Search results for: vision based technology

Authors: Olaje Monday Olaje

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Science and technology has been prove to be the back bone for economic development of any country, and for Nigeria, it has more critical role to play. This paper examines the importance of science and technology education for national development and self dependence for Nigerian citizens. A historical overview of the interconnectivity of science and technology and self dependence is heighted. The current situation and challenges facing science and technology education are also highlighted to bring out the theoretical importance of science and technology education for self dependence which actually has not been practically achieved. Recommendations are also made at the of the study so as to skill acquisition through science and technology for self dependence.

Keywords: acquisition, education, self-dependence, science, technology

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Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

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One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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Authors: Nurulnadwan Aziz, Ariffin Abdul Mutalib, Siti Mahfuzah Sarif

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This paper reports an ongoing project regarding the development of Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) learners. Having developed the intended model, it has to be validated prior to producing it as guidance for the developers to develop an AC4LV. This study requires two phases of validation process which are through expert review and prototyping method. This paper presents a part of the validation process which is findings from experts review on Conceptual Design Model of AC4LV which has been carried out through a questionnaire. Results from 12 international and local experts from various respectable fields in Human-Computer Interaction (HCI) were discussed and justified. In a nutshell, reviewed Conceptual Design Model of AC4LV was formed. Future works of this study are to validate the reviewed model through prototyping method prior to testing it to the targeted users.

Keywords: assistive courseware, conceptual design model, expert review, low vision learners

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Authors: Lai Wenfang

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

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

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Authors: A. Al Hinai, H. Jayasuriya, H. Kotagama

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Most Gulf Cooperation Council (GCC) countries with oil-based economy like Oman are looking for other potential revenue generation options as the crude oil price is regularly fluctuating due to changing geopolitical environment. Oman has advantage of possessing world-heritage nature tourism hotspots around the country and the government is making investments and strategies to uplift the tourism industry following Oman Vision 2040 strategies. Oman’s agriculture is not significantly contributing to the economy, but possesses specific and diversified arid cropping systems. Oman has modern farms; nevertheless some of the agricultural production activities are done with cultural practices and styles that would be attractive to tourists. The aim of this paper is to investigate the potentials for promoting agritourism industry in Oman; recognize potential sites, commodities and activities, and predict potential revenue generation as a projection from that of the tourism sector. Moreover, the study enables to foresee possible auxiliary advantages of agritourism such as, empowerment of women and youth, enhancement in the value-addition industry for agricultural produce through technology transfer and capacity building, and producing export quality products. Agritourism could increase employability, empowerment of women and youth, improve value-addition industry and export-oriented agribusiness. These efforts including provision of necessary technology-transfer and capacity-building should be rendered by the collaboration of academic institutions, relevant ministries and other public and private sector stakeholders.

Keywords: agritourism, nature-based tourism, potentials, revenue generation, value addition

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Authors: Wafeek Mohamed Ibrahim Mohamed

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In the era of globalization and openness informational. Anyone who thinks about innovation in the earth population in Islam in our contemporary reality, he will find that it is not destined to its civilized extension to last. The purpose of the research is a trial to reach a realistic vision for creative, innovative and intellectual thought for the earth population in Islam as an instrument to Confrontation and observe the changes that have affected in the architecture of the land during different eras. Through knowing the controls of the ruling legitimacy(that served as definitions and laws which formulate its features) and using customs, traditions, and conventions as a telescope for the earth population in Islam, It explained the impact of them on features of creative formation for the architecture of the land in our contemporary reality. The study shows a modern vision to identify innovation in the earth population in Islam. As well as reformulating its mental image and monitoring its changes in Islamic heritage cities. This will be done through a two main branches: firstly, set forth a theory represented in studying creative concepts which formulate the population of the earth in Islam. Such as initiative and responsibility for reviving the dead land, the lane [alley] as formation unit and social solidarity,… Etc.. The second branch is preparing a practical, critical vision for innovative conceptual thought for the architecture of the land of Islam, through studying the development of a traditional Islamic city., The conceptual thought of making the birth festival ["Al-Refaee"] and its emulation for governing roles in the traditional city building. The research concludes The necessity of forming the suggested a creative vision for identifying how to re-form the conceptual for our contemporary population of the earth. It poses an important question which is how to return to creativity in the architecture of the land of Islam in our built environments.

