Search results for: digital image correlation technology

Authors: Suphaphon Udomluck, Pannathorn Chachvarat

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Information Communication Technology (ICT) using management is essential for effective decision making in organization. The Concerns Based Adoption Model (CBAM) was employed as the conceptual framework. The purposes of the study were to assess the situation of Information Communication Technology (ICT) using management in College of Nursing under the Praboromarajchanok Institute. The samples were multi – stage sampling of 10 colleges of nursing that participated include directors, vice directors, head of learning groups, teachers, system administrator and responsible for ICT. The total participants were 280; the instrument used were questionnaires that include 4 parts, general information, Information Communication Technology (ICT) using management, the Stage of concern Questionnaires (SoC), and the Levels of Use (LoU) ICT Questionnaires respectively. Reliability coefficients were tested; alpha coefficients were 0.967for Information Communication Technology (ICT) using management, 0.884 for SoC and 0.945 for LoU. The data were analyzed by frequency, percentage, mean, standard deviation, Pearson Product Moment Correlation and Multiple Regression. They were founded as follows: The high level overall score of Information Communication Technology (ICT) using management and issue were administration, hardware, software, and people. The overall score of the Stage of concern (SoC)ICTis at high level and the overall score of the Levels of Use (LoU) ICTis at moderate. The Information Communication Technology (ICT) using management had the positive relationship with the Stage of concern (SoC)ICTand the Levels of Use (LoU) ICT(p < .01). The results of Multiple Regression revealed that administration hardwear, software and people ware could predict SoC of ICT (18.5%) and LoU of ICT (20.8%).The factors that were significantly influenced by SoCs were people ware. The factors that were significantly influenced by LoU of ICT were administration hardware and people ware.

Keywords: information communication technology (ICT), management, the concerns-based adoption model (CBAM), stage of concern(SoC), the levels of use(LoU)

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Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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Authors: Mazhar Hamayun

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Organizations need to take a holistic approach to their Zero Trust strategic and tactical security needs. This includes using a framework-agnostic model that will ensure all enterprise resources are being accessed securely, regardless of their location. Such can be achieved through the implementation of a security posture, monitoring the posture, and adjusting the posture through the Identify, Detect, Protect, Respond, and Recover Methods, The target audience of this document includes those involved in the management and operational functions of risk, information security, and information technology. This audience consists of the chief information security officer, chief information officer, chief technology officer, and those leading digital transformation initiatives where Zero Trust methods can help protect an organization’s data assets.

Keywords: ZTNA, zerotrust architecture, microsegmentation, NIST SP 800-207

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Authors: Snehal G. Teli, R. J. Shelke

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CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: James R. Ogden, Denise T. Ogden

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The National Football League (USA) is the largest sporting business in the United States. In order to generate revenue, it is important that NFL teams win. Coaches, owners and general managers of the NFL teams want to create powerful teams with reliable players and they are willing to spend large amounts of money in order to do so. This research looks at one of the National Football League’s key players, the kicker. It would be intuitively obvious to suggest that those kickers who perform the best get paid the most. In this paper the researchers performed a correlation and regression analysis to determine if there is a correlation between an NFL kicker’s field goal percentage and salary. The research proposition was that higher performing kickers receive higher salaries. The data suggest that there is no correlation between salary and on-field performance.

