Search results for: visual recognition

Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Mohammad I. Hossain, Omar F. Hamim

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This paper presents a case study on a pile integrity test for assessing the integrity of piles as well as a physical dimension (e.g., cross-sectional area, length), continuity, and consistency of the pile materials. The recent boom in the socio-economic condition of Bangladesh has given rise to the building of high-rise commercial and residential infrastructures. The advantage of the pile integrity test lies in the fact that it is possible to get an approximate indication regarding the quality of the sub-structure before commencing the construction of the super-structure. This paper aims at providing a classification of cast-in-situ piles based on characteristic reflectograms obtained using the Sonic Integrity Testing program for the sub-soil condition of Narayanganj, Bangladesh. The piles have been classified as 'Pile Type-1', 'Pile Type-2', 'Pile Type-3', 'Pile type-4', 'Pile Type-5' or 'Pile Type-6' from the visual observations of reflections from the generated stress waves by striking the pile head with a handheld hammer. With respect to construction quality and integrity, piles have been further classified into three distinct categories, i.e., satisfactory, may be satisfactory, and unsatisfactory.

Keywords: cast-in-situ piles, characteristic reflectograms, pile integrity test, sonic integrity testing program

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Authors: Anne Eugenia Wright

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This study examines issues in accessibility to maritime cultural heritage. Using the Pillar Dollar Wreck in Biscayne National Park, Florida, this study presents an approach to public outreach based on the concept of Design for All. Design for All advocates creating products that are accessible and functional for all users, including those with visual, hearing, learning, mobility, or economic impairments. As a part of this study, a small exhibit was created that uses 3D products as a way to bring maritime cultural heritage to the public. It was presented to the public at East Carolina University’s Joyner Library. Additionally, this study presents a methodology for 3D printing scaled photogrammetry models of archaeological sites in full color. This methodology can be used to present a realistic depiction of underwater archaeological sites to those who are incapable of accessing them in the water. Additionally, this methodology can be used to present underwater archaeological sites that are inaccessible to the public due to conditions such as visibility, depth, or protected status. This study presents a practical use for 3D photogrammetry models, as well as an accessibility strategy to expand the outreach potential for maritime archaeology.

Keywords: Underwater Archaeology, 3D Printing, Photogrammetry, Design for All

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Authors: H. Shafaattalab Dehghani, H. R. Zarei

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The large karstic Bell spring with a discharge ranging between 250 and 5300 lit/ sec is one of the most important springs of Kermanshah Province. This spring supplies drinking water of Nodsheh City and its surrounding villages. The spring is located in the reservoir of Daryan Dam and its mouth would be submerged after impounding under a water column of about 110 m height. This paper has aimed to render an account of the karstification pattern around the spring under consideration with the intention of preventing Bell Spring from being submerged in Daryan Dam Reservoir. The studies comprise engineering geology and hydrogeology investigations. Some geotechnical activities included in these studies include geophysical studies, drilling, excavation of exploratory gallery and shaft and diving. The results depict that Bell is a single-conduit siphon spring with 4 m diameter and 85 m height that 32 m of the conduit is located below the spring outlet. To survive the spring, it was decided to plug the outlet and convey the water to upper elevations under the natural pressure of the aquifer. After plugging, water was successfully conveyed to elevation 837 meter above sea level (about 120 m from the outlet) under the natural pressure of the aquifer. This signifies the accuracy of the studies done and proper recognition of the karstification pattern of Bell Spring. This is a unique experience in karst problems in Iran.

Keywords: bell spring, Karst, Daryan Dam, submerged

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Authors: Sabiu Bala Muhammad, Rosli Saad

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Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy.

