Search results for: support vector machine

Authors: Tianyu Cao, KIRA (Ruizhi Zhao)

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The purpose of our research is to study the possibility of people with physical disabilities manipulating mechanical prostheses through brain-computer interface (BCI) technology. The brain-machine interface (BCI) of the neural prosthesis records signals from neurons and uses mathematical modeling to decode them, converting desired movements into body movements. In order to improve the patient's neural control, the prosthesis is given a natural feeling. It records data from sensitive areas from the body to the prosthetic limb and encodes signals in the form of electrical stimulation to the brain. In our research, the brain-computer interface (BCI) is a bridge connecting patients’ cognition and the real world, allowing information to interact with each other. The efficient work between the two is achieved through external devices. The flow of information is controlled by BCI’s ability to record neuronal signals and decode signals, which are converted into device control. In this way, we could encode information and then send it to the brain through electrical stimulation, which has significant medical application.

Keywords: biomedical engineering, brain-computer interface, prosthesis, neural control

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Authors: Comfort Aina

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Modern English, as we all know it to be a foreign language to many, will require training and re-training on the path of the teacher and learners alike. As a teacher, you cannot give that which you do not have. Teachers, many of whom are non-native speakers, are required to be competent in solving problems occurring in the teaching and learning processes. They should be conscious of up to date information about new approaches, methods, techniques as well as they should be capable in the use of information and communication technology (ICT) and, of course, should work on the improvement of their language components and competence. For teachers to be successful in these goals, they need to be encouraged and motivated. So, for EFL teachers to be successful, they are enrolled to in-service teacher training, ICT training, some of the training they undergo and the benefits accrued to it will be the focus of the paper.

Keywords: training, management, method, english language, EFL teachers

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Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar

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

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

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Authors: Rosina U. Ndukwe, Diane Crone, Nick Cavill

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Active transport (i.e. walking to school, cycle to work schemes etc.) is an effective approach with multiple social and environmental benefits for transforming urban environments into active urban environments. Although walking and cycling often remain on the margins of urban planning and infrastructure, there are new approaches emerging, along with policy intervention relevant for the creation of sustainable urban active environments conductive to active travel, increasing physical activity levels of involved communities and supporting social inclusion through more active participation. SPAcE - Supporting Policy and Action for Active Environments is a 3 year Erasmus+ project that aims to integrate active transport programmes into public policy across the EU. SPAcE focuses on cities/towns with recorded low physical activity levels to support the development of active environments in 5 sites: Latvia [Tukums], Italy [Palermo], Romania [Brasov], Spain [Castilla-La Mancha] and Greece [Trikala]. The first part of the project involved a review of good practice including case studies from across the EU and project partner countries. This has resulted in the first output from the project, an evidence of good practice summary with case study examples. In the second part of the project, working groups across the 5 sites have carried out co-production to develop Urban Active Environments (UActivE) Action Plans aimed at influencing policy and practice for increasing physical activity primarily through the use of cycling and walking. Action plans are based on international evidence and guidance for healthy urban planning. Remaining project partners include Universities (Gloucestershire, Oxford, Zurich, Thessaly) and Fit for Life programme (National physical activity promotion program, Finland) who provide support and advice incorporating current evidence, healthy urban planning and mentoring. Cooperation and co-production with public health professionals, local government officers, education authorities and transport agencies has been a key approach of the project. The third stage of the project has involved training partners in the WHO HEAT tool to support the implementation of the Action Plans. Project results show how multi-agency, transnational collaboration can produce real-life Action Plans in five EU countries, based on published evidence, real-life experience, consultation and collaborative working with other organisations across the EU. Learning from the processes adopted within this project will demonstrate how public health, local government and transport agencies across the EU, can work together to create healthy environments that have the aim of facilitating active behaviour, even in times of constrained public budgets. The SPAcE project has captured both the challenges and solutions for increasing population physical activity levels, health and wellness in urban spaces and translating evidence into policy and practice ensuring innovation at policy level. Funding acknowledgment: SPAcE (www.activeenvironments.eu) is co-funded by the Sport action of the ERASMUS+ programme.