Keywords: business management, sports marketing, tourism, American football

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Authors: Oluronke Odunjo

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The world is becoming increasingly urbanized and Nigeria is not left out. One of the indicators of human developments is housing and as such, water is needed by households for survival. This Paper assesses sources of water being used by residents in the newly urbanized areas of Ogbomoso, Southwest, Nigeria. Multistage sampling technique was used and Oke-Adunin Community was purposively selected for the study as it has large concentration of staff and students of Ladoke Akintola University of Technology. The area was captured with Google earth and two hundred and twenty two inhabited houses were found. Questionnaire was the instrument for data collection which was administered using total enumeration technique. Data obtained however, were analyzed with descriptive and inferential statistical analyses. Findings revealed that most of the respondents were male, while 36.03% house owners were between the ages of 46 and 55 years. Sources of water used by residents include well (56.94%), water vendors (17.77%), rain (15.29%) and borehole (3.72%). Distance travelled by house owners to sources of water was as high as 5.06 metres, resulting into stress (30.00 %), depression (25.00%) and aggressiveness (18.75%). Result of correlation analysis between the sources of water of respondents and disease prevalence showed that both rain water and water vendor had very strong positive correlation with typhoid, diarrhea and dysentery, while well water only had positive correlation with dysentery. Recommendations were therefore, proffered towards solving the problems associated with water in the area.

Keywords: newly urbanized area, Ogbomoso, sources of water, residents

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

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Authors: R. Cooper, M. Kurien

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Background: Coeliac Disease affects around 1 in 100 people. Untreated, it can result in serious morbidity such as malabsorption and cancers. The only treatment is to adhere to a gluten free diet (GFD). International guidelines recommend that people with the coeliac disease receive follow-up healthcare annually to detect complications early and support their adherence to a GFD. However, there is a finite amount of healthcare in the UK, and as such, not all patients receive follow-up care as recommended by the guidelines. Furthermore, there is an increasing number of patients being diagnosed with coeliac disease. Given the potential severe morbidity that non-adherence to a GFD could result in, alongside reports that the rate of non- GFD adherence could be as high as 91%, it is imperative that action is taken. One potential solution to this would be to provide follow-up care digitally through utilising technology. This abstract reports on a rapid review undertaken to explore the existing evidence in this area. Methods: In June 2020, 11 bibliographic databases were searched to find any pertinent studies. The inclusion criteria required the study to be written in the English language and report on the use of digital healthcare interventions for people with Coeliac Disease. Results: A small amount of evidence (n=8) was found which met our inclusion criteria and pertained to the provision of CD follow-up digitally. These studies focussed either on educating and supporting patients to adhere to a GFD or providing consultation remotely with a focus on detecting complications early. These studies showed that there is potential for digital healthcare interventions to positively impact people with coeliac disease. However, it is suggested that the effectiveness of these interventions may depend on local circumstances, individual knowledge of CD and general attitudes. Conclusion: The above studies suggest that providing follow-up care digitally may offer a potential solution; however, the evidence about how this should be done and in what circumstances this will work for individuals is scarce. In the light of the COVID-19 pandemic, the introduction of digital healthcare interventions appears to be highly topical, and as such, this review may benefit from being refreshed in the future.

Keywords: coeliac disease, follow-up, gluten free diet, digital healthcare interventions

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Authors: Rene Hellmuth, Jorg Frohnmayer

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The requirements of the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Even today, the methods and process models used in factory planning are predominantly based on the classical planning principles of Schmigalla, Aggteleky and Kettner, which, however, are not specifically designed for reorganization. In addition, they are designed for a largely static environmental situation and a manageable planning complexity as well as for medium to long-term planning cycles with a low variability of the factory. Existing approaches already regard factory planning as a continuous process that makes it possible to react quickly to adaptation requirements. However, digital factory models are not yet used as a source of information for building data. Approaches which consider building information modeling (BIM) or digital factory models in general either do not refer to factory conversions or do not yet go beyond a concept. This deficit can be further substantiated. A method for factory conversion planning using a current digital building model is lacking. A corresponding approach must take into account both the existing approaches to factory planning and the use of digital factory models in practice. A literature review will be conducted first. In it, approaches to classic factory planning and approaches to conversion planning are examined. In addition, it will be investigated which approaches already contain digital factory models. In the second step, an approach is presented how digital factory models based on building information modeling can be used as a basis for augmented reality tablet applications. This application is suitable for construction sites and provides information on the costs and time required for conversion variants. Thus a fast decision making is supported. In summary, the paper provides an overview of existing factory planning approaches and critically examines the use of digital tools. Based on this preliminary work, an approach is presented, which suggests the sensible use of digital factory models for decision support in the case of conversion variants of the factory building. The augmented reality application is designed to summarize the most important information for decision-makers during a reconstruction process.

