Search results for: administrative support

Authors: Deanna Ruano-Meas, Laura Shenkman

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Variances are seen in the way healthcare personnel (HCP) don and doff PPE risking contamination to self and others. By standardizing practice, variances in technique decrease, and so does the risk of contamination. To implement this change, the Model for Improvement will be used. A system change will be developed that will outline the role of the organizational leader’s support of HCP in the proper donning and doffing of PPE. Interventions will include environmental surveys to assess the safety and work situation ensuring a permissible environment, plan audits to confirm consistency, and the assessment of PPE wear for standardization. The change will also include an educational plan that will involve instruction of the current guidelines recommended by the Centers for Disease Control and Prevention (CDC) to all pertinent HCP, and the incorporation of PPE education in yearly educational training. The goal is a standardized practice and a reduced risk of contamination through education and organizational support. Personal protective equipment has had recent attention with the coming of the SARS-CoV-2. The realization that proper technique is important to decreasing contamination of pathogens has led to the revising of current processes.

Keywords: donning and doffing, HAI, infection control, PPE

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Authors: Ana Mercedes Vernia Carrasco

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The objective of this work is to reflect through the theoretical framework on the access to the university for the formation of a degree in a teacher of primary education. The University Access Tests in Spain evaluate a series of skills and competencies in writing, which leave aside the sample of another set of skills and tools that this type of test cannot evaluate. In the last years, a very much diversified student body has arrived in the classrooms of the Universities. Nowadays, talking about special education means attending to the changes that are being experienced in this area. At present, the educational model focuses on the reinforcement by the educational institutions so that they form the students according to their personal characteristics and that it is not the students that must adapt to the system. A bibliographic review plus some years of experience in training for the future teacher allows us to make an initial assessment about the lack of rigor in the tests of access to the university. In conclusion, we can say that, although we are not a specialist in the type of Special Educational Needs that can manifest the students, therefore, we understand that teacher today needs training and support to develop their teaching with the best quality possible. These teacher and student needs also imply more institutional support.

Keywords: training, special needs, didactics, music

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Authors: Iqbaldeep Kaur, Amarjeet Kaur

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Software Reusability is important part of software development. So component based software development in case of software testing has gained a lot of practical importance in the field of software engineering from academic researcher and also from software development industry perspective. Finding test cases for efficient reuse of test cases is one of the important problems aimed by researcher. Clustering reduce the search space, reuse test cases by grouping similar entities according to requirements ensuring reduced time complexity as it reduce the search time for retrieval the test cases. In this research paper we proposed approach for re-usability of test cases by unsupervised approach. In unsupervised learning we proposed k-mean and Support Vector Machine. We have designed the algorithm for requirement and test case document clustering according to its tf-idf vector space and the output is set of highly cohesive pattern groups.

Keywords: software testing, reusability, clustering, k-mean, SVM

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Authors: Jiawei Dai, Xinrong Li, Yulong Sun, Yunxiao Hao

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Recently, participatory approaches have become popular in a variety of fields, including social work, community, and population health, as important research tools for researchers to understand and immerse communities and conceptualize social phenomena. The participatory visual research methods promote the diversification and depth of the exploration process and communication forms to support the feasibility and practicality of the scheme, which helps to further inspire designers and avoid blind spots caused by the solidification of single thinking. This paper focuses on how to develop visual toolkits for participatory methods to assist and shape crowd participation and trigger idea generation in community issues. This project helps to verify the value of participatory visual tools in shaping participation and arousing expression, which provides support for gaining community diversity insights and community problem-solving. In addition, a visual toolbox was developed based on an actual case in a community for field testing, and further discussion was carried out after the data results were analyzed.

Keywords: participatory design, community service, visual toolbox, visual metaphor

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Authors: Elena Carbone, Chiara Meneghetti, Ivan Innocenti, Monica Musicanti, Paola Volpe, Francesca Pazzaglia

