Search results for: gaps in data ecosystems

Authors: Johnstone Walubengo Wangusi

Abstract:

Climate change is undeniably altering the frequency, intensity, and geographic distribution of extreme weather events worldwide. In this paper, we explore the complex interconnections between climate change and extreme weather phenomena, drawing upon research from atmospheric science, geology, and climatology. We examine the underlying mechanisms driving these changes, the impacts on natural ecosystems and human societies, and strategies for adaptation and mitigation. By synthesizing insights from interdisciplinary research, this paper aims to provide a comprehensive understanding of the multifaceted relationship between climate change and extreme weather, informing efforts to address the challenges posed by a changing climate.

Keywords: climate change, extreme weather, atmospheric science, geology, climatology, impacts, adaptation, mitigation

Procedia PDF Downloads 40

Authors: Natalie Preville, Carlos Joel Mejia-Olivares

Abstract:

In the UK, since the early 1950s when the NHS was founded, international staff in the NHS have played an important role. Currently, they represent 16% of the workforce within the NHS in the UK. Furthermore, to address the shortfalls in nursing staff, international recruitment programs have been essential to reduce the gaps in the UK nursing workforce over the last two decades. The NHS Long Term Plan (2019) aims to have a significant reduction of nursing vacancies to 5% by 2028. However, in 2021 and 2022, Workforce Race Equality Standards (WRES) reports stated that there is inequitable Career Progression (CP) among Internationally Recruited (IR) nurses as compared to British counterparts. In addition, there is sufficient literature exploring the motives and lived experiences of IR nurses, which underpins the findings. Therefore, the overall aim of this report is to conduct a scoping project to understand the experiences of the IR nurses who joined the NHS in the South East of England within the last 5 years. Methodology- This document is based on the data from a survey developed by Royal Berkshire NHS Foundation Trust using Microsoft forms and consisted of 23 questions divided into four themes, staff background, career experience, career progression and future career plans within Royal Berkshire NHS Foundation Trust. The descriptive analysis provided the initial analysis of the quantitative data. As a result, 44 responses were collected and evaluated by utilising Microsoft excel. Key findings: Career experiences; 72% of respondents felt that their current role was a good fit, and in a subsequent question, the main reason cited was having “relevant skills”. This indicates that, for the most part, the prior experience of IR nurses is a large factor in their placement, which is viewed positively; the next step is to effectively apply similar relevance in aligning prior experience with career progression opportunities. Moreover, 67% of respondents feel valued by the department/team, which is a great reflection of the values of the Trust being demonstrated towards IR Nurses. However, further studies may be necessary to explore the reasons why the remaining 33% may not feel valued; this can include having a better understanding of cultural perceptions of value. Perceived Barriers: Although 37% of respondents had been promoted since commencing employment with the Trust, the data indicates that there is still room for CP opportunities, as it is the leading barrier reported by the respondents. Secondly, the growing mix of cultures within the nursing workforce gives the appearance of inclusion. However, this is not the experience of some IR nurses. Conclusion statemen: Survey results indicate that this NHS Trust has an excellent foundation to integrate international nurses into their workforce with scope for career progression in a reasonable timeframe. However, it would be recommendable to include fast-tracking career promotions by recognizing previous studies and professional experience. Further exploration of staff career experiences and goals may provide additional useful data for future planning.

Keywords: career progression, International nurses, perceived barriers, staff survey

Procedia PDF Downloads 64

Authors: Dyah Adi Sriwahyuni

Abstract:

