Search results for: low vision aids

Authors: Ksenia Meshkova

Abstract:

With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

Procedia PDF Downloads 104

Authors: S. M. Amin Hosseini, Oriol Pons, Albert de la Fuente

Abstract:

An earthquake hit the Kermanshah province, which is located in the west of Iran, on 12th November 2017 at 18:18 UTC (21:48 Iran Standard Time). This earthquake caused several deaths and injured people. In this disaster, substantial homes were destroyed and many homes were damaged. The Iranian government, local authorities, and several non-governmental organizations responded to affected populations’ needs, such as foods, blanket, water, a tent as a temporary shelter, etc. Considerable national groups, including governmental, non-governmental organizations, and people from non-organized groups, directly and indirectly, tried to bring donated goods to the affected populations. However, some of these aids could not satisfy all the affected populations. Moreover, these impossibilities led to waste extensive resources. In this regard, this research study aims to assess the problems of the Kermanshah disaster responses. At the same time, this project searches possible solutions in order to increase emergency management efficiencies for encountering future events. To this end, this study assesses the problem from all beneficiaries´ point of views. In this regard, a survey and a questionnaire were designed for statistical analyses of the responses of people, who were involved in the Kermanshah earthquake recovery program. Additionally, this research study takes into account diverse strategies, which have been applied in other recovery programs, with the Kermanshah case in order to determine similarities and differences. Finally, this study presents possible solutions taken from other recovery programs that could be applied for the Kermanshah emergency responses. However, the results demonstrate that it is required to customize applied strategies based on local conditions and requirements.

Keywords: disaster response, Kermanshah earthquake, natural disasters, NGOs

Procedia PDF Downloads 152

Authors: Ibrahim Abubakar Mikugi

Abstract:

Nigerian graduates could only be self-employed and marketable if they acquire relevant skills and knowledge for successful establishment in various occupation and gainful employment. Research has shown that entrepreneurship education will be successful through developing individual entrepreneurial attitudes, raising awareness of career options by integrating and inculcating a positive attitude in the mind of students through skill acquisition. This paper examined the student- led entrepreneurship education through skill acquisition with specific emphasis on analysis of David Kolb experiential learning cycle. This Model allows individual to review their experience through reflection and converting ideas into action by doing. The methodology used was theoretical approach through journal, internet and Textbooks. Challenges to entrepreneurship education through skill acquisition were outlined. The paper concludes that entrepreneurship education is recognised by both policy makers and academics; entrepreneurship is more than mere encouraging business start-ups. Recommendations were given which include the need for authorities to have a clear vision towards entrepreneurship education and skill acquisition. Authorities should also emphasise a periodic and appropriate evaluation of entrepreneurship and to also integrate into schools academic curriculum to encourage practical learning by doing.

Keywords: entrepreneurship, entrepreneurship education, active learning, Cefe methodology

Procedia PDF Downloads 493

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

Abstract:

Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

Procedia PDF Downloads 135

Authors: Vangelis Drosos, Dimitrios Tsoukalos, Dimitrios Tsolis

Abstract:

We present a simple algorithm for capturing a 3D scene (focused on the usage of mobile device cameras in the context of augmented/mixed reality) by using a floating origin camera solution and storing the resulting information in a linear voxel octree. Data is derived from cloud points captured by a mobile device camera. For the purposes of this paper, we assume a scene of fixed size (known to us or determined beforehand) and a fixed voxel resolution. The resulting data is stored in a linear voxel octree using a hashtable. We commence by briefly discussing the logic behind floating origin approaches and the usage of linear voxel octrees for efficient storage. Following that, we present the algorithm for translating captured feature points into voxel data in the context of a fixed origin world and storing them. Finally, we discuss potential applications and areas of future development and improvement to the efficiency of our solution.

Keywords: voxel, octree, computer vision, XR, floating origin

Procedia PDF Downloads 116

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

Procedia PDF Downloads 169

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

Abstract:

The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

Procedia PDF Downloads 149

Authors: Jonah Kenei, Elisha Opiyo

Abstract:

Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing.