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Promoting environmental sustainability is becoming a priority for organizations. Little is known, however, on the extent to which green workplace behaviors are linked, alongside organizational determinants, and also to various employees’ individual characteristics. The BE-GREEN research project, in collaboration with Eni S.p.A., aimed at investigating the relationship between the adoption of green workplace behaviors and various employees’ job-related and broader individual characteristics as well as organizational determinants. A sample of 513 Eni employees was administered a survey assessing the adoption of green workplace behaviors and the management of events (e.g., near-miss, unsafe conditions, weak signals) that could anticipate the occurrence of incidents with a harmful environmental impact. The survey also assessed employees’ job-related (e.g., proneness toward behaving pro-environmentally at work) and general (e.g., soft skills, connectedness to nature and environmental awareness) characteristics and perceived organizational support (e.g., environmental culture, leadership). Results showed that the adoption of green workplace behaviors was associated with employees’ proneness toward behaving pro-environmentally at work, and these factors were, in turn, influenced by broader individual characteristics related to soft skills as well as a connectedness to nature and environmental awareness, along with perceived organizational support. The management of events potentially anticipating the occurrence of incidents with a harmful environmental impact was mainly associated with perceived organizational support. These findings highlight how, alongside organizational determinants, different employees’ individual characteristics influence their adoption of green workplace behaviors, with important implications for the development of interventions tailored to promote environmental sustainability in organizations.

Keywords: green workplace behaviors, soft skills, connectedness to nature, environmental awareness.

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Bin Liu

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As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

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Authors: Nicole Nicholson, Anne Spillane

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The purpose of this quantitative, descriptive analysis was to determine the success of a post-graduate new teacher education program, designed to teach educators the knowledge and skills necessary to use technology in the classroom, improve the ability to communicate with stakeholders, and implement EBPs and UDL principles into instruction for students with ASD (Autism Spectrum Disorders ). The success of candidates (n=20) in the program provided evidence as to how candidates were effectively able to use technology to create meaningful learning opportunities and implement EBPs for individuals with ASD. ≥90% of participants achieved the following competencies: podcast creation; technology used to share information about assistive technology; and created a resource website on ASD (including information on EBPs, local and national support groups, ASD characteristics, and the latest research on ASD). 59% of students successfully created animation. Results of the analysis indicated that the teacher education program was successful in teaching candidates desired competencies during its first year of implementation.

Keywords: autism spectrum disorders, ASD, evidence based practices, EBP, universal design for learning, UDL

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: virtualization, remote desktop, HTML5, cloud computing

Procedia PDF Downloads 339

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

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Media has revealed a variety of corruption cases in the regional and local governments all over the world. Many governments pursued many anti-corruption reforms and have created a system of checks and balances. Three types of corruption are faced by citizens; administrative corruption, collusion and extortion. Accountability is one of the benchmarks for building transparent government. The public sector is required to report the results of the programs that have been implemented so that the citizen can judge whether the institution has been working such as economical, efficient and effective. Open Data is offering solutions for the implementation of good governance in organizations who want to be more transparent. In addition, Open Data can create transparency and accountability to the community. The objective of this paper is to build a framework of open data for accountability to combating corruption. This paper will investigate the relationship between open data, and accountability as part of anti-corruption initiatives. This research will investigate the impact of open data implementation on public organization.

Keywords: open data, accountability, anti-corruption, framework

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Authors: Jobo Dubihlela, Kofi Boamah

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The inimitable role of the internal auditing, challenges and the predicament of state-owned enterprises in emerging markets are acknowledged. Study sought to address the inter-related questions, about how does IAF complement the performance and sustainability of SOEs? How can effective IA control systems be implemented to improve the performance results and culture of SOEs in Namibia? The weaknesses inherent in the SOE sector, unfortunately, impacts on the IAF ability to effectively support the SOEs. Despite these challenges, the study has unearthed IAF potential capabilities to contribute to SOE survival in Namibia by complementing the governance practices of the sector. Using a quantitative research approach, the dataset was collected and analysed from SOEs to confirm the role of the internal auditing function (IAF) as an indispensable concomitant of SOE performance. The study adopted a data approach supported by the literary evidence, which enabled generalisation and connectedness of the issues being addressed. The outcome of the data analysis contributed to achieving the results, which are discussed and eventually support the conclusions reached. Results show that the intractable task of internal auditing depends on the leadership of the board of directors of the SOEs. Study also revealed critical priorities needed to influence policymakers and oversight bodies to overcome the iniquities influencing SOE operations, understand and embrace IAF to salvage a sector that has a lot to offer and yet is severely mismanaged. Results support literature on IA’s contribution to SOE development from a developing country’s point of view and is the first of its kind in Namibia. Findings suggest ways to possibly enhance knowledge development of future researchers and ‘wet their appetite’ for further research in emerging markets and on a global scale.