Keywords: action plans, active transport, SPAcE, UActivE urban active environments, walking and cycling

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Authors: Saarah Juman, Ilona Johnson, Stephen Richmond, Brett Duane, Sheelagh Rogers

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Introduction: Researchers suggest that within 50 years or less, the available supply of a range of metals will be exhausted, potentially leading to increases in resource conflict and largescale production shortages. The healthcare, dental and orthodontic sectors will undoubtedly be affected as stainless steel instruments are generally heavily relied on. Although changing orthodontic archwires are unavoidable and necessary to allow orthodontic tooth movement through the progression of an archwire sequence with fixed appliances, they are thought to be manufactured in excess of what is needed. Furthermore, orthodontic archwires require trimming extraorally to allow safe intraoral insertion, thus contributing to unnecessary waste of natural resources. Currently, there is no evidence to support the optimisation of archwire length according to orthodontic fixed appliance stage. As such, this study aims to quantify archwire excess (extraoral archwire trimmings) for different stages of orthodontic fixed appliance treatment. Methodology: This prospective, observational, quantitative study observed trimmings made extraorally against pre-treatment study models by clinicians over a 3-month period. Archwires were categorised into one of three categories (initial aligning, sequence, working/finishing arcwhires) within the orthodontic fixed appliance archwire sequence. Data collection included archwire material composition and the corresponding length and weight of excess archwire. Data was entered using a Microsoft Excel spreadsheet and imported into statistical software to obtain simple descriptive statistics. Results: Measurements were obtained for a total of 144 archwires. Archwire materials included nickel titanium and stainless steel. All archwires observed required extraorally trimming to allow safe intraoral insertion. The manufactured lengths of orthodontic initial aligning, sequence, and working/finishing arcwhires were at least 31%, 26%, and 39% in excess, respectively. Conclusions: Orthodontic archwires are manufactured to be excessively long at all orthodontic archwire sequence stages. To conserve natural resources, this study’s findings support the optimisation of orthodontic archwire lengths by manufacturers according to the typical stages of an orthodontic archwire sequence.

Keywords: archwire, orthodontics, sustainability, waste

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Authors: Emmanuelle Maria, Pierre Crançon, Gaëtane Lespes

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Colloids are ubiquitous in the environment and are known to play a major role in enhancing the transport of trace elements, thus being an important vector for contaminants dispersion. Colloids study and characterization are necessary to improve our understanding of the fate of pollutants in the environment. However, in stream water and groundwater, colloids are often very poorly concentrated. It is therefore necessary to pre-concentrate colloids in order to get enough material for analysis, while preserving their initial structure. Many techniques are used to extract and/or pre-concentrate the colloidal phase from bulk aqueous phase, but yet there is neither reference method nor estimation of the impact of these different techniques on the colloids structure, as well as the bias introduced by the separation method. In the present work, we have tested and compared several methods of colloidal phase extraction/pre-concentration, and their impact on colloids properties, particularly their size distribution and their elementary composition. Ultrafiltration methods (frontal, tangential and centrifugal) have been considered since they are widely used for the extraction of colloids in natural waters. To compare these methods, a ‘synthetic groundwater’ was used as a reference. The size distribution (obtained by Field-Flow Fractionation (FFF)) and the chemical composition of the colloidal phase (obtained by Inductively Coupled Plasma Mass Spectrometry (ICPMS) and Total Organic Carbon analysis (TOC)) were chosen as comparison factors. In this way, it is possible to estimate the pre-concentration impact on the colloidal phase preservation. It appears that some of these methods preserve in a more efficient manner the colloidal phase composition while others are easier/faster to use. The choice of the extraction/pre-concentration method is therefore a compromise between efficiency (including speed and ease of use) and impact on the structural and chemical composition of the colloidal phase. In perspective, the use of these methods should enhance the consideration of colloidal phase in the transport of pollutants in environmental assessment studies and forensics.

