Search results for: visual recognition

Authors: Saidu Dalhat Dansadau, Aykut Karaman

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The integration of photography into architecture was a pivotal point in the journey of architectural representation; photography proved itself useful for the betterment of architecture early on, as well as established itself as a necessary tool in the realm of architecture. The main study this paper was extracted from looked into the inquiry of knowing exactly what are the key picturesque locations/structures in Sultanahmet, Fatih-Istanbul, and how can their spatial distribution and cultural significance be characterized and mapped for urban design and development as well as the secondary objective, of which this paper focuses on, is to “Investigate the role of perception in urban environments and how photography serves as a tool for capturing and conveying the perception of Sultanahmet's picturesque structures/locations”. The study achieved these objectives by utilizing methodologies such as geo-tagged photography, sequential photography, social media metadata extraction, GIS mapping, spatial analysis, and visual analysis, focusing on the historically rich and culturally significant study area of Sultanahmet, Fatih-Istanbul. By looking at potential structures/locations and then dissecting their special distribution and cultural significance, the main study was able to achieve the main objective as well as unveil a more nuanced understanding of the dynamics between photography, architecture, and urban design with respect to perception using sequential photography.

Keywords: perception, architectural photography, picturesque, urban design, Sultanahmet, Istanbul

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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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: Maria Melania Muda, Retno Wibawanti, Retno Asti Werdhani

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Background: Flight attendant (FA) is a job that is often exposed to ergonomic stressors; thus, they are very susceptible to symptoms of musculoskeletal disorders (MSDs). One of the ways to overcome musculoskeletal complaints is by stretching. This study aimed to examine the prevalence of MSDs and the effect of a 2-week stretching exercise program using the Indonesian Ministry of Health's stretching video on changes in musculoskeletal pain intensity in FA on commercial aircraft in Indonesia. Methods: A pre-post study was conducted using Nordic Musculoskeletal Questionnaire (NMQ) for MSDs’ identification and Visual Analog Scale (VAS) as pain intensity measurement. Data was collected and then analyzed using SPSS with Wilcoxon test. The change in pain intensity was considered significant if the p value was less than 0.05. Results: The results showed that 92% of the FA (n=75) had MSDs in at least 1 area of the body in the last 12 months. Thirty-four respondents participated as subjects. The complaint level score in 28 body areas before intervention was a median of 34 (29-84), with pain intensity of a median of 6 (2-9) became a median of 32 (28-67) and a median of 3 (0-9) after the intervention, respectively, with p-value <0.001. Conclusion: The stretching exercise program showed significant changes in the complaint level scores in 28 body areas (p < 0.001) and pain intensity before and after the stretching exercise intervention (p < 0.001).

Keywords: flight attendant, MSDs, Nordic Musculoskeletal Questionnaire, stretching exercise program, visual analog scale

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Visvaganthie Moodley

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While rhetoric goes back as far as Aristotle who focalised its meaning as the “art of persuasion”, most scholars have focused on elocutio and dispositio canons, neglecting the rhetorical impact of multimodal texts, such as documentaries. Film documentaries are being increasingly rhetoric, often used by wildlife conservationists for influencing people to become more mindful about humanity’s connection with nature. This paper examines the award-winning film documentary, “My Octopus Teacher”, which depicts naturalist, Craig Foster’s unique discovery and relationship with a female octopus in the southern tip of Africa, the Cape of Storms in South Africa. It is anchored in Leech and Short’s (2007) framework of linguistic and stylistic categories – comprising lexical items, grammatical features, figures of speech and other rhetoric features, and cohesiveness – with particular foci on diction, anthropomorphic language, metaphors and symbolism. It also draws on Kress and van Leeuwen’s (2006) multimodal analysis to show how verbal cues (the narrator’s commentary), visual images in motion, visual images as metaphors and symbolism, and aural sensory images such as music and sound synergise for rhetoric effect. In addition, the analysis of “My Octopus Teacher” is guided by Nichol’s (2010) narrative theory; features of a documentary which foregrounds the credibility of the narrative as a text that represents real events with real people; and its modes of construction, viz., the poetic mode, the expository mode, observational mode and participatory mode, and their integration – forging documentaries as multimodal texts. This paper presents a multimodal rhetoric discussion on the sequence of salient episodes captured in the slow moving one-and-a-half-hour documentary. These are: (i) The prologue: on the brink of something extraordinary; (ii) The day it all started; (iii) The narrator’s turmoil: getting back into the ocean; (iv) The incredible encounter with the octopus; (v) Establishing a relationship; (vi) Outwitting the predatory pyjama shark; (vii) The cycle of life; and (viii) The conclusion: lessons from an octopus. The paper argues that wildlife documentaries, characterized by plausibility and which provide researchers the lens to examine the ideologies about animals and humans, offer an assimilation of the various senses – vocal, visual and audial – for engaging viewers in stylized compelling way; they have the ability to persuade people to think and act in particular ways. As multimodal texts, with its use of lexical items; diction; anthropomorphic language; linguistic, visual and aural metaphors and symbolism; and depictions of anthropocentrism, wildlife documentaries are powerful resources for promoting wildlife conservation and conscientizing people of the need for establishing a harmonious relationship with nature and humans alike.

