Search results for: WEKA data mining tool

Authors: Lok Yi Joyce Poon

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China's mobile payment market has boomed in the past few years. WeChat (Chinese name as Weixin) owned by Tencent is known as the fastest growing all-in-one social messaging platforms. The company has launched the WeChat Pay in 2013, in which users can link their credit card to their user account and make payments within the app’s built in digital wallet. WeChat Payment is a one-stop payment tool that can provide a seamless online experience for the shoppers to transfer money between WeChat users (peer-to-peer) and make payments online by scanning a QR code, a prominent facilitator for transactions in WeChat, to complete the payment with the app without directing the users to the external websites. The aims of this study are to examine the effectiveness of WeChat mobile payment in China as well as the impacts of the China teen’s online purchasing behavior since the establishment of WeChat Payment. The research method of this study is conducted by both online survey on Sojump, a popular online survey platform in China. A total of 120 respondents among 18 to 25 teens in China completed the survey. Data sources included participants’ response to an end-of-session questionnaire, encompassing with the types of multiple choice, open-ended questions. To have an in-depth analysis, a face-to-face interview with a Chinese teen who is a frequent user of the WeChat Pay. The main finding of the study shows that the majority of the teenagers frequently use the WeChat payment tool because of its convenience, user-friendliness and the scenarios offered within the WeChat Wallet. The respondents claimed that they will settle the bills in their daily lives via WeChat Pay. However, the respondents in the age group of 40 or above will not use the WeChat Pay due to the security concern and they do not see the app as a platform for commercial activities like online shopping. Throughout the study, it is recommended WeChat should put more efforts on the security issue and improve the payment technology by adopting the near-field communication terminals instead of requiring users to scan QR codes before they complete the transaction.

Keywords: digital wallet, mobile payment, online purchasing behavior, WeChat Pay

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Authors: Fonseca Jully, Chia Maribel, Rodríguez Ilba

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This paper is a qualitative research report. A group of students form a public university in a small town in Colombia participated in this study which aimed at describing to what extend the use of social ads, published on the internet, helped to develop their critical thinking skills. Students’ productions, field notes, video recordings and direct observation were the instruments and techniques used by the researches in order to gather the data which was analyzed under the principles of grounded theory and triangulation. The implementation of social ads into the classroom evidenced a noticeable improvement in students’ ability to interpret and argue social issues, as well as, their self-improvement in oral and written production in English, as a foreign language.

Keywords: Ads, critical argumentation, critical thinking, social issues

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Authors: Francesca Radice

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Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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Authors: Mangana B. Rampheri, Timothy Dube, Farai Dondofema, Tatenda Dalu

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Identifying and delineating groundwater-dependent ecosystems (GDEs) is critical to the well understanding of the GDEs spatial distribution as well as groundwater allocation. However, this information is inadequately understood due to limited available data for the most area of concerns. Thus, this study aims to address this gap using remotely sensed, analytical hierarchy process (AHP) and in-situ data to identify and delineate GDEs in Khakea-Bray Transboundary Aquifer. Our study developed GDEs index, which integrates seven explanatory variables, namely, Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Land-use and landcover (LULC), slope, Topographic Wetness Index (TWI), flow accumulation and curvature. The GDEs map was delineated using the weighted overlay tool in ArcGIS environments. The map was spatially classified into two classes, namely, GDEs and Non-GDEs. The results showed that only 1,34 % (721,91 km2) of the area is characterised by GDEs. Finally, groundwater level (GWL) data was used for validation through correlation analysis. Our results indicated that: 1) GDEs are concentrated at the northern, central, and south-western part of our study area, and 2) the validation results showed that GDEs classes do not overlap with GWL located in the 22 boreholes found in the given area. However, the results show a possible delineation of GDEs in the study area using remote sensing and GIS techniques along with AHP. The results of this study further contribute to identifying and delineating priority areas where appropriate water conservation programs, as well as strategies for sustainable groundwater development, can be implemented.

Keywords: analytical hierarchy process (AHP), explanatory variables, groundwater-dependent ecosystems (GDEs), khakea-bray transboundary aquifer, sentinel-2

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Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu

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Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.

Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis

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Authors: Masood Ahmed

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There is a plethora of literature (including judicial and extra-judicial comments) concerning the virtues of alternative dispute resolution processes within the English civil justice system. Lord Woolf in his Access to Justice Report ushered in a new pro-ADR philosophy and this was reinforced by Sir Rupert Jackson in his review of civil litigation costs. More recently, Briggs LJ, in his review of the Chancery Court, reiterated the significant role played by ADR and the need for better integration of ADR processes within the Chancery Court. His Lordship also noted that ADR which had failed to produce a settlement (i.e. a failed-ADR) continued to play a significant role in contributing to a ‘substantial narrowing of the issues or increased focus on the key issues’ which were ‘capable of assisting both the parties and the court in the economical determination of the dispute at trial.’ With the assistance of empirical data, this paper investigates the nature of failed-ADR and, in particular, assesses the effectiveness of failed-ADR processes as a tool in: (a) narrowing the legal and/or factual issues which may assist the courts in more effective and efficient case management of the dispute; (b) assisting the parties in the future settlement of the matter. This paper will also measure the effectiveness of failed-ADR by considering the views and experiences of legal practitioners who have engaged in failed-ADR.

Keywords: English civil justice system, alternative dispute resolution processes, civil court process, empirical data from legal profession regarding failed ADR

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Authors: Ali Albadri

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Step band in an escalator moves in a cyclic periodic pattern. Similarly, most if not all of the components and sub-assemblies in the escalator operate in the same way. If you mark up one step in the step band of an escalator and stand next to the escalator, on the incline, to watch the marked-up step when it passes by, you ask yourself, does the marked up step behaves exactly the same way during each revolution when it passes you by again and again? We can say that; there is some similarity in this example and the example when an astronomer watches planets in the sky, and he or she asks himself or herself, does each planet intersects the plan of observation in the same position for every pantry rotation? For a fact, we know for the answer to the second example is no, because scientist, astronomers, and mathematicians have proven that planets deviate from their paths to take new paths during their planetary moves, albeit with minimal change. But what about the answer to the question in the first example? considering that there is increase in the wear and tear of components with time in the step, in the step band, in the tracks and in many other places in the escalator. There is also the accumulation of fatigue in the components and sub-assemblies. This research is part of many studies which we are conducting to address the answer for the question in the first example. We have been using the fractal dimension as a quantities tool and the Poincare map as a qualitative tool. This study has shown that the fractal dimension value and the shape and distribution of the orbits in the Poincare map has significant correlation with the quality of the mechanical components and sub-assemblies in the escalator.

Keywords: fractal dimension, Poincare map, rugby ball orbit, worm orbit

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Authors: Edmaritz Hernandez-Pagan, Kanjana Laosuntisuk, Alex Harris, Allison Haynes, David Buitrago, Michael Kudenov, Colleen Doherty

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Rare Earth Elements (REEs) are critical metals for modern electronics, green technologies, and defense systems. However, due to their dispersed nature in the Earth’s crust, frequent co-occurrence with radioactive materials, and similar chemical properties, acquiring and purifying REEs is costly and environmentally damaging, restricting access to these metals. Plants could serve as resources for bioengineering REE mining systems. Although there is limited information on how REEs affect plants at a cellular and molecular level, plants with high REE tolerance and hyperaccumulation have been identified. This dissertation aims to develop a plant-based system for harvesting REEs from industrial waste material with a focus on Acid Mine Drainage (AMD), a toxic coal mining product. The objectives are 1) to develop a non-destructive, in vivo detection method for REE detection in Phytolacca plants (REE hyperaccumulator) plants utilizing fluorescence spectroscopy and with a primary focus on dysprosium, 2) to characterize the uptake of REE and Heavy Metals in Phytolacca americana and Phytolacca acinosa (REE hyperaccumulator) in AMD for potential implementation in the plant-based system, 3) to implement the REE detection method to identify REE-binding proteins and peptides for potential enhancement of uptake and selectivity for targeted REEs in the plants implemented in the plant-based system. The candidates are known REE-binding peptides or proteins, orthologs of known metal-binding proteins from REE hyperaccumulator plants, and novel proteins and peptides identified by comparative plant transcriptomics. Lanmodulin, a high-affinity REE-binding protein from methylotrophic bacteria, is used as a benchmark for the REE-protein binding fluorescence assays and expression in A. thaliana to test for changes in REE plant tolerance and uptake.