Keywords: chemical composition, colloids, extraction, preconcentration methods, size distribution

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Authors: Walid M. Adel, Liang Guo-Zhu

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To investigate the characterization of the mechanical properties of composite solid propellant (CSP) based on hydroxyl-terminated polybutadiene (HTPB) at different temperatures and strain rates, uniaxial tensile tests were conducted over a range of temperatures -60 °C to +76 °C and strain rates 0.000164 to 0.328084 s^-1 using a conventional universal testing machine. From the experimental data, it can be noted that the mechanical properties of AP/HTPB propellant are mainly dependent on the applied strain rate and the temperature condition. The stress-strain responses exhibited an initial yielding followed by the viscoelastic phase, which was strongly affected by the strain rate and temperature. It was found that the mechanical properties increased with both increasing strain rate and decreasing temperature. Based on the experimental tests, the master curves of the tensile properties are drawn using predetermined shift factor and the results were discussed. This work is a first step in preliminary investigation the nonlinear viscoelasticity behavior of CSP.

Keywords: AP/HTPB composite solid propellant, mechanical behavior, nonlinear viscoelastic, tensile test, strain rate

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Authors: Kanokrat Makkwao, Tassanee Prueksasit

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This study aimed to investigate PM₁₀ emitted from different limestone mines in Saraburi province, Thailand. The blasting and crushing were the main processes selected for PM₁₀ sampling. PM₁₀ was collected in two mines including, a limestone mine for cement manufacturing (mine A) and a limestone mine for construction (mine B). The IMPACT samplers were used to collect PM₁₀. At blasting, the points aligning with the upwind and downwind direction were assigned for the sampling. The ranges of PM₁₀ concentrations at mine A and B were 0.267-5.592 and 0.130-0.325 mg/m³, respectively, and the concentration at blasting from mine A was significantly higher than mine B (p < 0.05). During crushing at mine A, the PM₁₀ concentration with the range of 1.153-3.716 and 0.085-1.724 mg/m³ at crusher and piles in respectively were observed whereas the PM₁₀ concentration measured at four sampling points in mine B, including secondary crusher, tertiary crusher, screening point, and piles, were ranged 1.032-16.529, 10.957-74.057, 0.655-4.956, and 0.169-1.699 mg/m³, respectively. The emission of PM₁₀ concentration at the crushing units was different in the ranges depending on types of machine, its operation, dust collection and control system, and environmental conditions.

Keywords: PM₁₀ concentration, limestone mines, blasting, crushing

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Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Piyas Palit, Urbi Pal, Jitendra Mathur, Santanu Das

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Bearing is an important machinery part in the industry. When bearings fail to meet their expected life the consequences are increased downtime, loss of revenue and missed the delivery. This article describes the failure of a gearbox bearing in rolling contact fatigue. The investigation consists of visual observation, chemical analysis, characterization of microstructures using optical microscopes and hardness test. The present study also considers bearing life as well as the operational condition of bearings. Surface-initiated rolling contact fatigue, leading to a surface failure known as pitting, is a life-limiting failure mode in many modern machine elements, particularly rolling element bearings. Metallography analysis of crack propagation, crack morphology was also described. Indication of fatigue spalling in the ferrography test was also discussed. The analysis suggested the probable reasons for such kind of failure in operation. This type of spalling occurred due to (1) heavier external loading condition or (2) exceeds its service life.

Keywords: bearing, rolling contact fatigue, bearing life

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Authors: Daniel Muwooya

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This paper analyses economic factors that have affected the competitiveness of petroleum refinery and petrochemical projects in sub-Saharan Africa in the past and continue to plague greenfield projects today. Traditional factors like plant sizing and complexity, low-capacity utilization, changing regulatory environment, and tighter product specifications have been important in the past. Additional factors include the development of excess refinery capacity in Asia and the growth of renewable sources of energy – especially for transportation. These factors create both challenges and opportunities for the development of greenfield refineries and petrochemical projects in areas of increased demand growth and new low-cost crude oil production – like sub-Saharan Africa. This paper evaluates the strategies available to project developers and host countries to address contemporary issues of energy transition and the apparent reduction of funds available for greenfield oil and gas projects. The paper also evaluates the structuring of greenfield refinery and petrochemical projects for limited recourse project finance bankability. The methodology of this paper includes analysis of current industry data, conference proceedings, academic papers, and academic books on the subjects of petroleum refinery economics, refinery financing, refinery operations, and project finance generally and specifically in the oil and gas industry; evaluation of expert opinions from journal articles; working papers from international bodies like the World Bank and the International Energy Agency; and experience from playing an active role in the development and financing of US$ 10 Billion greenfield oil development project in Uganda. The paper also applies the discounted cash flow modelling to illustrate the circumstances of an inland greenfield refinery project in Uganda. Greenfield refinery and petrochemical projects are still necessary in sub-Saharan Africa to, among other aspirations, support the transition from traditional sources of energy like biomass to such modern forms as liquefied petroleum gas. Project developers and host governments will be required to structure projects that support global climate change goals without occasioning undue delays to project execution.

