Search results for: raw complex data

Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Maria Pavlova

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In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

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Authors: Cory Callahan

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Here the author synthesizes findings and implications from two research studies that comprise a continuing line of inquiry into the potential of an innovative professional development program to help in-service teachers understand and implement a complex model of social studies instruction. The paper specifically explores the question: To what degree can a collaborative professional development program centered around innovative curriculum materials help social studies teachers understand and implement a powerful social studies approach? Findings suggest the teachers increasingly incorporated substantive thinking (i.e., second-order historical domain knowledge) into their respective practice and they facilitated students’ use of historical photographs as evidence to begin to answer a compelling question. The teachers also began to effectively support students’ abilities to make claims about the past. Implications include the foregrounding of high-quality questions during planning and the need for explicit guidance in the form of structures and procedures (i.e., scaffolds) to help teachers systematically review students’ work products. The work shared here may contribute to scholarship that posits explanations for why teacher-support is routinely ineffectual and suggests ways to provide substantive collaborative support for in-service social studies teachers.

Keywords: educative curriculum, social studies, professional development, lesson study

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Authors: Kyungsuk Cho, Seungun Chae, Jihun Choi

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Elevators are examined as one of evacuation methods in super-tall buildings. However, data on the use of elevators for evacuation at a fire are extremely scarce. Therefore, a test to measure delay time in using an evacuation elevator was conducted. In the test, time taken to get on and get off an elevator was measured and the case in which people gave up boarding when the capacity of the elevator was exceeded was also taken into consideration. 170 men and women participated in the test, 130 of whom were young people (20 ~ 50 years old) and 40 were senior citizens (over 60 years old). The capacity of the elevator was 25 people and it travelled between the 2nd and 4th floors. A video recording device was used to analyze the test. An elevator at an ordinary building, not a super-tall building, was used in the test to measure delay time in getting on and getting off an elevator. In order to minimize interference from other elements, elevator platforms on the 2nd and 4th floors were partitioned off. The elevator travelled between the 2nd and 4th floors where people got on and off. If less than 20 people got on the elevator which was empty, the data were excluded. If the elevator carrying 10 passengers stopped and less than 10 new passengers got on the elevator, the data were excluded. Getting-on an empty elevator was observed 49 times. The average number of passengers was 23.7, it took 14.98 seconds for the passengers to get on the empty elevator and the load factor was 1.67 N/s. It took the passengers, whose average number was 23.7, 10.84 seconds to get off the elevator and the unload factor was 2.33 N/s. When an elevator’s capacity is exceeded, the excessive number of people should get off. Time taken for it and the probability of the case were measure in the test. 37% of the times of boarding experienced excessive number of people. As the number of people who gave up boarding increased, the load factor of the ride decreased. When 1 person gave up boarding, the load factor was 1.55 N/s. The case was observed 10 times, which was 12.7% of the total. When 2 people gave up boarding, the load factor was 1.15 N/s. The case was observed 7 times, which was 8.9% of the total. When 3 people gave up boarding, the load factor was 1.26 N/s. The case was observed 4 times, which was 5.1% of the total. When 4 people gave up boarding, the load factor was 1.03 N/s. The case was observed 5 times, which was 6.3% of the total. Getting-on and getting-off time data for people who can walk freely were obtained from the test. In addition, quantitative results were obtained from the relation between the number of people giving up boarding and time taken for getting on. This work was supported by the National Research Council of Science & Technology (NST) grant by the Korea government (MSIP) (No. CRC-16-02-KICT).

Keywords: evacuation elevator, super tall buildings, evacuees, delay time

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Authors: Rohollah Asadian Kohestani, Nazanin Sedghi