Keywords: internal auditing activity, state-owned enterprises, emerging markets, auditing function

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Authors: Farid Arya, Trevor Hyde, Andrea Trevisi, Paolo Basso, Danilo Bardaro

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Heat transfer through multiple pane windows can be reduced by creating a vacuum pressure less than 0.1 Pa between the glass panes, with low emittance coatings on one or more of the internal surfaces. Fabrication of vacuum glazing (VG) requires the formation of a hermetic seal around the periphery of the glass panes together with an array of support pillars between the panes to prevent them from touching under atmospheric pressure. Atmospheric pressure and temperature differentials induce stress which can affect the integrity of the glazing. Several parameters define the stresses in VG including the glass thickness, pillar specifications, glazing dimensions and edge seal configuration. Inherent stresses in VG can result in fractures in the glass panes and failure of the edge seal. In this study, stress in VG with different glass thicknesses is theoretically studied using Finite Element Modelling (FEM). Based on the finding in this study, suggestions are made to address problems resulting from the use of thinner glass panes in the fabrication of VG. This can lead to the development of high performance, light and thin VG.

Keywords: vacuum glazing, stress, vacuum insulation, support pillars

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Authors: Chu Shi Wei

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Supported employment in Malaysia is in the early stages of development. The development of supported employment in Malaysia is an important step towards the inclusion of individuals with disabilities who have previously lacked the necessary support for employment in the open labour market as they were confined to sheltered workshops. There is a paradigm shift from sheltered to supported employment as the sheltered workshop is based on the medical model of disability, which focuses on the disability of the individual and segregated training institutions. The paradigm shift revolves around the social model of disability, which emphasizes the abilities of the individual and the removal of the barriers in the environment by the provision of support. This study explores the development of supported employment by utilizing a mixed methods approach which consists of collecting quantitative data through a survey and interviewing participants to collect qualitative data. Job coaches from six employment sectors participated in the survey and interview. The findings of the study indicate that the role of job coaches is integral to the development of supported employment. The role of job coaches includes job matching, on-the-job training, and developing natural supports to foster greater diversity and inclusion in the workplace.

Keywords: supported employment, disabilities, diversity, development

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Authors: Kishen Prathivadi

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The Sewer Authority Mid-Coastside (SAM) is a Joint Powers Authority formed in 1976 and provides secondary wastewater treatment to an average flow of 2.0 million gallons per day. SAM owns and operates a Wastewater Treatment Plant (WWTP) and a sanitary sewage collection system that collects sewage from its three member agencies: the City of Half Moon Bay, the Granada Community Services District and Montara Water and Sanitary District. The Sewer Authority Mid-Coastside (SAM) partnered with Pacific Gas & Electric, and its contractor GEL America, to review and replace all inefficient lighting fixtures and bulbs at the SAM treatment plant and administrative office. The project focused on replacing old and inefficient lighting fixtures and bulbs, reducing annual operating and maintenance costs, and reducing SAM’s carbon footprint. The project resulted in a 55% overall energy reduction, higher light quality and acuity, and a total operational savings of $495,000 over ten years.

Keywords: energy savings, LED, lighting, electrical

Procedia PDF Downloads 139

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

Procedia PDF Downloads 129

Authors: Sin Ying Tan, Mohammed Alloghani, A. J. Aljaaf, Abir Hussain, Jamila Mustafina

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Industry 4.0 is a term frequently used to describe the new upcoming industry era. Higher education institutions aim to prepare students to fulfil the future industry needs. Advancement of digital technology has paved the way for the evolution of education and technology. Evolution of education has proven its conservative nature and a high level of resistance to changes and transformation. The gap between the industry's needs and competencies offered generally by education is revealing the increasing need to find new educational models to face the future. The aim of this study was to identify the main issues faced by both universities and students in preparing the future workforce. From December 2018 to April 2019, a regional qualitative study was undertaken in Liverpool, United Kingdom (UK). Interviews were conducted with employers, faculty members and undergraduate students, and the results were analyzed using the open coding method. Four main issues had been identified, which are the characteristics of the future workforce, student's readiness to work, expectations on different roles played at the tertiary education level and awareness of the latest trends. The finding of this paper concluded that the employers and academic practitioners agree that their expectations on each other’s roles are different and in order to face the rapidly changing technology era, students should not only have the right skills, but they should also have the right attitude in learning. Therefore, the authors address this issue by proposing a learning framework known as 'ASK SUMA' framework as a guideline to support the students, academicians and employers in meeting the needs of 'Industry 4.0'. Furthermore, this technology era requires the employers, academic practitioners and students to work together in order to face the upcoming challenges and fast-changing technologies. It is also suggested that an interactive system should be provided as a platform to support the three different parties to play their roles.

