Search results for: cone of vision

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

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Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

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We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

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Authors: Naim Izet Kajtazi

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Context: Increased intracranial pressure and associated symptoms such as headache, papilledema, motor or sensory deficits, seizures, and conscious disturbance are well-known in acute CVT. However, visual loss is not commonly associated with this disease, except in the case of secondary IIH associated with it. Process: We report a case of a 40-year-old male with Behçet’s disease and cerebral venous thrombosis, and other multiple comorbidities admitted with a four-day history of increasing headache and rapidly progressive visual loss bilaterally. The neurological examination was positive for bilateral papilledema of grade 3 with light perception on the left eye and counting fingers on the right eye. Brain imaging showed old findings of cerebral venous thrombosis without any intraparenchymal lesions to suggest a flare-up of Behçet’s disease. The lumbar puncture, followed by the lumbar drain insertion, gave no benefit in headache or vision. However, he completely lost sight. The right optic nerve sheath fenestration did not result in vision improvement. The acute spinal shock complicated the lumbar drain removal due to epidural hematoma. An urgent lumbar laminectomy with hematoma evacuation undertook. Intra-operatively, the neurosurgeon noted suspicious abnormal vessels at conus medullaris with the possibility of an arteriovenous malformation. Outcome: In a few days following the spinal surgery, the patient vision started to improve. Further improvement was achieved after plasma exchange sessions followed by cyclophosphamide. In the recent follow-up in the clinic, he reported better vision, drove, and completed his Ph.D. studies. Relevance: Visual loss in patients with Behçet’s disease should always be anticipated and taken reasonable care of, ensuring that they receive well-combined immunosuppression with anticoagulation and agents to reduce intracranial pressure. This patient’s story is significant for a high disease burden and complicated hospital course by acute spinal shock due to spinal lumbar drain removal with a possible underlying spinal arteriovenous malformation.

Keywords: Behcet disease, optic neuritis, IIH, CVT

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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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: Mogens Frank Mikkelsen

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Special Relativity Theory (SRT) includes only one characteristic of light, the speed is equal to all observers, and by excluding other relevant characteristics of light, the common interpretation of SRT should be regarded as merely an approximative theory. By rethinking the iconic double light cones, a revised version of SRT can be developed. The revised concept of light cones acknowledges an asymmetry of past and future light cones and introduced a concept of the extended past to explain the predictions as something other than the future. Combining this with the concept of photon-paired events, led to the inference that Special Relativity theory can support the existence of Now.

Keywords: relativity, light cone, Minkowski, time

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Authors: Dongho Kim, Sung Choi, Kyowoong Pee, Youngsik Cho, Seungwoo Jeong, Soo-Ho Kim

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This study is about the orbital TIG welding robot system which travels on the guide rail installed on the pipe, and welds and tracks the pipe seam using the LVS (Laser Vision Sensor) joint profile data. The orbital welding robot system consists of the robot, welder, controller, and LVS. Moreover we can define the relationship between welding travel speed and wire feed speed, and we can make the linear equation using the maximum and minimum amount of weld metal. Using the linear equation we can determine the welding travel speed and the wire feed speed accurately corresponding to the area of weld captured by LVS. We applied this orbital TIG welding robot system to the stainless steel or duplex pipe on DSME (Daewoo Shipbuilding and Marine Engineering Co. Ltd.,) shipyard and the result of radiographic test is almost perfect. (Defect rate: 0.033%).

Keywords: adaptive welding, automatic welding, pipe welding, orbital welding, laser vision sensor, LVS, welding D/B

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Authors: M. J. Gibbons, A. J. Robinson

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Increasing expectations on small form factor electronics to be more compact while increasing performance has driven conventional cooling technologies to a thermal management threshold. An emerging solution to this problem is electrospray (ES) cooling. ES cooling enables two phase cooling by utilising Coulomb forces for energy efficient fluid atomization. Generated charged droplets are accelerated to the grounded target surface by the applied electric field and surrounding gravitational force. While in transit the like charged droplets enable plume dispersion and inhibit droplet coalescence. If the electric field is increased in the cone-jet regime, a subsequent increase in the plume spray angle has been shown. Droplet segregation in the spray plume has been observed, with primary droplets in the plume core and satellite droplets positioned on the periphery of the plume. This segregation is facilitated by inertial and electrostatic effects. This result has been corroborated by numerous authors. These satellite droplets are usually more densely charged and move at a lower relative velocity to that of the spray core due to the radial decay of the electric field. Previous experimental research by Gomez and Tang has shown that the number of droplets deposited on the periphery can be up to twice that of the spray core. This result has been substantiated by a numerical models derived by Wilhelm et al., Oh et al. and Yang et al. Yang et al. showed from their numerical model, that by varying the extractor potential the dispersion radius of the plume also varies proportionally. This research aims to investigate this dispersion density and the role it plays in the local heat transfer coefficient profile (h) of ES cooling. This will be carried out for different extractor – target separation heights (H2), working fluid flow rates (Q), and extractor applied potential (V2). The plume dispersion will be recorded by spraying a 25 µm thick, joule heated steel foil and by recording the thermal footprint of the ES plume using a Flir A-40 thermal imaging camera. The recorded results will then be analysed by in-house developed MATLAB code.