Keywords: innovation and creation, architecture, the land in Islam, criticism of design

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Authors: Jimmy L. Caldoza, Erlito M. Albina

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Information Systems are increasingly being used to monitor and assess government projects as well as improve transparency and combat corruption. With reference to existing information systems relevant to monitoring and evaluation systems adopted by various government agencies from other countries, this research paper aims to help the Philippine government, particularly the Department of Agriculture, in assessing the impact of their programs and projects on their target beneficiaries through the development of the web-based Monitoring and Evaluation Information System with the application of a short messaging system (sms) technology.

Keywords: monitoring and evaluation system, web-based information system, short messaging system technology, database structure and management

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Authors: Yaser Mohammed Altameemi

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This research looks at the representation of the social media for the Saudi Government decrees regarding the developmental projects of the Saudi 2030 vision. The paper analyses a television interview with the Crown Prince Mohammed Bin Salman who talks about the progress of the Saudi vision of 2030, and how the government had acted as response to the COVID-19 pandemic. The interview was on 28/4/2021. The paper analyses the tweets on Twitter that cover the interview for the purpose of investigating the development of concepts and meanings regarding the Saudi peoples’ orientations towards the Saudi projects. The data include all related tweets from the day of the interview and the following seven days after the interview. The finding of the collocation analysis suggests that nationalism notion is explicitly expressed by users in Twitter. The main finding of this paper suggests the importance of further analyses for the concordance lines. However, the collocation network suggests that there is a clear highlight for nationalism.

Keywords: social media, twitter, political interview, prince Mohammed Bin Salman, Saudi vision 2030

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Authors: Reta

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Coffee is widely consumed not only because of its typical taste, but coffee has antioxidant properties because of its polyphenols, and it stimulates brain's performance. The main problem with the consumption of coffee is its content of caffeine. Caffeine, when consumed in excess, can increase muscle tension, stimulate the heart, and increase the secretion of gastric acid. In this research, we applied ohmic-based fermentation technology, which is specially designed to mimic the stomach. We used Arabica coffee, which although cheaper than Luwak coffee, has high acidity, which needs to be reduced. Hence, we applied the ohmic technology, varied the time and temperature of the process and measured the total acidity of the coffee to determine optimum fermentation conditions. Results revealed total acidity of the coffee varied with fermentation conditions; 0.32% at 400C and 12 hr, and 0.52% at 400C and 6 hr. The longer the fermentation, the lower was the acidity. The acidity of the mongoose-fermented (natural fermentation) beans was 2.34%, which is substantially higher than the acidity of the ohmic samples. Ohmic-based fermentation technology, therefore, offers improvements in coffee quality, and this is discussed to highlight the potential of ohmic technology in coffee processing.

Keywords: ohmic technology, fermentation, coffee quality, Arabica coffee

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: P. P. S. Sifolo, P. Tladi, J. Maimela

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This article investigates technology used by Tshwane residents intended for tourism purposes. The aim is to contribute information to the Tshwane interested parties for planning and management concerning technology within the tourism sector. This study identified the types of tourist related technologies used by the Tshwane residents, be it for business purposes or personal use. The study connected the exploitation of technology for tourism purposes through unpacking the tourism sector as it utilizes technology. Quantitative research methodology was used whereby self-completed questionnaires were chosen as research instruments. The research study carried out a search for knowledge on technology for tourism and the Tshwane residents; however the study revealed that technology has certainly imprinted tourism massively because of its effectiveness and efficiency. Technology has assisted tourism businesses stay abreast of competition with ICT and because of that, SA is on the map as one the economically performing countries in Africa. Moreover, technology and tourism make a meaningful impact on job creation and Gross Domestic Product (GDP).

