Search results for: charging decision

Authors: Titik Wahyuningsih

Abstract:

The folktale to discuss is Ande-Ande Lumut, a story that is believed to be a history of two kingdoms in East Java, Indonesia. The title refers to the main male character in the story. This research is a library research which aims to know the patriarchal values in Indonesia. The data for the research is the song in the story that is actually the conversation between Ande-Ande Lumut and a mom who adopts him. It is told in the lines that many beautiful girls come to propose Ande-Ande Lumut but he does not want to accept them and keeps on staying in his upstairs room. Finally, he says yes for Klething Kuning to whom his mom describes as a girl with ugly face. Ande-Ande Lumut's decision is taken as Klething Kuning is the only girl who doesn't let Yuyu Kangkang help her. Yuyu Kangkang is described as a very big crab that helps the girls to cross the river but ask them to kiss him. Through the lense of feminist approach, Ande-Ande Lumut shows the men’s preference and dominance to make final decision over women. Even though the girls are actively propose their future husband, but they do it without giving any requirements. Meanwhile, the future husband chooses a girl with a criterion that no male has ever touched her, although the male is a crab.

Keywords: future spouse, Indonesian folktale, acceptance, patriarchal

Procedia PDF Downloads 293

Authors: Maryam Ziaee, Himanshu Shee, Amrik Sohal

Abstract:

Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through transactions in business environments and supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. BDA can assist organisations to capture, store, and analyse data specifically in the field of supply chain. Currently, there is a paucity of research on BDA in the pharmaceutical supply chain context. In this research, the Australian pharmaceutical supply chain was selected as the case study. This industry is highly significant since the right medicine must reach the right patients, at the right time, in right quantity, in good condition, and at the right price to save lives. However, drug shortages remain a substantial problem for hospitals across Australia with implications on patient care, staff resourcing, and expenditure. Furthermore, a massive volume and variety of data is generated at fast speed from multiple sources in pharmaceutical supply chain, which needs to be captured and analysed to benefit operational decisions at every stage of supply chain processes. As the pharmaceutical industry lags behind other industries in using BDA, it raises the question of whether the use of BDA can improve transparency among pharmaceutical supply chain by enabling the partners to make informed-decisions across their operational activities. This presentation explores the impacts of BDA on supply chain management. An exploratory qualitative approach was adopted to analyse data collected through interviews. This study also explores the BDA potential in the whole pharmaceutical supply chain rather than focusing on a single entity. Twenty semi-structured interviews were undertaken with top managers in fifteen organisations (five pharmaceutical manufacturers, five wholesalers/distributors, and five public hospital pharmacies) to investigate their views on the use of BDA. The findings revealed that BDA can enable pharmaceutical entities to have improved visibility over the whole supply chain and also the market; it enables entities, especially manufacturers, to monitor consumption and the demand rate in real-time and make accurate demand forecasts which reduce drug shortages. Timely and precise decision-making can allow the entities to source and manage their stocks more effectively. This can likely address the drug demand at hospitals and respond to unanticipated issues such as drug shortages. Earlier studies explore BDA in the context of clinical healthcare; however, this presentation investigates the benefits of BDA in the Australian pharmaceutical supply chain. Furthermore, this research enhances managers’ insight into the potentials of BDA at every stage of supply chain processes and helps to improve decision-making in their supply chain operations. The findings will turn the rhetoric of data-driven decision into a reality where the managers may opt for analytics for improved decision-making in the supply chain processes.

Keywords: big data analytics, data-driven decision, pharmaceutical industry, supply chain management

Procedia PDF Downloads 106

Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

Abstract:

The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

Procedia PDF Downloads 84

Authors: Yenie Norambuena

Abstract:

Analogical reasoning is a cognitive process that consists of structured comparisons of mental representations and scheme construction. Because of its heuristic function, it is ubiquitous in cognition and could play an important role in language development. The use of analogies is expressed early in children and this behavior is also reflected in language, suggesting a possible way to understand the complex links between thought and language. The current research examines factors of verbal and non-verbal reasoning that should be taken into consideration in the study of language development for their relations and predictive value. The study was conducted with 48 Chilean preschoolers (Spanish speakers) from 4 to 6-year-old. We assessed children’s verbal analogical reasoning, non-verbal analogical reasoning and linguistics skills (Listening Comprehension, Phonemic awareness, Alphabetic principle, Syllabification, Lexical repetition and Lexical decision). The results evidenced significant correlations between analogical reasoning factors and linguistic skills and they can predict linguistic performance mainly on oral comprehension, lexical decision and phonological skills. These findings suggest a fundamental interrelationship between analogical reasoning and linguistic performance on children’s and points to the need to consider this cognitive process in comprehensive theories of children's language development.