Keywords: classification, electronic health records, narrative texts, visualization

Procedia PDF Downloads 98

Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

Procedia PDF Downloads 243

Authors: Abul Quasem Al-Amin, Md. Hasanuzzaman, Mohammad Nurul Azam, Walter Leal Filho

Abstract:

With regard to the future energy strategy and vision, this study aimed to find the drawbacks of proposed energy diversification policy for 2020. To have a clear picture of the drawback and competitive alternative, this study has explored two scenarios, namely Scenario a and Scenario b. The Scenario a indicates that in the year 2020 the GHG emissions would be 823,498.00 million tons (Mt) with a 2020 final demand and proposed fuel mix such as by the Five-Fuel Diversification Strategy. In contrast, as an alternative, the Scenario b with biofuel potentials indicates that the substitution of coal energy by 5%, 10%, and 15%, respectively, with biofuel, would reduce the GHG emissions from 374,551.00, 405,118.00, and 823,498.00 million tons to 339,964.00, 329,834.00, and 305,288.00 million tons, respectively, by the present fuel mix, business-as-usual fuel mix, and proposed fuel mix up to the year 2020. Therefore, this study has explored a healthy alternative by introducing biofuel renewable energy option instead of conventional energy utilization in the power generation with environmental aspect in minds. This study effort would lessen the gap between GHG mitigation and future sustainable development and would useful to formulate effective renewable energy strategy in Malaysia.

Keywords: energy, environmental impacts, renewable energy, biofuel, energy policy

Procedia PDF Downloads 464

Authors: Mengjiao Hu

Abstract:

Nowadays, China's consumption pattern is entering the "experience era"; people's consumption behavior is no longer simply "buy, buy, buy" but the transition from "consumption in space" to "consumption of space". The street is a basic public product and an important public space in the city, and commerce along the street is an important space for people to consume in the "experience era". Therefore, in this way, it is particularly important to create the vitality of the gray space along the street. From the perspective of vitality construction, this paper takes Sha Zheng Street in Chongqing as the empirical object, combined with the theoretical knowledge of behavioral architecture, and based on the current situation of the commercial gray space along Sha Zheng Street, this paper explores the influence factors and the constraints behind the spatial vitality and then puts forward a general strategy to improve the spatial vitality of the commercial gray space along the street. The author hopes that through the exploration of the vitality of commercial gray space along the street, environmental design can be introduced into the integrated design vision of the urban public environment, and the urban designers can be inspired to create a street environment with a living atmosphere with a small start.

Keywords: vitality creation, gray space, street commerce, sha zheng street

Procedia PDF Downloads 74

Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li

Abstract:

High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.

Keywords: monocular camera, GPS, positioning, measurement

Procedia PDF Downloads 122

Authors: Flaurence Benjamain, Michel Casperance

Abstract:

We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

Procedia PDF Downloads 256

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

Abstract:

Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

Procedia PDF Downloads 492

Authors: Jenan Abu Qadourah

Abstract:

With the depletion of traditional fossil resources and the growing human population, it is now more important than ever to reduce our energy usage and harmful emissions. In the Mediterranean region, the intense solar radiation contributes to summertime overheating, which raises energy costs and building carbon footprints, alternatively making it suitable for the installation of solar energy systems. In urban settings, where multi-story structures predominate and roof space is limited, photovoltaic integrated shading devices (PVSD) are a clean solution for building designers. However, incorporating photovoltaic (PV) systems into a building's envelope is a complex procedure that, if not executed correctly, might result in the PV system failing. As a result, potential PVSD design solutions must be assessed based on their overall energy performance from the project's early design stage. Therefore, this paper aims to investigate and compare the possible impact of various PVSDs on the energy performance of new apartments in the Mediterranean region, with a focus on Amman, Jordan. To achieve the research aim, computer simulations were performed to assess and compare the energy performance of different PVSD configurations. Furthermore, an energy index was developed by taking into account all energy aspects, including the building's primary energy demand and the PVSD systems' net energy production. According to the findings, the PVSD system can meet 12% to 43% of the apartment building's electricity needs. By highlighting the potential interest in PVSD systems, this study aids the building designer in producing more energy-efficient buildings and encourages building owners to install PV systems on the façade of their buildings.