Keywords: tourism, information and communication technology, Tshwane residents, technology for tourism

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Laura Niño Cáceres, Daisy Yoo, Caroline Hummels

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COVID-19 accelerated digital healthcare technology usage in many countries, such as Colombia, whose digital healthcare vision and projects are proof of this. However, with a significant cultural indigenous and Afro-Colombian heritage, only some parts of the country are willing to follow the proposed digital Western approach to health. Our paper presents the national healthcare system’s digital narrative, which we contrast with the micro-narrative of an Afro-Colombian ethnomedicine unit in Bogota called Kilombo Yumma. This ethnomedical unit is building its mobile app to safeguard and represent its ancestral medicine practices in local and national healthcare information systems. Kilombo Yumma is keen on promoting their beliefs and practices, which have been passed on through oral traditions and currently exist in the hands of a few older women. We unraveled their ambition, core beliefs, and practices through asset-based design. These assets outlined pluriversal and decolonizing forms of digital healthcare to increase social justice and connect Western and ancestral medicine digital opportunities through HCI.

Keywords: asset-based design, mobile app, decolonizing HCI, Afro-Colombian ancestral medicine

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Authors: Maryam Amiri, Ali Rajabzade, Gholam Reza Goudarzi, Reza Heidari

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Growth of technology and environmental changes are so fast and therefore, companies and industries have much tendency to do activities of R&D for active participation in the market and achievement to a competitive advantages. Aviation industry and its subdivisions have high level technology and play a special role in economic and social development of countries. So, in the aviation industry for getting new technologies and competing with other countries aviation industry, there is a requirement for capability in R&D. Considering of appropriate R&D strategy is supportive that day technologies of the world can be achieved. Biofuel technology is one of the newest technologies that has allocated discussion of the world in aviation industry to itself. The purpose of this research has been formulation of R&D strategy of biofuel technology in aviation industry of Iran. After reviewing of the theoretical foundations of the methods and R&D strategies, finally we classified R&D strategies in four main categories as follows: internal R&D, collaboration R&D, out sourcing R&D and in-house R&D. After a review of R&D strategies, a model for formulation of R&D strategy with the aim of developing biofuel technology in aviation industry in Iran was offered. With regard to the requirements and aracteristics of industry and technology in the model, we presented an integrated approach to R&D. Based on the techniques of decision making and analyzing of structured expert opinion, 4 R&D strategies for different scenarios and with the aim of developing biofuel technology in aviation industry in Iran were recommended. In this research, based on the common features of the implementation process of R&D, a logical classification of these methods are presented as R&D strategies. Then, R&D strategies and their characteristics was developed according to the experts. In the end, we introduced a model to consider the role of aviation industry and biofuel technology in R&D strategies. And lastly, for conditions and various scenarios of the aviation industry, we have formulated a specific R&D strategy.

Keywords: aviation industry, biofuel technology, R&D, R&D strategy

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Authors: M. Maleki Sadabad, A. Pointing, N. Marashi

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With respect to the role and increasing importance of technology for countries development, in recent decades technology development has paid attention in a systematic form. Nowadays the markets face with highly complicated and competitive conditions in foreign markets, therefore, evaluation and selection of technology effectiveness and also formulating technology strategy have changed into a vital subject for some organizations. The study introduces the standards of empowerment evaluation and technology attractiveness especially strategic technologies which explain the way of technology evaluation, selection and finally formulating suitable technology strategy in the field of drilling in South Azadegan oil field. The study firstly identifies the key challenges of oil fields in order to evaluate the technologies in field of drilling in South Azadegan oil field through an interview with the experts of industry and then they have been prioritised. In the following, the existing and new technologies were identified to solve the challenges of South Azadegan oil field. In order to explore the ability, availability, and attractiveness of every technology, a questionnaire based on Julie indices has been designed and distributed among the industry elites. After determining the score of ability, availability and attractiveness, every technology which has been obtained by the average of expert’s ideas, the technology package has been introduced by Morin’s model. The matrix includes four areas which will follow the especial strategy. Finally, by analysing the above matrix, the technology options have been suggested in order to select and invest.