Keywords: documentaries, multimodality, rhetoric, style, wildlife, conservation

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Noorlizawati Abd Rahim, Zainai Mohamed, Zaidatun Tasir, Astuty Amrin, Haliyana Khalid, Nina Diana Nawi

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Entrepreneurial leaders have been sought as in-demand talents to lead profit-driven organizations during turbulent and unprecedented times. However, research regarding the pertinence of their roles in the public sector has been limited. This paper examined the characteristics of the challenging experiences encountered by senior leaders in public universities that require them to embrace entrepreneurialism in their leadership. Through a focus group interview with five Malaysian university top senior leaders with experience being Vice-Chancellor, we explored and developed a framework of institutional adversity characteristics and exemplary entrepreneurial leadership competency in the face of adversity. Complexity of diverse stakeholders, multiplicity of academic disciplines, unfamiliarity to lead different and broader roles, leading new directions, and creating change in high velocity and uncertain environment are among the dimensions that characterise institutional adversities. Our findings revealed that learning agility, opportunity recognition capacity, and bridging capability are among the characteristics of entrepreneurial university leaders. The findings reinforced that the presence of specific attributes in institutional adversity and experiences in overcoming those challenges may contribute to the development of entrepreneurial leadership capabilities.

Keywords: bridging capability, entrepreneurial leadership, leadership development, learning agility, opportunity recognition, university leaders

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Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts

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Authors: Chia-Chen Wu, Chih-Fu Wu, Pey-Weng Lien, Kai-Chieh Lin

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In the past, the most comprehensively adopted light source was incandescent light bulbs, but with the appearance of LED light sources, traditional light sources have been gradually replaced by LEDs because of its numerous superior characteristics. However, many of the standards do not apply to LEDs as the two light sources are characterized differently. This also intensifies the significance of studies on LEDs. As a Kansei design study investigating the visual glare produced by traffic arrows implemented with LEDs, this study conducted a semantic analysis on the styles of traffic arrows used in domestic and international occasions. The results will be able to reduce drivers’ misrecognition that results in the unsuccessful arrival at the destination, or in traffic accidents. This study started with a literature review and surveyed the status quo before conducting experiments that were divided in two parts. The first part involved a screening experiment of arrow samples, where cluster analysis was conducted to choose five representative samples of LED displays. The second part was a semantic experiment on the display of arrows using LEDs, where the five representative samples and the selected ten adjectives were incorporated. Analyzing the results with Quantification Theory Type I, it was found that among the composition of arrows, fletching was the most significant factor that influenced the adjectives. In contrast, a “no fletching” design was more abstract and vague. It lacked the ability to convey the intended message and might bear psychological negative connotation including “dangerous,” “forbidden,” and “unreliable.” The arrow design consisting of “> shaped fletching” was found to be more concrete and definite, showing positive connotation including “safe,” “cautious,” and “reliable.” When a stimulus was placed at a farther distance, the glare could be significantly reduced; moreover, the visual evaluation scores would be higher. On the contrary, if the fletching and the shaft had a similar proportion, looking at the stimuli caused higher evaluation at a closer distance. The above results will be able to be applied to the design of traffic arrows by conveying information definitely and rapidly. In addition, drivers’ safety could be enhanced by understanding the cause of glare and improving visual recognizability.