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As the number of banks and financial institutions working in Iran has been significantly increased, the attracting and retaining customers and encouraging them to continually use the modern banking services have been important and vital issues. Therefore, there would be a serious competition without a deep perception of consumers and fitness of banking services with their needs in the current economic conditions of Iran. It should be noted that concepts such as 'brand equity' is defined based on the view of consumers; however, it is also focused by shareholders, competitors and other beneficiaries of a firm in addition to bank and its consumers. This study examines the impact of brand equity on the competitive advantage in the banking industry as intensive competition between brands of different banks leads to pay more attention to the brands. This research is based on the Aaker’s model examining the impact of four dimensions of brand equity on the competitive advantage of private banks in Behshahr city. Moreover, conducting an applied research and data analysis has been carried out by a descriptive method. Data collection was done using literature review and questionnaire. A 'simple random' methodology was selected for sampling staff of banks while sampling methodology to select consumers of banks was the distribution of questionnaire between staff and consumers of five private banks including Tejarat, Mellat, Refah K., Ghavamin and, Tose’e Ta’avon banks. Results show that there is a significant relationship between brand equity and their competitive advantage. In this research, software of SPSS 16 and LISREL 8.5, as well as different methods of descriptive inferential statistics for analyzing data and test hypotheses, were employed.

Keywords: brand awareness, brand loyalty, brand equity, competitive advantage

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Ramin Karimi

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One of common highly mobile wireless ad hoc networks is Vehicular Ad Hoc Networks. Hence routing in vehicular ad hoc network (VANET) has attracted much attention during the last few years. VANET is characterized by its high mobility of nodes and specific topology patterns. Moreover these networks encounter a significant loss rate and a very short duration of communication. In vehicular ad hoc networks, one of challenging is routing of data due to high speed mobility and changing topology of vehicles. Geographic routing protocols are becoming popular due to advancement and availability of GPS devices. Delay Tolerant Networks (DTNs) are a class of networks that enable communication where connectivity issues like sparse connectivity, intermittent connectivity; high latency, long delay, high error rates, asymmetric data rate, and even no end-to-end connectivity exist. In this paper, we review the existing Geographic Routing Protocols for VANETs and also provide a qualitative comparison of them.

Keywords: vehicular ad hoc networks, mobility, geographic routing, delay tolerant networks

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Authors: Saad Bin Nasir

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This research will examine the impact of corporate governance on firm performance in family and non-family owned firms in Pakistan. For the purpose of this research, corporate governance mechanisms which included are board size, board composition, leadership structure, board meetings are taken as independent variable and firm performance taken as dependent variable and it will be measured with return on asset and return on equity. Firm size and firm’s age will be taken as control variables. Secondary data will collect from audited annul reports of companies and panel data regression model will applied, to check the impact of corporate governance on firm performance.

Keywords: board size, board composition, Leadership Structure, board meetings, firm performance, family and non-family owned firms

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Authors: Mike R. Bambach

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Increasing awareness of environmental concerns is leading a drive towards more sustainable structural products for the built environment. Natural fibres such as flax, jute and hemp have recently been considered for fibre-resin composites, with a major motivation for their implementation being their notable sustainability attributes. While recent decades have seen substantial interest in the use of such natural fibres in composite materials, much of this research has focused on the materials aspects, including fibre processing techniques, composite fabrication methodologies, matrix materials and their effects on the mechanical properties. The present study experimentally investigates the compression strength of structural channel sections of flax, jute and hemp, with a particular focus on their suitability for residential stud wall applications. The section geometry is optimised for maximum strength via the introduction of complex stiffeners in the webs and flanges. Experimental results on both natural fibre composite channel sections and typical steel and timber residential wall studs are compared. The geometrically optimised natural fibre composite channels are shown to have compression capacities suitable for residential wall stud applications, identifying them as a potentially viable alternative to traditional building materials in such application, and potentially other light structural applications.

Keywords: channel sections, natural fibre composites, residential stud walls, structural composites

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Authors: Pippa Sipanoun, Jo Wray, Kate Oulton, Faith Gibson

