Search results for: cloud accounting

Authors: Mona Awad Wanis Gad

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The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

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Authors: Zhongzhong Zeng, Zichen Liang

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In recent years, Beijing courtyards have been facing the problem of renewal and renovation, and the residents are faced with the problems of small house areas, large household sizes, old and dangerous houses, etc. Among the many renovation methods, the authors note two more common practices of using the front porch to expand the floor area and adding a loft. Residents and architects, however, did not give the ventilation performance of the significant interior consideration before beginning the remodeling. The aim of this article is to explore the good or negative impacts of both front porch and loft structures on the manner of interior ventilation in the courtyard. Ventilation, in turn, is crucial to the indoor environmental quality of a home. The major method utilized in this study is the comparative analysis method, in which the authors create four alternative house models with or without a front porch and an attic as two variables and examine internal ventilation using the CFD(Computational Fluid Dynamics) technique. The authors compare the indoor ventilation of four different architectural models with or without front porches and lofts as two variables. The results obtained from the analysis of the sectional airflow and the plane 1.5m height cloud are the existence of the loft, to a certain extent, disrupts the airflow organization of the building and makes the rear wall high windows of the building less effective. Occupying the front porch to become the area of the house has no significant effect on ventilation, but try not to occupy the front porch and add the loft at the same time in the building renovation. The findings of this study led to the following recommendations: strive to preserve the courtyard building's original architectural design and make adjustments to only the inappropriate elements or constructions. The ventilation in the loft portion is inadequate, and the inhabitants typically use the loft as a living area. This may lead to the building relying more on air conditioning in the summer, which would raise energy demand. The front porch serves as a transition place as well as a source of shade, weather protection, and inside ventilation. In conclusion, the examination of interior environments in upcoming studies should concentrate on cross-disciplinary, multi-angle, and multi-level research topics.

Keywords: Beijing courtyard renewal, CFD, indoor environment, ventilation analysis

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Authors: Ben Kwame Agyei-Mensah

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This study investigated the influence of firm-specific characteristics which include proportion of Non-Executive Directors, ownership concentration, firm size, profitability, debt equity ratio, liquidity and leverage on the extent and quality of financial ratios disclosed by firms listed on the Ghana Stock Exchange. The research was conducted through detailed analysis of the 2012 financial statements of the listed firms. Descriptive analysis was performed to provide the background statistics of the variables examined. This was followed by regression analysis which forms the main data analysis. The results of the extent of financial ratio disclosure level, mean of 62.78%, indicate that most of the firms listed on the Ghana Stock Exchange did not overwhelmingly disclose such ratios in their annual reports. The results of the low quality of financial ratio disclosure mean of 6.64% indicate that the disclosures failed woefully to meet the International Accounting Standards Board's qualitative characteristics of relevance, reliability, comparability and understandability. The results of the multiple regression analysis show that leverage (gearing ratio) and return on investment (dividend per share) are associated on a statistically significant level as far as the extent of financial ratio disclosure is concerned. Board ownership concentration and proportion of (independent) non-executive directors, on the other hand were found to be statistically associated with the quality of financial ratio disclosed. There is a significant negative relationship between ownership concentration and the quality of financial ratio disclosure. This means that under a higher level of ownership concentration less quality financial ratios are disclosed. The findings also show that there is a significant positive relationship between board composition (proportion of non-executive directors) and the quality of financial ratio disclosure.

Keywords: voluntary disclosure, firm-specific characteristics, financial reporting, financial ratio disclosure, Ghana stock exchange

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Authors: Seema Paul, John Mango Magero, Prosun Bhattacharya, Zahra Kalantari, Steve W. Lyon