Keywords: verbal analogical reasoning, non-verbal analogical reasoning, linguistic skills, language development

Procedia PDF Downloads 266

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 115

Authors: Adejoke Omowumi Adediran

Abstract:

The commitment of African states to liberalise civil aviation in Africa through the implementation of the Yamoussoukro Decision of 1999 was reiterated in 2015 at the African Union Assembly meeting. A declaration was made by African Heads of government at the meeting to ensure the immediate implementation of the decision towards the establishment of a Single African Air Transport Market (SAATM) by 2017. A SAATM will imply among others, a removal of all commercial restrictions for African airlines in Africa; access to any route in Africa by African airlines without any required permit or authorisation; and a common set of regulations for airlines in African member states. As the envisioned 2017 date for launching the SAATM could not be met, a new date of January 2018 has been set. The lack of political will by African States, however, remains a prominent challenge to the realisation of the SAATM. As at June 2017, only twenty-one states had signed the commitment to actualise the decision creating the SAATM. In actualisation of the SAATM, a regulatory framework has been established to efficiently manage the new African airline industry, and regulatory texts have been adopted as part of the legal regime. This legal regime is to regulate both interstate and domestic operations. Airlines in Nigeria are currently faced with certain challenges which ultimately affect their effectiveness and passengers as well do not enjoy utmost customer satisfaction with services rendered by the airlines. Although Nigeria has demonstrated support for the SAATM since 2015, as Nigeria alongside ten other states, signed the initial commitment, whether or not SAATM will eventually be beneficial to airlines and passengers has become an issue in the light of the challenges of the Nigerian airline industry. Remarkably, the benefit of the SAATM is to a large extent ultimately determined by its legal framework. Using doctrinal research, this paper examines the legal implications of the SAATM on airlines and passengers in Nigeria. This paper analyses the legal framework of SAATM and juxtaposes this with the particular issues affecting airlines and passengers in Nigeria such as financial difficulties on the part of airlines and consumer protection as regards passengers. Among others, it can be asserted that the legal regime affords an opportunity for business expansion and creates a fair environment for competition. This is beneficial not only to the airlines but to passengers as well. In addition, in the interest of passengers, consumer rights are prescribed, and the regulations also cater for situations where airlines interrupt their services, as losses arising from these situations will be mitigated. There is indeed no doubt that the SAATM will be of great utility to both airlines and passengers in Nigeria.

Keywords: airlines, civil aviation, competition, consumer protection, passengers, single African air transport market, yamoussoukro decision

Procedia PDF Downloads 139

Authors: Fayssal Ynineb, Toufik Hadjersi, Fatsah Moulai, Wafa Achour

Abstract:

Currently, tremendous attention has been paid to the rational design and synthesis of core/shell heterostructures for high-performance supercapacitors. In this study, the hierarchical NiO/ZnCo₂O₄ Core-Shell Nanorods Arrays were successfully deposited onto ITO substrate via a two-step hydrothermal and electrodeposition methods. The effect of the thin carbon layer between NiO and ZnCo₂O₄ in this multi-scale hierarchical structure was investigated. The selection of this structure was based on: (i) a high specific area of pseudo-capacitive NiO to maximize specific capacitance; (ii) an effective NiO-electrolyte interface to facilitate fast charging/discharging; and (iii) conducting carbon layer between ZnCo₂O₄ and NiO enhance the electric conductivity which reduces energy loss, and the corrosion protection of ZnCo₂O₄ in alkaline electrolyte. The obtained results indicate that hierarchical NiO/ZnCo₂O₄ present a high specific capacitance of 63 mF.cm⁻² at a current density of 0.05 mA.cm⁻² higher than that of pristine NiO and ZnCo₂O₄ of 6 and 3 mF.cm⁻², respectively. The carbon layer improves the electrical conductivity among NiO and ZnCo₂O₄ in the hierarchical NiO/C/ZnCo₂O₄ electrode. As well, the specific capacitance drastically increased to reach 125 mF.cm⁻². Moreover, this multi-scale hierarchical structure exhibits superior cycling stability with ~ 95.7 % capacitance retention after 65k cycles. These results indicate that the NiO/C/ZnCo₂O₄ nanocomposite material is an outstanding electrode material for supercapacitors.