Keywords: technology, technology identification, drilling technologies, technology capability

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Authors: Arne Hitzmann, Philipp Wentscher, Alexander Gabel, Reinhard Gerndt

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Autonomous mobile robots can be found in a wide field of applications. Their types range from household robots over workshop robots to autonomous cars and many more. All of them undergo a number of testing steps during development, production and maintenance. This paper describes an approach to improve testing of robot behavior. It was inspired by the RoboCup @work competition that itself reflects a robotics benchmark for industrial robotics. There, scaled down versions of mobile industrial robots have to navigate through a workshop-like environment or operation area and have to perform tasks of manipulating and transporting work pieces. This paper will introduce an approach of automated vision-based testing of the behavior of the so called youBot robot, which is the most widely used robot platform in the RoboCup @work competition. The proposed system allows automated testing of multiple tries of the robot to perform a specific missions and it allows for the flexibility of the robot, e.g. selecting different paths between two tasks within a mission. The approach is based on a multi-camera setup using, off the shelf cameras and optical markers. It has been applied for test-driven development (TDD) and maintenance-like verification of the robot behavior and performance.

Keywords: supervisory control, testing, markers, mono vision, automation

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Joao Fialho

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The mathematical modelling of idiopathic scoliosis has been studied throughout the years. The models presented on those papers are based on the orthotic stabilization of the idiopathic scoliosis, which are based on a transversal force being applied to the human spine on a continuous form. When considering the ATT (Antalgic-Trak Technology) device, the existent models cannot be used, as the type of forces applied are no longer transversal nor applied in a continuous manner. In this device, vertical traction is applied. In this study we propose to model the idiopathic scoliosis, using the ATT (Antalgic-Trak Technology) device, and with the parameters obtained from the mathematical modeling, set up a case-by-case individualized therapy plan, for each patient.

Keywords: idiopathic scoliosis, mathematical modelling, human spine, Antalgic-Trak technology

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Authors: Sunusi Tijjani

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Information and communication technology is an indispensable tool in the performance of office technology managers. Today's offices are automated and equipped with modern office machines that enhances and improve the work of office managers. However, today's office technology managers can process, evaluate, manage and communicate all forms of information using technological devices. Information and Communication Technology is viewed as the process of processing, storing ad dissemination information while office technology managers are trained professional who can effectively operate modern office machines, perform administrative duties and attend meetings to take dawn minute of meetings. This paper examines the importance of information and communication technology toward enhancing the work of office managers. It also stresses the importance of information and communication technology toward proper and accurate record management.

Keywords: communication, information, technology, managers

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Authors: Augustine Ndudi Egere, Shehu Adamu, Esther Ishaya Solomon

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As internet accessibility and smartphones continue to increase in Nigeria, Africa’s most populous country, social media platforms have become ubiquitous, causing students of 18-25 age brackets to spend more time on social media. The research investigated the impact of prolonged social media use on the physical health of students, with a specific focus on computer vision syndrome, hand pain, headaches and mental status. The study adopted a mixed-methods approach combining quantitative surveys to gather statistical data on usage patterns and symptoms, along with qualitative interviews into the experiences and perceptions of medical practitioners concerning cases under study within the geopolitical region. The result was analyzed using Regression analysis. It was observed that there is a significant correlation between social media usage by the students in the study age bracket concerning computer vision syndrome, hand pain, headache and general mental status. The research concluded by providing valuable insights into potential interventions and strategies to mitigate the adverse effects of excessive social media use on student well-being and recommends, among others, that educational institutions, parents, and students themselves collaborate to implement strategies aimed at promoting responsible and balanced use of social media.