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The purpose of this review paper is to develop an understanding of lake hydrodynamics and the potential climate impact on the Lake Victoria (LV) catchment scale. This paper briefly discusses the main problems of lake hydrodynamics and its’ solutions that are related to quality assessment and climate effect. An empirical methodology in modeling and mapping have considered for understanding lake hydrodynamic and visualizing the long-term observational daily, monthly, and yearly mean dataset results by using geographical information system (GIS) and Comsol techniques. Data were obtained for the whole lake and five different meteorological stations, and several geoprocessing tools with spatial analysis are considered to produce results. The linear regression analyses were developed to build climate scenarios and a linear trend on lake rainfall data for a long period. A potential evapotranspiration rate has been described by the MODIS and the Thornthwaite method. The rainfall effect on lake water level observed by Partial Differential Equations (PDE), and water quality has manifested by a few nutrients parameters. The study revealed monthly and yearly rainfall varies with monthly and yearly maximum and minimum temperatures, and the rainfall is high during cool years and the temperature is high associated with below and average rainfall patterns. Rising temperatures are likely to accelerate evapotranspiration rates and more evapotranspiration is likely to lead to more rainfall, drought is more correlated with temperature and cloud is more correlated with rainfall. There is a trend in lake rainfall and long-time rainfall on the lake water surface has affected the lake level. The onshore and offshore have been concentrated by initial literature nutrients data. The study recommended that further studies should consider fully lake bathymetry development with flow analysis and its’ water balance, hydro-meteorological processes, solute transport, wind hydrodynamics, pollution and eutrophication these are crucial for lake water quality, climate impact assessment, and water sustainability.

Keywords: climograph, climate scenarios, evapotranspiration, linear trend flow, rainfall event on LV, concentration

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Authors: Aneri Mehta, Krunal Mehta

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Financial administration is part of government which deals with collection, preservation and distribution of public funds, with the coordination of public revenue and expenditure, with the management of credit operation on behalf of the state and with the general control of the financial affairs of public households. The researcher has taken the prime body of the local self government viz. Municipal Corporation. However, the number of municipal corporations in India has rapidly increased in recent years. Countries 27% of the total population are living in urban area & in recent it increasing very fast. People are moving very fast from rural area to urban area. Their demand, awareness is increasing day by day. The Municipal Corporations render many services for the development of the urban area. Thus, researcher has taken a step to know the accounting practices of the municipal corporations of Gujarat state (AMC & BMC ). The research will try to show you the status of finance of municipal corporations. Article 243(w) of the constitution of India envisaged that the state government maybe, by law , endow the municipalities with such powers and authorities as may be necessary to enable them to function as institution of self government and such law may contain provision for devolution of powers and responsibilities upon municipalities subjects to such condition as may be specified there in with respect to (i) the peroration of plans for economic development and social justice and (ii) the performance of the function and the implementation of schemes as may be entrusted to them including those in relation to the matters listed in the twelfth schedule. The three tier structure of the Indian Government i.e. Union, State & Local Self Government is the scenario of the Indian constitution. Local Self Government performs or renders many services under the direct control of state government. They (local bodies) possess autonomy within its limited sphere, raise revenue through local taxation and spend its income on local services.

Keywords: financial administration, urban local bodies, local self government, constitution

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Authors: Kin On Kwok, Vivian Wei, Benjamin Cowling, Steven Riley, Jonathan Read

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Background: The role of social contact behavior measured in different contact constructs in the transmission of respiratory pathogens with acute respiratory illness (ARI) remains unclear. We, therefore, aim to depict the individual pattern of ARI in the community and investigate the association between different contact dimensions and ARI in Hong Kong. Methods: Between June 2013 and September 2013, 620 subjects participated in the last two waves of recruitment of the population based longitudinal phone social contact survey. Some of the subjects in this study are from the same household. They are also provided with the symptom diaries to self-report any acute respiratory illness related symptoms between the two days of phone recruitment. Data from 491 individuals who were not infected on the day of phone recruitment and returned the symptom diaries after the last phone recruitment were used for analysis. Results: After adjusting different follow-up periods among individuals, the overall incidence rate of ARI was 1.77 per 100 person-weeks. Over 75% ARI episodes involve running nose, cough, sore throat, which are followed by headache (55%), malagia (35%) and fever (18%). Using a generalized estimating equation framework accounting for the cluster effect of subjects living in the same household, we showed that both daily number of locations visited with contacts and the number of contacts, explained the ARI incidence rate better than only one single contact construct. Conclusion: Our result suggests that it is the intertwining property of contact quantity (number of contacts) and contact intensity (ratio of subject-to-contact) that governs the infection risk by a collective set of respiratory pathogens. Our results provide empirical evidence that multiple contact constructs should be incorporated in the mathematical transmission models to feature a more realistic dynamics of respiratory disease.