Keywords: phytomining, agromining, rare earth elements, pokeweed, phytolacca

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Authors: Asha Dukkipati

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Cognitive neuroscience explores neural functioning and aberrant brain activity during cognitive and perceptual tasks. Neurocinematics is a subfield of cognitive neuroscience that observes neural responses of individuals watching a film to see similarities and differences between individuals. This method is typically used for commercial use, allowing directors and filmmakers to produce better visuals and increasing their results in the box office. However, neurocinematics is increasingly becoming a common tool for neuroscientists interested in studying similar patterns of brain activity across viewers outside of the film industry. In this review, it argue that neurocinematics provides an easy, naturalistic approach for studying and diagnosing learning disorders. While the neural underpinnings of developmental learning disorders are traditionally assessed with well-established methods like EEG and fMRI that target particular cognitive domains, such as simple visual and attention tasks, there is initial evidence and theoretical background in support of neurocinematics as a biomarker for learning differences. By using ADHD, dyslexia, and autism as case studies, this literature review discusses the potential advantages of neurocinematics as a new tool for learning disorders research.

Keywords: behavioral and social sciences, neuroscience, neurocinematics, biomarkers, neurobehavioral disorders

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Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

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In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

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Authors: Katarzyna Oberda

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The aim of this paper is to conceptual emotions in the process of mediation. Although human emotions have been approached from various disciplines and perspectives, e.g. philosophy, linguistics, psychology and neurology, this complex phenomenon still needs further investigation into its discursive character with the an open mind and heart. To attain this aim, the theoretical and practical considerations are taken into account both to contextualize the discursive psychology of emotions in mediation and show how cognitive and linguistic activity expressed in language may lead to the emotional turn in the process of mediation. The double directions of this research into the discursive psychology of emotions have been partially inspired by the evaluative components of mediation forms. In the conducted research, we apply the methodology of discursive psychology with the discourse analysis as a tool. The practical data come from the recorded mediations online. The major findings of the conducted research result in the reconstruction of the emotional transformation model in mediation.

Keywords: discourse analysis, discursive psychology, emotions, mediation

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Authors: R. Bernaoui, P. Ohly

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Our research shows the use of the mobile phone that consolidates the relationship between veterinarians, and that between breeders and veterinarians. On the other hand it asserts that the tool in question is a means of economic development. The results of our survey reveal a positive return to the veterinary community, which shows that the mobile phone has become an effective means of sustainable development through the transfer of a rapid and punctual information inheritance via social networks; including many Internet applications. Our results show that almost all veterinarians use the mobile phone for interprofessional communication. We therefore believe that the use of the mobile phone by livestock operators has greatly improved the working conditions, just as the use of this tool contributes to a better management of the exploitation as long as it allows limit travel but also save time. These results show that we are witnessing a growth in the use of mobile telephony technologies that impact is as much in terms of sustainable development. Allowing access to information, especially technical information, the mobile phone, and Information and Communication of Technology (ICT) in general, give livestock sector players not only security, by limiting losses, but also an efficiency that allows them a better production and productivity.

Keywords: algeria, breeder-veterinarian, digital heritage, networking

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

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The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using Partial Least Squares (PLS) and Structural Equation Modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: building management, stratified low-cost housing, safety, health model

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

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Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Mitra Savabi-Esfahani, Fariba Taleghani, Mahnaz Noroozi, Maryam Tabatabaeian, Elsebeth Lynge

