Search results for: audio/visual peer learning

Authors: Nawt Almutairi, Ramzi El-Haddadeh

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With the extensive increase in the number of online shops, loyalty becomes the most purpose for e-retailers by which they can maintain their exit customers and regular income instead of spending large deal of money to target new segmentation. To obtain customers’ loyalty e-marketers should firstly satisfy customers by providing a high quality of services that could fulfil their demand. They have to satisfy them to trust the web-site then increase their intention to re-visit it. This study intends to investigate to what extend the elements of e-service quality presented in the literature affect customers’ satisfaction and how these influences contribute to customers’ trust and loyalty. Three dimensions of service quality are estimated. The first element is web-site interactivity, which is perceived the quality of interactive support and the accessible communications-tool. The second aspect is security/privacy, which is perceived the quality of controlling security and privacy while transaction over the web-site. The third element is web-design that perceived a pleasant user interface with visual appealing. These elements present positive effects on shoppers’ satisfaction. Thus, To examine the proposed constructs of this research, some measurements scale-items adapted from similar prior studies. Survey data collected online from Saudi customers (n=106) were utilized to test the research hypotheses. After that, the hypotheses were analyzed by using a variety of regression tools. The analytical results of this study propose that perceived quality of interactivity and security/privacy affects customers’ satisfaction. As well as trust seems to be a substantial construct that highly affects loyalty in online shopping. This study provides a developed model to obtain a simple understanding of the series of customers’ loyalty in online shopping. One construct presenting in the research model is web-design appears to be not important antecedent of satisfaction (the path to loyalty) in online shopping.

Keywords: e-service, satisfaction, trust, loyalty

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Authors: Jakia Rajoana

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The aim of this paper is to examine the role of women entrepreneurs in bringing about sustainable rural tourism (SRT) development in Sundarbans area of Bangladesh. Theoretically, it draws upon empowerment and entrepreneurial marketing concepts. Women entrepreneurship development and lack of empowered women as role models is an important issue for developing economies in South Asia. Despite the substantial role women play in rural economy of Sundarbans, their contribution remains overlooked as enterprises led by them are run on an informal basis and their business acumen is not taken seriously both by their families and society at large. Studies on SRT fail to engage in sufficient depth with the term applied in this paper as ‘invisible women on the margins’ who run their enterprises with no formal training or societal/familial support. Moreover, the link between their (non) tourism enterprise and their empowerment remains under-theorized. Thus empirically, this research seeks to fill a significant gap by focusing on a considerably under-researched Sundarbans region. Methodologically, this study follows a qualitative research design using visual ethnographic approach. Participant observation, semi-structured interviews, and documentation are the primary data collection instruments in three coastal communities – Munshigonj, Burigoalini and Gabura – in the Sundarbans area. By focusing on the narratives of these under-investigated women, this work aims to provide in-depth and nuanced insights into salient issues on marginal communities experience from rural women’s perspectives. Initial findings illustrate that the Sundarbans women have low income due to no or little education. In addition, socio-cultural and religious factors also restrict the scope of their extensive contribution to workplace. In addition, physical and social violence which is a common occurrence for these women inhibits their agency and contributes to their disempowerment.

Keywords: gender, empowerment, entrepreneurial marketing, sustainable rural tourism, Sundarbans

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Irina Peterburgsky

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We have been working on finding internship positions for our math and computer science majors. Among many other positive outcomes of internship for students majoring in mathematics, there are: students see new applications of mathematics to real life and see new scientific problems; they learn new methods, tools, etc. that they have not seen in their classes; they appreciate the power of mathematics that increases their interest in learning mathematics; they make decisions to take more advanced math courses; students understand better what their potentials, strong points, and limitations are; learn what work ethic is; learn how to work as a member of a team at a workplace; understand better how to offer their help and how to ask for help; start building their professional relationship; build self-confidence as young professionals, and what is the most important - they get a better understanding of their goals in their future professional careers.

Keywords: internship, mathematics, positive outcoms for students, workplace

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Authors: Pallavi Singh

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Developing library knowledge centres involves transforming traditional library spaces into dynamic, interactive environments that support collaborative learning, digital literacy, and access to various resources. Knowledge centres, also known as knowledge hubs or centres of excellence, play a crucial role in organizations and communities by serving as repositories of expertise and information. The Energy and Resources Institute (TERI) is a research organisation dedicated to sustainable community solutions. TERI Knowledge Resource Center is also aligned with the objective of the host organization within TERI; there are several specialized knowledge centers dedicated to various aspects of sustainability, energy, climate change, environmental management, green mobility, etc.