Keywords: acute respiratory illness, longitudinal study, social contact, symptom diaries

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Authors: Stephanie Liu Lu

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With the proliferation of artificial intelligence tools in the field of education, it is crucial to explore their impact on language learning outcomes. This paper examines the use of AI tools, such as ChatGPT, in practical writing within business Chinese teaching to investigate how AI can enhance practical writing skills and teaching effectiveness. The study involved third and fourth-year university students majoring in accounting and finance from a university in Hong Kong within the context of a business correspondence writing class. Students were randomly assigned to a control group, who completed business letter writing independently, and an experimental group, who completed the writing with the assistance of AI. In the latter, the AI-assisted business letters were initially drafted by the students issuing commands and interacting with the AI tool, followed by the students' revisions of the draft. The paper assesses the performance of both groups in terms of grammatical expression, communicative effect, and situational awareness. Additionally, the study collected dialogue texts from interactions between students and the AI tool to explore factors that affect text generation and the potential impact of AI on enhancing students' communicative and identity awareness. By collecting and comparing textual performances, it was found that students assisted by AI showed better situational awareness, as well as more skilled organization and grammar. However, the research also revealed that AI-generated articles frequently lacked a proper balance of identity and writing purpose due to limitations in students' communicative awareness and expression during the instruction and interaction process. Furthermore, the revision of drafts also tested the students' linguistic foundation, logical thinking abilities, and practical workplace experience. Therefore, integrating AI tools and related teaching into the curriculum is key to the future of business Chinese teaching.

Keywords: AI-assistance, business Chinese, textual analysis, language education

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Authors: Sarah Hebbouch

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Two decades ago, research on diasporic women’s participation within Sufi circles would have been inconceivable, not only because of a general lack of recognition of their contribution to Sufism but due to the intimacy of the rituals, often taking place in confined spaces, like zawiyas (Sufi lodges). Recent scholarly attention to female spiritual experience owes to a digital awareness and interest in exploring diasporic community reproduction of those experiences. Within a context where female disciples of a Sufi convent undergo a physical separation from the saint’s sanctuary -because of immigration from the homeland to the host country- technology becomes a social hub accounting for Sufis’ ritual commitment and preservation of cultural capital in the diaspora. This paper elucidates how female Sufi immigrants affiliating with the Boudchichi brotherhood (Morocco-based) maintain ‘a relational network’ and strong social online relationships with their female compatriots in Morocco through the use of online platforms. Sufi communities living in the diaspora find the internet an open interactive space that serves to kindle their distance of spiritual participation and corroborate their transnational belonging. The current paper explores the implications of the use of a digital baseline named “Tariqa Info,” the convent’s digital online platform, and how it mediates everyday ritual performance, the promotion of digital connection, and the communication of ideas and discourses. Such a platform serves the bolstering emotional bonds for transnational female disciples and inclusion within online communities in the homeland. Assisted by an ethnographic lens, this paper discusses the research findings of participatory field observation of Sufi women’s online communities, informed by the need to trace the many ostensible aspects of interconnectedness and divergences.