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Breast cancer is a health concern in worldwide. All women have not adequate information about breast cancer, resulting in undetected some tumors until advanced stages. Therefore awareness of people was recommended as a strategy to control that. The aim of this study was to assess the effect of an educational intervention on women's knowledge and attitude about breast cancer and screening. This study was conducted in 2016 on 191 women. All women living in one of big cities were invited to enroll in training classes. Inclusion criteria consisted women who were 20 - 69 years and not participated in any educational intervention. The lecture with group discussion was used as educational methods. Data collection tool was a structured questionnaire which filled out before and after intervention. The reliability of the questionnaire was determined by Cronbach's alpha. The data were analyzed using SPSS software. The average age was 44/4 ± 11.5 and 42.6% of the women had obtained high school. Of the 191 women, 70(36.6%) and 76(39.8%) had low and medium level of knowledge respectively and half of them, 95(50%) had medium level of attitude in before intervention. There was significant difference between mean scores of knowledge and attitude before and after the intervention by Paired T test (p < 0/001). It seems applying effective educational interventions can increase knowledge and attitude women about breast cancer particularly in community that they have insufficient levels. Moreover, the lecture method along with group discussion can be proposed as effective and conventional methods for this purpose.

Keywords: attitude, breast cancer, educational intervention, knowledge

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Authors: Yude Wu

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Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Xiyue Wang, Shaoning Yan

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Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

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Authors: Se-Hyuk Park, Hee-Jung Seo

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Previous studies have investigated effective coping strategies for excessive stress, positive adaptation, resilience, mental health, and personal growth. However, to the best of the authors' knowledge, little research has been conducted to investigate how Koreans with physical disabilities deal with the COVID-19 pandemic. The purpose of this study was to identify coping strategies and coping resources that Koreans with physical disabilities utilized during the COVID-19 crisis. This study used semi-structured, in-depth interviews with 15 participants. Data were qualitatively analyzed using the constant comparative method with content mapping and content mining questions. We identified three salient themes that were used by participants as coping strategies to deal with various COVID-related challenges: (a) engagement in meaningful activities, (b) improvement of social and emotional support, and (c) experience of resilience. The findings of the present study highlighted that Korean adults with SCI actively engaged in various leisure activities, maintained and developed closer social relationships, and experienced resilience to face COVID-19-related stressors. These coping strategies were noted as a catalyst for physical health as well as psychological well-being of individuals with SCI.

Keywords: spinal cord injury, covid-19 pandemic, coping strategies, coping resources, leisure

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

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In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: activity modeling, clustering, PLSA, video representation

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Authors: Shoumodip Roy, Ankit Singhania, Santanu Mallick, Abhiram Jha, M. K. Agarwal, R. V. Ramna, Uttam Singh

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The quality of hot metal at any blast furnace is judged by the silicon content in it. Lower hot metal silicon not only enhances process efficiency at steel melting shops but also reduces hot metal costs. The Hot metal produced at G-Blast furnace Tata Steel Jamshedpur has a significantly higher Si content than Benchmark Blast furnaces. The higher content of hot metal Si is mainly due to inferior raw material quality than those used in benchmark blast furnaces. With minimum control over raw material quality, the only option left to control hot metal Si is via optimizing the furnace parameters. Therefore, in order to identify the levers to reduce hot metal Si, Data mining was carried out, and multiple regression models were developed. The statistical analysis revealed that Slag B3{(CaO+MgO)/SiO2}, Slag Alumina and Hot metal temperature are key controllable parameters affecting hot metal silicon. Contour Plots were used to determine the optimum range of levels identified through statistical analysis. A trial plan was formulated to operate relevant parameters, at G blast furnace, in the identified range to reduce hot metal silicon. This paper details out the process followed and subsequent reduction in hot metal silicon by 15% at G blast furnace.

Keywords: blast furnace, optimization, silicon, statistical tools

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Authors: Yananda Siraphatthada

