Search results for: real-time data acquisition and reporting

Authors: Ramzi Shawahna

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Background: Neonatal intensive care units are high-risk settings where medication errors can occur and cause harm to this fragile segment of patients. This multicenter qualitative study was conducted to describe medication errors that occurred in neonatal intensive care units in Palestine from the perspectives of healthcare providers. Methods: This exploratory multicenter qualitative study was conducted and reported in adherence to the consolidated criteria for reporting qualitative research checklist. Semi-structured in-depth interviews were conducted with healthcare professionals (4 pediatricians/neonatologists and 11 intensive care unit nurses) who provided care services for patients admitted to neonatal intensive care units in Palestine. An interview schedule guided the semi-structured in-depth interviews. The qualitative interpretive description approach was used to thematically analyze the data. Results: The total duration of the interviews was 282 min. The healthcare providers described their experiences with 41 different medication errors. These medication errors were categorized under 3 categories and 10 subcategories. Errors that occurred while preparing/diluting/storing medications were related to calculations, using a wrong solvent/diluent, dilution errors, failure to adhere to guidelines while preparing the medication, failure to adhere to storage/packaging guidelines, and failure to adhere to labeling guidelines. Errors that occurred while prescribing/administering medications were related to inappropriate medication for the neonate, using a different administration technique from the one that was intended and administering a different dose from the one that was intended. Errors that occurred after administering the medications were related to failure to adhere to monitoring guidelines. Conclusion: In this multicenter study, pediatricians/neonatologists and neonatal intensive care unit nurses described medication errors occurring in intensive care units in Palestine. Medication errors occur in different stages of the medication process: preparation/dilution/storage, prescription/administration, and monitoring. Further studies are still needed to quantify medication errors occurring in neonatal intensive care units and investigate if the designed strategies could be effective in minimizing medication errors.

Keywords: medication errors, pharmacist, pharmacology, neonates

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Sunday Ose Ugadu

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Unemployment, especially graduate unemployment is, for now, the greatest problem facing Nigeria as a nation. It is responsible for most of the other ills of the country, including kidnapping, armed robbery, youth restiveness, thuggery, to mention but a few. More and more people in Nigeria are now losing confidence in the prospect of tertiary education as an instrument par excellence for effecting national development. This paper, therefore, critically examined the problem of graduate unemployment in Nigeria. It briefly traced the history of university education in Nigeria. The rate and causes of graduate unemployment in Nigeria were also discussed. Previous attempts made by the government to solve the problem of unemployment were highlighted. The paper also harped on the prospect of entrepreneurship education as an instrument for fighting graduate unemployment identifying obstacles to entrepreneurship education in Nigeria. The paper drew conclusion, and major recommendation made was a call for converting the National Youth Service Corps Scheme in Nigeria to entrepreneurship and skills acquisition scheme as soon as possible.

Keywords: graduate, unemployment, entrepreneurship education, national development

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Authors: Ashima Anurag Sharma

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Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini

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Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.

Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling

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Authors: Waziri Victor Onomza, John K. Alhassan, Idris Ismaila, Noel Dogonyaro Moses

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This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute theoretical presentations in high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, homomorphic, homomorphic encryption scheme

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Authors: Besa Muthuri

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This paper examines the correlation between the organization's human resources (HR) and marketing entities and reviews the literature on customer acquisition and loyalty retention and the various aspects of employer branding. It will also explore how these concepts can be applied to the marketing and human resources departments. HR and marketing teams in the organization function to educate, attract and retain the attention and interests of the modern talent market. While the teams' target products, personas, or services tend to differ, their execution, desired results, and implementation of the respective activities are closely related. Therefore, promoting collaboration between HR and marketing enables the company to enhance business branding and recruitment of top-tier talents that will drive the much-needed change in the organization and promote a higher employee and customer retention rate. To achieve the ultimate HR and marketing relationship, organizations should build their external and internal awareness, track their performance and programs, and promote in-house meetings among employees from all interfacing departments.

