulfil at best demand while minimizing undesirable situations. In this paper, we present new model of electric cars sharing with relocation based on monitoring system. The proposed approach also help to precise the influence of battery charging level on the behaviour of system as important decision parameter of this complex and dynamical system.

Keywords: electric car-sharing systems, smart mobility, Petri nets modelling, discrete event simulation

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Authors: A. S. CohenMiller, Jenifer Lewis, Gwen McEvoy, Kristy Kelly

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This international, interdisciplinary study presents the first stage of a gender mainstreaming project within one university as a microcosm of society in Kazakhstan to make concrete policy recommendations and set up the potential for new research to monitor change over time. Local, regional, and UN representatives have noted the critical need and interest in gender related issues in Kazakhstan. Gender mainstreaming has been noted as a strategy to understand and address gender equality and equity such as within the academy in exploring and examining organizational/management issues, university decision-making and leadership, assessing the overall academic climate, discrimination issues, hiring and promotion, and student recruitment and retention. This presentation provides preliminary findings from the university gender audit, highlighting key elements for moving forward in gender mainstreaming. The full study analyzes findings from the full gender audit including interview with key stakeholders, time-use surveys, participant-observations and interviews with female students, staff and faculty, and reviews of formal organizational policies and practices.

Keywords: academia, equity, Eurasia, gender audit, gender mainstreaming, Kazakhstan, policy, time-use survey

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Mi Ok Kang

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This study explores the factors that motivate urban high school students from racially/ethnically diverse backgrounds to choose teaching as a future career. It draws on in-depth interviews with high school students of color living in an urban downtown located in an intermountain area in the U.S. Using the factors influencing teaching choice (FIT-Choice) model, this study examines the motivations, mobility experiences, and aspirations of participating high school students who self-identified as Latino/a, Tongan, and Chinese. The study identifies influential factors -both challenges and strengthening effects- that high school students of color experience in their career decision making. The study concludes that self-perceptions of teaching abilities, parental support, social connections, job security, and prior work with children during the internship in K-12 classroom motivated them to be a teacher. Limitations such as financial struggles of parents, the low social status of teaching career, and the low salary and benefit packages in the U.S. are among the factors that cause students to waver in or doubt their career choice.

Keywords: career development, diversifying teaching force, FIT-Choice, high school students of color

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Ch. Sandeep Kumar Subudhi, S. Sivanandam

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Our system is to monitor the human body temperature, blood pressure (BP), Pulse Rate and ECG and tracking the patient location. In our system the body temperature is detected by using LM35 temperature sensor, blood pressure is detected by the BP sensor, pulse rate is detected by the ear plug pulse sensor and the ECG is detected by the three lead ECG sensor in the working environment of the patient. The sensed information is sent to the PIC16F877 microcontroller through signal conditioning circuit. A desired amount of sensor value is set and if it is exceeded preliminary steps should be taken by indication by buzzer. The sensor information will be transmitted from the patient unit to the main controller unit with the help of Zigbee communication medium which is connected with the microcontrollers in the both units. The main controller unit will send those sensor data as well as the location of that patient by the help of GPS module to the observer/doctor. The observer/doctor can receive the SMS sent by GSM module and further decision can be taken. The message is sent to a cell phone using global system mobile (GSM) Modem. MAX232 acts as a driver between microcontroller and modem.

Keywords: LM35, heart beat sensor, ECG Sensor, BP Sensor, Zigbee module, GSM module, GPS module, PIC16F877A microcontroller

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Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

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Authors: Abegunde Linda, Adedeji Oluwatayo, Tope-Ajayi Opeyemi

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Maize constitutes a major agrarian production for use by the vast population but despite its economic importance, it has not been produced to meet the economic needs of the country. Achieving optimum yield in maize can meaningfully be supported by land suitability analysis in order to guarantee self-sufficiency for future production optimization. This study examines land suitability for maize production through the analysis of the physic-chemical variations in soil properties over space using a Geographic Information System (GIS) framework. Physic-chemical parameters of importance selected include slope, landuse, and physical and chemical properties of the soil. Landsat imagery was used to categorize the landuse, Shuttle Radar Topographic Mapping (SRTM) generated the slope and soil samples were analyzed for its physical and chemical components. Suitability was categorized into highly, moderately and marginally suitable based on Food and Agricultural Organisation (FAO) classification using the Analytical Hierarchy Process (AHP) technique of GIS. This result can be used by small scale farmers for efficient decision making in the allocation of land for maize production.