Keywords: LED, arrow, Kansei research, preferred imagery

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Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

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The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Sabra Saeidi

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When we talk about tangible heritage, the first thing that comes to mind is historic places: what they look like, who made them, and what materials they are made of. But each monument is not limited to its physical constituents and is a complex and related set of human perceptions, memories, narratives, and the structure that shapes its character. In this article, based on the ideology of two great architects, Juhani Pallasmaa and Christian Norberg-Schulz, we discussed the sense of the place and how the human presence in a place with all its senses (visual, auditory, tactile, olfactory, taste) gives life and value to it. This value is all about feeling and definitions and is recorded in the form of our memoirs. An attempt has been made to conclude that our perception of the environment, by our sensory tools, is an intangible and thematic heritage itself, whose existence depends on our existence and has no less value than monuments' physical form and structure. The sense of smell is one of the most powerful, personal and inexplicable, unrecorded, and unexpressed senses and has a solid connection with our memories. by reviewing the case of Kerman Bazaar and its change of use in recent years, we define that one of the ways to protect the olfactory heritage of this valuable complex is to draw a Smellscape: a way to record the moment of present and past memories. Smellscapes are tools for transferring the sense of smell to a visual form to record scents and understand them in a more comprehensive, common, and artistic form.

Keywords: sence of the place, spirit of the place, smellscape, multisensory perception

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

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This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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Authors: Małgorzata Jakubowska, Monika Michałowska

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Since the beginning of the cinematographic industry, there has been a visible interest in two leading themes: death and sexuality. One of the reasons of the unfading popularity of these motives was the fact that death or sex employed as leitmotivs attracted great attention of the viewers, and this guaranteed a financial success. What seems interesting is the fact that the themes of death and sexuality/eroticism seem to be mutually exclusive in the mainstream movies to such extent that they almost never appear together on the screen. As leitmotivs they describe opposite experiences of human life, one refers to affirmation of life, the other points to atrophy and decay. This film paradigm is rarely challenged. Thus, a relatively less attention has been devoted so far to entwining dying and sexuality/eroticism in one movie. In our paper, we wish to have a closer look at the visualizations of dying with focus on the aspect of sexuality/eroticism. Our analysis will concentrate on the contemporary European and American cinema, and especially the recent productions that contribute to the cultural phenomenon of entwining the two realms of human life. We will investigate the main clichés, plot and visual schemes, motives and narrative techniques on the examples of Sweet November (2001), A Little Bit of Heaven (2011) and Now is good (2012). We will also shed some light on the recent film productions that seem to provide a shift in portraying the realms of dying and sexuality concentrating on The Garden of Earthly Delights (2003) as the most paradigmatic example.

Keywords: contemporary cinema, dying and sexuality, narrative techniques, plot and visual schemes

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Jelena Kovačević Vorgučin, Sibila Petenji Arbutina

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The postmodern age brings a rapid development of technology which inevitably leads to man's need to adapt to modern lifestyle. On the one hand, technological achievements have made human life easier, but there are numerous risks involved. Moreover, man's awareness and perception is changing and adapting unconsciously to the world we live in, while communication in the 21st century is predominantly based on the consumption of images. This paper presents sociological aspects of a community which is confined due to turbulent political-economic circumstances and its impact on the development of media literacy in Serbia. Previous researches led to the conclusion that the media culture is on an extremely low level, and that it can have a strong influence on the general development of the society, starting from the youngest segment of the population. Our aim is to use the conceptual authorial photographs inspired by the obtained research results to emphasize the importance that the impact of visual art has in delivering the message, its role in education and in raising awareness of universal social problems. The paper presents a number of stages involved in the conceptual project which is designed to last over a longer period of time in order to facilitate dissemination of information. First, a survey was carried out in several preschool institutions. This resulted in obtaining the necessary information on the habitual use of the medium of television in children and their carers-parents. The second stage focused on the relationship between the parent and the child in TV consumption. Further, an overview of the visual part of the project was made, which consisted of photographs in various dimensions, ranging from miniature to large dimensions, and following various exhibition principles in both gallery and alternative spaces. This stage of the project placed particular emphasis on the non-standard exhibiting formats and alternative exhibition principles which are increasingly present in all kinds of visual art aimed at achieving a higher level of information noticing and memorizing. The motif on the authorial photographs is children's portraits taken while they are watching different television contents, with emphasis on their emotional response. The importance of the medium of TV is particularly emphasized due to the fact that its consumption is the highest, even though there are newer and more advanced information-technological achievements. The already realized part of the project was used for an analysis of the results in the last stage of the project, which led to the conclusion that the response to the entire visual expression campaign was extremely positive, and action as such very useful indeed. The results obtained speak in favour of widening and continuation of the project, both on a greater number of sites locally as well as in other communities in Serbia with the aim of guiding people towards meaningful consumption of the television medium.