Keywords: digital connection, Sufi convent, social online relationship, transnational female disciples

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Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Wenyang Wan

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The study of urban land use and landscape pattern is the current hotspot in the fields of planning and design, ecology, etc., which is of great significance for the construction of the overall humanistic ecosystem of the city and optimization of the urban spatial structure. Banan District, as the main part of the eastern eco-city planning of Chongqing Municipality, is a new high ground for highlighting the ecological characteristics of Chongqing, realizing effective transformation of ecological value, and promoting the integrated development of urban and rural areas. The analytical methods of land use transfer matrix (GIS) and landscape pattern index (Fragstats) were used to study the characteristics and laws of the evolution of land use landscape pattern in Banan District from 2000 to 2020, which provide some reference value for Banan District to alleviate the ecological contradiction of landscape. The results of the study show that: ① Banan District is rich in land use types, of which the area of cultivated land will still account for 57.15% of the total area of the landscape until 2020, accounting for an absolute advantage in the land use structure of Banan District; ② From 2000 to 2020, land use conversion in Banan District is characterized as: Cropland > woodland > grassland > shrubland > built-up land > water bodies > wetlands, with cropland converted to built-up land being the largest; ③ From 2000 to 2020, the landscape elements of Banan District were distributed in a balanced way, and the landscape types were rich and diversified, but due to the influence of human interference, it also presented the characteristics that the shape of the landscape elements tended to be irregular, and the dominant patches were distributed in a scattered manner, and the patches had poor connectivity. It is recommended that in future regional ecological construction, the layout should be rationally optimized, the relationship between landscape components should be coordinated, and the connectivity between landscape patches should be strengthened, and the degree of landscape fragmentation should be reduced.

Keywords: land use transfer, landscape pattern evolution, GIS and FRAGSTATS, Banan District

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Charles Iledun Oyewole

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The daunting challenge that the ‘man with the hoe’ is going to face in the coming decades will be complex and interwoven. With global population already above 7 billion people, it has been estimated that food (crop) production must more than double by 2050 to meet up with the world’s food requirements. Nigeria population is also expected to reach over 240 million people by 2050, at the current annual population growth of 2.61 per cent. The country’s farming population is estimated at over 65 per cent, but the country still depends on food importation to complement production. The small scale farmer, who depends on simple hand tools: hoes and cutlasses, remains the centre of agricultural production, accounting for 90 per cent of the total agricultural output and 80 per cent of the market flow. While the hoe may have been a tool for sustainable development at a time in human history, this role has been smothered by population growth, which has brought too many mouths to be fed (over 170 million), as well as many industries to fuel with raw materials. It may then be argued that the hoe is unfortunately not a tool for the coming challenges and that agricultural mechanization should be the focus. However, agriculture as an enterprise is a ‘complete wheel’ which does not work when broken, particularly, in respect to mechanization. Generally, mechanization will prompt increase production, where land is readily available; increase production, will require post-harvest handling mechanisms, crop processing and subsequent storage. An important aspect of this is readily available and favourable markets for such produce; fuel by good agricultural policies. A break in this wheel will lead to the process of mechanization crashing back to subsistence production, and probably reversal to the hoe. The focus of any agricultural policy should be to chart a course for sustainable mechanization that is environmentally friendly, that may ameliorate Nigeria’s food and raw material gaps. This is the focal point of this article.

Keywords: Crop production, Farmer, Hoes, Mechanization, Policy framework, Population, Growth, Rural areas

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Authors: Chaiwat Kongsom, Vitoon Panyakul

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The objective of this study was to assess the production and market of certified organic products in Thailand. A purposive sampling technique was used to identify a sample group of 154 organic entrepreneurs for the study. A survey and in-depth interview were employed for data collection. Also, secondary data from organic agriculture certification body and publications was collected. Then descriptive statistics and content analysis technique were used to describe about production and market of certified organic products in Thailand. Results showed that there were 9,218 farmers on 213,183.68 Rai (83,309.2 acre) of certified organic agriculture land (0.29% of national agriculture land). A total of 57.8% of certified organic agricultural lands were certified by the international certification body. Organic farmers produced around 71,847 tons/year and worth around THB 1,914 million (Euro 47.92 million). Excluding primary producers, 471 operators involved in the Thai organic supply chains, including processors, exporters, distributors, green shops, modern trade shops (supermarket shop), farmer’s markets and food establishments were included. Export market was the major market channel and most of organic products were exported to Europe and North America. The total Thai organic market in 2014 was estimated to be worth around THB 2,331.55 million (Euro 58.22 million), of which, 77.9% was for export and 22.06% was for the domestic market. The largest exports of certified organic products were processed foods (66.1% of total export value), followed by organic rice (30.4%). In the domestic market, modern trade was the largest sale channel, accounting for 59.48% of total domestic sales, followed by green shop (29.47%) and food establishment (5.85%). To become a center of organic farming and trading within ASEAN, the Thai organic sector needs to have more policy support in regard to agricultural chemicals, GMO, and community land title. In addition, appropriate strategies need to be developed.