Institutional work has become a prominent and contemporary institutional theory perspective in organization studies. A wealth of studies in organizations have explored actor activities in creating, maintaining, and disrupting institutions at the field level. However, the exploration of the work of actors in creating new management practices at the organizational level has been somewhat limited. The current institutional work literature mostly describes the work of actors at the field level and ignores organizational actors who work to realize management practices. Organizational actors here are defined as actors in organizations who work to institutionalize a particular management practice within the organizations. The extant literature has also generalized the types of management practices, which meant overlooking the unique characteristics of each management fashion as well as a management practice. To fill these gaps, this study aims to provide empirical evidence so as to contribute theoretically to institutional work through a comparative case study on organizational actors’ creation of knowledge management (KM) practice in two public sector organizations in Indonesia. KM is a contemporary management practice employed to manage individual and organizational knowledge in order to improve organizational performance. This practice presents a suitable practical setting with which to provide a rich understanding of the organizational actors’ institutional work and their connection with technology. Drawing on and extending the work of Perkmann and Spicer (2008), this study explores the forms of institutional work performed by organizational actors, including their motivation, skills, challenges, and opportunities. The primary data collection is semi-structured interviews with knowledgeable actors and document analysis for validity and triangulation. Following Eisenhardt's cross-case patterns, the researcher analyzed the collected data focusing on within-group similarities and intergroup differences. The researcher coded interview data using NVivo and used documents to corroborate the findings. The study’s findings add to the wealth of institutional theory literature in organization studies, particularly institutional work related to management practices. This study builds a theory about the work of organizational actors in creating knowledge management practices. Using the perspective of institutional work, research can show the roles of the various actors involved, their practices, and their relationship to technology (materiality), not only focusing on actors with a power which has been the theorizing of institutional entrepreneurship. The development of knowledge management practices in the Indonesian public sector is also a significant additional contribution, given that the current KM literature is dominated by conceptualizing the KM framework and the impact of KM on organizations. The public sector, which is the research setting, also provides important lessons on how actors in a highly institutionalized context are creating an institution, in this case, a knowledge management practice.

Keywords: institutional work, knowledge management, case study, public sector organizations

Procedia PDF Downloads 95

Authors: Nicole Scott, Emily Dwyer, Cara Patrissy, Samantha Bonventre, Lina Begdache

Abstract:

Across North America, the use and abuse of Attention Deficit Hyperactivity Disorder (ADHD) medication, cannabis, nicotine, and other psychoactive substances across college campuses have become an increasingly prevalent problem. Students frequently use these substances to aid their studying or deal with their mental health issues. However, it is still unknown what psychoactive substances are likely to be abused when college students illicitly use ADHD medication. In addition, it is not clear which psychoactive substance is associated with mental distress. Thus, the purpose of this study is to fill these gaps by assessing the use of different psychoactive substances when illicit ADHD medication is used; and how this association relates to mental stress. A total of 702 undergraduate students from different college campuses in the U.S. completed an anonymous survey distributed online. Data were self-reported on demographics, the use of ADHD medications, cannabis, nicotine, other psychoactive drugs, and mental distress, and feelings and opinions on the use of illicit study drugs were all included in the survey. Mental distress was assessed using the Kessler Psychological Distress 6 Scale. Data were analyzed in SPSS, Version 25.0, using Pearson’s Correlation Coefficient. Our results show that use of ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent), there were both statistically significant positive and negative correlations to specific psychoactive substances and their corresponding frequencies. Along the same lines, ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent) had statistically significant positive and negative correlations to specific mental distress experiences. As these findings are combined, a vicious loop can initiate a cycle where individuals who abuse psychoactive substances may or may not be inclined to use other psychoactive substances. This may later inhibit brain functions in those main areas of the brain stem, amygdala, and prefrontal cortex where this vicious cycle may or may not impact their mental distress. Addressing the impact of study drug abuse and its potential to be associated with further substance abuse may provide an educational framework and support proactive approaches to promote awareness among college students.

Keywords: stimulant, depressant, nicotine, ADHD medication, psychoactive substances, mental health, illicit, ecstasy, adrenochrome

Procedia PDF Downloads 53

Authors: Karolina Wieczorek, Zofia Przypaśniak

Abstract:

Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

Procedia PDF Downloads 72

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

Procedia PDF Downloads 444

Authors: In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

Abstract:

An Inverter type arc-welding machine is inclined to be designed for higher frequency in order to reduce the size and cost. The need of the core material reconsideration for high frequency pulse transformer is more important since core loss grows as the frequency rises. An arc welding machine’s pulse transformer is designed using an Area Product (Ap) method and is considered margin air gap core design in order to prevent the burning of the IGBT by the inrush current. Finally, the reduction of the core weight and the core size are compared according to different materials for 30kW inverter type arc welding machine.