Keywords: electronic cooling, electrospray, electrospray plume dispersion, spray cooling

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Authors: Ferran Paulí Pla, Pere Palacín Farré, Albert Fornells Herrera, Pol Toldrà Fernández

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Poor image acquisition is limiting the promising growth of industrial vision in food control. In recent years, the food industry has witnessed a significant increase in the implementation of automation in quality control through artificial vision, a trend that continues to grow. During the packaging process, some defects may appear, compromising the proper sealing of the products and diminishing their shelf life, sanitary conditions and overall properties. While failure to detect a defective product leads to major losses, food producers also aim to minimize over-rejection to avoid unnecessary waste. Thus, accuracy in the evaluation of the products is crucial, and, given the large production volumes, even small improvements have a significant impact. Recently, efforts have been focused on maximizing the performance of classification neural networks; nevertheless, their performance is limited by the quality of the input data. Monochrome linear backlight systems are most commonly used for online inspections of food packaging thermo-sealing zones. These simple acquisition systems fit the high cadence of the production lines imposed by the market demand. Nevertheless, they provide a limited amount of data, which negatively impacts classification algorithm training. A desired situation would be one where data quality is maximized in terms of obtaining the key information to detect defects while maintaining a fast working pace. This work presents a backlight hyperspectral imaging system designed and implemented replicating an industrial environment to better understand the relationship between visual data quality and spectral illumination range for a variety of packed food products. Furthermore, results led to the identification of advantageous spectral bands that significantly enhance image quality, providing clearer detection of defects.

Keywords: artificial vision, food packaging, hyperspectral imaging, image acquisition, quality control

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Authors: F. B. Masok, S. S Songdeg, R. R. Dawam

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Vision is an important process for learning and communication as man depends greatly on vision to sense his environment. Prevalence and variation of refractive errors conducted between December 2010 and May 2011 in Jos, revealed that 735 (77.50%) out 950 subjects examined for refractive error had various refractive errors. Myopia was observed in 373 (49.79%) of the subjects, the error in the right eyes was 263 (55.60%) while the error in the left was 210(44.39%). The mean myopic error was found to be -1.54± 3.32. Hyperopia was observed in 385 (40.53%) of the sampled population comprising 203(52.73%) of the right eyes and 182(47.27%). The mean hyperopic error was found to be +1.74± 3.13. Astigmatism accounted for 359 (38.84%) of the subjects, out of which 193(53.76%) were in the right eyes while 168(46.79%) were in the left eyes. Presbyopia was found in 404(42.53%) of the subjects, of this figure, 164(40.59%) were in the right eyes while 240(59.41%) were in left eyes. The number of right eyes and left eyes with refractive errors was observed in some age groups to increase with age and later had its peak within 60 – 69 age groups. This pattern of refractive errors could be attributed to exposure to various forms of light particularly the ultraviolet rays (e.g rays from television and computer screen). There was no remarkable differences between the mean Myopic error and mean Hyperopic error in the right eyes and in the left eyes which suggest the right eye and the left eye are similar.

Keywords: left eye, refractive errors, right eye, variation

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Authors: Keunho Park, Sunghwan Jeong

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The 4th Industrial Revolution, the next-generation industrial revolution, which is made up of convergence of information and communication technology (ICT), is no exception to the livestock industry, and various studies are being conducted to apply the livestock smart farm. In order to monitor livestock using sensors, it is necessary to drill holes in the organs such as the nose, ears, and even the stomach of the livestock to wear or insert the sensor into the livestock. This increases the stress of livestock, which in turn lowers the quality of livestock products or raises the issue of animal ethics, which has become a major issue in recent years. In this paper, we conducted a study to monitor livestock activity based on vision technology, effectively monitoring livestock activity without increasing animal stress and violating animal ethics. The movement rate was calculated based on the difference images between the frames, and the livestock activity was evaluated. As a result, the average F1-score was 96.67.