Keywords: branding, employee retention, human resources, marketing

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Authors: Jong Yeop Kim, Sung Young Park, Dae Hee Kim, Han Bum Joe, Ji Young Yoo, Jong Bum Choi, Sook Young Lee

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Emergence agitation (EA) is commonly reported adverse events after sevoflurane anesthesia in pediatric patients. The efficacy of prophylactic remifentanil, one of mu opioid agonist, in preventing EA is controversial. This meta-analysis assessed the effectiveness of remifentanil to decrease the incidence of EA from sevoflurane anesthesia in children. We searched for randomized controlled trials comparing sevoflurane alone anesthesia with sevoflurane and remifentanil anesthesia to prevent EA in the Cochrane Library, Embase, Pubmed, and KoreaMed, and included 6 studies with 361 patients. The number of patients of reporting EA was summarized using risk ratio (RR) with 95% confidence interval (CI), with point estimates and 95CIs derived from a random effects Mantel-Haenszel method. Overall incidence of EA was about 41%. Compared with sevoflurane alone anesthesia, intravenous infusion of remifentanil with sevoflurane significantly reduced the incidence of EA (RR 0.53, 95% CI 0.39-0.73, P < 0.0001), (heterogeneity, I2 = 0, P = 0.42). This meta-analysis suggested that continuous infusion of remifentanil could be effective in decreasing the EA of about 47% after sevoflurane anesthesia. However, considering limitations of the included studies, more randomized controlled studies are required to verify our results.

Keywords: emergence agitation, meta-analysis, remifentanil, pediatrics

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Authors: Bilquis Ferdousi

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With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

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Authors: Anca Maria Cimpean, Serban Comsa

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Chick embryo chorioallantoic membrane (CAM) is a well vascularised in vivo experimental model used as a platform for testing the behavior of different implants inserted on it from tumor fragments to therapeutic agents or various biomaterials. Five types of collagen-based biomaterials with 2D and 3D structure (MotifMesh, Optimaix2D, Optimaix3D, Dual Layer Collagen and Xenoderm) were implanted on CAM and continuously evaluated by stereomicroscope for up to 5 days post-implant with an emphasis of their ability to requisite and develop new blood vessels (BVs) followed by microscopic analysis. MotifMEsh did not induce any angiogenic response lacking to be invaded by BVs from the CAM, but it induced intense inflammatory response necrosis and fibroblastic reaction around the implant. Optimaix2D has good adherence. CAM with minimal or no inflammatory reaction, a good integration of the CAM between the collagen mesh’s fibers, consistent adhesion of the cells to the collagen fibers,and a good ability to form pseudo-vascular channels filled with cells. Optimaix3D induced the highest angiogenic effects on CAM. The material shows good integration on CAM. The collagen fibers of the material show the ability to organize themselves into linear and tubular structures. It is possible to see blood elements, especially at the periphery of the implant. Dual-layer collagen behaves similar to Optimaix 3D, while Xenoderm induced a moderate angiogenic effect on CAM. Based on these data, we may conclude that collagen-based materials have variable ability to requisite and develop new blood vessels. A proper selection of collagen-based biomaterial scaffolds may crucially influence the acquisition and development of blood vessels during angiogenesis assays.

Keywords: chick embryo chorioallantoic membrane, collagen scaffolds, blood vessels, vascular microenvironment

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Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

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This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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Authors: Odenigbo Veronica Ngozi, Ukwuaba Loretta Chika, Ukamaka Eze