Keywords: augmented reality, digital factory model, factory planning, restructuring

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Authors: Guantao Bai

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Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

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Authors: Judith Hanke

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Due to the increase of students with reading difficulties, digital reading support with diagnostics was developed to foster the individual student's reading comprehension. The digital reading support focused on the reading comprehension of elementary school students. The digital reading packages consist of literary texts with aligned reading exercises. The number of students with German as a second language is growing in Germany. Students with multilingualism, language 1, and language 2 learn German together in school. The research's focus is on determining whether and to what extent multilingualism, language 1, and language 2 affect reading comprehension. For the methodology, an ABA design was selected for the intervention study to examine the reading support. The study was expedited from April 2023 until July 2023 and collected quantitative data of individuals, groups, and classes. It comprised a survey group (N = 58) and a control group (N = 53). The quantitative data was collected from 3 classes of 3 teachers and 47 students for all three test times. To show differences between the groups, a standardized reading comprehension test was used for the three test times, pretest, posttest, and follow-up. The standardized test consists of three subtests regarding word comprehension, sentence comprehension, and text comprehension. The main findings include that students who spoke German as their first language had the best test scores. Interestingly, students with a different language had better testing scores than students with German as the first language and (an) other language/s. Also, the students with another language outperformed the native language speakers in one of the subtests of the post-testing. The variables of spoken language at home and German as a second language were also examined and correlated with the test results. One significant correlation was found between spoken language at home and the text comprehension test of the pretesting. Additionally, the variable German as a second language had multiple significant correlations in the pretest, posttest and follow-up. The study's significance is to understand the influence of several languages, language 1, and language 2, on reading comprehension.

Keywords: multilingualism, language 1, language 2, reading comprehension, second language

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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Authors: Tokuei Sako

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The ground and low-lying singly-excited states of He and He-like atomic ions have been studied by the Full Configuration Interaction (FCI) method focusing on the angular correlation between two electrons in the studied systems. The two-electron angle density distribution obtained by integrating the square-modulus of the FCI wave function over the coordinates other than the interelectronic angle shows a distinct trend between the singlet-triplet pair of states for different values of the nuclear charge Zn. Further, both of these singlet and triplet distributions tend to show an increasingly stronger dependence on the interelectronic angle as Zn increases, in contrast to the well-known fact that the correlation energy approaches towards zero for increasing Zn. This controversial observation has been rationalized on the basis of the recently introduced concept of so-called conjugate Fermi holes.

Keywords: He-like systems, angular correlation, configuration interaction wave function, conjugate Fermi hole

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Authors: Ranj Tofik

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This article aims to demonstrate a link and/or correlation between the rise of China and the US-Iranian conflict, from a US point of view. To demonstrate this link, the article relies on the content analysis method by analyzing American reports and official data. This article concludes that this correlation indicates that the more China rises and the greater the Chinese threat to America, the more changes will occur in the US-Iranian conflict and the US actions regarding this conflict will increase – in the form of imposing sanctions and using means of pressure on Iran, or trying to reach an agreement and settlement with Iran. This article, via noting and observing that correlation, also claims that before 2012, Iran was a regional threat to US interests in the Middle East. However, after 2012 when the rise of China became one of the major threats to America, Iran, because of its rapprochement with China, became also part of the Chinese threat, which is a threat to America's global standing. In addition, observing this correlation indicates the possibility that the rise of China and its threat to the USA has become one of the main drivers in the US-Iranian conflict. Consequently, it can be said that Iran has become a vital issue in the US-China rivalry, as it has become an appropriate gateway for China to enter the Middle East and undermine US hegemony there.