Keywords: attitude, expectations, industry needs, knowledge, skills

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Authors: Humaira Mujeeb, Farah Qadir

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The present study aimed to explore the association between interpersonal relationship and postpartum depression with a special focus on gender of the infant among women in Gilgit, Gilgit-Baltistan, Pakistan. The research was quantitative in nature. It was a correlation study with a cross-sectional study design. The target population was women between six weeks to six months after the delivery of a baby. The sample size of 158 women has been computed by using G*Power (3.0.10 version). The sample was taken through quota sampling technique which was used to gather data according to the specifically predefined groups (79 women with female infants and 79 women with male infants). The sample was selected non-randomly according to the fixed quota. A protocol which had demographic and interpersonal relationship variables alongside with the Urdu version Edinburgh postnatal depression scale was used to collect the relevant data. The data was analyzed by using SPSS 16.0 software package. A statistically significant association between the attachment with husband in women who had a female infant and postpartum depression has been found. The association between the husband’s emotional and physical support in women who had a female infant and postpartum depression had also been found significant. In case of women with a male infant, the association between support of in-laws and postpartum depression is statistically significant. An association between the violence/discrimination based on the basis of infant's gender in women who had a female infant and postpartum depression is also found. These findings points out that when studying the correlates of postpartum depression, it is imperative to carry out an analysis in the context of gender by considering gender of the infant especially in societies where strict gender preferences exists.

Keywords: infant, gender, attachment, husband, in-laws, support, violence, discrimination, Edinburgh postnatal depression scale, Gilgit, Pakistan

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Authors: Xiaolian Jiang, Dongling Liu, Kun Liu

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Aims: To examine the prevalence of POST-TRAUMATIC STRESS DISORDER (PTSD) symptoms among Tibetan adolescents in heavily-hit disaster area three years after Yushu earthquake, and to explore the interactions of the psycho-social-genetic risk factors. Methods: This was a three-stage study. Firstly, demographic variables，PTSD Checklist-Civilian Version （PCL-C），the Internality、Powerful other、Chance Scale，（IPC），Coping Style Scale（CSS），and the Social Support Appraisal（SSA）were used to explore the psychosocial factors of PTSD symptoms among adolescent survivors. PCL-C was used to examine the PTSD symptoms among 4072 Tibetan adolescents，and the Structured Clinical Interview for DSM-IV Disorders（SCID）was used by psychiatrists to make the diagnosis precisely. Secondly，a case-control trial was used to explore the relationship between PTSD and gene polymorphisms. 287adolescents diagnosed with PTSD were recruited in study group, and 280 adolescents without PTSD in control group. Polymerase chain reaction-restriction fragment length polymorphism technology（PCR-RFLP）was used to test gene polymorphisms. Thirdly，SPSS 22.0 was used to explore the interactions of the psycho-social-genetic risk factors of PTSD on the basis of the above results. Results and conclusions: 1．The prevalence of PTSD was 9.70%. 2．The predictive psychosocial factors of PTSD included earthquake exposure, support from others, imagine, abreact, tolerant, powerful others and family support. 3．Synergistic interactions between A1 gene of DRD2 TaqIA and the external locus of control, negative coping style, severe earthquake exposure were found. Antagonism interactions between A1 gene of DRD2 TaqIA and poor social support was found. Synergistic interactions between A1/A1 genotype and the external locus of control, negative coping style were found. Synergistic interactions between 12 gene of 5-HTTVNTR and the external locus of control, negative coping style, severe earthquake exposure were found. Synergistic interactions between 12/12 genotype and the external locus of control, negative coping style, severe earthquake exposure were also found.

Keywords: adolescents, earthquake, PTSD, risk factors

Procedia PDF Downloads 152

Authors: Shah Muhammad Butt

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The study aimed to investigate the factors influencing the adoption of e-governance in Pakistan's public universities and how that adoption has affected organizational performance. An online Likert scale survey was utilized to gather information from 350 participants from different public universities in Pakistan. The data were examined using descriptive statistics and correlation analysis. The findings suggest that organizational culture, infrastructure, and leadership support are among the elements impacting the adoption of e-governance at Pakistan's public sector universities. A further finding of the study was that e-governance adoption benefited organizational performance, including effectiveness, efficiency, and customer satisfaction. The study emphasizes the significance of e-governance adoption at public sector universities and the demand for successful policies and strategies to support its implementation. To increase organisational performance and raise the standard of higher education in Pakistan, policymakers and university administrators should use the study's findings to develop and practice e-governance policies and initiatives.