Keywords: pulse transformers, welding, inrush current, air gaps

Procedia PDF Downloads 439

Authors: Djamila Benhaddouche, Abdelkader Benyettou

Abstract:

In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

Procedia PDF Downloads 542

Authors: Usama Ahmed

Abstract:

Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

Procedia PDF Downloads 134

Authors: Eleni Panagiotarakou

Abstract:

This paper argues that humans have a collective moral responsibility to help wild animals during the Anthropocene era. Seen from the perspective of deontic logic, this moral responsibility did not exist in the Holocene era (ca. 11,700 BC-1945 AD) on account of humanity’s limited impact on the natural environment. By contrast in the Anthropocene, human activities are causing significant disturbances to planetary ecosystems and by inference to wildlife communities. Under these circumstances controversial and deeply regrettable interventional methods such as Managed Relocations (MR) and synthetic biology should be expanded and become policy measures despite their known and unknown risks. The main rationale for the above stems from the fact that traditional management strategies are simply insufficient in the Anthropocene. If the same anthropogenic activities continue unabated they risk triggering a sixth mass species extinction.

Keywords: anthropocene, humanitarian interventions, managed relocations, species extinctions, synthetic biology

Procedia PDF Downloads 234

Authors: Rawan K. Al-Duaij, Salem A. Al-Salem

Abstract:

Projects, the unique and temporary process of achieving a set of requirements have always been challenging; Planning the schedule and budget, managing the resources and risks are mostly driven by a similar past experience or the technical consultations of experts in the matter. With that complexity of Projects in Scope, Time, and execution environment, Adjustment Orders are tools to reflect changes to the original project parameters after Contract signature. Adjustment Orders are the official/legal amendments to the terms and conditions of a live Contract. Reasons for issuing Adjustment Orders arise from changes in Contract scope, technical requirement and specification resulting in scope addition, deletion, or alteration. It can be as well a combination of most of these parameters resulting in an increase or decrease in time and/or cost. Most business leaders (handling projects in the interest of the owner) refrain from using Adjustment Orders considering their main objectives of staying within budget and on schedule. Success in managing the changes results in uninterrupted execution and agreed project costs as well as schedule. Nevertheless, this is not always practically achievable. In this paper, a detailed study through utilizing Industrial Engineering & Systems Management tools such as Six Sigma, Data Analysis, and Quality Control were implemented on the organization’s five years records of the issued Adjustment Orders in order to investigate their prevalence, and time and cost impact. The analysis outcome revealed and helped to identify and categorize the predominant causations with the highest impacts, which were considered most in recommending the corrective measures to reach the objective of minimizing the Adjustment Orders impacts. Data analysis demonstrated no specific trend in the AO frequency in past five years; however, time impact is more than the cost impact. Although Adjustment Orders might never be avoidable; this analysis offers’ some insight to the procedural gaps, and where it is highly impacting the organization. Possible solutions are concluded such as improving project handling team’s coordination and communication, utilizing a blanket service contract, and modifying the projects gate system procedures to minimize the possibility of having similar struggles in future. Projects in the Oil and Gas sector are always evolving and demand a certain amount of flexibility to sustain the goals of the field. As it will be demonstrated, the uncertainty of project parameters, in adequate project definition, operational constraints and stringent procedures are main factors resulting in the need for Adjustment Orders and accordingly the recommendation will be to address that challenge.

Keywords: adjustment orders, data analysis, oil and gas sector, systems management

Procedia PDF Downloads 148

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

Abstract:

Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 69

Authors: Rajaa Filali, Mohamed Bouhdadi

Abstract:

This paper presents an incremental development of the Dynamic Host Configuration Protocol (DHCP) in Event-B. DHCP is widely used communication protocol, which provides a standard mechanism to obtain configuration parameters. The specification is performed in a stepwise manner and verified through a series of refinements. The Event-B formal method uses the Rodin platform to modeling and verifying some properties of the protocol such as safety, liveness and deadlock freedom. To model and verify the protocol, we use the formal technique Event-B which provides an accessible and rigorous development method. This interaction between modelling and proving reduces the complexity and helps to eliminate misunderstandings, inconsistencies, and specification gaps.