Keywords: NiO/C/ZnCo₂O₄, specific capacitance, hydrothermal, supercapacitors

Procedia PDF Downloads 99

Authors: Adedayo Ajayi, Patrick Luk, Liyun Lao

Abstract:

This paper studies the supportive needs for the electrical infrastructure of the green airport. In particular, the core objective revolves around the choice of electric grid configuration required to meet the expected electrified loads, i.e., the taxiing and charging loads of hybrid /pure electric aircraft in the airport. Further, reliability and resilience are critical aspects of a newly proposed grid; the concept of mobile energy storage as energy as a service (EAAS) for grid support in the proposed green airport is investigated using an autonomous electric taxiing robot (A-ETR) at a case study (Cranfield Airport). The performance of the model is verified and validated through DigSILENT power factory simulation software to compare the networks in terms of power quality, short circuit fault levels, system voltage profile, and power losses. Contingency and reliability index analysis are further carried out to show the potential of EAAS on the grid. The results demonstrate that the low voltage a.c network ( LVAC) architecture gives better performance with adequate compensation than the low voltage d.c (LVDC) microgrid architecture for future green airport electrification integration. And A-ETR can deliver energy as a service (EaaS) to improve the airport's electrical power system resilience and energy supply.

Keywords: reliability, voltage profile, flightpath 2050, green airport

Procedia PDF Downloads 81

Authors: Nureni Amoo, Sunday Aroge, Oluranti Akintola, Hakeem Olujide, Ibrahim Alabi

Abstract:

This study investigated the optimum landfill site in Osogbo so as to identify suitable solid waste dumpsite for proper waste management in the capital city. Despite an increase in alternative techniques for disposing of waste, landfilling remains the primary means of waste disposal. These changes in attitudes in many parts of the world have been supported by changes in laws and policies regarding the environment and waste disposal. Selecting the most suitable site for landfill can avoid any ecological and socio-economic effects. The increase in industrial and economic development, along with the increase of population growth in Osogbo town, generates a tremendous amount of solid waste within the region. Factors such as the scarcity of land, the lifespan of the landfill, and environmental considerations warrant that the scientific and fundamental studies are carried out in determining the suitability of a landfill site. The analysis of spatial data and consideration of regulations and accepted criteria are part of the important elements in the site selection. This paper presents a multi-criteria decision-making method using geographic information system (GIS) with the integration of the fuzzy logic multi-criteria decision making (FMCDM) technique for landfill suitability site evaluation. By using the fuzzy logic method (classification of suitable areas in the range of 0 to 1 scale), the superposing of the information layers related to drainage, soil, land use/land cover, slope, land use, and geology maps were performed in the study. Based on the result obtained in this study, five (5) potential sites are suitable for the construction of a landfill are proposed, two of which belong to the most suitable zone, and the existing waste disposal site belonged to the unsuitable zone.

Keywords: fuzzy logic multi-criteria decision making, geographic information system, landfill, suitable site, waste disposal

Procedia PDF Downloads 143

Authors: Toshitaka Higashino, Naoki Wakamiya

Abstract:

Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: brain activity, EEG, information processing model, model human processor

Procedia PDF Downloads 98

Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Stanley Mburu

Abstract:

Maintenance performance measurement (MPM) represents an integrated aspect that considers both operational and maintenance related aspects while evaluating the effectiveness and efficiency of maintenance to ensure assets are working as they should. Three salient issues require to be addressed for an asset-intensive organization to employ an MPM-based framework to optimize maintenance. Firstly, the organization should establish important perfomance metric(s), in this case the maintenance objective(s), which they will be focuss on. The second issue entails aligning the maintenance objective(s) with maintenance optimization. This is achieved by deriving maintenance performance indicators that subsequently form an objective function for the optimization program. Lastly, the objective function is employed in an optimization program to derive maintenance decision support. In this study, we develop a framework that initially identifies the crucial maintenance performance measures, and employs them to derive maintenance decision support. The proposed framework is demonstrated in a case study of a geothermal drilling rig, where the objective function is evaluated utilizing a simulation-based model whose parameters are derived from empirical maintenance data. Availability, reliability and maintenance inventory are depicted as essential objectives requiring further attention. A simulation model is developed mimicking a drilling rig operations and maintenance where the sub-systems are modelled undergoing imperfect maintenance, corrective (CM) and preventive (PM), with the total cost as the primary performance measurement. Moreover, three maintenance spare inventory policies are considered; classical (retaining stocks for a contractual period), vendor-managed inventory with consignment stock and periodic monitoring order-to-stock (s, S) policy. Optimization results infer that the adoption of (s, S) inventory policy, increased PM interval and reduced reliance of CM actions offers improved availability and total costs reduction.