Keywords: photovoltaic integrated shading device, solar energy, architecture, energy performance, simulation, overall energy index, Jordan

Procedia PDF Downloads 62

Authors: Karlee J. Hall, Mark Laylor, Jessy Varghese, Paula Polastri, Karen Van Ooteghem, William McIlroy

Abstract:

Balance training is a common part of physiotherapy treatment and often involves a set of proprioceptive exercises which the patient carries out in the clinic and as part of their exercise program. Understanding all contributing factors to altered balance is of utmost importance to the clinical success of treatment of balance dysfunctions. A critical role for the autonomic nervous system (ANS) in the control of balance reactions has been proposed previously, with evidence for potential involvement being inferred from the observation of phasic galvanic skin responses (GSR) evoked by external balance perturbations. The current study explored whether the coupling between ANS reactivity and balance reactions would be observed during spontaneously occurring instability while standing, including standard positions typical of physiotherapy balance assessments. It was hypothesized that time-varying changes in GSR (ANS reactivity) would be associated with time-varying changes in the mediolateral center of pressure (ML-COP) (somatomotor reactivity). Nine individuals (5 females, 4 males, aged 19-37 years) were recruited. To induce varying balance demands during standing, the study compared ML-COP and GSR data across different task conditions varying the availability of vision and width of the base of support. Subjects completed 3, 30-second trials for each of the following stance conditions: standard, narrow, and tandem eyes closed, tandem eyes open, tandem eyes open with dome to shield visual input, and restricted peripheral visual field. ANS activity was evaluated by measures of GSR recorded from Ag-AgCl electrodes on the middle phalanges of digits 2 and 4 on the left hand; balance measures include ML-COP excursion frequency and amplitude recorded from two force plates embedded in the floor underneath each foot. Subjects were instructed to stand as still as possible with arms crossed in front of their chest. When comparing mean task differences across subjects, there was an expected increase in postural sway from tasks with a wide stance and no sensory restrictions (least challenging) to those with a narrow stance and no vision (most challenging). The correlation analysis revealed a significant positive relationship between ML-COP variability and GSR variability when comparing across tasks (r=0.94, df=5, p < 0.05). In addition, correlations coincided within each subject and revealed a significant positive correlation in 7 participants (r= 0.47, 0.57, 0.62, 0.62, 0.81, 0.64, 0.69 respectively, df=19, p < 0.05) and no significant relationship in 2 participants (r=0.36, 0.29 respectively, df=19, p > 0.05). The current study revealed a significant relationship between ML-COP and GSR during balance tasks, revealing the ANS reactivity associated with naturally occurring instability when standing still, which is proportional to the degree of instability. Understanding the link between ANS activity and control of COP is an important step forward in the enhancement of assessment of contributing factors to poor balance and treatment of balance dysfunctions. The next steps will explore the temporal association between the time-varying changes in COP and GSR to establish if the ANS reactivity phase leads or lags the evoked motor reactions, as well as exploration of potential biomarkers for use in screening of ANS activity as a contributing factor to altered balance control clinically.

Keywords: autonomic nervous system, balance control, center of pressure, somatic nervous system

Procedia PDF Downloads 151

Authors: Jacqueline Żammit

Abstract:

Recent research indicates that the utilization of right-brain strategies holds significant implications for the acquisition of language skills. Nevertheless, the utilization of visual culture as a means to stimulate these strategies and amplify language retention among adults engaging in second language (L2) learning remains a relatively unexplored area. This investigation delves into the impact of visual culture on activating right-brain processes during the initial stages of language acquisition, particularly in the context of teaching Maltese as a second language (ML2) to adult learners. By employing a qualitative research approach, this study convenes a focus group comprising twenty-seven educators to delve into a range of visual culture techniques integrated within language instruction. The collected data is subjected to thematic analysis using NVivo software. The findings underscore a variety of impactful visual culture techniques, encompassing activities such as drawing, sketching, interactive matching games, orthographic mapping, memory palace strategies, wordless picture books, picture-centered learning methodologies, infographics, Face Memory Game, Spot the Difference, Word Search Puzzles, the Hidden Object Game, educational videos, the Shadow Matching technique, Find the Differences exercises, and color-coded methodologies. These identified techniques hold potential for application within ML2 classes for adult learners. Consequently, this study not only provides insights into optimizing language learning through specific visual culture strategies but also furnishes practical recommendations for enhancing language competencies and skills.

Keywords: visual culture, right-brain strategies, second language acquisition, maltese as a second language, visual aids, language-based activities

Procedia PDF Downloads 41

Authors: A. Alem, Y. Dahmani, A. Hadjali, A. Boualem

Abstract:

Managing the problem of the conflict, either by using the Dempster-Shafer theory, or by the application of the fusion process to push researchers in recent years to find ways to get to make best decisions especially; for information systems, vision, robotic and wireless sensor networks. In this paper we are interested to take account of the conflict in the combination step that took the conflict into account and tries to manage such a way that it does not influence the decision step, the conflict what from reliable sources. According to [1], the conflict lead to erroneous decisions in cases where was with strong degrees between sources of information, if the conflict is more than the maximum of the functions of belief mass K > max1...n (mi (A)), then the decision becomes impossible. We will demonstrate in this paper that the multiplication of mass functions by coefficients of reliability is a decreasing function; it leads to the reduction of conflict and a good decision. The definition of reliability coefficients accurately and multiply them by the mass functions of each information source to resolve the conflict and allow deciding whether the degree of conflict. The evaluation of this technique is done by a use case; a comparison of the combination of springs with a maximum conflict without, and with reliability coefficients.