Keywords: China-Iran relations, China's rise, JCPOA, US-Chinese competition, US-Iranian conflict

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Authors: Shubha T., Latha H. K. E., Yogananth Karuppiah

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Accessing and sharing automobiles will become much simpler thanks to the wide range of automotive use cases made possible by digital keys. This study aims to provide digital keys to car owners and drivers so they can lock or unlock their automobiles and start the engine using a smartphone or other Bluetooth low energy-enabled mobile device. Private automobile owners can digitally lend their car keys to family members or friends without having to physically meet them, possibly for a certain period of time. Owners of company automobile fleets can electronically distribute car keys to staff members, possibly granting access for a given day or length of time. Customers no longer need to physically pick up car keys at a rental desk because automobile owners can digitally transfer keys with them.

Keywords: NFC, BLE, CCC, digital key, OEM

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Authors: Jianrong Wu, Xuan Fu, Akihiro Higashi, Zhiming Tan

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CMOS image sensors with a rolling shutter are used broadly in the digital cameras embedded in mobile devices. The rolling shutter suffers the flicker artifacts from the fluorescent lamp, and it could be observed easily. In this paper, the characteristics of illumination flicker in motion case were analyzed, and two efficient detection methods based on matching fragment selection were proposed. According to the experimental results, our methods could achieve as high as 100% accuracy in static scene, and at least 97% in motion scene.

Keywords: illumination flicker, embedded camera, rolling shutter, detection

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Authors: Tayaa Karima, Bouaziz Amina

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Today's world is knowledge-based; everything we do is somehow connected with technology which it has a remarkable influence on socio-cultural and economic developments, including educational settings. This type of technology is supported in many teaching/learning setting where the medium of instruction is through computer technology, and particularly involving digital technologies. There has been much debate over the use of computers and the internet in foreign language teaching for more than two decades. Various studies highlights that the integration of Information Communications Technology (ICT) in foreign language teaching will have positive effects on both the teachers and students to help them be aware of the modernized world and meet the current demands of the globalised world. Information and communication technology has been gradually integrated in foreign learning environment as a platform for providing learners with learning opportunities. Thus, the impact of ICT on language teaching and learning has been acknowledged globally, this is because of the fundamental role that it plays in the enhancement of teaching and learning quality, modify the pedagogical practice, and motivate learners. Due to ICT related developments, many Maghreb countries regard ICT as a tool for changes and innovations in education. Therefore, the ministry of education attempted to set up computer laboratories and provide internet connection in the schools. Investment in ICT for educational innovations and improvement purposes has been continuing the need of teacher who will employ it in the classroom as vital role of the curriculum. ICT does not have an educational value in itself, but it becomes precious when teachers use it in learning and teaching process. This paper examines the impacts of ICT on teacher development rather than on teaching quality and highlights some challenges facing using ICT in the language learning/teaching.

Keywords: information communications technology (ICT), integration, foreign language teaching, teacher development, learning opportunity

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Authors: Kaznah Alshammari, Thomas Beach, Yacine Rezgui

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Technological advances in the construction sector are helping to make smart cities a reality by means of cyber-physical systems (CPS). CPS integrate information and the physical world through the use of information communication technologies (ICT). An increasingly common goal in the built environment is to integrate building information models (BIM) with the Internet of Things (IoT) and sensor technologies using CPS. Future advances could see the adoption of digital twins, creating new opportunities for CPS using monitoring, simulation, and optimisation technologies. However, researchers often fail to fully consider the security implications. To date, it is not widely possible to assimilate BIM data and cybersecurity concepts, and, therefore, security has thus far been overlooked. This paper reviews the empirical literature concerning IoT applications in the built environment and discusses real-world applications of the IoT intended to enhance construction practices, people’s lives and bolster cybersecurity. Specifically, this research addresses two research questions: (a) how suitable are the current IoT and CPS security stacks to address the cybersecurity threats facing digital twins in the context of smart buildings and districts? and (b) what are the current obstacles to tackling cybersecurity threats to the built environment CPS? To answer these questions, this paper reviews the current state-of-the-art research concerning digital twins in the built environment, the IoT, BIM, urban cities, and cybersecurity. The results of these findings of this study confirmed the importance of using digital twins in both IoT and BIM. Also, eight reference zones across Europe have gained special recognition for their contributions to the advancement of IoT science. Therefore, this paper evaluates the use of digital twins in CPS to arrive at recommendations for expanding BIM specifications to facilitate IoT compliance, bolster cybersecurity and integrate digital twin and city standards in the smart cities of the future.