Keywords: AHP, GIS, MCE, suitability, Zea mays

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Authors: Nicholas Marinus Batt, Angus Radford, Khaled Saraya

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Pulmonary Embolus Severity Index (PESI) score is a well-validated decision-making score grading mortality rates (MR) in patients with a suspected or confirmed diagnosis of pulmonary embolism (PE) into 5 classes. Thirty and 90 days MR in class I and II are lower allowing the treatment of these patients as outpatients. In a London District General Hospital (DGH) with mixed ethnicity and high disease burden, we looked at MR at 1, 3, and 7 days of all PESI score classes. Our pilot study of 112 patients showed MR of 0% in class I, II, and III. The current study includes positive Computed Tomographic Scans (CT scans) for PE over the following three years (total of 555). MR was calculated for all PESI score classes at 1, 3 & 7 days. Thirty days MR was additionally calculated to validate the study. Our initial results so far are in line with our pilot studies. Further subgroup analysis accounting for the local co-morbidities and disease burden and its impact on the MR will be undertaken.

Keywords: Pulmonary Embolism (PE), Pulmonary Embolism Severity Index (PESI) score, mortality rate (MR), CT pulmonary artery

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Authors: Fu Lin

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We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

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Authors: Betty Makena, Tsegaye Tadesse, Mark Svoboda

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Global warming has intensified the frequency and intensity of extreme climate disasters and led to unpredictable weather conditions. Consequently, rapid shifts between drought and floods, known as Drought-Flood Abrupt Alteration (DFAA), have become increasingly common. DFAA results in superimposed impacts of drought and floods within a short period, exacerbating the effects of the floods or drought event. Current disaster management plans often overlook DFAA events, as they primarily focus on either floods or drought. Therefore, effectively identifying DFAA events is crucial for developing effective mitigation strategies. This study aims to identify historical DFAA events in Kenya using the Long Cycle Drought-Flood Abrupt Alteration Index (LDFAI). The research will analyze the spatial distribution, temporal variation, and intensity of DFAA events from 1990 to 2023, as well as their socio-economic impacts. Understanding these events is important to develop more effective strategies to address the impacts of DFAA events. Findings from this study will inform decision making to develop coping strategies to mitigate the adverse effects of DFAA in Kenya.

Keywords: abrupt, alteration, drought, floods

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Authors: Stefanie Kasparek

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The United Nations Security Council (UNSC) is probably the most recognized international security organization. It is also profoundly misunderstood and undervalued in its effort to promote peace and security. With the rising involvement of non-state actors and the way states fight wars, international governance has become increasingly complex. However, the formal UNSC agenda has long remained static, reflecting states' unwillingness to entertain more conflicts. Nevertheless, resolutions remain the scholarly measure of states' interests and policies, neglecting the significant share of issues the Council entertains informally. This project builds on a rational institutionalism framework. It provides a systematic analysis of how and under what conditions states use informal governance instead of, or in combination with, formal rules at the agenda-setting stage of the policy process. Data for this project comes from elite interviews and a newly created dataset on governance choices. The results show that counter existing arguments, weaker states successfully circumvent formal institutional roadblocks and use informal governance mechanisms to pursue vital interests, thereby countering institutional restrictions and power asymmetries present informal governance settings.

Keywords: agenda-setting, decision-making, international governance, UNSC

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Authors: Dragana Calic

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The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

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Authors: Ayman M. Mansour

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In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

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Authors: Shihab-Uz-Zaman Shah, Sanjeeb Roy, Habiba Akter

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Keeping the high impact of the Ready-Made Garments (RMG) on the country’s economic growth in mind, this research paves a way for the implementation of Industry 4.0 in the garments industry of Bangladesh. At present, Industry 4.0 is a common buzzword representing the adoption of digital technologies in the production process to transform the existing industries into smart factories and create a great change in the global value chain. The RMG industry is the largest industrial sector of Bangladesh which provides 12.26% to its National GDP (Gross Domestic Product). The work starts with identifying possible enablers of Industry 4.0. To evaluate the enablers, a Multiple-Criteria Decision-Making (MCDM) procedure named Fuzzy Analytical Hierarchy Process (FAHP) was used. A questionnaire was developed as a part of a survey for collecting and analyzing expert opinions from relevant academicians and industrialists. The responses were eventually used as the input for the FAHP which helped to assign weight matrices to the enablers. This weight matrix indicated the level of importance of these enablers. The full paper will discuss the way of a successful evaluation of the enablers and implementation of Industry 4.0 by using these enablers.