Keywords: knowledge centres, environmental management, green mobility, energy

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Authors: Kittivate Boonyopakorn

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The purposes of this study were to investigate the method of the English use of the businessmen and to study their behavior of the utilization for the ASEAN economic community. The participants were divided into the three types of the merchants including the construction contractors, the construction material traders, and SME entrepreneurs. Survey questionnaires and interviews were used in this study. The findings showed that in the type of traders, 23 of the participants are construction contractors, 121 are construction material traders, and 206 are SME entrepreneurs. The study of English in language institute is highly 51.4%. The use of Google in translating English into Thai is 41.7%. Learning English themselves is 41.1% respectively. The businessmen study English for readiness for their trade.

Keywords: way of rnglish use, businessmen, ASEAN economic community, Chonburi province

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Authors: Noha Mohammed Ismael Awad Eladal, Aala Shoukry Emara

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Background: Wound healing after dental implant surgery is critical to the procedure's success. The aim of this study was to explore the effects of rutin+vitamin C supplementation in wound healing following the placement of dental implants. Methodology: There were 20 participants in this randomized controlled clinical trial who needed dental implants to replace missing teeth. Patients were divided into two groups, and group A received dental implants. Group B received dental implants with vitamin C administration. Follow-up appointments were performed on day 3, day 7, and day 14 post-surgery, during which soft tissue healing and pain response scores were evaluated using the visual analog scale. Postoperative digital panoramas were taken immediately after surgery, 3 months and 6 months postoperatively. Changes in bone density along with the bone-implant interface at the mesial, distal and apical sides were assessed using the digora software. Results: An independent t-test was used to compare the means of variables between the two groups. At the same time, repeated measures were employed to compare the means of variables between two groups. ANOVA was used to compare bone density for the same group at different dates. Significant increased differences were observed at the mesial, distal and apical sides Surrounding the implants of both groups per time. However, the rate of increase was significantly higher in group B The mean difference at the mesial side after 6 months was 21.99 ± 5.48 in the group B and 14.21 ± 4.95 in group A, while it read 21.74 ± 3.56 in the group B and 10.78 ± 3.90 in group A at the distal side and was 18.90 ± 5.91 in the group B and 10.39 ± 3.49 group A at the apical side. Significance was recorded at P = 0.004, P = 0.0001, and 0.001 at the mesial, distal and apical sides respectively. The mean pain score and wound healing were significantly higher in group A as compared to group B, respectively. Conclusion: The rutin c + vitamin c group significantly promoted bone healing and speeded up the osseointegration process and improved soft tissue healing.

Keywords: osseointegration, soft tissue, rutin c, dental implant

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Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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Authors: Annisa Ulfah Pristya, Andi Setiawan

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Indonesia placed in sixth rank total Acute Respiratory Infection (ARI) patient in the world and Riau as one of the province with the highest number of people with respiratory infection in Indonesia reached 37 thousand people. Usually society using a mask as prevention action. Unfortunately the commercial mouth mask only can work maximum for 4 hours and the pores are too large to filter out microorganisms and viruses carried by infectious droplets nucleated 1-5 μm. On the other hand, Indonesia is rich with Titanium dioxide (TiO2) and purple sweet potato anthocyanin pigment. Therefore, offered Bio-nano-mask which is a antimicrobial and antiviral mouth mask with Nano-TiO2 coating and purple sweet potato anthocyanins utilization as an effective solution to high ARI patients in Riau, which has the advantage of the mask surface can’t be attached by infectious droplets, self-cleaning and have anthocyanins biosensors that give visual response can be understood easily by the general public in the form of a mask color change from blue/purple to pink when acid levels increase. Acid level is an indicator of microorganisms accumulation in the mouth and surrounding areas. Bio-nano mask making process begins with the preparation (design, Nano-TiO2 liquid preparation, anthocyanins biosensors manufacture) and then superimposing the Nano-TiO2 on the outer surface of spunbond color using a sprayer, then superimposing anthocyanins biosensors film on the Meltdown surface, making bio nano-mask and it pack. Bio-nano mask has the advantage is effectively preventing pathogenic microorganisms and infectious droplets and has accumulated indicator microorganisms that color changes which easily observed by the common people though.