Keywords: DHCP protocol, Event-B, refinement, proof obligation, Rodin

Procedia PDF Downloads 217

Authors: Lazaro E. Nnko, Japhet J. Kashaigili, Gerald C. Monela, Pantaleo K. T. Munishi

Abstract:

Agroforestry systems and practices are perceived to improve livelihood and sustainable management of natural resources. However, their adoption in various regions differs with the biophysical conditions and societal characteristics. This study was conducted in Kilombero District to investigate the factors influencing the adoption of different agroforestry systems and practices in agro-ecosystems and farming systems. A household survey, key informant interviews, and focus group discussion was used for data collection in three villages. Descriptive statistics and multinomial logistic regression in SPSS were applied for analysis. Results show that Igima and Ngajengwa villages had home garden practices dominated, as revealed by 63.3% and 66.7%, respectively, while Mbingu village had mixed intercropping practice with 56.67%. Agrosilvopasture systems were dominant in Igima and Ngajengwa villages with 56.7% and 66.7%, respectively, while in Mbingu village, the dominant system was agrosilviculture with 66.7%. The results from multinomial logistic regression show that different explanatory variable was statistical significance as predictors of the adoption of agroforestry systems and practices. Residence type and sex were the most dominant factor influencing the adoption of agroforestry systems. Duration of stay in the village, availability of extension education, residence, and sex were the dominant factor influencing the adoption of agroforestry practices. The most important and statistically significant factors among these were residence type and sex. The study concludes that agroforestry will be more successful if the local priorities, which include social-economic need characteristics of the society, will be considered in designing systems and practices. The socio-economic need of the community should be addressed in the process of expanding the adoption of agroforestry systems and practices.

Keywords: agroforestry adoption, agroforestry systems, agroforestry practices, agroforestry, Kilombero

Procedia PDF Downloads 99

Authors: Abhiram Siva Prasad Pamula

Abstract:

Access to clean drinking water becomes scarce due to the increase in extreme weather events because of the rise in the average global temperatures and climate change. By 2030, approximately 47% of the world’s population will face water shortages due to uncertainty in seasonal rainfall. Over 10000 varieties of synthetic dyes are commercially available in the market and used by textile and paper industries, negatively impacting human health when ingested. Besides humans, textile dyes have a negative impact on aquatic ecosystems by increasing biological oxygen demand and chemical oxygen demand. This study assesses different treatment methods that remove dyes from textile wastewater while focusing on energy, economic, and engineering aspects of the treatment processes.

Keywords: textile wastewater, dye removal, treatment methods, hazardous pollutants

Procedia PDF Downloads 82

Authors: Jaroslav Krutil, Simona Fialová, , František Pochylý

Abstract:

A nonlinear mathematical model of mutual fluid-structure interaction is presented in the work. The model is applicable to the general shape of sealing gaps. An in compressible fluid and turbulent flow is assumed. The shaft carries a rotational and procession motion, the gap is axially flowed through. The achieved results of the additional mass, damping and stiffness matrices may be used in the solution of the rotor dynamics. The usage of this mathematical model is expected particularly in hydraulic machines. The method of control volumes in the ANSYS Fluent was used for the simulation. The obtained results of the pressure and velocity fields are used in the mathematical model of additional effects.