Keywords: alternative space exhibiting, children and TV, conceptual portrait photography, media literacy

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Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

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Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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Authors: Teresa B. King

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In the millennial age, with more students desiring a fashion major yet fewer having sewing and manufacturing knowledge, this increases demand on academicians to adequately educate. While fashion museums have a prominent place for historical preservation, the need for apparel education via working collections of handmade or mass manufactured apparel is lacking in most universities in the United States, especially in the Southern region. Created in 1988, Middle Tennessee State University’s historic clothing collection provides opportunities to study apparel construction methods throughout history, to compare and apply to today’s construction and manufacturing methods, as well as to learn the cyclical nature/importance of historic styles on current and upcoming fashion. In 2019, a class exercise experiment was implemented for which students researched their family genealogy using Ancestry.com, identified the oldest visual media (photographs, etc.) available, and analyzed the garment represented in said media. The student then located a comparable garment in the historic collection and evaluated the construction methods of the ancestor’s time period. A class 'fashion' genealogy tree was created and mounted for public viewing/education. Results of this exercise indicated that student learning increased due to the 'personal/familial connection' as it triggered more interest in historical garments as related to the student’s own personal culture. Students better identified garments regarding the historical time period, fiber content, fabric, and construction methods utilized, thus increasing learning and retention. Students also developed increased learning and recognition of custom construction methods versus current mass manufacturing techniques, which impact today’s fashion industry. A longitudinal effort will continue with the growth of the historic collection and as students continue to utilize the historic clothing collection.

Keywords: ancestry, clothing history, fashion history, genealogy, historic fashion museum collection

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: K. Doi, T. Nishimura, H. Fujimoto

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The number of people who become visually impaired and do not have sufficient tactile experiences has increased by various disease. Especially, many acquired visually impaired persons due to accidents, disorders, and aging cannot adequately read Braille. It is known that learning Braille requires a great deal of time and the acquisition of various skills. In our previous studies, we reported one of the problems in learning Braille. Concretely, the standard Braille size is too small for Braille beginners. And also we are short of the objective data regarding easily readable Braille size. Therefore, it is necessary to conduct various experiments for evaluating Braille size that would make learning easier for beginners. In this study, for the purpose of investigating easy-to-read conditions of vertical and horizontal dot spacing for beginners, we conducted one Braille reading experiment. In this our experiment, we prepared test pieces by use of our original Braille printer with controlling function of Braille size. We specifically considered Braille beginners with acquired visual impairments who were unfamiliar with Braille. Therefore, ten sighted subjects with no experience of reading Braille participated in this experiment. Size of vertical and horizontal dot spacing was following conditions. Each dot spacing was 2.0, 2.3, 2.5, 2.7, 2.9, 3.1mm. The subjects were asked to read one Braille character with controlled Braille size. The results of this experiment reveal that Braille beginners can read Braille accurately and quickly when both vertical and horizontal dot spacing are 3.1 mm or more. This knowledge will be helpful data in considering Braille size for acquired visually impaired persons.