Keywords: maintenance, vendor-managed, decision support, performance, optimization

Procedia PDF Downloads 125

Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

Abstract:

The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

Procedia PDF Downloads 21

Authors: Jiri Barta

Abstract:

At the present time, awareness, education, computer simulation and information systems protection are very serious and relevant topics. The article deals with perspectives and possibilities of implementation of emergence or natural hazard threats into the system which is developed for communication among members of crisis management staffs. The Czech Hydro-Meteorological Institute with its System of Integrated Warning Service resents the largest usable base of information. National information systems are connected to foreign systems, especially to flooding emergency systems of neighboring countries, systems of European Union and international organizations where the Czech Republic is a member. Use of outputs of particular information systems and computer simulations on a single communication interface of information system for communication among members of crisis management staff and setting the site interoperability in the net will lead to time savings in decision-making processes in solving extraordinary events and crisis situations. Faster managing of an extraordinary event or a crisis situation will bring positive effects and minimize the impact of negative effects on the environment.

Keywords: computer simulation, communication, continuity, critical infrastructure, information systems, safety

Procedia PDF Downloads 333

Authors: Rattanakorn Phadungthin, Juthathip Haema

Abstract:

This research presents an assessment of the criticality of the substation's power transformer using the Entropy Weight method to enable more effective maintenance planning. Typically, transformers fail due to heat, electricity, chemical reactions, mechanical stress, and extreme climatic conditions. Effective monitoring of the insulating oil is critical to prevent transformer failure. However, finding appropriate weights for dissolved gases is a major difficulty due to the lack of a defined baseline and the requirement for subjective expert opinion. To decrease expert prejudice and subjectivity, the Entropy Weight method is used to optimise the weightings of eleven key dissolved gases. The algorithm to assess the criticality operates through five steps: create a decision matrix, normalise the decision matrix, compute the entropy, calculate the weight, and calculate the criticality score. This study not only optimises gas weighing but also greatly minimises the need for expert judgment in transformer maintenance. It is expected to improve the efficiency and reliability of power transformers so failures and related economic costs are minimized. Furthermore, maintenance schemes and ranking are accomplished appropriately when the assessment of criticality is reached.

Keywords: criticality assessment, dissolved gas, maintenance scheme, power transformer

Procedia PDF Downloads 8

Authors: J. Thirunavukkarasu, M. Poulet, T. Turner, S. Pickering

Abstract:

Composite waste from manufacturing can consist of different fiber materials, including blends of different fiber. Commercially, the recycling of composite waste is currently limited to carbon fiber waste and recycling glass fiber waste is currently not economically viable due to the low cost of virgin glass fiber and the reduced mechanical properties of the recovered fibers. For this reason, the recycling of hybrid fiber materials, where carbon fiber is combined with a proportion of glass fiber, cannot be processed economically. Therefore, a separation method is required to remove the glass fiber materials during the recycling process. An electrostatic separation method is chosen for this work because of the significant difference between carbon and glass fiber electrical properties. In this study, an experimental rig has been developed to measure the electrostatic charge achievable as the materials are passed through a tube. A range of particle lengths (80-100 µm, 6 mm and 12 mm), surface state conditions (0%SA, 2%SA and 6%SA), and several tube wall materials have been studied. A polytetrafluoroethylene (PTFE) tube and recycled without sizing agent was identified as the most suitable parameters for the electrical separation method. It was also found that shorter fiber lengths helped to encourage particle flow and attain higher charge values. These findings can be used to develop a separation process to enable the cost-effective recycling of hybrid fiber composite waste.