Keywords: Dempster-Shafer theory, fusion process, conflict managing, reliability factors, decision

Procedia PDF Downloads 405

Authors: G. C. Almiranez, J. Mercado, L. U. Aumentado, J. M. Mahaguay, J. P. Cruz, M. L. Saballe

Abstract:

This research project focused on the development of an application that aids the university administrators to establish an efficient and effective system in managing faculty attendance and discourage unnecessary absences. The Faculty Attendance Management System (FAMS) is a web based and mobile application which is proven to be efficient and effective in handling and recording data, generating updated reports and analytics needed in managing faculty attendance. The FAMS can facilitate not only a convenient and faster way of gathering and recording of data but it can also provide data analytics, immediate feedback system mechanism and analysis. The software database architecture uses MySQL for web based and SQLite for mobile applications. The system includes different modules that capture daily attendance of faculty members, generate faculty attendance reports and analytics, absences notification system for faculty members, chairperson and dean regarding absences, and immediate communication system concerning the absences incurred. Quantitative and qualitative evaluation showed that the system satisfactory meet the stakeholder’s requirements. The functionality, usability, reliability, performance, and security all turned out to be above average. System testing, integration testing and user acceptance testing had been conducted. Results showed that the system performed very satisfactory and functions as designed. Performance of the system is also affected by Internet infrastructure or connectivity of the university. The faculty analytics generated from the system may not only be used by Deans and Chairperson in their evaluation of faculty performance but as well as the individual faculty to increase awareness on their attendance in class. Hence, the system facilitates effective communication between system stakeholders through FAMS feedback mechanism and up to date posting of information.

Keywords: faculty attendance management system, MySQL, SQLite, FAMS, analytics

Procedia PDF Downloads 424

Authors: Nisha Thapa, Ram Prasad Mainali, Prakriti Chand

Abstract:

Broadleaf mustard is a commercialized leafy vegetable of Nepal. However, its utilization is hindered in terms of production and productivity due to the high intensity of insects, pests, and diseases causing great loss. The plant protection part of the crop’s disease and damage intensity has not been studied much from research perspectives in Nepal. The research aimed to evaluate broadleaf mustard genotypes for resistance against different diseases. A total of 35 native genotypes of broadleaf mustard were screened at weekly intervals by scoring the plants for ten weeks. Five different diseases, such as Rhizoctonia root rot, Alternaria blight, black rot, turnip mosaic virus disease, and white rust, were reported from the broad leaf mustard genotypes. Out of 35 genotypes, 23 genotypes were found with very high Rhizoctonia Root Rot severity, whereas 8 genotypes showed very high Alternaria blight severity. Likewise, 3 genotypes were found with high Black rot severity, and 1 genotype was found with very high Turnip mosaic virus disease incidence. Similarly, 2 genotypes were found to have very high White rust severity. Among the disease of national importance, Rhizoctonia root rot was found to be the most severe disease with the greatest loss. Broadleaf mustard genotypes like Rato Rayo, CO 1002, and CO 11007 showed average to the high level of field resistance; therefore, these genotypes should be used, conserved, and stored in a mustard improvement program as the disease resistance quality or susceptibility of these genotypes can be helpful for seed producing farmers, companies and other stakeholders through varietal improvement and developmental works that further aids in sustainable disease management of the vegetable.