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This study delved into youth’s empowerment pathway to unlocking entrepreneurial skills and employability in Enugu state, Nigeria. The purpose of the study is to ascertain the effect of youth joblessness in Enugu State. Two research questions guided the study, and two null hypotheses, which were formulated and tested at a 0.05 level of significance, were used for the analysis. A descriptive survey research design was employed for the study. The population for the study consisted of 103 male and female youths in Enugu state, who were randomly sampled among youths as respondents. A structured questionnaire which was developed by researchers and titled ‘Youth Empowerment a Pathway to Unlocking Entrepreneurial Skills and Employability (YEPUESEQ)’, was used to elicit information from the respondents. The instrument was validated by three experts, one from the Department of Measurement and Evaluation and two from the Department of Continuing Education and Development Studies, all from Enugu State University of Science and Technology, Agbani (ESUT). Cronbach Alpha reliability estimate was used to determine the internal consistency of the instrument with a reliability index of 0.74, indicating that the instrument is highly reliable and suitable to elicit information from the respondent. Data collected were analyzed using mean and standard deviation to answer the two research questions, while the null hypotheses were tested at 0.05 level of significance using a t-test. The findings of the study indicated that when the youths are jobless, they tend to join bad gangs in as much as they can get money, but when they are empowered, they tend towards supporting themselves, the community, and the nation as a whole in bringing in human, economic and social development to society. Based on the findings, the researchers recommended, among others, that the government should establish skill acquisition centers while the youths can enroll for a particular skill of their choice with good facilities, infrastructures and qualified facilitators.

Keywords: youth, empowerment, entrepreneurial skill, employability skill

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Authors: Grace Iember Anweh, Er Shipp

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Child Sexual Abuse (CSA) has been a contending issue across the globe. The menace of child sexual violence cuts across all continents. From 0 - 13 years, children have been sexually abused – some to the extent that their reproductive organs have been permanently damaged. The research in view is timely, as it will contribute data on CSA and media role to the communication parlance. This study believes that the adverse effects of this menace can hinder children who are potential leaders of tomorrow from harnessing their potentials to contribute to the growth and development of societies due to the psychological, health, and social effects of sex abuse. Where government policies, the law, cultural beliefs, and bottle necks surrounding processes of fighting child sexual abuse have failed, this study assumes that adequate coverage by the mass media, especially the newspapers known for their in-depth coverage and reporting, can help to eradicate or reduce to its barest minimum, the menace of CSA. Therefore, this study aims at assessing the coverage of newspapers – their policies and content towards preventive strategies, and how the public access and receive the messages to the extent they take action to forestall the persistence of sexual violation of children in Nigeria. Methodologically, the study has adopted qualitative and quantitative methods to answer the problem. The study used in-depth interview method to find out from journalists and editors of newspapers the policies that define the production of news content on sexual gender-based violence. In addition, selected National Daily newspapers are content - analysed to determine the focus of media coverage and whether the contents are preventive-based or case-based. In addition, caregivers of the reproductive ages from 16 years and above, ranging from parents, guardians, and school management, will form the study population through a survey using the questionnaire. The aim is to determine their views regarding mass media coverage of sexual violence against children and the effectiveness of the content, to the extent of prompting them to keep the child safe from sexual molesters. Findings from the content analysis so far show that newspapers in Nigeria are not engaged in preventive content of CSA. Their contents are rather case-based.

Keywords: newspaper, coverage, prevention, child, sexual abuse

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Authors: Asad Ullah Khalid

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This paper encompasses the application of the concept of political economy of mass media in Pakistan. The media has developed at a massive pace and now is considered as one of the vital parts in having better administration furthermore helps in conveying the issues identified with the government to the public. Albeit Pakistani media has gained much independence after 2003 but there are many social, political and economy factors which influence the content of the media. The study employs triangulation of quantitative and qualitative methods. In terms of methods, content analysis and interview method both are used. The content of Pakistani media is analyzed quantitatively and qualitatively. Moreover, interviews with various journalists are conducted, and their findings are disclosed in this paper. Pakistan's communication landscape is neither well documented nor well understood, leaving its public off guard with regards to reviewing the role and impact of news inflow, correspondence and media in political, economic and social life. It has been found out that on particular issues some media channels have strong affiliations with certain political parties, moreover reporting and coverage have also been affected by the factors like terrorism, state policies(written and verbal), advertising/economic and demographic factors like the composition of the population.