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Background: With rapidly evolving digital health innovation, there is a need for digital health transformation that is accessible and sustainable, that demonstrates utility for all stakeholders while maintaining data safety. Great Ormond Street Hospital for Children aimed to future-proof the hospital by transitioning to an electronic patient record (EPR) system with a tethered patient portal (MyGOSH) in April 2019. MyGOSH patient portal enables patients 12 years or older (with their parent's consent) to access their digital health data. This includes access to results, documentation, and appointments that facilitate communication with their care team. As part of the Going Digital Study conducted between 2018-2021, data were collected from a sample of all relevant stakeholders before and after EPR and MyGOSH implementation. Data collection reach was wide and included the hospital legal and ethics teams. Aims: This study aims to understand the ethical and legal implications of young people and their parents accessing their digital health data. Methods: A focus group was conducted. Recruited participants were members of the Great Ormond Street Hospital Paediatric Bioethics Centre. Participants included expert and lay members from the Committee from a variety of professional or academic disciplines. Written informed consent was provided by all participants (n=7). The focus group was recorded, transcribed verbatim, and analyzed using thematic analysis. Results: Six themes were identified: access, competence and capacity - granting access to the system; inequalities in access resulting in inequities; burden, uncertainty and responding to change - managing expectations; documenting, risks and data safety; engagement, empowerment and understanding – how to use and manage personal information; legal considerations and obligations. Discussion: If healthcare professionals are to empower young people to be more engaged in their care, the importance of including them in decisions about their health is paramount, especially when they are approaching the age of becoming the consenter for treatment. Complexities exist in assessing competence or capacity when granting system access, when disclosing sensitive information, and maintaining confidentiality. Difficulties are also present in managing clinician burden, managing user expectations whilst providing an equitable service, and data management that meets professional and legal requirements. Conclusion: EPR and tethered-portal implementation at Great Ormond Street Hospital for Children was not only timely, due to the need for a rapid transition to remote consultations during the COVID-19 pandemic, which would not have been possible had EPR/MyGOSH not been implemented, but also integral to the digital health revolution required in healthcare today. This study is highly relevant in understanding the complexities around young people and their parents accessing their digital health data and, although the focus of this research related to portal use and access, the findings translate to young people in the wider digital health context. Ongoing support is required for all relevant stakeholders following MyGOSH patient portal implementation to navigate the ethical and legal complexities. Continued commitment is needed to balance the benefits and burdens, promote inclusion and equity, and ensure portal utility for patient benefit, whilst maintaining an individualized approach to care.

Keywords: patient portal, young people and their parents, ethical, legal

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Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Kamran Taghizadeh

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This study was aimed at evaluating the effect of IMS including occupational health system, environmental management system, and safety and health system on the social responsibility (case study of NISOC`s oil and gas production companies). This study`s objectives include evaluating the IMS situation and its effect on social responsibility in addition of providing appropriate solutions based on the study`s hypotheses as a basis for future. Data collection was carried out by library and field studies as well as a questionnaire. The stratified random method was the sampling method and a sample of 285 employees in addition to the collected data (from the questionnaire) were analyzed by inferential statistics methods using SPSS software. Finally, results of regression and fitted model at a significance level of 5% confirmed all hypotheses meaning that IMS and its items have a significant effect on social responsibility.

Keywords: social responsibility, integrated management, oil and gas production companies, regression

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Authors: Rachel Williams, Shiqi Yang

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Our research explores the influence nationalism has had on media coverage of the COVID-19 pandemic as it relates to China in the United States through an inclusive qualitative analysis of two US news networks, Fox News and CNN. In total, the transcripts of sixteen videos uploaded on YouTube, each with more than 100,000 views, were gathered for data processing. Co-occurrence networks generated by KH Coder illuminate the themes and narratives underpinning the reports from Fox News and CNN. The results of in-depth content analysis with keywords suggest that the pandemic has been framed in an ethnopopulist nationalist manner, although to varying degrees between networks. Specifically, the authors found that Fox News is more likely to report hypotheses or statements as a fact; on the contrary, CNN is more likely to quote data and statements from official institutions. Future research into how nationalist narratives have developed in China and in other US news coverage with a more systematic and quantitative method can be conducted to expand on these findings.