Keywords: e-governance, adoption, public sector universities, Pakistan, organizational performance, higher education, technology, ICT, factors, comparative analysis

Procedia PDF Downloads 92

Authors: Lan Wu

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The declared transformation towards a ‘new electricity system dominated by renewable energy’ by China requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power as a consequence of integration constraints. The upcoming energy law of the PRC (energy law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new energy law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity reform and legislative development, the present paper investigates whether there is a paradigm shift in energy law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 draft for comments on the energy law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five key aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids, and dispatching. The analysis shows that it is reasonable to expect a more open and well-organized electricity market enabling absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming energy law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.

Keywords: energy law, energy transition, electricity market reform, renewable energy integration

Procedia PDF Downloads 195

Authors: Carlos A. C. G. Neto, Natan C. G. e Silva , Thaís de O. Costa, Luciana R. B. Gonçalves, Maria V. P. Rocha

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β-galactosidases (E.C. 3.2.1.23) are enzymes that have attracted by catalyzing the hydrolysis of lactose and in producing galacto-oligosaccharides by favoring transgalactosylation reactions. These enzymes, when immobilized, can have some enzymatic characteristics substantially improved, and the coating of supports with multifunctional polymers is a promising alternative to enhance the stability of the biocatalysts, among which polyethylenimine (PEI) stands out. PEI has certain properties, such as being a flexible polymer that suits the structure of the enzyme, giving greater stability, especially for multimeric enzymes such as β-galactosidases. Besides that, protects them from environmental variations. The use of chitosan support coated with PEI could improve the catalytic efficiency of β-galactosidase from Kluyveromyces lactis in the transgalactosylation reaction for the production of prebiotics, such as lactulose since this strain is more effective in the hydrolysis reaction. In this context, the aim of the present work was first to develop biocatalysts of β-galactosidase from K. lactis immobilized on chitosan-coated with PEI, determining the immobilization parameters, its operational and thermal stability, and then to apply it in hydrolysis and transgalactolisation reactions to produce lactulose using whey as a substrate. The immobilization of β-galactosidase in chitosan previously functionalized with 0.8% (v/v) glutaraldehyde and then coated with 10% (w/v) PEI solution was evaluated using an enzymatic load of 10 mg protein per gram support. Subsequently, the hydrolysis and transgalactosylation reactions were conducted at 50 °C, 120 RPM for 20 minutes, using whey supplemented with fructose at a ratio of 1:2 lactose/fructose, totaling 200 g/L. Operational stability studies were performed in the same conditions for 10 cycles. Thermal stabilities of biocatalysts were conducted at 50 ºC in 50 mM phosphate buffer, pH 6.6 with 0.1 mM MnCl2. The biocatalyst whose support was coated was named CHI_GLU_PEI_GAL, and the one that was not coated was named CHI_GLU_GAL. The coating of the support with PEI considerably improved the parameters of immobilization. The immobilization yield increased from 56.53% to 97.45%, biocatalyst activity from 38.93 U/g to 95.26 U/g and the efficiency from 3.51% to 6.0% for uncoated and coated support, respectively. The biocatalyst CHI_GLU_PEI_GAL was better than CHI_GLU_GAL in the hydrolysis of lactose and production of lactulose, converting 97.05% of lactose at 5 min of reaction and producing 7.60 g/L lactulose in the same time interval. QUI_GLU_PEI_GAL biocatalyst was stable in the hydrolysis reactions of lactose during the 10 cycles evaluated, converting 73.45% lactose even after the tenth cycle, and in the lactulose production was stable until the fifth cycle evaluated, producing 10.95 g/L lactulose. However, the thermal stability of CHI_GLU_GAL biocatalyst was superior, with a half-life time 6 times higher, probably because the enzyme was immobilized by covalent bonding, which is stronger than adsorption (CHI_GLU_PEI_GAL). Therefore, the strategy of coating the supports with PEI has proven to be effective for the immobilization of β-galactosidase from K. lactis, considerably improving the immobilization parameters, as well as, the catalytic action of the enzyme. Besides that, this process can be economically viable due to the use of an industrial residue as a substrate.