Keywords: anthocyanins, ARI, nano-TiO2 liquid, self cleaning

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Authors: Jonathan Rodriguez, Dominga Guerrero, Surupa Shaw

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Automobiles are modeled in various forms, and they interact with air when in motion. Aerodynamics is the study of such interactions where solid bodies affect the way air moves around them. The shape of solid bodies can impact the ease at which they move against the flow of air; due to which any additional freightage, or loads, impact its aerodynamics. It is important to transport people and cargo safely. Despite the various safety measures, there are a large number of vehicle-related accidents. This study precisely explores the effects an automobile experiences, with added cargo and covers. The addition of these items changes the original vehicle shape and the approved design for safe driving. This paper showcases the effects of the changed vehicle shape and design via experimental testing conducted on a physical 1:27 scale and CAD model of an F-150 pickup truck, the most common pickup truck in the United States, with differently shaped loads and weight traveling at a constant speed. The additional freightage produces unwanted drag or lift resulting in lower fuel efficiencies and unsafe driving conditions. This study employs an adjustable external shell on the F-150 pickup truck to create a controlled aerodynamic geometry to combat the detrimental effects of additional freightage. The results utilize colored powder [ which acts as a visual medium for the interaction of air with the vehicle], to highlight the impact of the additional freight on the automobile’s external shell. This will be done along with simulation models using Altair CFD software of twelve cases regarding the effects of an added load onto an F-150 pickup truck. This paper is an attempt toward standardizing the geometric design of the external shell, given the uniqueness of every load and its placement on the vehicle; while providing real-time data to be compared to simulation results from the existing literature.

Keywords: aerodynamics, CFD, freightage, pickup cover

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Authors: Omar Baissane and, Hassan Zaid

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The purpose of this study was to determine whether self-efficacy, task value, and metacognitive self-regulation predict students’ English language achievement among Vietnamese high school students. In this non-experimental quantitative study, 403 Vietnamese random participants were required to fill out the Motivated Strategies for Learning Questionnaire to measure self-efficacy, task value and metacognitive self-regulation. Criterion for English language achievement was the final grade that students themselves reported. The results revealed that, unlike metacognitive self-regulation, self-efficacy and task value were significantly correlated with language achievement. Moreover, the findings showed that self-efficacy was the only significant predictor of language achievement.

Keywords: language achievement, metacognitive self-regulation, predictor, self-efficacy, task value

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Asmaa Hamdy, Israa Nassar, Tarek Aly

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Introduction: Femoral fractures are the most common presentation in the Emergency Department (ED), and they can present as isolated injuries or as part of a polytrauma situation. To provide optimum pain management care to these patients, practitioners must be well prepared and current with utilizing modern evidence-based knowledge and practices. Management of pain associated with fracture femur in the emergency department has a critical role in the satisfaction of patients and preventing further complications. This study aimed to evaluate the analgesic efficacy of ultrasound-guided femoral nerve block compared with intravenous fentanyl in fractures of the femur in patients presented to the Emergency Department. Patients and Methods: Fifty patients with femur fractures were divided into two groups: Group A: In this group (twenty-five patients) were given intravenous fentanyl 2 micro-grams/kg and re-assessed for pain by Visual Analogue Score (VAS). Group B: In this group (twenty-five patients) underwent ultrasonography-guided femoral nerve block and were re-assessed for pain by VAS. Results: VAS score on the movement of the fractured limb between group A and group B at a 10-minute post-intervention period shows P= 0.043, and hence the difference is significant. VAS score on the movement of the fractured limb between group A and group B during a 10-minute post-intervention period showed a significant difference. Seventeen patients in group A had major PID with a percentage of 63% VS 10 patients in group B with a percentage of 37%. conclusion: both femoral nerve block and intravenous fentanyl are effective in relieving pain in patients with femur fractures. But femoral nerve block provides better and more intense analgesia and major pain intensity difference in less time. Moreover, the use of FNB had fewer side effects and more Hemodynamics stability compared to opioids.