Keywords: barn monitoring, livestock, machine vision, smart farm

Procedia PDF Downloads 123

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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Over the years,increased demands on railways, the emergence of high-speed trains and heavy axle loads, ageing, and deterioration of the existing tracks, is imposing costly maintenance actions on the railway sector. The need for developing a fast andcost-efficient non-destructive assessment method for the structural evaluation of railway tracksis therefore critically important. The layer modulus is the main parameter used in the structural design and evaluation of the railway track substructure (foundation). Among many recently developed NDTs, Falling Weight Deflectometer (FWD) test, widely used in pavement evaluation, has shown promising results for railway track substructure monitoring. The surface deflection data collected by FWD are used to estimate the modulus of substructure layers through the back-analysis technique. Although there are different commerciallyavailableback-analysis programs are used for pavement applications, there are onlya limited number of research-based techniques have been so far developed for railway track evaluation. In this paper, the suitability, accuracy, and reliability of the BAKFAAsoftware are investigated. The main rationale for selecting BAKFAA as it has a relatively straightforward user interfacethat is freely available and widely used in highway and airport pavement evaluation. As part of the study, a finite element (FE) model of a railway track section near Leominsterstation, Herefordshire, UK subjected to the FWD test, was developed and validated against available field data. Then, a virtual experimental database (including 218 sets of FWD testing data) was generated using theFE model and employed as the measured database for the BAKFAA software. This database was generated considering various layers’ moduli for each layer of track substructure over a predefined range. The BAKFAA predictions were compared against the cone penetration test (CPT) data (available from literature; conducted near to Leominster station same section as the FWD was performed). The results reveal that BAKFAA overestimatesthe layers’ moduli of each substructure layer. To adjust the BAKFA with the CPT data, this study introduces a correlation model to make the BAKFAA applicable in railway applications.

Keywords: back-analysis, bakfaa, railway track substructure, falling weight deflectometer (FWD), cone penetration test (CPT)

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 224

Authors: Hung Nguyen, Norma Harrison

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This paper examines the role supply chain dependence as contingency factors which affect the effectiveness of different critical factors (in terms trust, information exchange and shared culture) in delivering supply chain satisfaction and financial performance. Using the data of 468 manufacturing firms in the Global Manufacturing Research Group, this study shows that supply chain dependence strengthens the positive relationship between shared culture & vision and supply chain satisfaction while dampens the relationship between trust and satisfaction. The study also demonstrates the direct positive effect of satisfaction on financial performance. Supply chain managers were advised to emphasize on the alignments of common understanding, codes, languages, common shared vision and similar cultures.

Keywords: information exchange, shared culture, satisfaction, supply chain dependence

Procedia PDF Downloads 383

Authors: Aikaterini Tavoulari

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This research aims to address the types of repetitive behaviours (RBs) observed by adults in children with vision impairment (VI) or autism spectrum disorder (ASD), the explanations the adults employ to interpret these behaviours, and the impact RBs have on the child, the caregiver, the professional and society. The underlying reason for this is an attempt to discover any potential differences between two different disabilities in a comparative fashion. The study is based on the interpretivism paradigm and follows a qualitative approach. A comparative case study design based on the ecological systems theory (EST) is adopted. Thirty-five caregivers and accredited professionals were recruited (17 for the VI group, out of whom 8 were caregivers and 9 were professionals, and 18 for the ASD group, out of whom 9 were caregivers and 9 were professionals). Following the completion of a pilot study, all participants were interviewed regarding one specific child – their own child/student – via semi-structured interviews. During the interviews, the researcher used a research diary as a methodological tool and video elicitation as a facilitation tool. A cross-case analysis was conducted, and data were analysed according to the method of thematic analysis. A link has been indicated between VI and ASD, which concerns perceptions about the socially constructed manner in which an RB is perceived. ASD is perceived by the participants as a disability with challenging characteristics, such as an RB. The ASD group perceived RB as linked to ableism, social stigmatisation, and taboo, in contrast to VI, where the existence of RB seems to be a consequence of sensory loss. Bi-directionality of EST seems to have been lost completely, and the macrosystem seems to drive the interactions between the ecological systems.