Keywords: paper-based Braille, vertical and horizontal dot spacing, readability, acquired visual impairment, Braille beginner

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Authors: Hayder H. Kareem, Ayad K. Hussein, Aseel A. Alkatib

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Groundwater accumulated at geological formations constitutes a worldwide vital water resource component which can be used to supply agriculture, industry, and domestic uses. The subsurface environment is affected by human activities; consequently, planning and sustainable management of aquifers require serious attention, especially as the world is exposed to the problem of global warming. Establishing accurate and efficient groundwater models will provide confident results for the behavior of the aquifer's system. The new approach, 'Distributed Value Property Zones,' available in Visual MODFLOW, is used to reconstruct the subsurface zones of the Al-Najaf region aquifer, and then its effect is compared with those manual and automated (PEST) approaches. Results show that the model has become more accurate with the use of the new approach, as the calibration and results analyses revealed. The assessment of the Al-Najaf region groundwater aquifer has revealed a degree of insufficiency of the required pumping demand, which reflects dry areas in both of the aquifer's layers. In addition, with pumping, the Euphrates River loses water of 7458 m³/day to the aquifer, while without pumping, it gains 28837 m³/day from the rainfall's recharge. The distributed value property zones approach achieves a precise groundwater model to assess the state of the Al-Najaf region aquifer.

Keywords: Al-Najaf region, distributed value property zones approach, hydraulic conductivity, groundwater modelling using visual MODFLOW

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Authors: Mohammed Asiri, Saleh Alsuwayt, Mohammed Bin Mugren, Abdulmalik Almufarrih, Tariq Alotaibi, Saad Almodameg

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Background: End-stage renal disease is a major public health concern with high incidence and mortality rate. Most of ESRD patients are on hemodialysis therapy which is a long-term treatment that disturbs patients’ lifestyle. As a result, he will be susceptible to develop psychiatric disorders like anxiety that may direct him to non-compliance on physician instructions and hemodialysis therapy. Although there are studies conducted on psychiatric issues in hemodialysis patients, but few studies focused on the effect of anxiety disorder and the patient’s compliance. Hence, we are interested in determining the prevalence of anxiety disorder among hemodialysis patients in Saudi Arabia, as well as in defining the correlation between anxiety disorder and compliance on physician instructions and hemodialysis therapy. We hypothesize that our study will show a higher prevalence of anxiety in hemodialysis patients than in general population. Also, we expect the anxiety to have a negative impact on their compliance. Methodology: We used a cross-sectional study design carried out at dialysis unit of four major hospitals in Riyadh, KSA. We interviewed 235 End Stage Renal Disease male and female patients who are on hemodialysis. We divided the patients into two categories according to their compliance. we used modified general questionnaire to get their demographic data, then we used a psychometric response scale called visual analog scale (VAS) to assess patient’s compliance to hemodialysis and physician’s instructions. Also, we used the Arabic validated version of the hospital anxiety and depression scale (HAD scale) used mainly for anxiety assessment. Results: The overall response rate was 54%. Respondents included 147 (62.6%) males and 88 (37.4%) females. The prevalence of anxiety among hemodialysis patients is 13.3%. According to visual analog scale, we found that 189 compliant patients and 45 non-compliant patients. For HAD scale, the mean ± standard deviation of the total score for females was (4.44 ± 4.7) and it’s higher than males which was 2.65 ± 3.08 (P-value= 0.002). The mean ± standard deviation of HAD score in the non-compliant group was (5.88  4.88) and it was higher than the compliant group (2.7  3.32) (P-value= 0.004). Among non-complaint group, 33.3% of anxious patients were males and 66.6% were females. There was a negative correlation between HAD score of anxiety and visual analog scale (R= - 0.285). Conclusion: We conclude that there is a high prevalence of anxiety among patients with End Stage Renal Disease that was higher in females with association of non-compliance to physician’s instructions and hemodialysis therapy.

Keywords: anxiety, end-stage renal disease, renal failure, anxiety disorder

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Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

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Authors: Kuo-Cheng Liu

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In the latest research efforts, the structures of the image in the spatial domain have been successfully analyzed and proved to deduce the visual masking for accurately estimating the visibility thresholds of the image. If the structural properties of the video sequence in the temporal domain are taken into account to estimate the temporal masking, the improvement and enhancement of the as-sessing spatio-temporal visibility thresholds are reasonably expected. In this paper, the temporal characteristics of human perception to the change in block structures on the time axis are analyzed. The temporal characteristics of human perception are represented in terms of the significant variation in block structures for the analysis of human visual system (HVS). Herein, the block structure in each frame is computed by combined the pattern masking and the contrast masking simultaneously. The contrast masking always overestimates the visibility thresholds of edge regions and underestimates that of texture regions, while the pattern masking is weak on a uniform background and is strong on the complex background with spatial patterns. Under considering the significant variation of block structures between successive frames, we extend the block structures of images in the spatial domain to that of video sequences in the temporal domain to analyze the relation between the inter-frame variation of structures and the temporal masking. Meanwhile, the subjective viewing test and the fair rating process are designed to evaluate the consistency of the temporal characteristics with the HVS under a specified viewing condition.