Keywords: social media, student health, computer vision syndrome, hand pain, headaches, mental staus

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Yu Qin

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In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

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Authors: Aikaterini Tavoulari, Michael Proulx, Karin Petrini

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Objective: This study aims to explore the unique challenges faced by young individuals with vision impairment (VI) during key life transitions, utilizing a community-based participatory research (CBPR) approach to identify limitations and positive aspects of existing support systems, with a focus on accessibility and diversity. Design: The study employs a qualitative CBPR design, engaging young participants with VI through online and in-person working groups over six months, prioritizing their active involvement and diverse perspectives. Methods: Twenty-one young individuals with VI from across the UK and with different VI conditions were recruited to participate in the study via a climbing and virtual reality event and stakeholders’ support. Data collection methods included open discussions, forum exchanges, and qualitative questionnaires. The data were analyzed with NVivo using inductive thematic analysis to identify key themes and patterns related to the challenges and experiences of life transitions for this diverse population. Results: The analysis revealed barriers to accessibility, such as assumptions about what a person with VI can do, inaccessibility to material, noisy environments, and insufficient training with assistive technologies. Enablers included guidance from diverse professionals and peers, multisensory approaches (beyond tactile), and peer collaborations. This study underscores the need for developing accessible and tailored strategies together with these young people to address the specific needs of this diverse population during critical life transitions (e.g., to independent living, employment and higher education). Conclusion: Engaging and co-designing effective approaches and tools with young people with VI is key to tackling the specific accessibility barriers they encounter. These approaches should be targeted at different transitional periods of their life journey, promoting diversity and inclusion.

Keywords: vision impairement, life transitions, qualitative research, community-based participatory design, accessibility

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Authors: Bersufekad Wubie

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Introduction: Near visual impairment is presenting near visual acuity of the eye worse than N6 at a 40 cm distance. Teachers' regular duties, such as reading books, writing on the blackboard, and recognizing students' faces, need good near vision. If a teacher has near-visual impairment, the work output is unsatisfactory. Objective: The study was aimed to assess the prevalence and associated factors near vision impairment among school teachers at Gondar city Northwest Ethiopia, August 2022. Methods: To select 567 teachers in Gondar city schools, an institutional-based cross-sectional study design with a multistage sampling technique were used. The study was conducted in selected schools from May 1 to May 30, 2022. Trained data collectors used well-structured Amharic and English language questionnaires and ophthalmic instruments for examination. The collected data were checked for completeness and entered into Epi data version 4.6, then exported to SPSS version 26 for further analysis. A binary and multivariate logistic regression model was fitted. And associated factors of the outcome variable. Result: The prevalence of near visual impairment was 64.6%, with a confidence interval of 60.3%–68.4%. Near visual impairment was significantly associated with age >= 35 years (AOR: 4.90 at 95% CI: 3.15, 7.65), having prolonged years of teaching experience (AOR: 3.29 at 95% CI: 1.70, 4.62), having a history of ocular surgery (AOR: 1.96 at 95% CI: 1.10, 4.62), smokers (AOR: 2.21 at 95% CI: 1.22, 4.07), history of ocular trauma (AOR : 1.80 at 95%CI:1.11,3.18 and uncorrected refractive error (AOR:2.01 at 95%CI:1.13,4.03). Conclusion and recommendations: This study showed the prevalence of near vision impairment among school teachers was high, and it is not a problem of the presbyopia age group alone; it also happens at a young age. So teachers' ocular health should be well accommodated in the school's eye health.

Keywords: Gondar, near visual impairment, school, teachers

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

Abstract:

In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

Procedia PDF Downloads 68

Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

Abstract:

Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

Procedia PDF Downloads 32

Authors: Bernardo Cedano, Ahmed H. Eltom, Bob Hay, Jim Glass, Raga Ahmed

Abstract:

The deployment of smart grid devices such as smart meters and smart switches (SS) supported by a reliable and fast communications system makes automated distribution possible, and thus, provides great benefits to electric power consumers and providers alike. However, more research is needed before the full utility of smart switch data is realized. This paper presents new automated switching techniques using SS within the electric power grid. A concise background of the SS is provided, and operational examples are shown. Organization and presentation of data obtained from SS are shown in the context of the future goal of total automation of the distribution network. The description of application techniques, the examples of success with SS, and the vision outlined in this paper serve to motivate future research pertinent to disturbance analysis automation.

Keywords: disturbance automation, electric power grid, smart grid, smart switches

Procedia PDF Downloads 309

Authors: Tudor Barbu

Abstract:

An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

Procedia PDF Downloads 416