Keywords: nonlinear mathematical model, CFD modeling, hydrodynamic sealing gap, matrices of mass, stiffness, damping

Procedia PDF Downloads 522

Authors: Anna Gaspard, Stéphane Boudreau, Martin Simard

Abstract:

Altered temperature and precipitation regimes associated with climate change generally result in improved conditions for plant growth. For Arctic and sub-Arctic ecosystems, this new climatic context favours an increase in primary productivity, a phenomenon often referred to as "greening". The development of an erect shrub cover has been identified as the main driver of Arctic greening. Although this phenomenon has been widely documented at the circumpolar scale, little information is available at the scale of plant communities, the basic unit of the Arctic, and sub-Arctic landscape mosaic. The objective of this study is to quantify the variation of NDVI within the different plant communities of Nunavik, which will allow us to identify the plant formations that contribute the most to the increase in productivity observed in this territory. To do so, the variation of NDVI extracted from Landsat images for the period 1984 to 2020 was quantified. From the Landsat scenes, annual summer NDVI mosaics with a resolution of 30 m were generated. The ecological mapping of Northern Quebec vegetation was then overlaid on the time series of NDVI maps to calculate the average NDVI per vegetation polygon for each year. Our results show that NDVI increases are more important for the bioclimatic domains of forest tundra and erect shrub tundra, and shrubby formations. Surface deposits, variations in mean annual temperature, and variations in winter precipitation are involved in NDVI variations. This study has thus allowed us to quantify changes in Nunavik's vegetation communities, using fine spatial resolution satellite imagery data.

Keywords: climate change, latitudinal gradient, plant communities, productivity

Procedia PDF Downloads 168

Authors: Muna Slehat

Abstract:

Jordan is endowed with over 14,500 productive archaeological sites and also a wealth of heritage sites that need to be protected from the pressing threat of destruction and damage. Archaeological sites in Jordan face significant threats, including insensitive development, urbanization, pollution, tourism, and vandalism, therefore an effective management plan is a key element, not only for the conservation of this heritage, but also to address issues such as tourism and sustainable development. This study highlights the obstacles that confront the management of the archaeological and tourism sites in Jordan, prior to and after the launch of the Strategies for Management of Jordan’s Archaeological Heritage by the Department of Antiquities (DoA) 2007-2010 and 2014-2018, as well as the establishment of the Directorate of the Management of Archaeological Sites in 2010, and instructions for the proper use of tourism sites, 2014, by the Ministry of Tourism and Antiquities (MoTA). The study has revealed that the management of the archaeological and tourism sites under the pretext of improvement of services for tourists and visitors to Jordan would allow access to so-called polarization tourism and facilitate tourism development that would be sustainable economically and provide attractive returns. The data required have been collected through conducting interviews with 18 specialists. The main findings of the study are that management is new in Jordan, and has become a vital and dynamic force in Jordan after 2000 but that there have also been many mistakes, with sustainability of the sites being ignored and a lack of awareness among local communities surrounding these sites. Management of the sites has also suffered from a lack of organizational vision, with no instructions for practical application and no legislative provisions which cater for the efficient management of the sites. All of this needs to be amended to remove gaps, overlaps and ambiguities, so that the authorities responsible for the rehabilitation and promotion, development and management of these sites can overcome the problems, such as lack of human resources (specialists) and financial resources.

Keywords: Jordan, management, archaeological sites, tourism, challenges

Procedia PDF Downloads 288

Authors: Awole Seid, Yosef Zenebe, Hadgu Gerensea, Kebede Haile Misgina

Abstract:

Background: Clinical competence is one of the ultimate goals of nursing education. Clinical skills are more than successfully performing tasks; it incorporates client assessment, identification of deficits and the ability to critically think to provide solutions. Assessment of clinical competence, particularly identifying gaps that need improvement and determining the educational needs of nursing students have great importance in nursing education. Thus this study aims determining clinical self-efficacy of final year school of nursing students in three universities of Tigray Region. Methods: A cross-sectional study was conducted on 224 final year school of nursing students from department of nursing, psychiatric nursing, and midwifery on three universities of Tigray region. Anonymous self-administered questionnaire was administered to generate data collected on June, 2017. The data were analyzed using SPSS version 20. The result is described using tables and charts as required. Logistic regression was employed to test associations. Result: The mean age of students was 22.94 + 1.44. Generally, 21% of students have been graduated in the department in which they are not interested. The study demonstrated 28.6% had poor and 71.4% had good perceived clinical self-efficacy. Beside this, 43.8% of psychiatric nursing and 32.6% of comprehensive nursing students have poor clinical self-efficacy. Among the four domains, 39.3% and 37.9% have poor clinical self- efficacy with regard to ‘Professional development’ and ‘Management of care’. Place of the institution [AOR=3.480 (1.333 - 9.088), p=0.011], interest during department selection [AOR=2.202 (1.045 - 4.642), p=.038], and theory-practice gap [AOR=0.224 (0.110 - 0.457), p=0.000] were significantly associated with perceived clinical self-efficacy. Conclusion: The magnitude of students with poor clinically self efficacy was high. Place of institution, theory-practice gap, students interest to the discipline were the significant predictors of clinical self-efficacy. Students from youngest universities have good clinical self-efficacy. During department selection, student’s interest should be respected. The universities and other stakeholders should improve the capacity of surrounding affiliate teaching hospitals to set and improve care standards in order to narrow the theory-practice gap. School faculties should provide trainings to hospital staffs and monitor standards of clinical procedures.