Keywords: political economy, news media, Pakistan, electronic news media, journalism, mass media

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: Xinge Liao, Francesc Xavier Roige Ventura, Dolores Sanchez Aguilera

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With the development of the Internet, the study of tourism behavior has rapidly expanded from the traditional physical market to the online market. Data on the Internet is characterized by dynamic changes, and new data appear all the time. In recent years the generation of a large volume of data was characterized, such as forums, blogs, and other sources, which have expanded over time and space, together they constitute large-scale Internet data, known as Big Data. This data of technological origin that derives from the use of devices and the activity of multiple users is becoming a source of great importance for the study of geography and the behavior of tourists. The study will focus on cultural heritage tourist practices in the context of Big Data. The research will focus on exploring the characteristics and behavior of Chinese tourists in relation to the cultural heritage of Catalonia. Geographical information, target image, perceptions in user-generated content will be studied through data analysis from Weibo -the largest social networks of blogs in China. Through the analysis of the behavior of heritage tourists in the Big Data environment, this study will understand the practices (activities, motivations, perceptions) of cultural tourists and then understand the needs and preferences of tourists in order to better guide the sustainable development of tourism in heritage sites.

Keywords: Barcelona, Big Data, Catalonia, cultural heritage, Chinese tourism market, tourists’ behavior

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Authors: Andreas Jede, Frank Teuteberg

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Cloud computing (CC) has already gained overall appreciation in research and practice. Whereas the willingness to integrate cloud services in various IT environments is still unbroken, the previous CC procurement processes run mostly in an unorganized and non-standardized way. In practice, a sufficiently specific, yet applicable business process for the important acquisition phase is often lacking. And research does not appropriately remedy this deficiency yet. Therefore, this paper introduces a field-tested approach for CC procurement. Based on an extensive literature review and augmented by expert interviews, we designed a model that is validated and further refined through an in-depth real-life case study. For the detailed process description, we apply the event-driven process chain notation (EPC). The gained valuable insights into the case study may help CC research to shift to a more socio-technical area. For practice, next to giving useful organizational instructions we will provide extended checklists and lessons learned.

Keywords: cloud procurement process, IT-organization, event-driven process chain, in-depth case study

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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: Mohammad Abu-Taleb

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The final report of the Royal Commission into Australian financial services misconduct, released in February 2019, has had a significant impact on the financial advice industry. The recommendations released in the Commissioner’s final report include changes to ongoing fee arrangements, a new disciplinary system for financial advisers, and mandatory reporting of compliance concerns. This thesis aims to explore the impact of the Royal Commission’s recommendations on the operating model of financial advice firms in terms of advice products, processes, delivery models, and customer segments. Also, this research seeks to investigate whether the Royal Commission’s outcome has accelerated the use of enhanced technology solutions within the operating model of financial advice firms. And to identify the key challenges confronting financial advice firms whilst implementing the Commissioner’s recommendations across their operating models. In order to achieve the objectives of this thesis, a qualitative research design has been adopted through semi-structured in-depth interviews with 24 financial advisers and managers who are engaged in the operation of financial advice services. The study used the thematic analysis approach to interpret the qualitative data collected from the interviews. The findings of this thesis reveal that customer-centric operating models will become more prominent across the financial advice industry in response to the Commissioner’s final report. And the Royal Commission’s outcome has accelerated the use of advice technology solutions within the operating model of financial advice firms. In addition, financial advice firms have started more than before using simpler and more automated web-based advice services, which enable financial advisers to provide simple advice in a greater scale, and also to accelerate the use of robo-advice models and digital delivery to mass customers in the long term. Furthermore, the study identifies process and technology changes as, long with technical and interpersonal skills development, as the key challenges encountered financial advice firms whilst implementing the Commissioner’s recommendations across their operating models.

Keywords: hayne royal commission, financial planning advice, operating model, advice products, advice processes, delivery models, customer segments, digital advice solutions

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Authors: Rabih Nehme, Abdullah Al Mutawa

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The general goal behind this research is to gain a better understanding of factors leading to dysfunctional behavior of auditors. Recent accounting scandals -Enron, Waste Management Inc., WorldCom, Xerox Corporation, etc. -provided an ample proof of how the role of auditors has become the basis of controversial debates in many circles and instances in our modern time. The majority of lawsuits and accounting scandals seem to have a central topic in focus, namely the question ''Where were the auditors? The survey we offer up for research is made up of 34 questions that are designed to analyse the perception of auditors and the cause of dysfunctional behavior. The object of this research is comprised of auditors positioned and employed at the Big Four audit firms in Kuwait. Dysfunctional behavior (DB) is measured against two signal proxies of dysfunctional behavior; premature sign-off and under reporting of chargeable time. DB is analysed against time budget pressure and time deadline pressure. The research results' suggest that the general belief among auditors is that the profession of accountancy predetermines their tendency to commit certain patterns of dysfunctional behavior. Having our investigation conducted at the Big Four audit firms, we have come to the conclusion that there is a general difference in behavior patterns among perceptions of dysfunctional behavior and normal skeptic professional behavior.