Keywords: enablers, fuzzy AHP, industry 4.0, RMG sector

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Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

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Authors: Fernandez liporace, Mercedes Uriel Fabiana

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Academic achievement in high school and college students is currently a matter of concern. National and international assessments show high schoolers as low achievers, and local statistics indicate alarming dropout percentages in this educational level. Even so, 80% of those students intend attending higher education. On the other hand, applications to Public National Universities are free and non-selective by examination procedures. Though initial registrations are massive (307.894 students), only 50% of freshmen pass their first year classes, and 23% achieves a degree. Low performances use to be a common problem. Hence, freshmen adaptation, their adjustment, dropout and low academic achievement arise as topics of agenda. Besides, the hinge between high school and college must be examined in depth, in order to get an integrated and successful path from one educational stratum to the other. Psychology aims at developing two main research lines to analyse the situation. One regarding psychometric scales, designing and/or adapting tests, examining their technical properties and their theoretical validity (e.g., academic motivation, learning strategies, learning styles, coping, perceived social support, parenting styles and parental consistency, paradoxical personality as correlated to creative skills, psychopathological symptomatology). The second research line emphasizes relationships within the variables measured by the former scales, facing the formulation and testing of predictive models of academic achievement, establishing differences by sex, age, educational level (high school vs college), and career. Pursuing these goals, several studies were carried out in recent years, reporting findings and producing assessment technology useful to detect students academically at risk as well as good achievers. Multiple samples were analysed totalizing more than 3500 participants (2500 from college and 1000 from high school), including descriptive, correlational, group differences and explicative designs. A brief on the most relevant results is presented. Providing information to design specific interventions according to every learner’s features and his/her educational environment comes up as a mid-term accomplishment. Furthermore, that information might be helpful to adapt curricula by career, as well as for implementing special didactic strategies differentiated by sex and personal characteristics.

Keywords: academic achievement, higher education, high school, psychological assessment

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Authors: T. J. Hasanova, C. N. Imamalieva

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The problem about the movement of the rigid cylinder keeping the vertical position under the influence of running superficial waves in a liquid is considered. The indignation of a falling wave caused by the presence of the cylinder which moves is thus considered. Special decomposition on a falling harmonious wave is used. The problem dares an operational method. For a finding of the original decision, Considering that the image denominator represents a tabular function, Voltaire's integrated equation of the first sort which dares a numerical method is used. Cylinder movement in the continuous environment under the influence of waves is considered in work. Problems are solved by an operational method, thus originals of required functions are looked for by the numerical definition of poles of combinations of transcendental functions and calculation of not own integrals. Using specificity of a task below, Decisions are under construction the numerical solution of the integrated equation of Volter of the first sort that does not create computing problems of the complex roots of transcendental functions connected with search.

Keywords: rigid cylinder, linear interpolation, fluctuations, Voltaire's integrated equation, harmonious wave

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Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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Authors: Eliane Abdo

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Small and medium sized firms “SMEs” play essential role in the countries’ economic development mainly in terms of production, employment and equitable distribution of income. For innovative SMEs, the investment in the human capital and in research and development are crucial to survive in a competitive environment. In this paper we perform a literature review to underline the financing difficulties and constraints which innovative SMEs face while investing in intangible assets: not only when defining amount of the investments but also while choosing its financing methods. Literature review revealed that in order to finance their intangible assets, SMEs rely in first on their internal financing: the availability of internal cash flows can then determine their investment’s decision. Moreover SMEs face difficulties to finance their intangibles by financial debts due to the uncertainty of future cash flow and the absence of physical guarantees; they will therefore go for the issuance of new shares as a second choice, since innovative companies have high opportunity of growth that attract new shareholders.

Keywords: small and medium sized firms, capital structure, intangible investment, financial constraints

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 203

Authors: S. Vavias, T. R. Brewer, T. S. Farewell

Abstract:

Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

Procedia PDF Downloads 397

Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

Abstract:

This paper shortly describes biomass types and growing amount in the Czech Republic. The considerable part of this paper deals with energy parameters of the most frequent utilizing biomass types and results of their gasification testing. There was chosen sixteen the most exploited "Czech" woody plants and grasses. There were determinated raw, element and biochemical analysis, basic calorimetric values, ash composition and ash characteristic temperatures. After that, each biofuel was tested by fluid bed gasification. The essential part of this paper yields results of chosen biomass types gasification experiments. Partly, there are described an operating conditions in detail with accentuation of individual fuels particularities partly, there is summarized gas composition and impurities content. The essential difference was determined mainly between woody plants and grasses both from point of view of the operating conditions and gas quality. The woody plants was evaluated as more suitable fuels for fluid bed gasifiers. This results will be able to significantly help with decision which energy plants are suitable for growing or with optimal biomass-treatment technology selection.

Keywords: biomass growing, biomass types, gasification, biomass fuels

Procedia PDF Downloads 572