Keywords: certified organic products, production, market, Thailand

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

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Authors: Thabiso Sthembiso Msomi

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SMEs are the main engine of growth in most developing economies. One of the main factors that hinder the development of SME is access to finance. In this study, we explored the factors that hinder the growth and survival of SMEs in South Africa. The capital structure theory formed the theoretical underpinning for the study. The quantitative research design was adopted and data was collected from retail, construction, manufacturing and agriculture sectors of SMEs within the KwaZulu-Natal province of South Africa. The modified version of the Cochran formula was used to determine the sample size as 321 SMEs and analysed using the five-point Likert scale. The purposive sampling technique was used to select owners of SME. Statistical Package for the Social Sciences (SPSS) was used for the data analysis through Exploratory Factor Analysis (EFA) to determine the factor structures of items employed to measure each of the constructs in this study. Then, the Cronbach’s alpha test was conducted to determine the reliability of each construct. Kaiser-Meyer-Olkin (KMO) was used to determine the adequacy of the sample size. Linear regression was done to determine the effect of the independent variables on the dependent variable. The findings suggest that the main constraints facing South African SMEs were the lack of experienced management. Furthermore, the SMEs would fail to raise customer awareness of their products and services, which in turn affects their market access and monthly turnover. The study recommends that SMEs keep up-to-date records of business transactions to enable the business to keep track of its operations. The study recommends that South African banks adopt an SME accounting and bookkeeping program. The finding of this study benefits policymakers in both the private and public sectors.

Keywords: small businesses, access to finances, COVID-19, SMEs survival

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Authors: Wenyang Wan

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The study of urban land use and landscape pattern is the current hotspot in the fields of planning and design, ecology, etc., which is of great significance for the construction of the overall humanistic ecosystem of the city and optimization of the urban spatial structure. Banan District, as the main part of the eastern eco-city planning of Chongqing Municipality, is a high ground for highlighting the ecological characteristics of Chongqing, realizing effective transformation of ecological value, and promoting the integrated development of urban and rural areas. The analytical methods of land use transfer matrix (GIS) and landscape pattern index (Fragstats) were used to study the characteristics and laws of the evolution of land use landscape pattern in Banan District from 2000 to 2020, which provide some reference value for Banan District to alleviate the ecological contradiction of landscape. The results of the study show that ① Banan District is rich in land use types, of which the area of cultivated land will still account for 57.15% of the total area of the landscape until 2020, accounting for an absolute advantage in land use structure of Banan District; ② From 2000 to 2020, land use conversion in Banan District is characterized as Cropland > woodland > grassland > shrubland > built-up land > water bodies > wetlands, with cropland converted to built-up land being the largest; ③ From 2000 to 2020, the landscape elements of Banan District were distributed in a balanced way, and the landscape types were rich and diversified, but due to the influence of human interference, it also presented the characteristics that the shape of the landscape elements tended to be irregular, and the dominant patches were distributed in a scattered manner, and the patches had poor connectivity. It is recommended that in future regional ecological construction, the layout should be rationally optimized, the relationship between landscape components should be coordinated, the connectivity between landscape patches should be strengthened, and the degree of landscape fragmentation should be reduced.