Keywords: nationalism, media studies, us and china, COVID-19, social media, communication studies

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Authors: Amenah Dhannoon, Ciaran Martin Hurley, Laura Wrafter, Podraic J. Regan

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Introduction: The COVID-19 pandemic continues to present unprecedented challenges for healthcare systems. This has resulted in the pragmatic shift in the practice of plastic surgery units worldwide. During this period, many units reported a significant fall in urgent melanoma referrals, leading to patients presenting with advanced disease requiring more extensive surgery and inferior outcomes. Our objective was to evaluate our unit's experience with both non-invasive and invasive melanoma during the COVID-19 pandemic and characterize our experience and contrast it to that experienced by our neighbors in the UK, mainland Europe and North America. Methods: a retrospective chart review was performed on all patients diagnosed with invasive and non-invasive cutaneous melanoma between March to December of 2019 (control) compared to 2020 (COVID-19 pandemic) in a single plastic surgery unit in Ireland. Patient demographics, referral source, surgical procedures, tumour characteristics, radiological findings, oncological therapies and follow-up were recorded. All data were anonymized and stored in Microsoft Excel. Results: A total of 589 patients were included in the study. Of these, 314 (53%) with invasive melanoma, compared to 275 (47%) with the non-invasive disease. Overall, more patients were diagnosed with both invasive and non-invasive melanoma in 2020 than in 2019 (p<0.05). However, significantly longer waiting times in 2020 (64 days) compared to 2019 (28 days) (p<0.05), with the majority of the referral being from GP in 2019 (83%) compared to 61% in 2020. Positive sentinel lymph node were higher in 2019 at 56% (n=28) compared to 24% (n=22) in 2020. There was no statistically significant difference in the tutor characteristics or metastasis status. Discussion: While other countries have noticed a fall in the melanoma diagnosis. Our units experienced a higher number of disease diagnoses. This can be due to multiple reasons. In Ireland, the government reached an early agreement with the private sector to continue elective surgery on an urgent basis in private hospitals. This allowed access to local anesthetic procedures and local skin cancer cases were triaged to non-COVID-19 provider centers. Our unit also adapted a fast, effective and minimal patient contact strategy for triaging skin cancer based on telemedicine. Thirdly, a skin cancer nurse specialist maintained patient follow-ups and triaging a dedicated email service. Finally, our plastic surgery service continued to maintain a virtual complex skin cancer multidisciplinary team meeting during the pandemic, ensuring local clinical governance has adhered to each clinical case. Conclusion: Our study highlights that with the prompt efficient restructuring of services, we could reserve successful management of skin cancer even in the most devastating times. It is important to reflect on the success during the pandemic and emphasize the importance of preparation for a potentially difficult future

Keywords: malignant melanoma, skin cancer, COVID-19, triage

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Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

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Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer

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Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

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In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

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Authors: Mingxi Zhou, Jiří Kubásek, Iva Mozgová

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In Arabidopsis thaliana, histone 3 lysine 27 tri-methylation catalysed byPRC2 is playing essential functions in the regulation of plant development, growth, and reproduction[1-2]. Despite numerous studies related to the role of PRC2 in developmental control, how PRC2 works in the operational control in plants is unknown. In the present, the evidence that PRC2 probably participates in the regulation of retrograde singalling pathway in Arabidopsisis found. Firstly, we observed that the rosette size and biomass in PRC2-depletion mutants (clf-29 and swn-3) is significantly higher than WTunder medium light condition (ML: 125 µmol m⁻² s⁻²), while under medium high light condition (MHL: 300 µmol m⁻² s-2), the increase was reverse. Under ML condition, the photosynthesis related parameters determined by fluorCam did not show significant differences between WT and mutants, while the pigments concentration increased in the leaf of PRC2-depletion mutants, especially in swn. The dynamic of light-responsive genes and circadian clock genes expression by RT-qPCRwithin 24 hours in the mutants were comparable to WT. However, we observed upregulation of photosynthesis-associated nuclear genes in the PRC2-depletion mutants under chloroplast damaging condition (treated by lincomycin), corresponding to the so-called genome uncoupled (gun) phenotype. Here, we will present our results describing these phenotypes and our suggestion and outlook for studying the involvement of PRC2 in chloroplast-to-nucleus retrograde signalling.