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The objectives of this research were to study the level of influencing factors, leadership, supply chain management, innovation, competitive advantages, business success, and affecting factors to the business success of the mobile phone system service providers in Bangkok Metropolitan. This research was done by the quantitative approach and the qualitative approach. The quantitative approach was used for questionnaires to collect data from the 331 mobile service shop managers franchised by AIS, Dtac and TrueMove. The mobile phone system service providers/shop managers were randomly stratified and proportionally allocated into subgroups exclusive to the number of the providers in each network. In terms of qualitative method, there were in-depth interviews of 6 mobile service providers/managers of Telewiz and Dtac and TrueMove shop to find the agreement or disagreement with the content analysis method. Descriptive Statistics, including Frequency, Percentage, Means and Standard Deviation were employed; also, the Structural Equation Model (SEM) was used as a tool for data analysis. The content analysis method was applied to identify key patterns emerging from the interview responses. The two data sets were brought together for comparing and contrasting to make the findings, providing triangulation to enrich result interpretation. It revealed that the level of the influencing factors – leadership, innovation management, supply chain management, and business competitiveness had an impact at a great level, but that the level of factors, innovation and the business, financial success and nonbusiness financial success of the mobile phone system service providers in Bangkok Metropolitan, is at the highest level. Moreover, the business influencing factors, competitive advantages in the business of mobile system service providers which were leadership, supply chain management, innovation management, business advantages, and business success, had statistical significance at .01 which corresponded to the data from the interviews.

Keywords: mobile service providers, facilitating factors, Bangkok Metropolitan, business success

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Authors: D. Muyama, M. Luyiga, P. Buyungo, D. Chemonges, M. Namukwaya, L. Ssekabembe, B. Lukwago, D. Kyamagwa

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Context: The study focuses on the sustainability of health interventions in Uganda, particularly in the private sector, beyond donor-funded project periods. The Population Services International (PSI) implemented the Women Health Project (WHP) to ensure continued access to quality family planning, cervical cancer screening, and post-abortion care services through private clinics. Research Aim: The aim of the study is to assess the continued access to quality family planning, cervical cancer screening, and post-abortion care services through the private sector after the closure or reduction in funding of the WHP. Methodology: PSI trained and mentored 83 clinics to establish functional systems in self-regulatory quality improvement, supply chain, referral, and demand creation. The clinics were also connected to the national reporting system and utilized Ministry of Health reporting tools. An assessment tool with six criteria was designed and used to evaluate the progress of the clinics. Clinics scoring 75% and above were considered independent and graduated from the program. Findings: Out of the 83 private clinics, 56 successfully met the graduation criteria and graduated from the program, while 25 lost interest and were gradually dropped. Two clinics failed to achieve the criteria due to leadership challenges. The 59 graduating clinics continued to provide high-quality family planning services, including IUD, implant, Depo-Provera, oral contraceptives, and post-abortion care. All graduating clinics were reassessed and found to still be capable of offering services, attributing their success to government stock availability and acquired skills through mentorships. The clinics expressed appreciation to PSI for the sustainable plan that allowed them to operate beyond the project period. Theoretical Importance: This study contributes to the understanding of sustainability planning and the importance of clinic owners' attitudes and buy-in for continued service provision. It emphasizes the implementation of sustainability plans through existing structures to leverage available resources and ensure continuity of care. Data Collection and Analysis Procedures: The study collected data through the assessment tool that evaluated the progress of clinics based on the established criteria. The tool was scored out of 100%, and clinics scoring above 75% were deemed independent. The findings were analyzed quantitatively to determine the success rate of clinics in meeting the graduation criteria. Questions Addressed: The study addresses the question of whether private clinics in Uganda can sustain the provision of family planning, cervical cancer screening, and post-abortion care services after the closure or reduction in funding of the WHP. Conclusion: The study concludes that the attitude and buy-in of clinic owners are essential for sustainability planning. Implementing sustainability plans through existing structures and leveraging available resources are crucial for the continuity of care after the end of a project or reduced funding. The findings highlight the importance of establishing sustainable plans to ensure continued access to essential health services beyond the project period. Contributions: This study contributes to the existing knowledge for programmers implementing or intending to implement donor-funded projects. It provides insights into designing sustainable plans that enable the independent operation of clinics even after the end of a project.