Keywords: femur fracture, nerve block, fentanyl, ultrasound guided

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Authors: Jawharah Alasmari

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In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

Procedia PDF Downloads 278

Authors: Nilay Balkan

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Introductory statement: The purpose of this study is to understand how small business owners develop social media marketing competency, the challenges they encounter in doing so, and establish the social media training needs of such businesses. These challenges impact the extent to which small business owners build effective social media knowledge and, in turn, impact their ability to implement effective social media marketing into their business practices. This means small businesses are not fully able to benefit from social media, such as benefits to customer relationship management or increasing brand image, which would support the overall business operations for these businesses. This research is part one of a two-phased study. The first phase aims to establish the challenges small business owners face in building social media marketing competency and their specific training needs. Phase two will then focus in more depth on the barriers and challenges emerging from phase one. Summary of Methodology: Interviews with ten small business owners were conducted from various sectors, including fitness, tourism, food, and drinks. These businesses were located in the central belt of Scotland, which is an area with the highest population and business density in Scotland. These interviews were in-depth and semi-structured, with the purpose of being investigative and understanding the phenomena from the lived experience of the small business owners. A purposive sampling was used, where small business owners fulfilling certain criteria were approached to take part in the interviews. Key findings: The study found four ways in which small business owners develop their social media competency (informal methods, formal methods, learning through a network, and experimenting) and the various challenges they face with these methods. Further, the study established four barriers impacting the development of social media marketing competency among the interviewed small business owners. In doing so, preliminary support needs have also emerged. Concluding statement: The contribution of this study is to understand the challenges small business owners face when learning how to use social media for business purposes and identifying their training needs. This understanding can help the development of specific and tailored support. In addition, specific and tailored training can support small businesses in building competency. This supports small businesses to progress to the next stage of their development, which could be to further their digital transformation or grow their business. The insights from this study can be used to support business competitiveness and support small businesses to become more resilient. Moreover, small businesses and entrepreneurs share some similar characteristics, such as limited resources and conflicting priorities, and the findings of this study may be able to support entrepreneurs in their social media marketing strategies as well.

Keywords: small business, marketing theory and applications, social media marketing, strategic management, digital competency, digitalisation, marketing research and strategy, entrepreneurship

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Authors: Man Wai Lei, Charles Mark Zaroff

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Objective: A majority of studies suggest that people with Autism Spectrum Disorder (ASD) have multisensory integration deficits. However, normal and even supranormal multisensory integration abilities have also been reported. Additionally, little of this work has been undertaken utilizing a dimensional conceptualization of ASD; i.e., a broader autism phenotype. Utilizing methodology that controls for common potential confounds, the current study aimed to examine if deficits in multisensory integration are associated with ASD traits in a non-clinical population. The contribution of affective versus non-affective components of sensory hypersensitivity to multisensory integration was also examined. Methods: Participants were 147 undergraduate university students in Macau, a Special Administrative Region of China, of Chinese ethnicity, aged 16 to 21 (Mean age = 19.13; SD = 1.07). Participants completed the Autism-Spectrum Quotient, the Sensory Perception Quotient, and the Adolescent/Adult Sensory Profile, in order to measure ASD traits, non-affective, and affective aspects of sensory/perceptual hypersensitivity, respectively. In order to explore multisensory integration across visual and haptic domains, participants were asked to judge which one of two equally weighted, but different sized cylinders was heavier, as a means of detecting the presence of the size-weight illusion (SWI). Results: ASD trait level was significantly and negatively correlated with susceptibility to the SWI (p < 0.05); this correlation was not associated with either accuracy in weight discrimination or gender. Examining the top decile of the non-normally distributed SWI scores revealed a significant negative association with sensation avoiding, but not other aspects of effective or non-effective sensory hypersensitivity. Conclusion and Implications: Within the normal population, a greater degree of ASD traits is associated with a lower likelihood of multisensory integration; echoing was often found in individuals with a clinical diagnosis of ASD, and providing further evidence for the dimensional nature of this disorder. This tendency appears to be associated with dysphoric emotional reactions to sensory input.