Keywords: financing, refinery and petrochemical economics, Africa, project finance

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Authors: Bintou Jobe

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The construction sector, both in the United Kingdom (UK) and developing Anglophone West African countries, specifically The Gambia, is facing significant health and safety challenges. While the UK has established legislation and regulations to support Occupational Health and Safety (OHS) in the industry, the same level of support is lacking in developing countries. The significance of this review is to assess the extent and effectiveness of OHS legislation and regulatory reform in the construction industry, with a focus on understanding the challenges faced by both the UK and developing Anglophone West African countries. It aims to highlight the benefits of implementing an OHS management system, specifically ISO 45001. This study uses a literature review approach, synthesizing publications from the past decade and identifying common themes and best practices related to Occupational Health and Safety in the construction industry. Findings were analysed, compared, and conclusions and recommendations were drawn after developing research questions and addressing them. This comprehensive review of the literature allows for a detailed understanding of the challenges faced by the industry in both contexts. The findings of the study indicate that while the UK has established robust health and safety legislation, many UK construction companies have not fully met the standards outlined in ISO 45001. These challenges faced by the UK include poor data management, inadequate communication of best practices, insufficient training, and a lack of safety culture mirroring those observed in the developing Anglophone countries. Therefore, compliance with OHS management systems has been shown to yield benefits, including injury prevention and centralized health and safety documentation. In conclusion, the effectiveness of OHS legislation for developing Anglophone West African countries should consider the positive impact experienced by the UK. The implementation of ISO 45001 can serve as a benchmark standard and potentially inform recommendations for developing countries. The selection criteria for literature include search keywords and phrases, such as occupational health and safety challenges, The Gambia, developing countries management systems, ISO 45001, and impact and effectiveness of OHS legislation. The literature was sourced from Google Scholar, the UK Health and Safety Executive websites, and Google Advanced Search.

Keywords: ISO 45001, developing countries, occupational health and safety, UK

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Authors: Tom Farrelly, Yvoonne Kavanagh, Tony Murphy

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In the last 20 years, Ireland has enjoyed an upsurge in the number of international students coming to avail of its well-regarded Higher Education system. While welcome, the influx of international students has posed a number of cultural, social and academic challenges for the Irish HE sector, both at institutional and individual lecturer level. Notwithstanding the challenge to the Irish HE sector, the difficulties that incoming students face needs to be acknowledged and addressed. For students who have never left their home country before the transition can be daunting even if they have not learned the customs and ways of the new country. In 2013, Ireland’s National Forum for the Advancement of Teaching and Learning in Higher Education invited submissions from interested parties to design and implement digital supports aimed at assisting students transitioning into or exiting higher education. Five colleges—the Institute of Technology, Tralee; University College Cork, Institute of Technology, Carlow; Cork Institute of Technology and Waterford Institute of Technology—collectively known as the Southern Cluster, were granted funding to research and develop digital objects to support international students' transition into the Irish higher education system. One of the key fundamentals of this project was its strong commitment to incorporating the student voice to help inform the design of the digital objects. The primary research method used to ascertain student views was the circulation of an online questionnaire using SurveyMonkey to existing international students in each of the five participant colleges. The questionnaire sought to examine the experiences and opinions of the students in relation to three main aspects of their living and studying in Ireland (hence the name of the project LiveAndLearnInIreland) (1) the academic environment (2) the social aspects of living in Ireland and (3) the practical aspects of living in Ireland. The response to the survey (n=573), revealed a number of sometimes surprising issues and themes for the digital objects to address. The research, therefore, offers insight into the types of concerns that any college, whether in Ireland or further afield, needs to take into consideration, if it is to genuinely assist what can be a difficult transition for the international student. That said, while there are a number of themes that emerged that have international implications there are other themes that have a particular resonance for the Irish HE sector.