Keywords: apparent resistivity, depth, horizontal location, multiple linear regression, true resistivity

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Authors: Alexis Dorado, Aralyn Quintos

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This study explores the utilization of natural dyes for wood stains as a transformative agent for wood, encompassing color alteration, grain enhancement, and protection against harm. Commonly, wood stains are petroleum-based and synthetically derived. Notably, commercially accessible wood stains exhibit around 4% greater volatility than the formulated wood stain (FWS), potentially indicating a heightened environmental impact. The application of FWS does not significantly affect the performance of polyurethane varnish. The impact of incorporating an FWS when was applied to Gmelina arborea wood sample, the initial lightness value (L*) of 68.5, a* 7.7, b* 29.2 decreased to 44.36, a* 23.49, b* 32.60, where a* denotes the red/ green value, b* denotes the yellow/ blue, indicating a shift towards darker shades. This alteration in lightness suggests that the FWS contains compounds or pigments that effectively absorb or scatter light, resulting in a change in the perceived color and visual appearance of the wood surface. Moreover, the successful formulation of an eco-friendly natural wood stain is detailed, presenting a promising alternative. This method finds applicability in the domains of furniture and handicraft creation, offering a sustainable choice for creative artisans.

Keywords: formulated wood stain (FWS), natural dyes, wood stains, eco-friendly natural wood stain,

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Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism

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Authors: Debasis Sarkar

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Building Information Modeling (BIM) is a holistic documentation process for operational visualization, design coordination, estimation and project scheduling. BIM software defines objects parametrically and it is a tool for virtual reality. Primary advantage of implementing BIM is the visual coordination of the building structure and systems such as Mechanical, Electrical and Plumbing (MEP) and it also identifies the possible conflicts between the building systems. This paper is an attempt to develop a risk based BIM model which would highlight the primary advantages of application of BIM pertaining to urban infrastructure transportation project. It has been observed that about 40% of the Architecture, Engineering and Construction (AEC) companies use BIM but primarily for their outsourced projects. Also, 65% of the respondents agree that BIM would be used quiet strongly for future construction projects in India. The 3D models developed with Revit 2015 software would reduce co-ordination problems amongst the architects, structural engineers, contractors and building service providers (MEP). Integration of risk management along with BIM would provide enhanced co-ordination, collaboration and high probability of successful completion of the complex infrastructure transportation project within stipulated time and cost frame.

Keywords: building information modeling (BIM), infrastructure transportation, project risk management, underground metro rail

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Authors: Farzad Khajavi

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Recognition of the interaction between active pharmaceutical ingredients (API) and excipients is a pivotal factor in the development of all pharmaceutical dosage forms. By predicting the interaction between API and excipients, we will be able to prevent the advent of impurities or at least lessen their amount. In this study, we used principle component analysis (PCA) to predict the interaction between Gliclazide as a secondary amine with Lactose in pharmaceutical solid dosage forms. The infrared spectra of binary mixtures of Gliclazide with Lactose at different mole ratios were recorded, and the obtained matrix was analyzed with PCA. By plotting score columns of the analyzed matrix, the incompatibility between Gliclazide and Lactose was observed. This incompatibility was seen experimentally. We observed the appearance of the impurity originated from the Maillard reaction between Gliclazide and Lactose at the chromatogram of the manufactured tablets in room temperature and under accelerated stability conditions. This impurity increases at the stability months. By changing Lactose to Mannitol and using Calcium Dibasic Phosphate in the tablet formulation, the amount of the impurity decreased and was in the acceptance range defined by British pharmacopeia for Gliclazide Tablets. This method is a fast and simple way to predict the existence of incompatibility between excipients and active pharmaceutical ingredients.