Keywords: β-galactosidase, immobilization, kluyveromyces lactis, lactulose, polyethylenimine, transgalactosylation reaction, whey

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Authors: Siti Mariani, Arwin DW Sumari, Retno Gumilang Dewi

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This paper analyzes the necessity of a structured tariff calculation for geothermal electricity in Indonesia. Indonesia is blessed with abundant natural resources and a choices of energy resources to generate electricity among other are coal, gas, biomass, hydro to geothermal, creating a fierce competition in electricity tariffs. While geothermal is inline with energy security principle and green growth initiative, it requires a huge capital funding. Geothermal electricity development consists of phases of project with each having its own financial characteristics. The Indonesian government has set a support in the form of ceiling price of geothermal electricity tariff by 11 U.S cents / kWh. However, the government did not set a levelized cost of geothermal, as an indication of lower limit capacity class, to which support is given. The government should establish a levelized cost of geothermal energy to reflect its financial capability in supporting geothermal development. Aside of that, the government is also need to establish a structured tariff calculation to reflect a fair and transparent business cooperation.

Keywords: load fator, levelized cost of geothermal, geothermal power plant, structured tariff calculation

Procedia PDF Downloads 440

Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

Procedia PDF Downloads 223

Authors: Jilu David

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Background: Schizophrenia is one of the most misunderstood mental illnesses across the globe. Lack of understanding about mental illnesses often delay treatment, severely affects the functionality of the person, and causes distress to the family. The study, Video-based Psychoeducation for Caregivers of Persons with Schizophrenia, consisted of developing a psychoeducational video about Schizophrenia, its symptoms, causes, treatment, and the importance of family support. Methodology: A quasi-experimental pre-post design was used to understand the feasibility of the study. Qualitative analysis strengthened the feasibility outcomes. Knowledge About Schizophrenia Interview was used to assess the level of knowledge of 10 participants, before and after the screening of the video. Results: Themes of usefulness, length, content, educational component, format of the intervention, and language emerged in the qualitative analysis. There was a statistically significant difference in the knowledge level of participants before and after the video screening. Conclusion: The statistical and qualitative analysis revealed that the video-based psychoeducation program was feasible and that it facilitated a general improvement in knowledge of the participants.

Keywords: Schizophrenia, mental illness, psychoeducation, video-based psychoeducation, family support

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Authors: Gulnara N. Nabiyeva, Stephen M. Wheeler

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Geographic Information Systems (GIS) is a multipurpose computer-based tool that provides a sophisticated ability to map and analyze data on different spatial layers. However, GIS is far more easily applied in some policy areas than others. This paper seeks to determine the areas of sustainable development, including environmental, economic, and social dimensions, where GIS has been used to date to support efforts to implement the United Nations Sustainable Development Goals (SDGs), and to discuss potential areas where it might be used more. Based on an extensive analysis of published literature, we ranked the SDGs according to how frequently GIS has been used to study related policy. We found that SDG#15 “Life on Land” is most often addressed with GIS, following by SDG#11 “Sustainable Cities and Communities”, and SDG#13 “Climate Action”. On the other hand, we determined that SDG#2 “Zero Hunger”, SDG#8 “Decent Work and Economic Growth”, and SDG#16 “Peace, Justice, and Strong Institutions” are least addressed with GIS. The paper outlines some specific ways that GIS might be applied to the SDGs least linked to this tool currently.

Keywords: GIS, GIS application, sustainable community development, sustainable development goals

Procedia PDF Downloads 133

Authors: G. Erkomaishvili, M. Kobalava, T. Lazariashvili, M. Saghareishvili

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The article discusses the consumer market of agricultural products and agricultural policy in Georgia. It is noted that development of the strategic areas of the agricultural sector needs a special support. These strategic areas should create the country's major export potential. It is important to develop strategies to access to the international markets, form extensive marketing network etc., which will become the basis for the promotion and revenue growth of the country. The Georgian agricultural sector, with the right state policy and support, can achieve success and gain access to the world market with competitive agricultural products. The paper discusses the current condition of agriculture, export and import of agricultural products and agricultural policy in Georgia. The conducted research concludes the information that there is an increasing demand on the green goods in the world market. Natural and climatic conditions of Georgia give a serious possibility of implementing it. The research presents an agricultural development strategy in Georgia and the findings and based on them recommendations are proposed.

Keywords: agriculture, export-import of agricultural products, agricultural cooperative society, agricultural policy, agricultural insurance

Procedia PDF Downloads 319

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 621

Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

Procedia PDF Downloads 422

Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

Abstract:

Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

Procedia PDF Downloads 515