Keywords: ableism, social stigma, disability, repetitive behaviour, vision impairment, autism spectrum disorder, perceptions

Procedia PDF Downloads 90

Authors: Michael Leontiev, Danil Zhilikov, Dmitry Lobanov, Lenar Klimov, Vyacheslav Chertan, Daniel Bobrov, Vladislav Maslov, Vasilii Vologdin, Ksenia Balabaeva

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Pharmaceutical manufacturing is a complex process, where each stage requires a high level of safety and sterility. Personal Protective Equipment (PPE) is used for this purpose. Despite all the measures of control, the human factor (improper PPE wearing) causes numerous losses to human health and material property. This research proposes a solid computer vision system for ensuring safety in pharmaceutical laboratories. For this, we have tested a wide range of state-of-the-art object detection methods. Composing previously obtained results in this sphere with our own approach to this problem, we have reached a high accuracy ([email protected]) ranging from 0.77 up to 0.98 in detecting all the elements of a common set of PPE used in pharmaceutical laboratories. Our system is a step towards safe medicine production.

Keywords: sterility and safety in pharmaceutical development, personal protective equipment, computer vision, object detection, monitoring in pharmaceutical development, PPE

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Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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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

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Authors: Edwin Foo, Woei Wen, Lui, Meijun Zhao, Shigeru Kuchii, Chin Sai Wong, Chung Sern Goh, Yi Hao He

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This presentation presents an elderly care and assistive social robot development work. We named this robot JOS and he is restricted to table top operation. JOS is designed to have a maximum volume of 3600 cm3 with its base restricted to 250 mm and his mission is to provide companion, assist and help the elderly. In order for JOS to accomplish his mission, he will be equipped with perception, reaction and cognition capability. His appearance will be not human like but more towards cute and approachable type. JOS will also be designed to be neutral gender. However, the robot will still have eyes, eyelid and a mouth. For his eyes and eyelids, they will be built entirely with Robotis Dynamixel AX18 motor. To realize this complex task, JOS will be also be equipped with micro-phone array, vision camera and Intel i5 NUC computer and a powered by a 12 V lithium battery that will be self-charging. His face is constructed using 1 motor each for the eyelid, 2 motors for the eyeballs, 3 motors for the neck mechanism and 1 motor for the lips movement. The vision senor will be house on JOS forehead and the microphone array will be somewhere below the mouth. For the vision system, Omron latest OKAO vision sensor is used. It is a compact and versatile sensor that is only 60mm by 40mm in size and operates with only 5V supply. In addition, OKAO vision sensor is capable of identifying the user and recognizing the expression of the user. With these functions, JOS is able to track and identify the user. If he cannot recognize the user, JOS will ask the user if he would want him to remember the user. If yes, JOS will store the user information together with the capture face image into a database. This will allow JOS to recognize the user the next time the user is with JOS. In addition, JOS is also able to interpret the mood of the user through the facial expression of the user. This will allow the robot to understand the user mood and behavior and react according. Machine learning will be later incorporated to learn the behavior of the user so as to understand the mood of the user and requirement better. For the speech system, Microsoft speech and grammar engine is used for the speech recognition. In order to use the speech engine, we need to build up a speech grammar database that captures the commonly used words by the elderly. This database is built from research journals and literature on elderly speech and also interviewing elderly what do they want to robot to assist them with. Using the result from the interview and research from journal, we are able to derive a set of common words the elderly frequently used to request for the help. It is from this set that we build up our grammar database. In situation where there is more than one person near JOS, he is able to identify the person who is talking to him through an in-house developed microphone array structure. In order to make the robot more interacting, we have also included the capability for the robot to express his emotion to the user through the facial expressions by changing the position and movement of the eyelids and mouth. All robot emotions will be in response to the user mood and request. Lastly, we are expecting to complete this phase of project and test it with elderly and also delirium patient by Feb 2015.

Keywords: social robot, vision, elderly care, machine learning

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

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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

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Authors: Ramesh Kumar Behera, Md. Izhar Hassan