Keywords: land use transfer, landscape pattern evolution, GIS and Fragstats, Banan district

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: Ahmad Mohammad Sharqi, Mohamed Hechmi El Ouni, Saleh Alsulamy

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Due to the emerging technologies revolution worldwide, the need to exploit and employ innovative technologies for other functions and purposes in different aspects has become a remarkable matter. Saudi Arabia is considered one of the most powerful economic countries in the world, where the construction sector participates effectively in its economy. Thus, the construction sector in KSA should convoy the rapid digital revolution and transformation and implement smart devices on sites. A Smart Construction Site (SCS) includes smart devices, artificial intelligence, the internet of things, augmented reality, building information modeling, geographical information systems, and cloud information. This paper aims to study the level of implementation of SCS in KSA, analyze the obstacles and challenges of adopting SCS and find out critical success factors for its implementation. A survey of close-ended questions (scale and multi-choices) has been conducted on professionals in the construction sector of Saudi Arabia. A total number of twenty-nine questions has been prepared for respondents. Twenty-four scale questions were established, and those questions were categorized into several themes: quality, scheduling, cost, occupational safety and health, technologies and applications, and general perception. Consequently, the 5-point Likert scale tool (very low to very high) was adopted for this survey. In addition, five close-ended questions with multi-choice types have also been prepared; these questions have been derived from a previous study implemented in the United Kingdom (UK) and the Dominic Republic (DR), these questions have been rearranged and organized to fit the structured survey in order to place the Kingdom of Saudi Arabia in comparison with the United Kingdom (UK) as well as the Dominican Republic (DR). A total number of one hundred respondents have participated in this survey from all regions of the Kingdom of Saudi Arabia: southern, central, western, eastern, and northern regions. The drivers, obstacles, and success factors for implementing smart devices and technologies in KSA’s construction sector have been investigated and analyzed. Besides, it has been concluded that KSA is on the right path toward adopting smart construction sites with attractive results comparable to and even better than the UK in some factors.

Keywords: artificial intelligence, construction projects management, internet of things, smart construction sites, smart devices

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Authors: Cuiyang Feng, Xu Tang, Yi Jin

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Coal is the most important primary energy source in China, which exerts a significant influence on the rapid economic growth. However, it makes the water resources to be a constraint on coal industry development, on account of the reverse geographical distribution between coal and water. To ease the pressure on water shortage, the ‘3 Red Lines’ water policies were announced by the Chinese government, and then ‘water for coal’ plan was added to that policies in 2013. This study utilized a structural path analysis (SPA) based on the multi-regional input-output table to quantify the virtual water flows caused by coal consumption in different stages. Results showed that the direct water input (the first stage) was the highest amount in all stages of coal consumption, accounting for approximately 30% of total virtual water content. Regional analysis demonstrated that virtual water trade alleviated the pressure on water use for coal consumption in water shortage areas, but the import of virtual water was not from the areas which are rich in water. Sectoral analysis indicated that the direct inputs from the sectors of ‘production and distribution of electric power and heat power’ and ‘Smelting and pressing of metals’ took up the major virtual water flows, while the sectors of ‘chemical industry’ and ‘manufacture of non-metallic mineral products’ importantly but indirectly consumed the water. With the population and economic growth in China, the water demand-and-supply gap in coal consumption would be more remarkable. In additional to water efficiency improvement measures, the central government should adjust the strategies of the virtual water trade to address local water scarcity issues. Water resource as the main constraints should be highly considered in coal policy to promote the sustainable development of the coal industry.

Keywords: coal consumption, multi-regional input-output model, structural path analysis, virtual water

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Authors: Rohin Rameswarapu, Sameer Valsangkar