Keywords: BIM, cybersecurity, digital twins, IoT, urban cities

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

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This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: Moudi Almousa

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This research paper explores Saudi Arabian female consumers’ experiences using 3D body scanning technology and their level of acceptance of possible market applications of this technology to adopt for apparel online shopping. Data was collected for 82 women after being scanned then viewed a short video explaining three possible scenarios of 3D body scanning applications, which include size prediction, customization, and virtual try-on, before completing the survey questionnaire. Although respondents have strong positive responses towards the scanning experience, the majority were concerned about their privacy during the scanning process. The results indicated that size prediction and virtual try on had greater market application potential and a higher chance of crossing the gap based on consumer interest. The results of the study also indicated a strong positive correlation between respondents’ concern with inability to try on apparel products in online environments and their willingness to use the 3D possible market applications.

Keywords: 3D body scanning, market applications, online, apparel fit

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Takaaki Miyabe, Hideharu Takahashi, Hiroshige Kikura

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The Government of Japan and Tokyo Electric Power Company Holdings, Incorporated (TEPCO) are struggling with the decommissioning of Fukushima Daiichi Nuclear Power Plants, especially fuel debris retrieval. In fuel debris retrieval, amount of fuel debris, location, characteristics, and distribution information are important. Recently, a survey was conducted using a robot with a small camera. Progress report in remote robot and camera research has speculated that fuel debris is present both at the bottom of the Pressure Containment Vessel (PCV) and inside the Reactor Pressure Vessel (RPV). The investigation found a 'tie plate' at the bottom of the containment, this is handles on the fuel rod. As a result, it is assumed that a hole large enough to allow the tie plate to fall is opened at the bottom of the reactor pressure vessel. Therefore, exploring the existence of holes that lead to inside the RCV is also an issue. Investigations of the lower part of the RPV are currently underway, but no investigations have been made inside or above the PCV. Therefore, a survey must be conducted for future fuel debris retrieval. The environment inside of the RPV cannot be imagined due to the effect of the melted fuel. To do this, we need a way to accurately check the internal situation. What we propose here is the adaptation of a technology called 'Structure from Motion' that reconstructs a 3D image from multiple photos taken by a single camera. The plan is to mount a monocular camera on the tip of long-arm robot, reach it to the upper part of the PCV, and to taking video. Now, we are making long-arm robot that has long-arm and used at high level radiation environment. However, the environment above the pressure vessel is not known exactly. Also, fog may be generated by the cooling water of fuel debris, and the radiation level in the environment may be high. Since camera alone cannot provide sufficient sensing in these environments, we will further propose using ultrasonic measurement technology in addition to cameras. Ultrasonic sensor can be resistant to environmental changes such as fog, and environments with high radiation dose. these systems can be used for a long time. The purpose is to develop a system adapted to the inside of the containment vessel by combining a camera and an ultrasound. Therefore, in this research, we performed a basic experiment on 3D image reconstruction using a camera and ultrasound. In this report, we select the good and bad condition of each sensing, and propose the reconstruction and detection method. The results revealed the strengths and weaknesses of each approach.