Keywords: PRC2, retrograde signalling, light acclimation, photosyntheis

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Authors: Neelesh Bharti Shukla, Suvankar Dutta, Esha Sharma, Shrikant Ralebhat, Gurudatt Krishnamurthy

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A key component of the physical attribute of textile fibers is lustre. It is a complex phenomenon arising from the interaction of light with fibers, yarn and fabrics. It is perceived as the contrast difference between the bright areas (specular reflection) and duller backgrounds (diffused reflection). Lustre of fibers is affected by their surface structure, morphology, cross-section profile as well as the presence of any additives/registrants. Due to complexities in measurements, objective measurements such as gloss meter do not give reproducible quantification of lustre. Other instruments such as SAMBA hair systems are expensive. In light of this, lustre quantification has largely remained subjective, judged visually by experts, but prone to errors. In this development, a physics-based approach was conceptualized and demonstrated. We have developed an image analysis based technique to quantify visually observed differences in lustre of fibers. Cellulosic fibers, produced with different approaches, with visually different levels of lustre were photographed under controlled optics. These images were subsequently analyzed using a configured software system. The ratio of Intensity of light from bright (specular reflection) and dull (diffused reflection) areas was used to numerically represent lustre. In the next step, the set of samples that were not visually distinguishable easily were also evaluated by the technique and it was established that quantification of lustre is feasible.

Keywords: lustre, fibre, image analysis, measurement

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Authors: Maléne Maria Magdalena Campbell, Jeremiah Mholo

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Low-income households earning less than 3,500 ZAR (about 175 GBP) per month can apply to the South African government, through the National Housing Subsidy, for fully subsidised houses. An objective of this subsidy is to enable low-income households’ participation in the formal housing market; however, the beneficiaries received houses without title deeds. As such, if the beneficiaries did not have a secured tenure at the time of their death then surviving family may face possible eviction. Therefore, an aim of this research was to determine how these beneficiaries interpret tenure security. The research focused on government subsidised housing in the Dithlake settlement of a rural hamlet named Koffiefontein, in the Letsemeng Local Municipality of South Africa. Quantitative data on the beneficiaries were collected from the local municipality, while qualitative data were collected from a sample of 45 beneficiaries.

Keywords: low-income families, subsidised housing, titling, housing market

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Authors: Ravneet Kaur

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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

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Authors: Farid Adisaputra Gumilang

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Kucing Liar Underground Mine is a future mine of PT Freeport Indonesia PTFI that is currently being developed. In the development process, problems were found when blasting the tunnels; there were overbreak, and void occur caused by geological contact or poor rock conditions. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate the depth of rock mass yield within pillars. To prevent the potential hazard caused by void zones, geotechnical engineers must ensure the planned drift is mined in the best location where people can work safely. GPR, or Ground penetrating radar, is a geophysical method that can image the subsurface. This non-destructive method uses electromagnetic radiation and detects the reflected signals from subsurface structures. The GPR survey measurements are conducted 48 meters along the drift that has a poor ground condition with 150MHz antenna with several angles (roof, wall, and floor). Concern grounds are determined by the continuity of reflector/low reflector in the radargram section. Concern grounds are determined by the continuity of reflector/low reflector in the radargram section. In this paper, processing data using instantaneous amplitude to identify the void zone. In order to have a good interpretation and result, it combines with the geological information and borehole camera data, so the calibrated GPR data allows the geotechnical engineer to determine the safe location to change the drift location.

Keywords: underground mine, ground penetrating radar, reflectivity, borehole camera

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Authors: Songul Cinaroglu

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Regional planning in health has gained speed for developing countries in recent years. In Turkey, 89 different Public Hospital Unions (PHUs) were conducted based on provincial levels. In this study technical efficiencies of 89 PHUs were examined by using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities of input and output indicators. Number of beds, physicians and nurses determined as input variables and number of outpatients, inpatients and surgical operations determined as output indicators. Before performing DEA, PHUs were grouped into two clusters. It is seen that the first cluster represents PHUs which have higher population, demand and service density than the others. The difference between clusters was statistically significant in terms of all study variables (p ˂ 0.001). After clustering, DEA was performed for general and for two clusters separately. It was found that 11% of PHUs were efficient in general, additionally 21% and 17% of them were efficient for the first and second clusters respectively. It is seen that PHUs, which are representing urban parts of the country and have higher population and service density, are more efficient than others. Random forest decision tree graph shows that number of inpatients is a determinative factor of efficiency of PHUs, which is a measure of service density. It is advisable for public health policy makers to use statistical learning methods in resource planning decisions to improve efficiency in health care.