Keywords: clinical self-efficacy, nursing students, Tigray, northern Ethiopia

Procedia PDF Downloads 160

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 261

Authors: Christopher Muhawe, Masooda Bashir

Abstract:

With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

Procedia PDF Downloads 183

Authors: Jeter Canete, Noreen Joyce Estrella, Yedda Sachi Patrice Madelo

Abstract:

Zooplankton plays a crucial role in aquatic ecosystems and a number of water parameters involved in it. Despite their relevance, there is inadequate information about zooplankton communities in Sarangani Bay, Sarangani Province: one of the most essential waterbodies in Mindanao. The aim of the present study was to determine the composition, abundance, and diversity of zooplankton as well as to provide more recent data about the physico-chemical characteristics of Sarangani Bay. Zooplankton samples were collected by vertical hauls using a zooplankton net (mouth diameter: 0.5m; mesh size opening: round, 350μm) in three stations in the coastal waters of Alabel, Malapatan, and Maasim during November 2018. A total of 74 species of zooplankton belonging mainly to Kingdom Protozoa, Phylum Arthropoda, Chaetognatha, and Chordata were identified. Results showed a total zooplankton abundance of 1,984,166 ind/m³ with the highest count recorded at Malapatan (717,169 ind/m³) and the lowest at Maasim (624,411 ind/m³). Among 22 zooplankton groups identified, subclass Copepoda was found to be the most dominant (73.10%), followed by Appendicularia (12.18%) and Vertebrata (3.54%). Diversity analysis revealed an even distribution of species and a diverse ecosystem in all stations sampled. Correlation analysis indicated a strong relationship between zooplankton abundance and physico-chemical parameters. Overall, the physico-chemical profile of Sarangani Bay did not differ from the standards set by DENR, and analysis of the zooplankton communities revealed that Sarangani Bay favorably supports marine organisms to flourish. The findings of this study provide useful knowledge on zooplankton communities and can be used to create management strategies to protect the aquatic biodiversity in Sarangani Bay.

Keywords: aquatic biomonitoring, biodiversity, physicochemical analysis, population survey, Sarangani Bay, Sarangani Province, zooplankton

Procedia PDF Downloads 292

Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

Abstract:

Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

Procedia PDF Downloads 112

Authors: Budiman Ibnu

Abstract:

This study investigates about enabling conditions to facilitate social innovation in the energy sector. This is important to support the energy transition in Indonesia. This research provides appropriate project direction, including research (and action) gaps for the energy actors in Indonesia. The actors are allowed to work further with the result of this study to stimulate the energy transition in Indonesia. This report uses systemic change framework which recognizes four drivers of systemic change in a region: 1. transforming political ecologies; 2. configuring green economies; 3. building of adaptive communities; 4. social innovation. These drivers are interconnected, and this report particularly focuses on how social innovation can be supported by other drivers. This study used methods of interview and literature review as the main sources for data collection in this report. There were interviews with eight experts in the related topic which come from different countries which have experienced social innovation in the energy sector. Afterwards, this research reviewed related journal papers from last five years, to check the latest development within the topic, to support the interview result. The result found that the enabling condition can focus on one of the drivers of systemic change, which is building communities by increasing their participation, through several integrated actions. This can be implemented in two types of citizen energy initiatives which are energy cooperatives and sustainable consumption initiatives. This implementation requires study about its related policy and governance support, in order to create complete enabling conditions to facilitate social innovation in the energy transition.

