Search results for: imageNet large scale visual recognition challenge (ILSVRC)

Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Anum Akhter, Sumaira Altaf

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Purpose: To study the effect of low vision devices i.e. telescope and magnifying glasses on distance visual acuity and near visual acuity of children with Stargardt’s disease. Setting: Low vision department, Alshifa Trust Eye Hospital, Rawalpindi, Pakistan. Methods: 52 children having Stargardt’s disease were included in the study. All children were diagnosed by pediatrics ophthalmologists. Comprehensive low vision assessment was done by me in Low vision clinic. Visual acuity was measured using ETDRS chart. Refraction and other supplementary tests were performed. Children with Stargardt’s disease were provided with different telescopes and magnifying glasses for improving far vision and near vision. Results: Out of 52 children, 17 children were males and 35 children were females. Distance visual acuity and near visual acuity improved significantly with low vision aid trial. All children showed visual acuity better than 6/19 with a telescope of higher magnification. Improvement in near visual acuity was also significant with magnifying glasses trial. Conclusions: Low vision aids are useful for improvement in visual acuity in children. Children with Stargardt’s disease who are having a problem in education and daily life activities can get help from low vision aids.

Keywords: Stargardt, s disease, low vision aids, telescope, magnifiers

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Authors: Roya Yumul, Chse, Ofelia Loani Elvir Lazo, David Chernobylsky, Omar Durra

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Background: Preoperative anxiety has been shown to be caused by the fear associated with surgical and anesthetic complications; however, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting given the duration and concentration required to complete the 40-item extensive questionnaire. Our primary aim in the study is to investigate the correlation of the Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparison analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs. rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%), and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety were determined to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusions: Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul FACES Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul FACES Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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Recognition of human activities from sensor data is an active research area, and the main objective is to obtain a high recognition rate. In this work, we propose a recognition system based on expert systems. The proposed system makes the recognition based on the objects, object states, and gestures, taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions, and the activity). This work focuses on complex activities which are decomposed into simple easy to recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Laila Zahran Mohammed Alsibani

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The aim of the research is to understand the aspects of semiotics in contemporary designs by redesigning an Omani donut brand with localized cultural identity. To do so, visual identity samples of Dice brand of donuts in Oman has been selected to be a case study. This study conducted based on semiotic theory by using mixed method research tools which are: documentation analysis, interview and survey. The literature review concentrates on key areas of semiotics in visual elements used in the brand designs. Also, it spotlights on the categories of semiotics in visual design. In addition, this research explores the visual cues in brand identity. The objectives of the research are to investigate the aspects of semiotics in providing meaning to visual cues and to identify visual cues for each visual element. It is hoped that this study will have the contribution to a better understanding of the different ways of using semiotics in contemporary designs. Moreover, this research can be a review of further studies in understanding and explaining current and future design trends. Future research can also focus on how brand-related signs are perceived by consumers.

Keywords: brands, semiotics, visual arts, visual communication

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: Taezoon Park, Wonil Hwang

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This study aims to build a design guideline for the effective visual display used for consumer products considering user characteristics; gender and age. Although a number of basic experiments identified the limits of human visual perception, the findings remain fragmented and many times in an unfriendly form. This study compiled a design cases along with tables aggregated from the experimental result of visual perception; brightness/contrast, useful field of view, color sensitivity. Visual design elements commonly used for consumer product, were selected and appropriate guidelines were developed based on the experimental result. Since the provided data with case example suggests a feasible design space, it will save time for a product designer to find appropriate design alternatives.

Keywords: design guideline, consumer product, visual design element, visual perception, emotional design

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Authors: Kang-In Lee, Woo-Jin Lee, Keun-Deuk Lee, Ju-Seung Chae

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In this study, small scale gap test (SSGT) was performed to measure shock sensitivity of nano-scaled 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX) samples. The shock sensitivity of energetic materials is usually evaluated by the method of large-scale gap test (LSGT) that has a higher reliability than other methods. But LSGT has the disadvantage that it takes a high cost and time by using a large amount of explosive. In this experiment, nano-scaled RDX samples were prepared by spray crystallization in two different drying methods. In addition, 30μm RDX sample produced by precipitation crystallization and 5μm RDX sample produced by fluid energy mill process were tested to compare shock sensitivity. The study of shock sensitivity measured by small-scale gap test shows that small sized RDX particles have greater insensitivity. As a result, we infer SSGT method has higher reliability compared to the literature as measurement of shock sensitivity of energetic materials.

Keywords: nano-scaled RDX, SSGT(small scale gap test), shock sensitivity, RDX

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Authors: Andrey A. Chernousov, Ben Y. B. Chan

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The thermal behavior of a large-scale, phase change material (PCM) enhanced building envelope system was studied in regard to the need for pre-fabricated construction in subtropical regions. The proposed large-scale envelope consists of a reinforced aluminum skin, insulation core, phase change material and reinforced gypsum board. The PCM impact on an energy efficiency of an enveloped room was resolved by validation of the Energy Plus numerical scheme and optimization of a smart material location in the core. The PCM location was optimized by a minimization method of a cooling energy demand. It has been shown that there is good agreement between the test and simulation results. The optimal location of the PCM layer in Hong Kong summer conditions has been then recomputed for core thicknesses of 40, 60 and 80 mm. A non-dimensional value of the optimal PCM location was obtained to be same for all the studied cases and the considered external and internal conditions.