Keywords: public hospital unions, efficiency, data envelopment analysis, random forest

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Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

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This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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Authors: Abdul Amir Hazbavi

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In recent years, there have been increasing requests in the field of translation studies to develop software facilitating the analysis of corpora. One of the specialized tools in that regard are Terminology Management Tools. Briefly explaining, Terminology Management Tools are applications developed to help create and store terminological data in the form which allows for a controlled use of the data. While it has a long history and an established ground in translation market in most parts of the globe, the Iranian translators and translation market still seem to be unaware or unfamiliar with Terminology Management Tools. In order to provide a preview on the perception and adoption of Terminology Management Tools by the Iranian translators, the present survey was carried out among 224 last-year undergraduate Iranian students of English translation at 10 different universities across the country. The study revealed a very low level of adoption and a very high level of willingness to get familiar with and learn about Terminology Management Tools by the Iranian translators.

Keywords: translation, translation technology, terminology management tools, terminology management survey

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Authors: Zhaohui Tian

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China’s growing and deepening engagement in Africa has attracted numerous controversial debates on Chinese-African social-racial relations both in the media and academia. Most research tends to discuss this issue and the tensions involved at the state level, but limited attention has been given to the individual relating processes of those two racial groups from an intercultural politeness evaluation angle. Thus, taking Kenya as a country focus and putting it under recent perspectives on pragmatics and politeness, this study explores the Chinese-Kenyan workplace relating experience in Chinese-owned companies with the aim to offer new insights on Chinese-African social-racial tensions. The original data were collected through 25 interviews from 29 Chinese and Kenyan participants working in different Chinese companies and industries, some of which had been later on converted into 182 short story data in order to better capture the process and content dimensions of their experiences using Spencer &Kádár’s politeness evaluation model. Both interview and story data were analysed in MAXQDA to understand the personal relating process and the criteria they were drawing from when making evaluative judgements of their relations. The result particular draws attention to tensions around goals, rights, and obligations, and social-moral dimensions that had been underrepresented in intercultural and pragmatics literature. The study offers alternative empirical insights into Chinese-Kenyan relations from an intercultural politeness management perspective and the possible mismatches of the evaluative criteria that potentially cause tension in this context.

Keywords: chinese-kenyan, evaluation, relating, workplace

Procedia PDF Downloads 95

Authors: Evuarherhe Veronica Abolo

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The study investigated the programs in Nigerian higher institutions and how they influence unemployment of graduates in the country. The study employed the survey design. The population of the study includes two universities, two polytechnics and two colleges of education in Lagos State. A total of 350 participants, which include graduates and students were sampled for the study. A structured interview schedule and direct observation were used to collect data on the three research questions drawn for the study. The data were analyzed using rating of the structured interview in tables and percentages. The results of the study revealed that Nigerian graduates are not only unemployed but can hardly meet the requirements of available job vacancies due to the stereotype nature in scope, content and methods of the programs in the institutions. Recommendations such as collaboration of companies (end- users) and institutions in the training of students, restructuring of the content and methodology of programs and providing soft loans and other facilities to the young graduates were proffered to reduce the rate of graduates’ unemployment in Nigeria.

Keywords: higher institution, graduate unemployment, soft loan, unemployment

Procedia PDF Downloads 484

Authors: Tamer Mohamed Atef

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The tourism and hospitality education is a branch of the overall tourism and hospitality industry that is dedicated to providing the industry with well-educated, well-trained, skilled, enthusiastic and committed workforce. The Tourism Department at the College of Arts and Social Sciences (Sultan Qaboos University), Oman, has been providing the Omani society with undergraduate tourism and hospitality educational services since Fall 2001. Despite the fact that Tourism Department graduates are not facing any employment concerns, fluctuation in the number of enrollees and graduates, however, has been a significant characteristic since the inception of the program. To address this concern, several tactical and strategic decisions have been made, notably that the program has received accreditation from two prestigious international accreditation institutions, which mark two major milestones in the educational journey of the Tourism Department. The current study, thus, aims to provide a tourism and hospitality education efficiency management model. To achieve this aim, the following objectives were identified: to analyze students in - graduates out matrix, and to assess graduates’ employment trends. A survey was conducted to assess the current employment status of the department graduates. Secondary data were collected from Deanship of Admission and Registration statistical reports on the Tourism Department. Data were tabulated and analyzed in such a way that set forth the major findings from the survey and the secondary data. This study sheds light on the educational system created and followed by the Tourism Department, in an effort to provide a tourism and hospitality education efficiency management model, that would help educators and administrators better manage their programs.