Keywords: genotype, disease resistance, Rhizoctonia root rot severity, varietal improvement

Procedia PDF Downloads 57

Authors: Fatma Koksal Çakirlar, Si̇nem Ozdemir, Selcan Akyol, Revazi̇ye Gulesen, Murat Gunaydin, Nevri̇ye Gonullu, Belkis Levent, Nuri̇ Kiraz

Abstract:

Vibrio cholerae O1 and O139 are the causative agent of epidemic or pandemic cholera. V. cholerae O1 is generally accepted as a non-invasive enterotoxigenic organism causing gastroenteritis of various severities. Non-O1 V. cholerae can cause small outbreaks of diarrhea due to consumption of contaminated food and water. Particularly, the patients with achlorydria have a risk for vibrio infections. There are numerous case reports of bacteremia caused by vibrio in patients with predisposing conditions like cirrhosis, nephrotic syndrome, diabetes, hematologic malignancy, gastrectomy, and AIDS. We described in this study the first case of nontoxigenic, non-01/non-O139 V. cholerae isolated from the blood culture of a 77-year-old female patient with hipertension, diabetes, coronary artery disease, gout and about 9 years ago migrated breast cancer history. The patient with complaints of shortness of breath, fever and malaise admitted to our emergency clinic were evaluated. There was no diarrhea or abdominal symptoms in the patient. No growth in her urine culture, but blood culture (BACTEC 9120 system, Becton Dickinson, USA) was positive for non-01/non-O139 V. cholerae that was identified by conventional methods and Phoenix automated system (BD Diagnostic Systems, Sparks, MD). It does not secrete the cholera toxin. The agglutination test was negative with polyvalent O1 antisera and O139 antiserum. Empirically ceftriaxone was administered to the patient and she was discharged with improvement in general condition. In this study we report bacteremia by non-01/non-O139 V. cholerae that is rare in the worldwide and first in Turkey.

Keywords: bacteremia, blood culture, immunocompromised patient, Non-O1 vibrio cholerae

Procedia PDF Downloads 199

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

Procedia PDF Downloads 62

Authors: A. G. Margaryan

Abstract:

Aims and Objectives: Assessment of health status and detection disorders of external respiration functions (ERF) during preventative medical examination among physicians of Armenia. Subjects and Methods: Overall, fifty-nine physicians (17 men and 42 women) were examined and spirometry was carried out. The average age of the physicians was 50 years old. The studies were conducted on the Micromedical MicroLab 3500 Spirometer. Results: 25.4% among 59 examined physicians are overweight; 22.0% of them suffer from obesity. Two physicians are currently smokers. About half of the examined physicians (50.8%) at the time of examination were diagnosed with some diseases and had different health-related problems (excluding the problems related to vision and hearing). FVC was 2.94±0.1, FEV1 – 2.64±0.1, PEF – 329.7±19.9, and FEV₁%/FVC – 89.7±1.3. Pathological changes of ERF are identified in 23 (39.0%) cases. 28.8% of physicians had first degree of restrictive disorders, 3.4% – first degree of combined obstructive/ restrictive disorders, 6.8% – second degree of combined obstructive/ restrictive disorders. Only three physicians with disorders of the ERF were diagnosed with chronic bronchitis and bronchial asthma. There were no statistically significant changes in ERF depending on the severity of obesity (P> 0.05). Conclusion: The study showed the prevalence of ERF among physicians, observing mainly mild and moderate changes in ERF parameters.

Keywords: Armenia, external respiration function, health status, physicians

Procedia PDF Downloads 182

Authors: Renata Hrecska

Abstract:

This research aims to present today's corporate law reforms in the micro, small and medium-sized enterprise sector. The UN Commission on International Trade Law (UNCITRAL) currently deals with emerging issues in the sector in its Working Group I that has specifically focused on possible company law simplifications, including the creation of a fully unique company, the UNCITRAL Limited Liability Organization. However, beyond the work at the UN, the different states has also been focusing on simplification efforts and demands in the sphere of commercial law. We can observe that e.g. Slovakia, Serbia, Poland, Croatia, Hungary, Romania and France are undergoing legal reforms aimed at restructuring the sector through simplification of registration or operation. An important objective of the research is to examine where the boundary is for the legal entity to be more transparent and accountable, while the legislator wants to bring the possibility of establishing a company closer to the citizen. The research material presents the advantages and disadvantages of different initiatives with comparative legal instruments and draws conclusions on the possible future vision. The researcher herself attended some of the meetings of the relevant UNCITRAL working group as a national delegated expert, giving her a personal insight into the UNLLO discourse.