Keywords: thermal performance, phase change material, energy efficiency, PCM optimization

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Authors: Intan Izafina Idrus, Mardina Abdullah, Alina Marie Hasbi, Asnawi Husin

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This paper presents the result of large-scale traveling ionospheric disturbance (LSTID) observation during moderate magnetic storm event on 25 October 2011 with SYM-H ~ -160 nT and Kp ~ 7 over Peninsular Malaysia at equatorial region using vertical total electron content (VTEC) from the Global Positioning System (GPS) observation measurement. The propagation of the LSTID signatures in the TEC measurements over Peninsular Malaysia was also investigated using VTEC map. The LSTID was found to propagate equator-ward during this event. The results showed that the LSTID propagated with an average phase velocity of 526.41 m/s and average periods of 140 min. The occurrence of this LSTID was also found to be the subsequent effects of substorm activities in the auroral region.

Keywords: Global Positioning System (GPS), large-scale traveling ionospheric disturbance (LSTID), moderate geomagnetic storm, vertical total electron content (VTEC)

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Authors: Huangmei Liu, Si Liu, Jia’nan Liu

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The present experiment investigated and compared the effectiveness of two kinds of methods of attention control: Task distraction and visual enhancement. In the study, the effectiveness of task distractions to explicit features and of visual enhancement to implicit features of the same group of Chinese characters were compared based on their effect on the participants’ reaction time, subjective confidence rating, and verbal report. We found support that the visual enhancement on implicit features did overcome the contrary effect of training distraction and led to awareness of those implicit features, at least to some extent.

Keywords: task distraction, visual enhancement, attention, awareness, learning

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

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Authors: Rana Zeina

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Objective: The association between Sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a neuropsychological test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Methods: Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/Little Circle (BLC), Simple Reaction Time (SRT), Intra/Extra Dimensional Set Shift (IED), Spatial Recognition Memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. Results: ASDs Individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. Conclusion: The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to stimuli.

Keywords: visual memory, attention, autism spectrum disorders, CANTAB eclipse

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Authors: Jentel Van Havermaet, Geert Van Hove, Elisabeth De Schauwer

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This study re-conceptualizes visual impairment in the interdependent context of James, his family, and allies. Living with a visual impairment is understood as an entanglement of assemblages, dynamics, disablism, systems… We narrated this diffractively into two meaningful events: decisions and processes on (inclusive) education and hinderances in connecting with others. We entangled and (un)raveled lived experiences in assemblages in which the contextualized meaning of visual impairment became more clearly. The contextualized narrative of James interwove complex intra-actions; showed the complexity and contextualization of entangled relationalities.

Keywords: disability studies, contextualization, visual impairment, assemblage, entanglement, lived experiences

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Authors: Pan Lee Ching, Chua Bee Seok

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The experience of negative work-life interaction often confronted with work related stress includes workload. The appraisal of challenge and hindrance jobs depend on the type of workload to stimulate stress response. Nevertheless, the effects of challenge and hindrance jobs on distress and negative work-life interaction are scarcely explored. Thus, research objective was to examine the relationship among challenge appraisal job (qualitative workload), hindrance appraisal job (quantitative workload), and negative work-life interaction with the mediating role of distress. A survey with random sampling method was performed on current serving public secondary school teachers in Sabah. Collected data showed 447 respondents completed three questionnaires, namely Challenge-hindrance Appraisal Scale, Stress Professional Positive and Negative Questionnaire, and Survey Work-home Interaction-Nijmegan. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to analyse mediation effect. Results showed distress fully mediates the relationship between challenge appraisal job (qualitative workload) and negative work-life interaction. The indirect effect was significant and negative. While distress partially mediates the relationship between hindrance appraisal job (quantitative workload) and negative work-life interaction. The indirect effect was significant and positive. The study implied that challenge appraisal job could be a positive resource for teacher to facilitate work and life, whereas hindrance appraisal job could disengage the facilitation. Hence, strengthen challenge appraisal job and control hindrance appraisal job could curb distress at work and underpin life interaction among the teachers.

Keywords: challenge-hindrance job, distress, work-life, workload

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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: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: Han Bai, Lemei Yu, Tong Zhang, Doudou Xie, Liang Zhao

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The brightness changes at highway tunnel entrance and exit have an effect on the physical and psychological conditions of drivers. It is more conducive for examining driving safety with quantitative analysis of the physical and psychological characteristics of drivers to determine the speed limit sign locations at the tunnel entrance and exit sections. In this study, the physical and psychological effects of tunnels on traffic sign recognition of drivers are analyzed; subsequently, experiments with the assistant of Eyelink-II Type eye movement monitoring system are conducted in the typical tunnels in Ji-Qing freeway and Xi-Zha freeway, to collect the data of eye movement indexes “Fixation Duration” and “Eyeball Rotating Speed”, which typically represent drivers' mental load and visual characteristics. On this basis, the paper establishes a visual recognition model for the speed limit signs at the highway tunnel entrances and exits. In combination with related standards and regulations, it further presents the recommended values for locating speed limit signs under different tunnel conditions. A case application on Panlong tunnel in Ji-Qing freeway is given to generate the helpful improvement suggestions.