Keywords: graduation, family planning, systems strengthening, sustainability

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Authors: Nabin Prasad Joshi

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A new variant of the coronavirus family found in the Wuhan city market of China is causing serious harm to human beings. After the WHO decided COVID-19 was a pandemic situation, everyone started to measure the prevention of infectious diseases according to WHO guidelines. It includes social distancing, isolation, quarantine, lockdown, sanitation, and masking, respectively. During this time, the researcher has observed the difficulties of cultivating the new normal in people in Nepal. People have perceived the single coronavirus differently; common populations and frontline workers have different perceptions of coronavirus. The researcher started to measure the psychosocial impact of the COVID-19 pandemic on frontline workers and general populations in Kathmandu valley. The total number of sample units for this research is 82; it includes 52 general populations and 30 frontline workers. These sample units are selected through convenient sampling and purposive sampling, respectively. This research is based on descriptive and exploratory design. DASS-21 of the Nepali version is a comprehensive data collection tool for depression, anxiety, and stress measurement in this research, and simultaneously the psychosocial checklist, key-informant interview, and case study have been done. Quantitative data are analyzed with the help of excel, and qualitative data are through thematic analysis. The study has shown that the occurrence of psychosocial issues among frontline workers is greater than in general populations. It is found that the informants with higher education status have greater psychosocial issues in comparison to low education status. In the context of a pandemic, family/friends’ support can function as a protective factor when at adequate levels.

Keywords: anxiety, depression, isolation, lockdown

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Authors: Chigozirim Onwusiribe, Jude Mbanasor

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Egusi Melon (Citrullus Lanatus Thunb. Mansf ) is a very important oil seed that serves a major ingredient in the diet of most of the households in Nigeria. Egusi Melon is very nutritious and very important in meeting the food security needs of Nigerians. Egusi Melon is cultivated in most farm enterprise in South East Nigeria but the profitability of its value chain needs to be investigated. This study analyzed the profitability of the Egusi Melon value chain. Specifically this study developed a value chain map for Egusi Melon, analysed the profitability of each stage of the Egusi Melon Value chain and analysed the determinants of the profitability of the Egusi Melon at each stage of the value chain. Multi stage sampling technique was used to select 125 farm enterprises with similar capacity and characteristics. Questionnaire and interview were used to elicit the required data while descriptive statistics, Food and Agriculture Organization Value Chain Analysis Tool, profitability ratios and multiple regression analysis were used for the data analysis. One of the findings showed that the stages of the Egusi Melon value chain are very profitable. Based on the findings, we recommend the provision of grants by government and donor agencies to the farm enterprises through their cooperative societies, this will provide the necessary funds for the local fabrication of value addition and processing equipment to suit their unique value addition needs not met by the imported equipment.

Keywords: value, chain, melon, farm, enterprises

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: L. Freeman, D. Bax, V. K. Sapong

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Community-based, preventative approaches to violent extremism may be effective and yet remain an underutilised method. In a realm where security approaches dominate, with the focus on countering violence extremism and combatting radicalisation, community resilience programming remains sparse. This paper will present a survey tool that aims to measure the risk and protective factors that can lead to violent extremism in Mozambique and Tanzania. Conducted in four districts in the Cabo Delgado region of Mozambique and one district in Pwani, Tanzania, the survey uses a combination of BRAVE-14, Afrocentric and context-specific questions in order to more fully understand community resilience opportunities and challenges in preventing and countering violent extremism. Developed in Australia and Canada to measure radicalisation risks in individuals and communities, BRAVE-14 is a tool not yet applied in the African continent. Given the emerging threat of Islamic extremism in Northern Mozambique and Eastern Tanzania, which both experience a combination of socio-political exclusion, resource marginalisation and religious/ideological motivations, the development of the survey is timely and fills a much-needed information gap in these regions. Not only have these Islamist groups succeeded in tapping into the grievances of communities by radicalising and recruiting individuals, but their presence in these regions has been characterised by extreme forms of violence, leaving isolated communities vulnerable to attack. The expected result of these findings will facilitate the contextualisation and comparison of the protective and risk factors that inhibit or promote the radicalisation of the youth in these communities. In identifying sources of resilience and vulnerability, this study emphasises the implementation of context-specific intervention programming and provides a strong research tool for understanding youth and community resilience to violent extremism.

Keywords: community resilience, Mozambique, preventing violent extremism, radicalisation, Tanzania

Procedia PDF Downloads 132