Keywords: tourism, hospitality, education, students, graduates, employability, indicators

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Authors: Macdonald Kanyangale, Sandram Naluso

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Globally, researchers have struggled over time to adequately define the notion of health system to inform research. This study is significant because it proposes an integrative framework for a robust definition of the health system. The objective of this article is to examine major pitfalls in definitions of health system used in prior literature and implications of these for research and management. The study used methodological steps of a scoping review proposed by Arksey and O'Malley to identify and examine 24 definitions of a health system in articles selected from six databases and web search engines. Thematic analysis was used to delineate and categorise definitional pitfalls into broader themes. There are a plethora of five major pitfalls in the extant definitions of a health system which may easily scupper any unsuspecting researcher if not avoided or addressed in research. These definitional pitfalls are reductionist assumptions which ignore dynamic and complex connections, overly wide boundary and lack of specification of levels in a health system, and limited focus on process in a health system. In addition, there is the tendency of treating different components of the health system as equal and simplifying of the ontological complexity of the health system. Future scholars are advised to avoid or address the identified five major pitfalls if they are to develop robust definitions of an HS. The use of an integrative framework for a robust definition of a health system is recommended, while implications of the pitfalls are discussed as a basis and catalyst for complexity-informed research and managing interactively.

Keywords: complexity management, health system, pitfalls, reductionism, research

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Authors: Omotolani Victoria Somoye

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The paper examines modern approaches to the insurable interest, which is a fundamental principle of insurance law that affects the enforceability of insurance contracts. The study starts by examining the competing definitions of the nature of the insurable interest doctrine. It finds that while legal interest theory is seen to be sufficient as the test of insurable interest, the paper argues on how this approach deprives the insured of a full indemnity of losses suffered. The problem with the Nigerian and English current legislative framework is that it defines insurable interest as a legally recognized interest of the insured in the subject matter of insurance. However, other countries like Australia, the United States, South Africa, and more recently, Canada, have rejected the English test and trodden their own path along the factual expectancy line. The study justifies the rationale behind the departure of similar common law jurisdictions and argues that the English and Nigerian position, which appears to be too rigid, harsh on the insured, and no longer fit for purpose in the 21st century, should be revised. The paper concludes that the common law doctrine does not represent better interests of certainty, justice, and fairness, as well as not meeting the policy behind the requirement of insurable interest. This paper adopts a doctrinal comparative research methodology to examine complex areas of insurable interest in selected countries and work out some suggestions for reforming the Nigerian and English laws by referring to the approaches of other jurisdictions.

Keywords: Australia, common law, English law, insurable interest, insurance, Nigeria

Procedia PDF Downloads 133

Authors: Marcelino Caetano Noronha, Vosco Pereira, Jose Soares Pinto, Ferdinando Da C. Saores

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One particularly popular social media platform is Youtube. It’s a video-sharing platform where users can submit videos, and other users can like, dislike or comment on the videos. In this study, we conduct a binary classification task on YouTube’s video comments and review from the users regarding the accession process of Timor Leste to become the eleventh member of the Association of South East Asian Nations (ASEAN). We scrape the data directly from the public YouTube video and apply several pre-processing and weighting techniques. Before conducting the classification, we categorized the data into two classes, namely positive and negative. In the classification part, we apply Support Vector Machine (SVM) algorithm. By comparing with Naïve Bayes Algorithm, the experiment showed SVM achieved 84.1% of Accuracy, 94.5% of Precision, and Recall 73.8% simultaneously.

Keywords: classification, YouTube, sentiment analysis, support sector machine

Procedia PDF Downloads 101