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Background: Globally, musculoskeletal disorders are the largest single cause of work-related illnesses accounting for over 33% of all newly reported occupational illnesses. Risk factors for MSD need to be delineated to suggest means for amelioration. Material and methods: In this current cross-sectional study, the prevalence of MSDs among workers in an electrical company assembly line, the socio-demographic and job characteristics associated with MSD were obtained through a semi-structured questionnaire. A quantitative assessment of the physical risk factors through the Rapid Upper Limb Assessment (RULA) tool, and measurement of psychosocial risk factors through a Likert scale was obtained. Statistical analysis was conducted using Epi-info software and descriptive and inferential statistics including chi-square and unpaired t test were obtained. Results: A total of 263 workers consented and participated in the study. Among these workers, 200 (76%) suffered from MSD. Most of the workers were aged between 18–27 years and majority of the workers were women with 198 (75.2%) of the 263 workers being women. A chi square test was significant for association between male gender and MSD with a P value of 0.007. Among the MSD positive group, 4 (2%) had a grand score of 5, 10 (5%) had a grand score of 6 and 186 (93%) had a grand score of 7 on RULA. There were significant differences between the non-MSD and MSD group on five out of the seven psychosocial domains, namely job demand, job monotony, co-worker support, decision control and family and environment domains. Discussion: The current cross-sectional study demonstrates a high prevalence of MSD among assembly line works with inherent physical and psychosocial risk factors and recommends that not only physical risk factors, addressing psychosocial risk factors through proper ergonomic means is also essential to the well-being of the employee.

Keywords: musculoskeletal disorders, India, occupational health, Rapid Upper Limb Assessment (RULA)

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Authors: S. Zhang, L. Zhang, X. Chen

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Due to the large uncertainty on the mechanical properties of FRP (fibre reinforced plastic), the reliability evaluation of FRP structures are currently receiving much attention in industry. However, possible statistical correlation between ply mechanical properties has been so far overlooked, and they are mostly assumed to be independent random variables. In this study, the statistical correlation between ply mechanical properties of uni-directional and plain weave composite is firstly analyzed by a combination of Monte-Carlo simulation and finite element modeling of the FRP unit cell. Large linear correlation coefficients between the in-plane mechanical properties are observed, and the correlation coefficients are heavily dependent on the uncertainty of the fibre volume ratio. It is also observed that the correlation coefficients related to Poisson’s ratio are negative while others are positive. To experimentally achieve the statistical correlation coefficients between in-plane mechanical properties of FRP, all concerned in-plane mechanical properties of the same specimen needs to be known. In-plane shear modulus of FRP is experimentally derived by the approach suggested in the ASTM standard D5379M. Tensile tests are conducted using the same specimens used for the shear test, and due to non-uniform tensile deformation a modification factor is derived by a finite element modeling. Digital image correlation is adopted to characterize the specimen non-uniform deformation. The preliminary experimental results show a good agreement with the numerical analysis on the statistical correlation. Then, failure probability of laminate plates is calculated in cases considering and not considering the statistical correlation, using the Monte-Carlo and Markov Chain Monte-Carlo methods, respectively. The results highlight the importance of accounting for the statistical correlation between ply mechanical properties to achieve accurate failure probability of laminate plates. Furthermore, it is found that for the multi-layer laminate plate, the statistical correlation between the ply elastic properties significantly affects the laminate reliability while the effect of statistical correlation between the ply strength is minimal.

Keywords: failure probability, FRP, reliability, statistical correlation

Procedia PDF Downloads 154

Authors: Akkasit Jongjareonrak, Supansa Namchaiya

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Unripe green coffee cherry (UGCC) accounting about 5 % of total raw material weight receiving to the coffee bean production process and is, in general, sorting out and dump as waste. The UGCC is known to rich in phenolic compounds such as caffeoylquinic acids, feruloylquinic acids, chlorogenic acid (CGA), etc. CGA is one of the potent bioactive compounds using in the nutraceutical and functional food industry. Therefore, this study aimed at optimization the extraction condition of CGA from UGCC using Accelerated Solvent Extractor (ASE). The ethanol/water mixture at various ethanol concentrations (50, 60 and 70 % (v/v)) was used as an extraction solvent at elevated pressure (10.34 MPa) and temperatures (90, 120 and 150 °C). The recovery yield of UGCC crude extract, total phenolic content, CGA content and some bioactivities of UGCC extract were investigated. Using of ASE at lower temperature with higher ethanol concentration provided higher CGA content in the UGCC crude extract. The maximum CGA content was observed at the ethanol concentration of 70% ethanol and 90 °C. The further purification of UGCC crude extract gave a higher purity of CGA with a purified CGA yield of 4.28 % (w/w, of dried UGCC sample) containing 72.52 % CGA equivalent. The antioxidant activity and antimicrobial activity of purified CGA extract were determined. The purified CGA exhibited the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity at 0.88 mg Trolox equivalent/mg purified CGA sample. The antibacterial activity against Escherichia coli was observed with the minimum inhibitory concentration (MIC) at 3.12 mg/ml and minimum bactericidal concentration (MBC) at 12.5 mg/ml. These results suggested that using of high concentration of ethanol and low temperature under elevated pressure of ASE condition could accelerate the extraction of CGA from UGCC. The purified CGA extract could be a promising alternative source of bioactive compound using for nutraceutical and functional food industry.