Keywords: Autism Spectrum Disorder, dimensional, multisensory integration, size-weight illusion

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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: Yu-Wen Huang, Yi-Cheng Chiang

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With urban development, lots of buildings are built around the city. The buildings always affect the urban wind environment. The accelerative situation of wind caused of buildings often makes pedestrians uncomfortable, even causes the accidents and dangers. Factors influencing pedestrian level wind including atmospheric boundary layer, wind direction, wind velocity, planting, building volume, geometric shape of the buildings and adjacent interference effects, etc. Planting has many functions including scraping and slowing urban heat island effect, creating a good visual landscape, increasing urban green area and improve pedestrian level wind. On the other hand, urban square is an important space element supporting the entrance to buildings, city landmarks, and activity collections, etc. The appropriateness of urban square environment usually dominates its success. This research focuses on the effect of tree-planting on the wind environment of urban square. This research studied the square belt of Taichung City Hall. Taichung City Hall is a cuboid building with a large mass opening. The square belt connects the front square, the central opening and the back square. There is often wind draft on the square belt. This phenomenon decreases the activities on the squares. This research applies tree-planting to improve the wind environment and evaluate the effects of two types of planting configuration. The Computational Fluid Dynamics (CFD) simulation analysis and extensive field measurements are applied to explore the improve efficiency of planting configuration on wind environment. This research compares efficiencies of different kinds of planting configuration, including the clustering array configuration and the dispersion, and evaluates the efficiencies by the SET*.

Keywords: micro-climate, wind environment, planting configuration, comfortableness, computational fluid dynamics (CFD)

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Authors: Azadeh Bashiri

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Introduction: In order to better designing of electronic health record system in Iran, integration of health information systems based on a common language must be done to interpret and exchange this information with this system is required. Background: This study, provides a conceptual model of radiology reporting system using unified modeling language. The proposed model can solve the problem of integration this information system with electronic health record system. By using this model and design its service based, easily connect to electronic health record in Iran and facilitate transfer radiology report data. Methods: This is a cross-sectional study that was conducted in 2013. The student community was 22 experts that working at the Imaging Center in Imam Khomeini Hospital in Tehran and the sample was accorded with the community. Research tool was a questionnaire that prepared by the researcher to determine the information requirements. Content validity and test-retest method was used to measure validity and reliability of questioner respectively. Data analyzed with average index, using SPSS. Also, Visual Paradigm software was used to design a conceptual model. Result: Based on the requirements assessment of experts and related texts, administrative, demographic and clinical data and radiological examination results and if the anesthesia procedure performed, anesthesia data suggested as minimum data set for radiology report and based it class diagram designed. Also by identifying radiology reporting system process, use case was drawn. Conclusion: According to the application of radiology reports in electronic health record system for diagnosing and managing of clinical problem of the patient, provide the conceptual Model for radiology reporting system; in order to systematically design it, the problem of data sharing between these systems and electronic health records system would eliminate.

Keywords: structured radiology report, information needs, minimum data set, electronic health record system in Iran

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Wing Mui Winnie So, Tian Luo, Zeyu Han

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To fully explore and develop the potentials of gifted students systematically and strategically by providing them with opportunities to receive education at appropriate levels, schools in Hong Kong are encouraged to adopt the "Three-Tier Implementation Model" to plan and implement the school-based gifted education, with Level Three refers to the provision of learning opportunities for the exceptionally gifted students in the form of specialist training outside the school setting by post-secondary institutions, non-government organisations, professional bodies and technology enterprises. Due to the growing concern worldwide about low interest among students in pursuing STEM (Science, Technology, Engineering, and Mathematics) careers, cultivating and boosting STEM career interest has been an emerging research focus worldwide. Although numerous studies have explored its critical contributors, little research has examined the effectiveness of comprehensive interventions such as “Studying with STEM professional”. This study aims to examine the effect on gifted students’ career interest during their participation in an off-school support programme designed and supervised by a team of STEM educators and STEM professionals from a university. Gifted students were provided opportunities and tasks to experience STEM career topics that are not included in the school syllabus, and to experience how to think and work like a STEM professional in their learning. Participants involved 40 primary school students joining the intervention programme outside the normal school setting. Research methods included adopting the STEM career interest survey and drawing tasks supplemented with writing before and after the programme, as well as interviews before the end of the programme. The semi-structured interviews focused on students’ views regarding STEM professionals; what’s it like to learn with a STEM professional; what’s it like to work and think like a STEM professional; and students’ STEM identity and career interest. The changes in gifted students’ STEM career interest and its well-recognised significant contributors, for example, STEM stereotypes, self-efficacy for STEM activities, and STEM outcome expectation, were collectively examined from the pre- and post-survey using T-test. Thematic analysis was conducted for the interview records to explore how studying with STEM professional intervention can help students understand STEM careers; build STEM identity; as well as how to think and work like a STEM professional. Results indicated a significant difference in STEM career interest before and after the intervention. The influencing mechanism was also identified from the measurement of the related contributors and the analysis of drawings and interviews. The potential of off-school support programme supervised by STEM educators and professionals to develop gifted students’ STEM career interest is argued to be further unleashed in future research and practice.