Keywords: driver psychological load, eye movement index, speed limit sign location, tunnel entrance and exit

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Yu Cheng-Yu

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‘Heterotopia’, ‘Visual Cultural Art Education’ and ‘New Media’ of these three subjects seemingly are irrelevant. In fact, there are synchronicity and intertextuality inside. In addition to visual culture, art education inspires students the ability to reflect on popular culture image through visual culture teaching strategies in school. We should get involved in the community to construct the learning environment that conveys visual culture art. This thesis attempts to probe the heterogeneity of space and value from Michel Foucault and to research sustainable development strategy in ‘New Media Art Village’ heterogeneity from Jean Baudrillard, Marshall McLuhan's media culture theory and social construction ideology. It is possible to find a new media group that can convey ‘Visual Culture Art Education’ around the National Taipei University of Technology in this commercial district that combines intelligent technology, fashion, media, entertainment, art education, and marketing network. Let the imagination and innovation of ‘New Media Art Village’ become ‘implementable’ and new media Heterotopia of inter-subjectivity with the engagement of big data and digital media. Visual culture art education will also bring aesthetics into the community by New Media Art Village.

Keywords: social construction, heterogeneity, new media, big data, visual culture art education

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Authors: M. Chavleishvili, E. Kharaishvili, G. Erkomaishvili

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The article presents the development trends of farms, estimates on the optimal scope of farming, as well as the experience of local and foreign countries in this area. As well, the advantages of small and large farms are discussed; herewith, the scales of farms are compared to the local reality. The study analyzes the results of farm operations and the possibilities of diversification of farms. The indicators of an effective use of land resources and land fragmentation are measured; also, a comparative analysis with other countries is presented, in particular, the measurements of agricultural lands for farming, as well as the indicators of population ensuring. The conducted research shows that most of the farms in Georgia are small and their development is at the initial stage, which outlines that the country has a high resource potential to increase the scale of the farming industry and its full integration into market relations. On the basis of the obtained results, according to the research on the scale of farming in Georgia and the identification of hampering factors of farming development, the conclusions are presented and the relevant recommendations are suggested.

Keywords: farm cooperatives.farms, farm scale, land fragmentation, small and large farms

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

Procedia PDF Downloads 156

Authors: Hirokatsu Kawashima

Abstract:

One important element of teaching/learning listening is intensive listening such as listening for precise sounds, words, grammatical, and semantic units. Several classroom-based investigations have been conducted to explore the usefulness of auditory recognition of phonological, grammatical and semantic errors in such a context. The current study reports the results of one such investigation, which targeted auditory recognition of phonological, grammatical, and semantic errors at the sentence level. 56 Japanese EFL learners participated in this investigation, in which their recognition performance of phonological, grammatical and semantic errors was measured on a 9-point scale by learners’ self-evaluation from the perspective of 1) two types of similar English sound (vowel and consonant minimal pair words), 2) two types of sentence word order (verb phrase-based and noun phrase-based word orders), and 3) two types of semantic consistency (verb-purpose and verb-place agreements), respectively, and their general listening proficiency was examined using standardized tests. A number of findings have been made about the interactive relationships between the three types of auditory error recognition and general listening proficiency. Analyses based on the OPLS (Orthogonal Projections to Latent Structure) regression model have disclosed, for example, that the three types of auditory error recognition are linked in a non-linear way: the highest explanatory power for general listening proficiency may be attained when quadratic interactions between auditory recognition of errors related to vowel minimal pair words and that of errors related to noun phrase-based word order are embraced (R2=.33, p=.01).

Keywords: auditory error recognition, intensive listening, interaction, investigation

Procedia PDF Downloads 488

Authors: Azlin Mohd Azmi, Tongming Zhou, Akira Rinoshika, Liang Cheng

Abstract:

The turbulent structures in the wake (x/d =10 to 60) of a screen cylinder have been reduced to understand the roles of the various structures as evolving downstream by comparing with those obtained in a solid circular cylinder wake at Reynolds number, Re of 7000. Using a wavelet multi-resolution technique, the flow structures are decomposed into a number of wavelet components based on their central frequencies. It is observed that in the solid cylinder wake, large-scale structures (of frequency f0 and 1.2 f0) make the largest contribution to the Reynolds stresses although they start to lose their roles significantly at x/d > 20. In the screen cylinder wake, the intermediate-scale structures (2f0 and 4f0) contribute the most to the Reynolds stresses at x/d =10 before being taken over by the large-scale structures (f0) further downstream.

Keywords: turbulent structure, screen cylinder, vortex, wavelet multi-resolution analysis

Procedia PDF Downloads 433