Keywords: commercial law, company formation, MSME, UNCITRAL

Procedia PDF Downloads 101

Authors: Hsiao-Yung Wang

Abstract:

This paper aims to elaborate methodology of visual rhetoric with constant reference to Mikhail Bakhtin’s concept of “chronotope”. First, it attempts to outline Ronald Barthes, the most representative scholar of visual rhetoric and structuralism, perspective on visual rhetoric and its time-space category by referring to the concurrent word-image, the symbolic systematicity, the outer dialogicity. Second, an alternative approach is explored for grasping the dynamics and functions of visual rhetoric by articulating Mikhail Bakhtin’s concept of “chronotope.” Furthermore, that visual rhetorical consciousness could be identified as “the meaning parabola which projects from word to image,” “the symbolic system which proceeds from sequence to disorder,” “the ideological environment which struggles from the local to the global.” Last but not least, primary vision of the 2014 Taipei LGBT parade would be analyzed preliminarily to evaluate the effectiveness and persuasiveness embodied by specific visual rhetorical strategies. How Bakhtin’s concept of “chronotope” to explain the potential or possible ideological struggle deployed by visual rhetoric might be interpreted empirically and extensively.

Keywords: barthes, chronotope, Mikhail Bakhtin, Taipei LGBT parade, visual rhetoric

Procedia PDF Downloads 453

Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

Abstract:

Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

Procedia PDF Downloads 197

Authors: Darko Babic, Maja Modric, Dario Babic, Mario Fiolic

Abstract:

For road markings as a part of traffic control plan, it is considered to have a positive impact on road safety. Their importance is particularly evident in low visibility conditions when the field of vision and the driver's visual acuity are significantly reduced. The aim of this article is to analyze how road marking retroreflectivity affects the frequency of traffic accidents in low visibility conditions. For this purpose, 10,417.4 km single carriageway roads were analysed across Croatia in the period from 2012 to 2016. The research included accidents that may be significantly affected by marking retroreflectivity: head-on collisions, running off the road, hitting a stationary object on the road and hitting a stationary roadside object. The results have shown that the retroreflectivity level is negatively correlated to the total number of accidents and the number of casualties and injuries, which ultimately means that the risk of traffic accidents and deaths and/or injuries of participants will be lower with the increase of road markings retroreflectivity. These results may assist in defining minimum values of retroreflectivity that the markings must meet at any time as well as the suitable technologies and materials for their implementation.

Keywords: retroreflectivity, road markings, traffic accidents, traffic safety

Procedia PDF Downloads 135

Authors: Thomas J. Bell III

Abstract:

Pursuing a business degree is fraught with perplexing questions regarding the rising tuition cost and the immediate value of earning a degree. Any decision to pursue an undergraduate business degree is perceived to have value if it facilitates post-graduate job placement. Business programs have decreased value in the absence of innovation in business programs that close the skills gap between recent graduates and employment opportunities. Industry-based certifications are seemingly becoming a requirement differentiator among job applicants. Texas Wesleyan University offers a Computer Information System (CIS) program with an innovative curriculum that integrates industry-recognized certification training into its traditional curriculum with core subjects and electives. This paper explores a culture of innovation in the CIS business program curriculum that creates sustainable stakeholder value for students, employers, the community, and the university. A quantitative research methodology surveying over one-hundred students in the CIS program will be used to examine factors influencing the success or failure of students taking certification exams. Researchers will analyze control variables to identify specific correlations between practice exams, teaching pedagogy, study time, age, work experience, etc. This study compared various exam preparation techniques to corresponding exam results across several industry certification exams. The findings will aid in understanding control variables with correlations that positively and negatively impact exam results. Such discovery may provide useful insight into pedagogical impact indicators that positively contribute to certification exam success and curriculum enhancement.

Keywords: taking certification exams, exam training, testing skills, exam study aids, certification exam curriculum

Procedia PDF Downloads 68

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 99

Authors: Chen Xi, Liu Xuebing, Lao Xuerui, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

Climate change is a global problem facing humanity and this is now the consensus of the mainstream scientific community. In accordance with the carbon peak and carbon neutral targets and visions set out in the United Nations Framework Convention on Climate Change, the Kyoto Protocol and the Paris Agreement, this project uses the City Intelligent Model (CIM) and Artificial Intelligence Machine Vision (ICR) as the core technologies to accurately quantify low carbon behaviour into green corn, which is a means of guiding ecologically sustainable living patterns. Using individual communities as management units and blockchain as a guarantee of fairness in the whole cycle of green currency circulation, the project will form a modern resident carbon track management system based on the principle of enhancing the ecological resilience of communities and the cohesiveness of community residents, ultimately forming an ecologically sustainable smart village that can be self-organised and managed.

Keywords: urban planning, urban governance, CIM, artificial Intelligence, sustainable development

Procedia PDF Downloads 66