Keywords: international, transition, support, inclusion

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Authors: Tekle Olbamo, Tegegn Tesfaye, Dikaso Unbushe, Belete Jorga

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Bovine trypanosomosis is a haemoprotozoan parasitic disease, mostly transmitted by the tsetse fly (Glossina species) and poses significant losses to the livestock industry in pastoral and agro-pastoral areas. Therefore, the current study was aimed to determine the prevalence of bovine trypanosomosis and its vectorial density in some selected tsetse suppression and non-tsetse suppression areas of South Omo Zonefrom December 2018- November 2019. Dark phase contrast buffy coat, hematocrit techniques, and thin blood smear method were used for determination of prevalence and packed cell volume of trypanosomosis infection, respectively. For entomological investigation, 96 NGU traps were deployed (64 traps in tsetse suppression areas, 32 traps in tsetse non-suppression areas) in vector breeding areas. The overall prevalence of bovine trypanosomosis was 11.05% (142/1284), and overall seasonal prevalence of disease was 14.33% (92/642) and 7.78% (50/642) for dry and wet seasons, respectively. There was a statistically significant difference (P <0.05) in disease prevalence between the two seasons. Trypanosomacongolensewas the dominant parasite species; 80% and 71.64%, followed by Trypanosomavivax. Overall mean packed cell volume indicated parasitaemic animals (23.57±3.13) had significantly lower PCV than aparasitaemic animals (27.80±4.95), and animals examined during dry season (26.22±4.37) had lower mean PCV than animals examined during wet season with the significant association. Entomological study result revealed a total of 2.64 F/T/D and 2.03 F/T/D respectively from tsetse suppression areas and tsetse non-suppression areas during dry season and 0.42 F/T/D and 0.56 F/T/D during the wet season. Glossinapallidipes was the only cyclical vectors collected and identified from current study areas along with numerous mechanical vectors of genus Tabanus, Stomoxys, and Haematopota. Therefore integrated and safe control and prevention effort should be engaged to uphold cattle production and productivity in the area.

Keywords: bovine trypanosomiasis, South Omo, tsetse fly density, epidemiological study

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Chow Jeng Hei, Pavel Tkalich, Low Kai Sheng Bryan

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Due to the growing demand for sustainability in the maritime industry, there has been a significant increase in focus on alternative fuels such as biofuels, liquefied natural gas (LNG), hydrogen, methanol and ammonia to reduce the carbon footprint of vessels. Alternative fuels offer efficient transportability and significantly reduce carbon dioxide emissions, a critical factor in combating global warming. In an era where the world is determined to tackle climate change, the utilization of methanol is projected to witness a consistent rise in demand, even during downturns in the oil and gas industry. Since 2022, there has been an increase in methanol loading and discharging operations for industrial use in Singapore. These operations were conducted across various storage tank terminals at Jurong Island of varying capacities, which are also used to store alternative fuels for bunkering requirements. The key objective of this research is to support the green shipping industries in the transformation to new fuels such as methanol and ammonia, especially in evolving the capability to inform risk assessment and management of spills. In the unlikely event of accidental spills, a highly reliable forecasting system must be in place to provide mitigation measures and ahead planning. The outcomes of this research would lead to an enhanced metocean prediction capability and, together with advanced sensing, will continuously build up a robust digital twin of the bunkering operating environment. Outputs from the developments will contribute to management strategies for alternative marine fuel spills, including best practices, safety challenges and crisis management. The outputs can also benefit key port operators and the various bunkering, petrochemicals, shipping, protection and indemnity, and emergency response sectors. The forecasted datasets provide a forecast of the expected atmosphere and hydrodynamic conditions prior to bunkering exercises, enabling a better understanding of the metocean conditions ahead and allowing for more refined spill incident management planning

Keywords: clean fuels, hydrodynamics, coastal engineering, impact assessments

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Authors: T. Konst

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Most jobs include training and communication tasks, but often the people in these jobs lack pedagogical competences to plan, implement and assess learning. This paper aims to discuss how a learning approach called innovation pedagogy developed in higher education can be utilized for learning development in various organizations. The methods presented how to implement innovation pedagogy such as process consultation and train the trainer model can provide added value to develop pedagogical knowhow in organizations and thus support their internal learning and development.