Keywords: big four, dysfunctional behavior, time budget, time deadline

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Authors: B. Ratchaneepun, N.S. Bardell

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It is recognized that people are the main drivers in almost all the processes that affect airworthiness assurance. This is especially true in the area of aircraft maintenance, which is an essential part of continuing airworthiness. This work investigates what impact English language proficiency, the intersection of the military and Thai cultures, and the lack of initial and continuing human factors training have on the work performance of maintenance personnel in the Royal Thai Air Force (RTAF). A quantitative research method based on a cross-sectional survey was used to gather data about these three key aspects of “people” in a military airworthiness environment. 30 questions were developed addressing the crucial topics of English language proficiency, impact of culture, and human factors training. The officers and the non-commissioned officers (NCOs) who work for the Aeronautical Engineering Divisions in the RTAF comprised the survey participants. The survey data were analysed to support various hypotheses by using a t-test method. English competency in the RTAF is very important since all of the service manuals for Thai military aircraft are written in English. Without such competency, it is difficult for maintenance staff to perform tasks and correctly interpret the relevant maintenance manual instructions; any misunderstandings could lead to potential accidents. The survey results showed that the officers appreciated the importance of this more than the NCOs, who are the people actually doing the hands-on maintenance work. Military culture focuses on the success of a given mission, and leverages the power distance between the lower and higher ranks. In Thai society, a power distance also exists between younger and older citizens. In the RTAF, such a combination tends to inhibit a just reporting culture and hence hinders safety. The survey results confirmed this, showing that the older people and higher ranks involved with RTAF aircraft maintenance believe that the workplace has a positive safety culture and climate, whereas the younger people and lower ranks think the opposite. The final area of consideration concerned human factors training and non-technical skills training. The survey revealed that those participants who had previously attended such courses appreciated its value and were aware of its benefits in daily life. However, currently there is no regulation in the RTAF to mandate recurrent training to maintain such knowledge and skills. The findings from this work suggest that the people involved in assuring the continuing airworthiness of the RTAF would benefit from: (i) more rigorous requirements and standards in the recruitment, initial training and continuation training regarding English competence; (ii) the development of a strong safety culture that exploits the uniqueness of both the military culture and the Thai culture; and (iii) providing more initial and recurrent training in human factors and non-technical skills.

Keywords: aircraft maintenance, continuing airworthiness, military culture, people, Royal Thai Air Force

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Authors: Lillie Lum

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Focusing on the role of official language in immigrant integration, this paper will first report the results of a literature review and demonstrate that there is no doubt on the necessity of adequate language skills for newcomers to successfully settle, adapt, and integrate socially, culturally and economically in Canada. This paper attempts to synthesize the literature in order to shed light on the language policy terrain which is not easy to navigate. Then, by outlining what is currently available in the language policy environment, it will ask if the current state of language training in Canada is adequate to assist newcomers in their language acquisition process. At a deeper level, it aims to continue to raise questions in this policy area. Are current policy responses likely to improve linguistic capabilities in the future, particularly for immigrant workers with poor language proficiency? This paper is timely given the magnitude of the language issue and the value of immigrants for Canada’s economic, social, and political vitality.

Keywords: official language education, immigrant integration into Canada, economic factors, policy implications

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

Abstract:

Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

Procedia PDF Downloads 291

Authors: Yuyun Wabula, B. J. Dewancker

Abstract:

In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

Procedia PDF Downloads 314

Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

Abstract:

Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

Procedia PDF Downloads 657

Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

Procedia PDF Downloads 225