Search results for: lest support orthogonal matching pursuit
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7987

Search results for: lest support orthogonal matching pursuit

6577 Developing Innovative Participatory Visual Toolkits for Community Story Collection

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

Abstract:

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

Procedia PDF Downloads 93
6576 Growing Architecture, Technical Product Harvesting of Near Net Shape Building Components

Authors: Franziska Moser, Martin Trautz, Anna-Lena Beger, Manuel Löwer, Jörg Feldhusen, Jürgen Prell, Alexandra Wormit, Björn Usadel, Christoph Kämpfer, Thomas-Benjamin Seiler, Henner Hollert

Abstract:

The demand for bio-based materials and components in architecture has increased in recent years due to society’s heightened environmental awareness. Nowadays, most components are being developed via a substitution approach, which aims at replacing conventional components with natural alternatives who are then being processed, shaped and manufactured to fit the desired application. This contribution introduces a novel approach to the development of bio-based products that decreases resource consumption and increases recyclability. In this approach, natural organisms like plants or trees are not being used in a processed form, but grow into a near net shape before then being harvested and utilized as building components. By minimizing the conventional production steps, the amount of resources used in manufacturing decreases whereas the recyclability increases. This paper presents the approach of technical product harvesting, explains the theoretical basis as well as the matching process of product requirements and biological properties, and shows first results of the growth manipulation studies.

Keywords: design with nature, eco manufacturing, sustainable construction materials, technical product harvesting

Procedia PDF Downloads 500
6575 Promoting Environmental Sustainability in the Workplace: The Be-Green Project

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

Abstract:

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.

Procedia PDF Downloads 63
6574 Optimizing Microwave Assisted Extraction of Anti-Diabetic Plant Tinospora cordifolia Used in Ayush System for Estimation of Berberine Using Taguchi L-9 Orthogonal Design

Authors: Saurabh Satija, Munish Garg

Abstract:

Present work reports an efficient extraction method using microwaves based solvent–sample duo-heating mechanism, for the extraction of an important anti-diabetic plant Tinospora cordifolia from AYUSH system for estimation of berberine content. The process is based on simultaneous heating of sample matrix and extracting solvent under microwave energy. Methanol was used as the extracting solvent, which has excellent berberine solubilizing power and warms up under microwave attributable to its great dispersal factor. Extraction conditions like time of irradition, microwave power, solute-solvent ratio and temperature were optimized using Taguchi design and berberine was quantified using high performance thin layer chromatography. The ranked optimized parameters were microwave power (rank 1), irradiation time (rank 2) and temperature (rank 3). This kind of extraction mechanism under dual heating provided choice of extraction parameters for better precision and higher yield with significant reduction in extraction time under optimum extraction conditions. This developed extraction protocol will lead to extract higher amounts of berberine which is a major anti-diabetic moiety in Tinospora cordifolia which can lead to development of cheaper formulations of the plant Tinospora cordifolia and can help in rapid prevention of diabetes in the world.

Keywords: berberine, microwave, optimization, Taguchi

Procedia PDF Downloads 347
6573 Digital Platform of Crops for Smart Agriculture

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

Abstract:

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

Procedia PDF Downloads 80
6572 Semantics of the Word “Nas” in the Verse 24 of Surah Al-Baqarah Based on Izutsus’ Semantic Field Theory

Authors: Seyedeh Khadijeh. Mirbazel, Masoumeh Arjmandi

Abstract:

Semantics is a linguistic approach and a scientific stream, and like all scientific streams, it is dynamic. The study of meaning is carried out in the broad semantic collections of words that form the discourse. In other words, meaning is not something that can be found in a word; rather, the formation of meaning is a process that takes place in a discourse as a whole. One of the contemporary semantic theories is Izutsu's Semantic Field Theory. According to this theory, the discovery of meaning depends on the function of words and takes place within the context of language. The purpose of this research is to identify the meaning of the word "Nas" in the discourse of verse 24 of Surah Al-Baqarah, which introduces "Nas" as the firewood of hell, but the translators have translated it as "people". The present research has investigated the semantic structure of the word "Nas" using the aforementioned theory through the descriptive-analytical method. In the process of investigation, by matching the semantic fields of the Quranic word "Nas", this research came to the conclusion that "Nas" implies those persons who have forgotten God and His covenant in believing in His Oneness. For this reason, God called them "Nas (the forgetful)" - the imperfect participle of the noun /næsiwoɔn/ in single trinity of Arabic language, which means “to forget”. Therefore, the intended meaning of "Nas" in the verses that have the word "Nas" is not equivalent to "People" which is a general noun.

Keywords: Nas, people, semantics, semantic field theory.

Procedia PDF Downloads 189
6571 Effect of Financing Sources on Firm Performance: A Study of Indian Private Limited Small and Medium Enterprises

Authors: Denila Jinny Arulraj, Thillai Rajan Annamalai

Abstract:

This paper aims to study the relationship between funding sources and firm performance of Indian private limited SMEs using cross-sectional data obtained from a nation-wide census. A unique feature of the study is that it analyses firms that use only one form of external funding. Employing Propensity Score Matching, we find that obtaining any form of external finance has a negative influence on equivalents of profit margin and return on assets and a negative influence on asset turnover of small firms. But, the impact of institutional sources of funding on small enterprises is found to be lesser than that of non-institutional sources of funding. External/institutional sources of funding have a less negative impact on the profit margin for medium enterprises and have no significant influence on other measures of performance. The contribution of this research is the discovery of institutional sources wielding a lesser influence on performance measures considered. It is also found that institutional sources can benefit small enterprises more than medium enterprises.

Keywords: external finance, institutional finance, non-institutional finance, performance, India, SME

Procedia PDF Downloads 277
6570 Protein Remote Homology Detection by Using Profile-Based Matrix Transformation Approaches

Authors: Bin Liu

Abstract:

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

Procedia PDF Downloads 125
6569 Teaching Practitioners to Use Technology to Support and Instruct Students with Autism Spectrum Disorders

Authors: Nicole Nicholson, Anne Spillane

Abstract:

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

Procedia PDF Downloads 163
6568 Improving Fake News Detection Using K-means and Support Vector Machine Approaches

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

Abstract:

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

Procedia PDF Downloads 176
6567 Internal Auditing and the Performance of State-Owned Enterprises in Emerging Markets

Authors: Jobo Dubihlela, Kofi Boamah

Abstract:

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

Procedia PDF Downloads 103
6566 Automatic Music Score Recognition System Using Digital Image Processing

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

Abstract:

Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

Procedia PDF Downloads 419
6565 The Effect of Glass Thickness on Stress in Vacuum Glazing

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

Abstract:

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

Procedia PDF Downloads 191
6564 Specific Emitter Identification Based on Refined Composite Multiscale Dispersion Entropy

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

Abstract:

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
6563 Effect of Injection Moulding Process Parameter on Tensile Strength of Using Taguchi Method

Authors: Gurjeet Singh, M. K. Pradhan, Ajay Verma

Abstract:

The plastic industry plays very important role in the economy of any country. It is generally among the leading share of the economy of the country. Since metals and their alloys are very rarely available on the earth. So to produce plastic products and components, which finds application in many industrial as well as household consumer products is beneficial. Since 50% plastic products are manufactured by injection moulding process. For production of better quality product, we have to control quality characteristics and performance of the product. The process parameters plays a significant role in production of plastic, hence the control of process parameter is essential. In this paper the effect of the parameters selection on injection moulding process has been described. It is to define suitable parameters in producing plastic product. Selecting the process parameter by trial and error is neither desirable nor acceptable, as it is often tends to increase the cost and time. Hence optimization of processing parameter of injection moulding process is essential. The experiments were designed with Taguchi’s orthogonal array to achieve the result with least number of experiments. Here Plastic material polypropylene is studied. Tensile strength test of material is done on universal testing machine, which is produced by injection moulding machine. By using Taguchi technique with the help of MiniTab-14 software the best value of injection pressure, melt temperature, packing pressure and packing time is obtained. We found that process parameter packing pressure contribute more in production of good tensile plastic product.