Keywords: gifted students, STEM career, STEM education, STEM professionals

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Siddarth Kannan

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Objectives: Deep Brain Stimulation (DBS) and Motor Cortex stimulation (MCS) are innovative interventions in order to treat various neuropathic pain disorders such as post-stroke pain. While each treatment has a varying degree of success in managing pain, comparative analysis has not yet been performed, and the success rates of these techniques using validated, objective pain scores have not been synthesised. The aim of this study was to compare the effect of pain relief offered by MCS and DBS on patients with post-stroke pain and to assess if either of these procedures offered better results. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines (PROSPEROID CRD42021277542). Three databases were searched, and articles published from 2000 to June 2023 were included (last search date 25 June 2023). Meta-analysis was performed using random effects models. We evaluated the performance of DBS or MCS by assessing studies that reported pain relief using the Visual Analogue Scale (VAS). Data analysis of descriptive statistics was performed using SPSS (Version 27; IBM; Armonk; NY; USA). R statistics (Rstudio Version 4.0.1) was used to perform meta-analysis. Results: Of the 478 articles identified, 27 were included in the analysis (232 patients- 117 DBS & 115 MCS). The pooled number of patients who improved after DBS was 0.68 (95% CI, 0.57-0.77, I2=36%). The pooled number of patients who improved after MCS was 0.72 (95% CI, 0.62-0.80, I2=59%). Further sensitivity analysis was done to include only studies with a minimum of 5 patients in order to assess if there was any impact on the overall results. Nine studies each for DBS and MCS met these criteria. There seemed to be no significant difference in results. Conclusions: The use of surgical interventions such as DBS and MCS is an upcoming field for the treatment of post-stroke pain, with limited studies exploring and comparing these two techniques. While our study shows that MCS might be a slightly better treatment option, further research would need to be done in order to determine the appropriate surgical intervention for post-stroke pain.

Keywords: post-stroke pain, deep brain stimulation, motor cortex stimulation, pain relief

Procedia PDF Downloads 142

Authors: Palaniraj Rama Raj, Himeesh Kumar, Paul Adler

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Purpose: To investigate the effect of ultrasound energy, expressed as cumulative dissipated energy (CDE), on short and long-term outcomes after uncomplicated cataract surgery by phacoemulsification. Methods: In this single-surgeon, two-center retrospective study, non-glaucomatous participants who underwent uncomplicated cataract surgery were investigated. Best-corrected visual acuity (BCVA) and intraocular pressure (IOP) were measured at 3 separate time points: pre-operative, Day 1 and ≥1 month. Anterior chamber (AC) inflammation and corneal odema (CO) were assessed at 2 separate time points: Pre-operative and Day 1. Short-term changes (Day 1) in BCVA, IOP, AC and CO and long-term changes (≥1 month) in BCVA and IOP were evaluated as a function of CDE using a multivariate multiple linear regression model, adjusting for age, gender, cataract type and grade, preoperative IOP, preoperative BCVA and duration of long-term follow-up. Results: 110 eyes from 97 non-glaucomatous participants were analysed. 60 (54.55%) were female and 50 (45.45%) were male. The mean (±SD) age was 73.40 (±10.96) years. Higher CDE counts were strongly associated with higher grades of sclerotic nuclear cataracts (p <0.001) and posterior subcapsular cataracts (p <0.036). There was no significant association between CDE counts and cortical cataracts. CDE counts also had a positive correlation with Day 1 CO (p <0.001). There was no correlation between CDE counts and Day 1 AC inflammation. Short-term and long-term changes in post-operative IOP did not demonstrate significant associations with CDE counts (all p >0.05). Though there was no significant correlation between CDE counts and short-term changes in BCVA, higher CDE counts were strongly associated with greater improvements in long-term BCVA (p = 0.011). Conclusion: Though higher CDE counts were strongly associated with higher grades of Day 1 postoperative CO, there appeared to be no detriment to long-term BCVA. Correspondingly, the strong positive correlation between CDE counts and long-term BCVA was likely reflective of the greater severity of underlying cataract type and grade. CDE counts were not associated with short-term or long-term postoperative changes in IOP.