Keywords: camera, image processing, reconstruction, ultrasound

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Shola Abidemi Olabode

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Nigeria as a country has been plagued by numerous conflicts since the British colonialists gave in to the advocacy of Nigerian dissents for independence and relinquished power in 1960. These conflicts are often motivated by different issues, from socio-political and economic issues to struggles of ethnic and religious orientation. The Niger Delta region which accounts for the country’s economic mainstay has been at the epicentre of such conflicts. Over the years, peaceful protests, and radical insurgency and resistance movements too numerous to mention have emerged in the region. The Niger Delta Avengers is an example of a recent conflict movement in the region. Using a case study approach, and looking through a cyberconflict perspective, this paper offers a discussion on the intersection between digital and social media and framing in the Niger Delta Avengers conflict. It advocates that the Niger Delta Avengers use digital and social media to legitimise and give credence to their struggle.

Keywords: digital and social media, framing, Niger delta avengers, cyberconflict, conflict

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Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

Abstract:

Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 403

Authors: Shivangi Agrawal, Hsiu-I Ting

Abstract:

Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g., online entrepreneurship education courses and programs) and other digital tools (e.g., digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.

Keywords: entrepreneurship education, digital technologies, academic entrepreneurship, COVID-19

Procedia PDF Downloads 259

Authors: Zihan Yu, Kohei Inoue, Kiichi Urahama

Abstract:

We present a method for de-hazing images. A dark envelope image is derived with the bilateral minimum filter and a bright envelope is derived with the bilateral maximum filter. The ambient light and transmission of the scene are estimated from these two envelope images. An image without haze is reconstructed from the estimated ambient light and transmission.

Keywords: image dehazing, bilateral minimum filter, bilateral maximum filter, local contrast

Procedia PDF Downloads 263

Authors: Kevin Wongleedee

Abstract:

The purposes of this research were to study the image of a flight attendant career from the perspective of high school students in Bangkok and to study the level of interest to pursue a flight attendant career. A probability random sampling of 400 students was utilized. Half the sample group came from private high schools and the other half came from public high schools. A questionnaire was used to collect the data and small in-depth interviews were also used to get their opinions about the image and their level of interest in the flight attendant career. The findings revealed that the majority of respondents had a medium level of interest in the flight attendant career. High school students who majored in Math-English were more interested in a flight attendant career than high school students who majored in Science-Math with a 0.05 level of significance. The image of flight attendant career was rated as a good career with a chance to travel to many countries. The image of flight attendance career can be ranked as follows: a career with a chance to travel, a career with ability to speak English, a career that requires punctuality, a career with a good service mind, and a career with an understanding of details. The findings from the in-depth interviews revealed that the major obstacles that prevented high school students from choosing a flight attendant as a career were their ability to speak English, their body proportions, and lack of information.

Keywords: flight attendant, high school students, image, media engineering

Procedia PDF Downloads 369

Authors: Davood Barari Tari

Abstract:

In order to investigate the correlation of rice traits in different nitrogen management methods by modeling programming, an experiment was laid out in rice paddy field in an experimental field at Caspian Coastal Sea region from 2013 to 2014. Variety used was Shiroudi as a high yielding variety. Nitrogen management was in two methods. Amount of nitrogen at four levels (30, 60, 90, and 120 Kg N ha-1 and control) and nitrogen-splitting at four levels (T1: 50% in base + 50% in maximum tillering stage, T2= 33.33% basal +33.33% in maximum tillering stage +33.33% in panicle initiation stage, T3=25% basal+37.5% in maximum tillering stage +37.5% in panicle initiation stage, T4: 25% in basal + 25% in maximum tillering stage + 50% in panicle initiation stage). Results showed that nitrogen traits, total grain number, filled spikelets, panicle number per m2 had a significant correlation with grain yield. Results related to calibrated and validation of rice model methods indicated that correlation between rice yield and yield components was accurate. The correlation between panicle length and grain yield was minimum. Physiological indices was simulated with low accuracy. According to results, investigation of the correlation between rice traits in physiological, morphological and phenological characters and yield by modeling and simulation methods are very useful.

Keywords: rice, physiology, modelling, simulation, yield traits

Procedia PDF Downloads 343