Keywords: injection moulding, tensile strength, poly-propylene, Taguchi

Procedia PDF Downloads 288
6562 A Perspective on Education to Support Industry 4.0: An Exploratory Study in the UK

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

Abstract:

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

Procedia PDF Downloads 125
6561 Gender of the Infant and Interpersonal Relationship Correlates of Postpartum Depression among Women in Gilgit, Gilgit-Baltistan, Pakistan

Authors: Humaira Mujeeb, Farah Qadir

Abstract:

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

Procedia PDF Downloads 596
6560 Study on the Post-Traumatic Stress Disorder and Its Psycho-Social-Genetic Risk Factors among Tibetan Alolescents in Heavily-Hit Area Three Years after Yushu Earthquake in Qinghai Province, China

Authors: Xiaolian Jiang, Dongling Liu, Kun Liu

Abstract:

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
6559 Adoption of E-Governance: A Case Study of Higher Education Institutes in Pakistan

Authors: Shah Muhammad Butt

Abstract:

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
6558 Analysing the Renewable Energy Integration Paradigm in the Post-COVID-19 Era: An Examination of the Upcoming Energy Law of China

Authors: Lan Wu

Abstract:

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
6557 Hardware Implementation of Local Binary Pattern Based Two-Bit Transform Motion Estimation

Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

Abstract:

Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

Procedia PDF Downloads 312
6556 Improvement of Activity of β-galactosidase from Kluyveromyces lactis via Immobilization on Polyethylenimine-Chitosan

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

Abstract:

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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6555 Structured Tariff Calculation to Promote Geothermal for Energy Security

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

Abstract:

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 441
6554 A Theoretical Model for Pattern Extraction in Large Datasets

Authors: Muhammad Usman

Abstract:

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
6553 A Slip Transmission through Alpha/Beta Boundaries in a Titanium Alloy (Ti-6Al-4V)

Authors: Rayan B. M. Ameen, Ian P. Jones, Yu Lung Chiu

Abstract:

Single alpha-beta colony micro-pillars have been manufactured from a polycrystalline commercial Ti-6Al-4V sample using Focused Ion Beam (FIB). Each pillar contained two alpha lamellae separated by a thin fillet of beta phase. A nano-indenter was then used to conduct uniaxial micro-compression tests on Ti alloy single crystals, using a diamond flat tip as a compression platen. By controlling the crystal orientation along the micro-pillar using Electron back scattering diffraction (EBSD) different slip systems have been selectively activated. The advantage of the micro-compression method over conventional mechanical testing techniques is the ability to localize a single crystal volume which is characterizable after deformation. By matching the stress-strain relations resulting from micro-compression experiments to TEM (Transmission Electron Microscopy) studies of slip transmission mechanisms through the α-β interfaces, some proper constitutive material parameters such as the role of these interfaces in determining yield, strain-hardening behaviour, initial dislocation density and the critical resolved shear stress are suggested.

Keywords: α/β-Ti alloy, focused ion beam, micro-mechanical test, nano-indentation, transmission electron diffraction, plastic flow

Procedia PDF Downloads 385
6552 Video-Based Psychoeducation for Caregivers of Persons with Schizophrenia

Authors: Jilu David

Abstract:

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

Procedia PDF Downloads 131
6551 Geographic Information Systems as a Tool to Support the Sustainable Development Goals

Authors: Gulnara N. Nabiyeva, Stephen M. Wheeler

Abstract:

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
6550 Consumer Market of Agricultural Products and Agricultural Policy in Georgia

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

Abstract:

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 321
6549 Comparison of Different Artificial Intelligence-Based Protein Secondary Structure Prediction Methods

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

Abstract:

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
6548 A Medical Resource Forecasting Model for Emergency Room Patients with Acute Hepatitis

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

Abstract:

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