Keywords: temporal characteristic, block structure, pattern masking, contrast masking

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Authors: Mamochana, A. Ramatea, Fumane, P. Khanare

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Enabling the learning environment is a significant and adaptive technique necessary to navigate learners’ educational challenges. However, research has indicated that quality provision of education in the environments that are enabling, especially to learners with visual impairments (LVIs, hereafter) in rural schools, remain an ongoing challenge globally. Hence, LVIs often have a lower level of academic performance as compared to their peers. To balance this gap and fulfill learners'fundamentalhuman rights¬ of receiving an equal quality education, appropriate measures and structures that make enabling learning environment a better place to learn must be better understood. This paper, therefore, intends to find possible means that rural schools of Lesotho can employ to make the learning environment for LVIs enabling. The present study aims to determine suitable assets that can be drawn to make the learning environment for LVIs enabling. The study is also informed by the transformative paradigm and situated within a qualitative research approach. Data were generated through focus group discussions with twelve teachers who were purposefully selected from two rural primary schools in Lesotho. The generated data were then analyzed thematically using Braun and Clarke's six-phase framework. The findings of the study indicated that participating teachers do have an understanding that rural schools boast of assets (existing and hidden) that have a positive influence in responding to the special educational needs of LVIs. However, the participants also admitted that although their schools boast of assets, they still experience limited knowledge about the use of the existing assets and thus, realized a need for improved collaboration, involvement of the existing assets, and enhancement of academic resources to make LVIs’ learning environment enabling. The findings of this study highlight the significance of the effective use of assets. Additionally, coincides with literature that shows recognizing and tapping into the existing assets enable learning for LVIs. In conclusion, the participants in the current study indicated that for LVIs’ learning environment to be enabling, there has to be sufficient use of the existing assets. The researchers, therefore, recommend that the appropriate use of assets is good, but may not be sufficient if the existing assets are not adequately managed. Hence,VILs experience a vicious cycle of vulnerability. It was thus, recommended that adequate use of assets and teachers' engagement as active assets should always be considered to make the learning environment a better place for LVIs to learan in the future

Keywords: assets, enabling learning environment, rural schools, learners with visual impairments

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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Authors: Hamidreza Torabi, Mohsen Moghtaderi

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Introduction: Currently, deep vitrectomy with silicone oil tamponade is the standard treatment method for patients with Rhegmatogenous Retinal Detachment (RRD). After retinal repair, it is necessary to remove silicone oil from the eye, but the appropriate time to remove the oil and complications related to that time has been less studied. The aim of this study was to compare the results of the early removal of silicone oil with the delayed removal of silicone oil in patients with RRD. Method & material: Patients who were referred to the Ophthalmology Clinic of Baqiyatallah Hospital, Tehran, Iran, due to RRD with detached macula in 2021 & 2022 were evaluated. These patients were treated with deep vitrectomy and silicone oil tamponade. Patients whose retinas were attached after the passage of time were candidates for silicone oil removal (SOR) surgery. For patients in the early SOR group, SOR surgery was performed 3-6 months after the initial vitrectomy surgery, and for the late SOR group, SOR was performed after 6 months after the initial vitrectomy surgery. Results: In this study, 60 patients with RRD were evaluated. 23 (38.3%) patients were in the early group, and 37 (61.7%) patients were in the late group. Based on our findings, it was seen that the mean visual acuity of patients based on the Snellen chart in the early group (0.48 ± 0.23 Decimal) was better than the late group (0.33 ± 0.18 Decimal) (P-value=0.009). Retinal re-detachment has happened only in one patient with early SOR. Conclusion: Early removal of silicone oil (less than 6 months) from the eyes of patients undergoing RRD surgery has been associated with better vision results compared to late removal.

Keywords: retinal detachment, vitrectomy, silicone oil, silicone oil removal, visual acuity

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