Keywords: PCA, gliclazide, impurity, infrared spectroscopy, interaction

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Authors: Dimitrios Akrivos, Alexandros K. Antoniou

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This paper looks at the crucial role of the British news media in the construction of extreme pornography as a social problem, suggesting that this paved the way for the subsequent criminalization of such material through the introduction of the Criminal Justice and Immigration Act 2008. Focusing on the high-profile case of Graham Coutts, it examines the British national press’ reaction to Jane Longhurst’s murder through a qualitative content analysis of 251 relevant news articles. Specifically, the paper documents the key arguments expressed in the corresponding claims-making process. It considers the different ways in which the consequent ‘trial by media’ presented this exceptional case as the ‘tip of the iceberg’ and eventually translated into policy. The analysis sheds light on the attempts to ‘piggyback’ the issue of extreme pornography on child sexual abuse images as well as the textual and visual mechanisms used to establish an ‘us versus them’ dichotomy in the pertinent media discourse. Finally, the paper assesses the severity of the actual risk posed by extreme pornography, concluding that its criminalization should not merely be dismissed as the outcome of an institutionalized media panic.

Keywords: criminalization, extreme pornography, social problem, trial by media

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

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Authors: Eric Agrie Ambele

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The norms and models for learning pronunciation in relation to the teaching and learning of English pronunciation are key issues nowadays in English Language Teaching in ESL contexts. This paper discusses these issues based on a study on the attitudes of some Francophone university students in Cameroon towards three English accents spoken in Cameroon: Cameroon Francophone English (CamFE), Cameroon English (CamE), and Hyperlectal Cameroon English (near standard British English). With the desire to know more about the treatment that these English accents receive among these students, an aspect that had hitherto received little attention in the literature, a language attitude questionnaire, and the matched-guise technique was used to investigate this phenomenon. Two methods of data analysis were employed: (1) the percentage count procedure, and (2) the semantic differential scale. The findings reveal that the participants’ attitudes towards the selected accents vary in degree. Though Hyperlectal CamE emerged first, CamE second and CamFE third, no accent, on average, received a negative evaluation. It can be deduced from this findings that, first, CamE is gaining more and more recognition and can stand as an autonomous accent; second, that the participants all rated Hyperlectal CamE higher than CamE implies that they would be less motivated in a context where CamE is the learning model. By implication, in the teaching of English pronunciation to francophone learners learning English in Cameroon, Hyperlectal Cameroon English should be the model.

Keywords: teaching pronunciation, English accents, Francophone learners, attitudes

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Authors: Yuying Liu

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Despite the increasing popularity of Chinese and the recognition of the growing commodifying ideology of Chinese language in many contexts (Liu and Gao, 2020; Guo, Shin and Shen 2020), the ideological orientations of the Chinese diaspora community towards the Chinese language remain under-researched. This research contributes seeks to bridge this gap by investigating the micro-level language ideologies embedded in the Chinese complementary schools in the Republic of Ireland. Informed by Ruíz’s (1984) metaphorical representations of language, 11 Chinese complementary schools’ websites were analysed as discursive texts that signal the language policy and ideology to prospective learners and parents were analysed. The results of the analysis suggest that a move from a portrayal of Chinese as linked to student heritage identity, to the commodification of linguistic and cultural diversity, is evident. It denotes the growing commodifying ideology among the Chinese complementary schools in the Republic of Ireland. The changing profile of the complementary school, from serving an ethnical community to teaching Chinese as a foreign language for the wider community, indicates the possibility of creating the a positive synergy between the Complementary school and the mainstream education. This study contributes to the wider discussions of language ideology and language planning, with regards to modern language learning and heritage language maintenance.

Keywords: the Chinese language;, Chinese as heritage language, Chinese as foreign language, Chinese community schools

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

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Authors: Kazi Hossain

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The National Australian Built Environment Rating System (NABERS) is the key industry standard for measuring and benchmarking environmental performance of existing buildings in Australia. Developed and run by the New South Wales government, NABERS measures the operational efficiency of different types of buildings by using a set of tools that provide an easy to understand graphical rating outcome ranged from 0 to 6 stars. This set of tools also include a tool called NABERS IE which enables tenants or building managers to benchmark their buildings indoor environment quality against the national market. Launched in 2009, the number NABERS IE ratings have steadily increased from 10 certified ratings in 2011 to 43 in 2013. However there is a massive uptake of over 50 ratings alone in 2014 making the number of ratings to reach over 100. This paper outlines the methodology used to create this tool, a statistical overview of the tool, and the driving factor that motivates the building owners and managers to use this tool every year to rate their buildings.