Keywords: electrostatic charging, hybrid fiber composites, recycling, short fiber composites

Procedia PDF Downloads 129

Authors: Ayat-Allah Bouramdane

Abstract:

Solar Photovoltaic (PV) and Concentrated Solar Power (CSP) do not burn fossil fuels and, therefore, could meet the world's needs for low-carbon power generation as they do not release greenhouse gases into the atmosphere as they generate electricity. The power output of the solar PV module and CSP collector is proportional to the temperature and the amount of solar radiation received by their surface. Hence, the determination of the most convenient locations of PV and CSP systems is crucial to maximizing their output power. This study aims to provide a hands-on and plausible approach to the multi-criteria evaluation of site suitability of PV and CSP plants using a combination of Geographic Referenced Information (GRI) and Analytic Hierarchy Process (AHP). Applying the GRI-based AHP approach is meant to specify the criteria and sub-criteria, to identify the unsuitable areas, the low-, moderate-, high- and very high suitable areas for each layer of GRI, to perform the pairwise comparison matrix at each level of the hierarchy structure based on experts' knowledge, and calculate the weights using AHP to create the final map of solar PV and CSP plants suitability in Morocco with a particular focus on the Dakhla city. The results recognize that solar irradiation is the main decision factor for the integration of these technologies on energy policy goals of Morocco but explicitly account for other factors that cannot only limit the potential of certain locations but can even exclude the Dakhla city classified as unsuitable area. We discuss the sensitivity of the PV and CSP site suitability to different aspects, such as the methodology, the climate conditions, and the technology used in each source, and provide the final recommendations to the Moroccan energy strategy by analyzing if actual Morocco's PV and CSP installations are located within areas deemed suitable and by discussing several cases to provide mutual benefits across the Food-Energy-Water nexus. The adapted methodology and conducted suitability map could be used by researchers or engineers to provide helpful information for decision-makers in terms of sites selection, design, and planning of future solar plants, especially in areas suffering from energy shortages, such as the Dakhla city, which is now one of Africa's most promising investment hubs and it is especially attractive to investors looking to root their operations in Africa and import to European markets.

Keywords: analytic hierarchy process, concentrated solar power, dakhla, geographic referenced information, Morocco, multi-criteria decision-making, photovoltaic, site suitability

Procedia PDF Downloads 175

Authors: Kuei-Ling Sun, Emily Chia-Yu Su

Abstract:

Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

Procedia PDF Downloads 303

Authors: F. Felipe

Abstract:

Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: air defense, effectiveness, system, simulation, decision-support

Procedia PDF Downloads 156

Authors: Yuanxiang Miao

Abstract:

Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.

Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning

Procedia PDF Downloads 131

Authors: Pataraporn Kheawwan

Abstract:

Preceptorship represents an important aspect in new nurse orientation. However, there was no formal preceptor training program developed for nurse preceptor in Thailand. The purposes of this study were to develop and evaluate formal preceptor training program for nurse preceptors in King Chulalongkorn Memorial Hospital, Thailand. A research and development study design was utilized in this study. Participants were 37 nurse preceptors. The program contents were delivered by e-learning material, class lecture, group discussion followed by simulation training. Knowledge of the participants was assessed pre and post program. Skill and critical thinking were assessed using Preceptor Skill and Decision Making Evaluation form at the end of program. Statistical significant difference in knowledge regarding preceptor role and coaching strategies between pre and post program were found. All participants had satisfied skill and decision making score after completed the program. Most of participants perceived benefits of preceptor training course. In conclusion, The results of this study reveal that the newly developed preceptorship course is an effective formal training course for nurse preceptors.

Keywords: preceptor, preceptorship, new nurse, clinical education

Procedia PDF Downloads 261

Authors: Thorsten Auer, Sumaya Islam, Sabrina Plaß, Colin Wooldridge

Abstract:

Whether individuals are more likely to forgo some ethical values if it is for a “great” social mission remains questionable. Research interest in the mechanism of moral disengagement has risen sharply in the organizational context over the last decades. Moral disengagement provides an explanatory approach to why individuals decide against their moral intent and describes the tendency to make unethical decisions due to a lack of self-regulation given various actions and their consequences. In our study, we examine the differences between individual decision-making given a commercial and social entrepreneurial context. Thereby, we investigate whether individuals in a social entrepreneurial context, characterized by pro-social goals and purpose beyond profit maximization, tend to make more or less “unethical” decisions in trade-off situations than those given a profit-focused commercial, entrepreneurial context. While a general priming effect may explain the tendency for individuals to make less unethical decisions given a social context, it remains unclear how individuals decide given a trade-off in that specific context. The trade-off in our study is characterized by the option to decide (un-) ethically to enhance the business purpose (in the social context, a social purpose, in the commercial context, a profit-maximization purpose). To investigate which characteristics of the context –and specifically of a trade-off – lead individuals to disregard and override their ethical values for a “greater good”, we design a conjoint analysis. This approach allows us to vary the attributes and scenarios and to test which attributes of a trade-off increase the probability of making an unethical choice. We add survey data to examine the individual propensity to morally disengage as an influencing factor to prefer certain attributes. Currently, we are in the final process of designing the conjoint analysis and plan to conduct the study by December 2022. We contribute to a better understanding of the role of moral disengagement in individual decision-making in a (social) entrepreneurial trade-off.

Keywords: moral disengagement, social entrepreneurship, unethical decision, conjoint analysis

Procedia PDF Downloads 87

Authors: Comfort Mokgothu

Abstract:

This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: decision making, fitness, information processing, reaction time, cognition movement time

Procedia PDF Downloads 145

Authors: Ross Lee, Pritpal Singh, Andrew Jester

Abstract:

As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, new battery technology is necessary for grid applications to curtail these risks. Biological cells, such as human neurons and electrolytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell, akin to the charging/discharging of a battery cell. This work serves as the first step to developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na⁺-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior similar to human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: battery, biomimetic, electrolytes, human neurons, ion-selective membranes, membrane potential

Procedia PDF Downloads 118

Authors: MeiBo, ZhaoXing, LuoLei, YuQingkui, TangMin, HanZhengsheng

Abstract:

The Single Event Transients (SETs) were investigated on 0.18μm PDSOI transistors and 100 series CMOS inverter chain using pulse laser. The effect of different laser energy and device bias for waveform on SET was characterized experimentally, as well as the generation and propagation of SET in inverter chain. In this paper, the effects of struck transistors type and struck locations on SETs were investigated. The results showed that when irradiate NMOSFETs from 100th to 2nd stages, the SET pulse width measured at the output terminal increased from 287.4 ps to 472.9 ps; and when irradiate PMOSFETs from 99th to 1st stages, the SET pulse width increased from 287.4 ps to 472.9 ps. When struck locations were close to the output of the chain, the SET pulse was narrow; however, when struck nodes were close to the input, the SET pulse was broadening. SET pulses were progressively broadened up when propagating along inverter chains. The SET pulse broadening is independent of the type of struck transistors. Through analysis, history effect induced threshold voltage hysteresis in PDSOI is the reason of pulse broadening. The positive pulse observed by oscilloscope, contrary to the expected results, is because of charging and discharging of capacitor.

Keywords: single event transients, pulse laser, partially-depleted silicon-on-insulator, propagation-induced pulse broadening effect

Procedia PDF Downloads 412

Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

Abstract:

The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

Procedia PDF Downloads 432

Authors: Arkaprabha Bhattacharyya, Makarand Hastak

Abstract:

The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

Procedia PDF Downloads 171

Authors: K. Saravanan, K. A.Rameshkumar, P. Maadeswaran

Abstract:

The depletion of fossil resources and the rise in global temperatures are two of the most important concerns we confront today. There are numerous renewable energy sources like solar power, tidal power, wind energy, radiant energy, hydroelectricity, geothermal energy, and biomass available to generate the needed energy demand. Engineers and scientists around the world are facing a massive barrier in the development of storage technologies for the energy developed from renewable energy sources. The development of electrochemical capacitors as a future energy storage technology is at the forefront of current research and development. This is due to the fact that the electrochemical capacitors have a significantly higher energy density, a faster charging-discharging rate, and a longer life span than capacitors, and they also have a higher power density than batteries, making them superior to both. In this research, electrochemical capacitors using the Nd2O3/Mn3O4/ N-rGO electrode material is chosen since the of hexagonal and tetragonal crystal structures of Nd2O3 and Mn3O4 and also has cycling stability of 68% over a long time at 50mVs-1 and a high coulombic efficiency of 99.64% at 5 Ag-1. This approach may also be used to create novel electrode materials with improved electrochemical and cyclic stability for high-performance supercapacitors.