Keywords: bioactive, chlorogenic acid, coffee, extraction

Procedia PDF Downloads 254

Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: Foteini Zagklavara, Peter Jimack, Nikil Kapur, Ozz Querin, Harvey Thompson

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The invention and development of the Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise their performance of those devices while reducing the total construction and operation costs. The present study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the trade-offs between competing objectives of DNA amplification efficiency and pressure drop to be explored. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a CF μPCR device by performing a series of simulations at a relatively small number of Design of Experiments (DoE) points, with the use of COMSOL Multiphysics 5.4. The values of the objectives are extracted from the CFD solutions, and response surfaces created using the polyharmonic splines and neural networks. After creating the respective response surfaces, genetic algorithm, and a multi-level coordinate search optimisation function are used to locate the optimum design parameters. Both optimisation methods produced similar results for both the neural network and the polyharmonic spline response surfaces. The results indicate that there is the possibility of improving the DNA efficiency by ∼2% in one PCR cycle when doubling the width of the microchannel to 400 μm while maintaining the height at the value of the original design (50μm). Moreover, the increase in the width of the serpentine microchannel is combined with a decrease in its total length in order to obtain the same residence times in all the simulations, resulting in a smaller total substrate volume (32.94% decrease). A multi-objective optimisation is also performed with the use of a Pareto Front plot. Such knowledge will enable designers to maximise the amount of DNA amplified or to minimise the time taken throughout thermal cycling in such devices.

Keywords: PCR, optimisation, microfluidics, COMSOL

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Mohammad Moridzadeh, Aaron Gallant

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The paper will present the design and construction of the underground excavations of a pump station forebay and its related components including connector tunnels, access shaft, riser shaft and well shafts. The underground openings include an 8 m-diameter riser shaft, an 8-m-diameter access shaft, 34 2.4-m-diameter well shafts, a 107-m-long forebay with a cross section having a height of 11 m and width of 10 m, and a 6 m by 6 m stub connector tunnel between the access shaft and a future forebay extension. The riser shaft extends down from the existing forebay connector tunnel at elevation 247 m to the crown of the forebay at elevation 770.0 feet. The access shaft will extend from the platform at the surface down to El. 223.5 m. The pump station will have the capacity to deliver 600 million gallons per day. The project is located on an uplifted horst consisting of a mass of Precambrian metamorphic rock trending in a north-south direction. The eastern slope of the area is very steep and pronounced and is likely the result of high-angle normal faulting. Toward the west, the area is bordered by a high angle normal fault and recent alluvial, lacustrine, and colluvial deposits. An evaluation of rock mass properties, fault and discontinuities, foliation and joints, and in situ stresses was performed. The response of the rock mass was evaluated in 3DEC using Discrete Element Method (DEM) by explicitly accounting for both major and minor discontinuities within the rock mass (i.e. joints, shear zones, faults). Moreover, the stability of the entire subsurface structure including the forebay, access and riser shafts, future forebay, well shafts, and connecting tunnels and their interactions with each other were evaluated using a 3D coupled hydromechanical Finite Element Analysis (FEA).

Keywords: coupled hydromechanical analysis, discontinuities, discrete element, finite element, pump station

Procedia PDF Downloads 259