Keywords: Acoustic comfort, Indoor air quality, Indoor Environment, NABERS, National Australian Built Environment Rating System, Performance rating, Rating System, Thermal comfort, Ventilation effectiveness, Visual comfort.

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Authors: Omer Abdalla Ishag, Magdi Baker Amien

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Physicians used the stethoscope for listening patient heart sounds in order to make a diagnosis. However, the determination of heart conditions by acoustic stethoscope is a difficult task so it requires special training of medical staff. This study developed an accurate model for analyzing the phonocardiograph signal based on PC and DSP processor. The system has been realized into two phases; offline and real time phase. In offline phase, 30 cases of heart sounds files were collected from medical students and doctor's world website. For experimental phase (real time), an electronic stethoscope has been designed, implemented and recorded signals from 30 volunteers, 17 were normal cases and 13 were various pathologies cases, these acquired 30 signals were preprocessed using an adaptive filter to remove lung sounds. The background noise has been removed from both offline and real data, using wavelet transform, then graphical and statistics features vector elements were extracted, finally a look-up table was used for classification heart sounds cases. The obtained results of the implemented system showed accuracy of 90%, 80% and sensitivity of 87.5%, 82.4% for offline data, and real data respectively. The whole system has been designed on TMS320VC5509a DSP Platform.

Keywords: code composer studio, heart sounds, phonocardiograph, wavelet transform

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Kaitlyn Deierlein, Janet Lydecker

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Stereotypes surrounding anorexia nervosa are that the illness is commonly perceived as a self-inflicted disorder influenced by controlling parents, vanity, and cultural pressures. According to the authors' best knowledge minimal research has examined interactions with other factors, including gender and racial stereotypes involving this disorder. A common stereotype of this disease is that it mainly only affects Caucasian women and is very rarely seen in any other ethnicity. Previous literature has failed to investigate how visual body image and ethnic stereotypes affect the mental health of different ethnic groups, how various cultures impact the type of anorexia nervosa in the patient, and the different stereotypes associated with their eating disorder. Participants completed a pre-test questionnaire with vignettes, an image exposure portion, and a post-test questionnaire, which will all be evaluated and analyzed by ANOVA t-test and SPSS. Results showed that participants picked Caucasian females as more likely to have anorexia nervosa than those of Asian, Latin American, or African American descent subjects in both picture identification and vignettes. Future research should be conducted to further the results of this study by examining differences between gender stereotypes with anorexia nervosa as well as how sexuality has a role in perception.