Keywords: Nd2O3/Mn3O4/N-rGO, nanocomposites, hydrothermal method, electrode material, specific capacitance, use of supercapacitors

Procedia PDF Downloads 96

Authors: Naznin Sultana Daisy, Mohammad Hesam Hafezi, Lei Liu

Abstract:

Nowadays, oily solid waste management has become an important issue for many countries due to frequent oil spill accidents and the increase of industrial oily wastewater. The historical oil spill data show that marine oil spills that affect the shoreline can, in extreme cases, produce up to 30 or 40 times more waste than the volume of oil initially released. Hence, responsive authorities aim to develop the most effective oily waste management solution in a timely manner to manage and minimize the waste generated. In this study initially, we tried to develop the roadmap of oily waste management for three-tiered spill scenarios for Atlantic Canada. For that purpose, three oily waste disposal scenarios are evaluated via six criteria which are determined according to the opinions of the experts from the field. Consequently, through sustainable response strategies, the most appropriate and feasible scenario is determined. The results of this study will assist to develop an integrated oily waste management system for identifying the optimal waste-generation-allocation-disposal schemes and generating the optimal management alternatives based on the holistic consideration of environmental, technological, economic, social, and regulatory factors.

Keywords: oily waste management, marine oil spill, multi-criteria decision making, oil spill response

Procedia PDF Downloads 137

Authors: Ana Nascimento

Abstract:

For several reasons and in different countries worldwide, there is an increasing difficulty of the States to finance higher education. However, most societies consider education as a public good, so it should be a State obligation to provide this service to citizens. In Portugal, over the last decades, state has diminished its contribution to public higher education and the public higher education institutions started to look for alternative incoming sources, namely charging student’s taxes and fees, provision of services to companies, production of applied research, search for sponsors, configuring new forms of fundraising. This financial policy can raise some concerns to the scientific and pedagogical autonomy of these institutions as well as concerns in access and equity in higher education. For these reasons and in the scope of a PhD research in the area of Economy of Education, a survey is taking place in all public higher education institutions in the Great Lisbon area that intends to analyze and discuss the policy measures in each institution in the search for external financing. The research aims to understand what these measures are and what implications they might have in the institution’s autonomy as well as in higher education access by students from less favored backgrounds. The research uses a qualitative approach, namely through semi-structured interviews to presidents, directors and rectors of each institution, totalizing 50 interviews. In this paper are discussed some of the results from the interviews made so far that present the subjects opinion about higher education finance, the right to education, the search for fundraising and the possible consequences to the institution’s autonomy as well as some literature on the state of the art.

Keywords: autonomy, finance, higher education, public goods

Procedia PDF Downloads 665

Authors: Saurav Dhawan, Sanchit Bansal

Abstract:

Background T-MACS is a computer-based decision aid that ‘rules in’ and ‘rules out’ ACS using a combination of the presence or absence of six clinical features with only one biomarker measured on arrival: hs-cTnT. T-MACS had 99.3% negative predictive value and 98.7% sensitivity for ACS, ‘ruling out’ ACS in 40% of patients while ‘ruling in’ 5% at the highest risk. We aim at benchmarking the use of T-MACS which could help to conserve healthcare resources, facilitate early discharges, and ensure safe practice. Methodology Randomized retrospective data collection (n=300) was done from ED electronic records across 3 hospital sites within MFT over a period of 2 months. Data was analysed and compared by percentage for the usage of T-MACS, number of admissions/discharges, and in days for length of stay in hospital. Results MRI A&E had the maximum compliance with the use of T-MACS in the trust at 66%, with minimum admissions (44%) and an average length of stay of 1.825 days. NMG A&E had an extremely low compliance rate (8 %), with 75% admission and 3.387 days as the average length of stay. WYT A&E had no TMACS recorded, with a maximum of 79% admissions and the longest average length of stay at 5.07 days. Conclusion All three hospital sites had a RAG rating of ‘RED’ as per the compliance levels. The assurance level was calculated as ‘Very Limited’ across all sites. There was a positive correlation observed between compliance with TMACS and direct discharges from ED, thereby reducing the average length of stay for patients in the hospital.

Keywords: ACS, discharges, ED, T-MACS

Procedia PDF Downloads 58