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Accident investigation and analysis are useful to identify deficiencies in plant, process, and management practices and formulate preventive strategies for injury elimination. In India and other parts of the world, industrial accidents are investigated to know the causes and also to fulfill legal compliances. However, findings of investigation are seldom used appropriately to strengthen Occupational Safety and Health (OSH) in expected lines. The mineral rich state of Odisha in eastern coast of India; known as a hub for Iron and Steel industries, witnessed frequent accidents during 2005-2009. This article based on study of 982 fatal ‘factory-accidents’ occurred in Odisha during the period 2001-2016, discusses the ‘turnaround-story’ resulting in reduction of fatal accident from 122 in 2009 to 45 in 2016. This paper examines various factors causing incidents; accident pattern in steel and chemical sector; role of climate and harsh weather conditions on accident causation. Software such as R, SQL, MS-Excel and Tableau were used for analysis of data. It is found that maximum fatality is caused due to ‘fall from height’ (24%); steel industries are relatively more accident prone; harsh weather conditions of summer increase chances of accident by 20%. Further, the study suggests that enforcement of partial work-restriction around lunch time during peak summer, screening and training of employees reduce accidents due to fall from height. The study indicates that learning from accident investigation and analysis can be used as a method to reduce work related accidents in the journey towards ‘Vision Zero’.

Keywords: accident investigation and analysis, fatal accidents in India, fall from height, vision zero

Procedia PDF Downloads 155

Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: Harshit Mittal, Neeraj Garg

Abstract:

Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Seyed Roozbeh Pishva, Alireza Aboudi Asl

Abstract:

In this investigation a hydrocyclone by using for separation particles from fluid in oil and gas, mining and other industries is simulated. Case study is cone – cylindrical and solid - liquid hydrocyclone. The fluid is water and the solid is a type of silis having diameters of 53, 75, 106, 150, 212, 250, and 300 micron. In this investigation CFD method used for analysis flow and movement of particles in hydrocyclone. In this modeling flow is three-dimention, turbulence and RSM model have been used for solving. Particles are three dimensional, spherical and non rotating and for tracking them Lagrangian model is used. The results of this study in addition to analyzing flowfield, obtaining efficiency of hydrocyclone in 5, 7, 12, and 15 percent concentrations and compare them with experimental result that both of them had suitable agreement with each other.

Keywords: hydrocyclone, RSM Model, CFD, copper industry

Procedia PDF Downloads 572

Authors: Milton Ixquiac, Erick Montenegro, Francisco Reynoso, Matthew Schmidt, Thomas Mazur, Tianyu Zhao, Hiram Gay, Geoffrey Hugo, Lauren Henke, Jeff Michael Michalski, Angel Velarde, Vicky de Falla, Franky Reyes, Osmar Hernandez, Edgar Aparicio Ruiz, Baozhou Sun

Abstract:

Purpose: Radiotherapy departments in low- and middle-income countries (LMICs) like Guatemala have recently introduced intensity-modulated radiotherapy (IMRT). IMRT has become the standard of care in high-income countries (HIC) due to reduced toxicity and improved outcomes in some cancers. The purpose of this work is to show the agreement between the dosimetric results shown in the Dose Volume Histograms (DVH) to the objectives proposed in the adopted protocol. This is the initial experience with an O-ring Linac. Methods and Materials: An O-Linac Linac was installed at our clinic in Guatemala in 2019 and has been used to treat approximately 90 patients daily with IMRT. This Linac is a completely Image Guided Device since to deliver each radiotherapy session must take a Mega Voltage Cone Beam Computerized Tomography (MVCBCT). In each MVCBCT, the Linac deliver 9 UM, and they are taken into account while performing the planning. To start the standardization, the TG263 was employed in the nomenclature and adopted a hypofractionated protocol to treat ChestWall, including supraclavicular nodes achieving 40.05Gy in 15 fractions. The planning was developed using 4 semiarcs from 179-305 degrees. The planner must create optimization volumes for targets and Organs at Risk (OARs); the difficulty for the planner was the dose base due to the MVCBCT. To evaluate the planning modality, we used 30 chestwall cases. Results: The plans created manually achieve the protocol objectives. The protocol objectives are the same as the RTOG1005, and the DHV curves look clinically acceptable. Conclusions: Despite the O-ring Linac doesn´t have the capacity to obtain kv images, the cone beam CT was created using MV energy, the dose delivered by the daily image setup process still without affect the dosimetric quality of the plans, and the dose distribution is acceptable achieving the protocol objectives.

Keywords: hypofrationation, VMAT, chestwall, radiotherapy planning

Procedia PDF Downloads 118

Authors: Florian Kleber, Martin Kampel

Abstract:

The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show that a higher contrast is achieved in the near infrared compared to ultraviolet and visible light.

Keywords: electronics waste, multispectral imaging, printed circuit boards, rare-earth elements

Procedia PDF Downloads 415

Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

Abstract:

This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

Procedia PDF Downloads 329

Authors: Elham Kiyani

Abstract:

In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

Procedia PDF Downloads 216