Keywords: anorexia nervosa, ethnicity, stereotypes, eating disorders, perception

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Authors: B. C. Biermann

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This in-depth exploration investigates the transformative integration of urban vibrancy into contemporary interior design through the strategic incorporation of vivid wall pieces. Bridging the gap between public dynamism and private tranquility, this study delves into the nuanced methodologies, creative processes, and profound impacts of this innovative approach. Drawing inspiration from street art's dynamic language and the timeless allure of natural beauty, these artworks serve as conduits, orchestrating a dialogue that challenges traditional boundaries and redefines the relationship between external chaos and internal sanctuaries. The fusion of urban vibrancy with contemporary interior design represents a paradigm shift, where the inherent dynamism of public spaces harmoniously converges with the curated tranquility of private environments. This paper aims to explore the underlying principles, creative processes, and transformative impacts of integrating vivid wall pieces as instruments for bringing the "outside in." Employing an innovative and meticulous methodology, street art elements are synthesized with the refined aesthetics of contemporary design. This delicate balance necessitates a nuanced understanding of both artistic realms, ensuring a synthesis that captures the essence of urban energy while seamlessly blending with the sophistication of modern interior design. The creative process involves a strategic selection of street art motifs, colors, and textures that resonate with the organic beauty found in natural landscapes, creating a symbiotic relationship between the grittiness of the streets and the elegance of interior spaces. This groundbreaking approach defies traditional boundaries by integrating dynamic street art into interior spaces, blurring the demarcation between external chaos and internal tranquility. Vivid wall pieces serve as dynamic focal points, transforming physical spaces and challenging conventional perceptions of where art belongs. This redefinition asserts that boundaries are fluid and meant to be transcended. Case studies illustrate the profound impact of integrating vivid wall pieces on the aesthetic appeal of interior spaces. Urban vibrancy revitalizes the atmosphere, infusing it with palpable energy that resonates with the vivacity of public spaces. The curated tranquility of private interiors coexists harmoniously with the dynamic visual language of street art, fostering a unique and evolving relationship between inhabitants and their living spaces. Emphasizing harmonious coexistence, the paper underscores the potential for a seamless dialogue between public urban spaces and private interiors. The integration of vivid wall pieces acts as a bridge rather than a dichotomy, merging the dynamism of street art with the curated elegance of contemporary design. This unique visual tapestry transcends traditional categorizations, fostering a symbiotic relationship between contrasting worlds. In conclusion, this paper posits that the integration of vivid wall pieces represents a transformative tool for contemporary interior design, challenging and redefining conventional boundaries. By strategically bringing the "outside in," this approach transforms interior spaces and heralds a paradigm shift in the relationship between urban aesthetics and contemporary living. The ongoing narrative between urban vibrancy and interior design creates spaces that reflect the dynamic and ever-evolving nature of the surrounding environment.

Keywords: Art Integration, Contemporary Interior Design, Interior Space Transformation, Vivid Wall Pieces

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Emiko Suzuki

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Although fitness is defined as the body’s ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies.

Keywords: Instagram, fitness, dehumanization, body image, embodiment

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Authors: Fernanda Miranda da Cruz

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This paper aims to systematize, descriptively and analytically, the relations between language, body and material world explored in a specific empirical context: everyday co-presence interactions between children diagnosed with Autistic Spectrum Disease ASD and various interlocutors. We will work based on 20 hours of an audiovisual corpus in Brazilian Portuguese language. This analysis focuses on 1) the analysis of daily interactions that have the presence/participation of subjects with a diagnosis of ASD based on an embodied interaction perspective; 2) the study of the status and role of gestures, body and material world in the construction and constitution of human interaction and its relation with linguistic-cognitive processes and Autistic Spectrum Disorders; 3) to highlight questions related to the field of videoanalysis, such as: procedures for recording interactions in complex environments (involving many participants, use of objects and body movement); the construction of audiovisual corpora for linguistic-interaction research; the invitation to a visual analytical mentality of human social interactions involving not only the verbal aspects that constitute it, but also the physical space, the body and the material world.

Keywords: autism spectrum disease, multimodality, social interaction, non-verbal interactions

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Authors: Ahreum Choi, Otgontuya Tsogbadrakh, Kwang-Hwan Jung

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Microbial rhodopsins are well-known seven-transmembrane proteins that have been extensively studied. These retinal-binding proteins have divided into two types. The type I is microbial rhodopsin, and type II (visual pigment) is expressed mostly in mammalian eyes. For type I rhodopsin, there are two main functions that are ion pumping activity and sensory transduction. Anabaena sensory rhodopsin (ASR) is one of the microbial rhodopsin with main function as photo-sensory transduction. Although ASR is expressed fairly well in Escherichia coli, the expression level is relatively less compare to Proteorhodopsin. In this study, full length of ASR was used to test for the expression influence by codon usage in E. coli. Eight amino acids of codon at N-terminal part of ASR were changed randomly with designed primers, which allow 8,192 nucleotide different cases. The codon changes were screened for the preferable codons of each residue, which have given higher expression yield. Among those 57 selected mutations, there are 24 color-enhanced E. coli colonies that contain ASR proteins, and it showed better expression level than the wild type ASR codon usage. This strongly suggests that high codon usage of only partial N-terminal of protein can increase the expression level of whole protein.