Keywords: innovation pedagogy, learning, organizational development, process consultation

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Authors: Magdi M. E. Zumrawi, Mohamed Awad

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Determination of Resilient Modulus (M_R) is quite important for characterizing materials in pavement design and evaluation. The main focus of this study is to develop a correlation that predict the resilient modulus of subgrade soils from simple and easy measured soil index properties. To achieve this objective, three subgrade soils representing typical Khartoum soils were selected and tested in the laboratory for measuring resilient modulus. Other basic laboratory tests were conducted on the soils to determine their physical properties. Several soil samples were prepared and compacted at different moisture contents and dry densities and then tested using resilient modulus testing machine. Based on experimental results, linear relationship of M_R with the consistency factor ‘F_c’ which is a combination of dry density, void ratio and consistency index had been developed. The results revealed that very good linear relationship found between the M_R and the consistency factor with a coefficient of linearity (R²) more than 0.9. The consistency factor could be used for the prediction of the M_R of compacted subgrade soils with precise and reliable results.

Keywords: Consistency factor, resilient modulus, subgrade soil, properties

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

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Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

Abstract:

The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Zahara Abdulhussan Al-Awadai

Abstract:

Currently, serious games play a significant role in education, sparking an increasing interest in using games for purposes beyond mere entertainment. In this research, we investigate the main requirements and aspects of designing and developing effective serious games for learning and developing a conceptual model to describe the structure of serious games with a focus on both aspects of serious games. The main contributions of this approach are to facilitate the design and development of serious games in a flexible and easy-to-use way and also to support the cooperative work between the multidisciplinary developer team.

Keywords: game development, game design, requirements, serious games, serious game model.

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Authors: Werner Roux Uys

Abstract:

The Commissioner for the South African Revenue Service (SARS) holds a high position of trust in South African society and a lack of trust by taxpayers in the Commissioner’s actions or conduct could compromise SARS’ management of public finances. Tax morality – which is implicit in the social contract between taxpayers and the state – includes distinct phenomena that can cause a breakdown if there is a perceived lack of action on the part of the Commissioner to ensure public finances are kept safe. To promote tax morality, the Commissioner must support the judiciary in the exercise of its discretion to punish fraudulent tax activities and corrupt tax practices. For several years the political meddling in the Commissioner’s actions and conduct have caused perceived abuse of power at SARS, and taxpayers believed their hard-earned income paid over to SARS would be fruitless and wasteful expenditure. The purpose of this article is to identify and analyse previous decisions held by the South African judiciary regarding the Commissioner’s actions and conduct in tax matters, as well as consider important political statements and newspaper bulletins for the purpose of this research. The study applies a qualitative research approach and exploratory case study technique. Keywords were selected and inserted in the LexisNexis electronic database to systematically identify applicable case law where the ratio decidendi of the court referred to the actions and/or conduct of the Commissioner. Specific real-life statements, including political statements and newspaper bulletins, were selected to support the topic at hand. The purpose of the study is to educate the public about the perceptions that have transformed taxpayers’ behaviour towards the Commissioner for SARS since South Africa’s fledgling constitutional democracy was inaugurated in 1994. The study adds to the literature by identifying key characteristics or distinct phenomena regarding the actions and conduct of the Commissioner affecting taxpayers’ behaviour, including discretionary decision-making. From the findings, it emerged that SARS must abide by its (own) laws and that there is a need to educate not only South African taxpayers about tax morality, but also the public in general.

Keywords: commissioner, SARS, action and conduct, judiciary, discretionry, decsion-making

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Authors: Kang Woobang

Abstract:

The base of the column is not only a support but also the embodiment of profound symbolism full of cosmic energy. Finding the full jars from which various energy emanate at the Notre Dame of Paris and Saint-Germain-des-Pres in France, the author was so shocked. As the column is cosmic tree, from the Full Jar full with cosmic energy emerges the cosmic tree composed of shaft and capital.

Keywords: full picher or jar, transcendental or supernatural birth from yonggi, yonggimun, yonggissak

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Authors: Yulan Wu

Abstract:

With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

Procedia PDF Downloads 88