Keywords: enabling condition, social innovation, citizen initiatives, community participation

Procedia PDF Downloads 140

Authors: Busra Gulnihan Dascıoglu, Ozalp Vayvay, Zeynep Tugce Kalender

Abstract:

Humanitarian supply chain management has gain popularity in recent years in research fields. The aim of this paper is to review the literature on humanitarian operations and crisis/disaster management from 2010 to latest researches in order to identify the current research and to provide direction for future research in this growing field. Researches are classified considering the research publication year, research fields. Articles from humanitarian supply chain management were reviewed, keywords were identified within a disaster management lifecycle framework. Research gaps are identified for future research areas.

Keywords: crisis, disaster, humanitarian supply chain management, relief operations

Procedia PDF Downloads 325

Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

Procedia PDF Downloads 32

Authors: Karin Johansson, Ola Johansson

Abstract:

Recycling is an important aspect of a sustainable society and depends to a large extent on consumers’ willingness to provide the voluntary work needed to take the first critical step in many return logistics systems. Based on a systematic review of articles on recycling behavior, this paper presents and discusses the findings in relation to Fogg’s Behavioral Model (FBM). Through the analysis of a corpus of 72 articles, the most important research contributions on recycling behavior are summarized and discussed. The choice of using FBM as a framework provides a new way of viewing previous research findings, and aids in identifying knowledge gaps. Based on the review, this work identifies and discusses four areas of potential interest for future research.

Keywords: recycling, reverse logistics, solid waste management, sustainability

Procedia PDF Downloads 130

Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

Abstract:

Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

Procedia PDF Downloads 331

Authors: E. Hegazy, S. Anderberg, J. Krook

Abstract:

The city's wire-based infrastructure systems (WBIS) are responsible for the delivery of electricity, telecommunications, sanitation, drainage, and district heating and are a necessity for sustainable modern urban life. Maintaining the functionality of these structures involves high costs and, brings disturbance to the local community and effects on the environment. One key reason for this is that the cables and pipes are placed under streets, making system parts easily worn and their service lifetime reduced, and all maintenance and renewal rely on recurrent needs for excavation. In Sweden, a significant part of wire-based infrastructure is already outdated and will need to be replaced in the coming decades. The replacement of these systems will entail massive costs as well as important traffic disruption and environmental disturbance. However, this challenge may also open a unique opportunity to introduce new, more sustainable technologies and management practices. The transformation of WBIS management for long-term sustainability and meeting maintenance and renewal needs does not have a comprehensive approach. However, a systemic approach may inform WBIS management. This approach considers both technical and non-technical aspects, as well as time-related factors. Nevertheless, there is limited systemic knowledge of how different factors influence current management practices. The aim of this study is to address this knowledge gap and contribute to the understanding of what factors influence the current practice of WBIS management. A case study approach is used to identify current management practices, the underlying factors that influence them, and their implications for sustainability outcomes. The case study is based on both quantitative data on the local system and data from interviews and workshops with local practitioners and other stakeholders. Linköping was selected as a case since it provided good accessibility to the water administration and relevant data for analyzing water infrastructure management strategies. It is a sufficiently important city in Sweden to be able to identify challenges, which, to some extent, are common to all Swedish cities. By uncovering current practices and what is influencing Linköping, knowledge gaps and uncertainties related to sustainability consequences were highlighted. The findings show that goals, priorities, and policies controlling management are short-termed, and decisions on maintenance and renewal are often restricted to finding solutions to the most urgent issues. Sustainability transformation in the infrastructure area will not be possible through individual efforts without coordinated technical, organizational, business, and regulatory changes.

Keywords: case study, infrastructure, management, practice, Sweden

Procedia PDF Downloads 71

Authors: Chuping Lo

Abstract:

This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

Procedia PDF Downloads 54