Keywords: 7-transmembrane, all-trans retinal, rhodopsin, codon-usage, protein expression

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

Abstract:

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Nida Amin, Fahad Tanveer, Hina Shabbir, Ayesha Saeed, Attiqa Riaz

Abstract:

The gradual progression of corneal disorder keratoconus significantly impairs eyesight and quality of life, increasing the likelihood of depression. Using the Hospital Anxiety and Depression Scale (HADS) at the AL-Ibrahim Eye Hospital in Karachi, this study aimed to evaluate the occurrence of depression and anxiety symptoms in patients with keratoconus and to suggest better treatment. A descriptive-analytical study was conducted at Al-Ibrahim Eye Hospital Karachi from March to April 2022, and patients diagnosed with symptomatic keratoconus were recruited using a non-probability convenient sampling technique. After obtaining written informed consent from patients, keratoconus severity was assessed using visual acuity and corneal topography. Symptoms of anxiety and depression were assessed using the Hospital Anxiety and Depression (HADS) Scale. The data were analyzed using SPSS version 20.0. Spearman correlation coefficient. Of the 108 participants, 60 (56%) were female and 48 (44%) were male. Using the HADS scale, 44 (40.7%) patients were classified as normal with a HADS score of (0-7), 23 (21.3%) as borderline with a HADS score of (8-10) and 41 (38%) patients were diagnosed with anxiety and depression with a HADS score of (11-21). Depression and anxiety are highly prevalent among patients in advanced stages of the disease.

Keywords: cornea, keratoconus, anxiety, depression, corneal topography, mental health

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Authors: Peter Adu

Abstract:

Background: There is a paucity of mental health research in Ghana. Little is known about the beliefs and attitudes regarding specific mental disorders in Ghana. Method: A vignette study was conducted to examine the relationship between causal attributions, help-seeking, and stigma towards depression and schizophrenia using lay Ghanaians (N = 410). This adapted questionnaire presented two unlabelled vignettes about a hypothetical person with the above disorders for participants to provide their impressions. Next, participants answered questions on beliefs and attitudes regarding this person. Results: The results showed that causal beliefs about mental disorders were related to treatment options and stigma: spiritual causal attributions associated positively with spiritual help-seeking and perceived stigma for the mental disorders, whilst biological and psychosocial causal attribution of the mental disorders was positively related with professional help-seeking. Finally, contrary to previous literature, belonging to a particular religious group did not negatively associate with professional help-seeking for mental disorders. Conclusion: In conclusion, results suggest that Ghanaians may benefit from exposure to corrective information about depression and schizophrenia. Our findings have implications for mental health literacy and anti-stigma campaigns in Ghana and other developing countries in the region.

Keywords: stigma, mental health literacy, depression, schizophrenia, spirituality, religion

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Authors: Timothy J. Grebec

Abstract:

This study investigated whether using a voice dictation software program (i.e., Google Voice Typing) has an impact on student writing quality. The research took place in a third-grade general education classroom in a suburban school setting. Because the study involved minors, all data was encrypted and deidentified before analysis. The students completed a series of writings prior to the beginning of the intervention to determine their thoughts and skill level with writing. During the intervention phase, the students were introduced to the voice dictation software, given an opportunity to practice using it, and then assigned writing prompts to be completed using the software. The prompts written by nineteen student participants and surveys of student opinions on writing established a baseline for the study. The data showed that using the dictation software resulted in a 34% increase in the response quality (compared to the Pennsylvania State Standardized Assessment [PSSA] writing guidelines). Of particular interest was the increase in students' proficiency in demonstrating mastery of the English language and conventions and elaborating on the content. Although this type of research is relatively no, it has the potential to reshape the strategies educators have at their disposal when instructing students on written language.

Keywords: educational technology, accommodations, students with disabilities, writing instruction, 21st century education

Procedia PDF Downloads 72