Keywords: cataract surgery, phacoemulsification, cumulative dissipated energy, CDE, surgical outcomes

Procedia PDF Downloads 185

Authors: Ruchi Agarwal, Jake Ansell

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Austerity impacts on all aspects of society. Companies into the future will have to be more capable of dealing with the risks they face. Enterprise Risk Management (ERM) has widely been accepted in recent years as an approach to manage risks within businesses. ERM attempts to tackle risk holistically with gains from opportunities in a managing risk and reduction in the risk of failure. The paper reviews merits and demerits of approaches to risk management in regard to antifragility. A qualitative study has investigated current practices and the problems with ERM implementation by interviewing over 25 chief risk officers and senior management. The findings indicate the gap in ERM description, understanding, and implementation. The paper suggests risk learning and expertise knowledge supports development of effective enterprise risk management by designing systems with inherent resilience.

Keywords: risk management, interviews, antifragility, failure

Procedia PDF Downloads 566

Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

Procedia PDF Downloads 490

Authors: Ashik Sarder

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Bangladesh is a disaster-prone and one of the most vulnerable countries to climate change. The country has a long coastal area which is frequently being affected by several types of natural disasters due to climate change. The disasters have impacts on the life and livelihood of different natural resources depending on communities living in the coastal areas. The Malo is a Hindu religious traditional fishing community living at Sarafpur Union of Dumuria Upazila of Khulna district of south-west coastal Bangladesh. Fishing is the only means of their livelihood and the community has been engaged in fishing practices inherently in rivers, estuaries, and sea for more than 300 years. and they are totally dependent on this traditional occupation. But, in recent year’s climate change has negative impacts on their only livelihood option. The study aims to examine the impacts of climate change on the livelihood of Malo fishing community in south-west coastal Bangladesh, identify the adaptation strategies undertaken and practiced by Malo fishing community to cope with climate change and sustain their livelihood and explore the changing adaptation strategies undertaken by Malo fishing community and others. The study has been conducted from both qualitative and quantitative perspectives. Data has been collected from both primary and secondary sources. The primary data has been collected in the participatory observation approach following both qualitative and quantitative method. The primary source of data includes village census, face-to-face interview and in-depth case studies using structured questionnaire. The secondary source of the literature includes different national and international documents, policy papers, books and articles; related websites and peer-viewed documents on climate change, vulnerability, adaptation, livelihood, and fisheries. The study has identified different practices of adaption to climate change by Malo fishing community and others in the selected area. Three types of adaption practices have been identified. Firstly, the indigenous adaptation practices by Malo fishing community to cope with climate change have been identified. These identified adaptation practices by Malo fishing community include; ensuring drinking water and sanitation facilities, planting trees to tackle impacts of cyclone, excavating dumps to preserve the valuable assets, growing vegetables and rearing domestic livestock to earn surplus money, taking loans for ensuring continuation of present livelihood and migrating to near city or towns for better livelihood options. Secondly, adaptation initiatives undertaken by the government have provided limited facility to this vulnerable fishing community and made them benefited. And thirdly, some adaptation initiatives commenced by few non-government and community-based organizations have also made the Malo fishing community as beneficiaries. The study has suggested recommendations for Malo fishing community to overcome the challenges and impacts of climate change for retaining their traditional fishing livelihood. The accumulated recommendations would be very useful for the researchers, academicians, policy-makers of Government and non-government organizations to conduct more researches and take initiatives for Malo fishing community to make them more capable to sustain their fishing livelihood.

Keywords: climate change, livelihood, adaptation, anthropology, vulnerability

Procedia PDF Downloads 121

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

Procedia PDF Downloads 265