Search results for: automatic image colorization

Authors: Karin M. Granstrom

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Paper mills produce wastewater with a high content of organic substances. Treatment usually consists of sedimentation, biological treatment of activated sludge basins, and chemical precipitation. The resulting sludges are currently a waste problem, deposited in landfills or used as low-grade fuels for incineration. There is a growing awareness of the need for energy efficiency and environmentally sound management of sludge. A resource-efficient method would be to digest the wastewater sludges anaerobically to produce biogas, refine the biogas to biomethane for use in the transportation sector, and utilize the resulting digestate for soil improvement. The biomethane yield of pulp and paper wastewater sludge is comparable to that of straw or manure. As a bonus, the digestate has an improved dewaterability compared to the feedstock biosludge. Limitations of this process are predominantly a weak economic viability - necessitating both sufficiently large-scale paper production for the necessary large amounts of produced wastewater sludge, and the resolving of remaining questions on the certifiability of the digestate and thus its sales price. A way to improve the practical and economical feasibility of using paper mill wastewater for biomethane production and soil improvement is to co-digest it with other feedstocks. In this study, pulp and paper sludge were co-digested with (1) silage and manure, (2) municipal sewage sludge, (3) food waste, or (4) microalgae. Biomethane yield analysis was performed in 500 ml batch reactors, using an Automatic Methane Potential Test System at thermophilic temperature, with a 20 days test duration. The results show that (1) the harvesting season of grass silage and manure collection was an important factor for methane production, with spring feedstocks producing much more than autumn feedstock, and pulp mill sludge benefitting the most from co-digestion; (2) pulp and paper mill sludge is a suitable co-substrate to add when a high nitrogen content cause impaired biogas production due to ammonia inhibition; (3) the combination of food waste and paper sludge gave higher methane yield than either of the substrates digested separately; (4) pure microalgae gave the highest methane yield. In conclusion, although pulp and paper mills are an almost untapped resource for biomethane production, their wastewater is a suitable feedstock for such a process. Furthermore, through co-digestion, the pulp and paper mill wastewater and mill sludges can aid biogas production from more nutrient-rich waste streams from other industries. Such co-digestion also enhances the soil improvement properties of the residue digestate.

Keywords: anaerobic, biogas, biomethane, paper, sludge, soil

Procedia PDF Downloads 259

Authors: I. Caldas, T. Duarte

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Avoidant Restrictive Food Intake Disorder (ARFID) was included for the first time in DSM-5, replacing the old diagnosis of DSM-4 'Early Childhood Eating Disorder'. An ARFID is characterized by a restrictive/avoidant eating pattern that can lead to severe nutritional deficiency, weight loss, nutritional supplementation dependence, and poor psychosocial functioning. This eating pattern is associated with decreased interest in food, worries about food characteristics or the act of ingestion, and lack of concern with weight or body image. This paper aims to understand the impact of this new diagnosis in other Eating Disorders (ED) prevalence, as well as to compare their therapeutic approaches. Methodology: Literature reviewed by PubMed with the following keywords: 'ARFID', 'Prevalence', and 'Eating Disorders'. We selected articles related to this theme, written since 2016. Results: In a population of children hospitalized with ED, 5% to 14% was diagnosed with ARFID, and, as outpatient treatment, the prevalence was 22%. People diagnosed with ARFID have more prevalence of other comorbidities, especially autism spectrum, are younger, and are more often male. Regarding the treatment of ARFID, it most often required nasogastric feeding, and with less suffering associated with this procedure, compared to AN. Despite these differences, 12% of patients diagnosed with ARFID transited to AN during treatment, suggesting that the first pathology may be a risk factor for the development of AN. Conclusions: The differences identified between ARFID and the other EDs are important when analyzed as differential diagnostic hypotheses and therapeutic approaches. Further study is necessary regarding its prevalence, risk factors, and treatment.

Keywords: avoidant restrictive food intake disorder, ARFID, differential diagnoses, eating disorders, prevalence

Procedia PDF Downloads 111

Authors: Li Hoon Lim, Nur Farhanah Said, Katie Simmons, Eric Pei Ping Pang, Sharon Mei Mei Wong

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Background and Purpose: Research regarding the sexual impact of breast cancer treatment on Asian women is both sensitive and scarce. This study aims to assess and evaluate the sexual health needs and concerns of breast cancer radiotherapy patients. It is hoped that awareness will be increased and an appropriate intervention can be developed to address the needs of future breast cancer patients. Methods: 110 consecutive unselected breast cancer patients were recruited prospectively. Questionnaires were administered once for patient undergoing radiotherapy to the breast. This study employed an anonymous questionnaire; any breast radiotherapy patient who can read English can voluntarily receive and complete the survey. The questionnaire consisted of items addressing demographics, potential informational needs, and educational preferences. Results: Patients’ interest to address sexual concerns decreases with age (p=0.024). Coherently, sexual concerns of patients are reported to decrease with age (p=0.015) where 70% of all respondents below age 50 [age 20-29 (60%); 30-39 (56.3%); 40-49(55.1%)] have started to have sexual concerns regarding their treatment effects on their sexual health. Patients who underwent breast conservation surgery (42.2%) and reconstruction surgery (83.3%) were more likely to have concerns about sexual health versus patients who underwent mastectomy (36.7%) (p=0.032). 74.2% of patients with sexual concern regardless of age would initiate conversation with their healthcare providers (p < 0.001). Conclusions: The results showed a staggering interest of female patients wanting information on this area which would not only boost their confidence and body image but also address concerns of the effect of breast radiotherapy on sexual health during their treatment.

Keywords: breast cancer, breast radiotherapy, sexual health, sexual impact

Procedia PDF Downloads 207

Authors: Yildiz Erdoganoglu, Unzile Tunc

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The aim of this study was to determine the relationship of body, upper extremity, lower extremity endurance, and core functionality with body perception and self-esteem in individuals who applied for a bodybuilding exercise program. Forty volunteer male subjects who underwent bodybuilding exercises for one year or more were included in the study. After obtaining demographic information of the individuals, trunk endurance was evaluated by curl-up and modified Sorensen test, upper extremity endurance by push-up test, lower extremity endurance by repeated squat test, core functionalities by single-leg wall sitting and repeated single-leg squatting tests. body perception, body image perception scale, and self-esteem were evaluated with Rosenberg self-esteem scale. The mean age of the individuals was 25.60 ± 4.70 years, mean exercise time was 22.47 ± 34.60 months. At the end of the study, body perception was low, and self-esteem was moderate. There was no significant relationship between abdominal endurance, back extensor endurance, upper extremity, and lower extremity endurance, core functionality, and body perception (p > 0.05). Also, there was no significant relationship between abdominal extensor, back extensor, upper extremity and lower extremity endurance, core functionality, and self-esteem (p > 0.05). The body, upper and lower extremity endurance, and core functionality of bodybuilders did not have any effect on body perception and self-esteem, suggesting that these individuals did not contribute positively to their efforts to improve their body perception and self- esteem.

Keywords: body endurance, body perception, core functionality, self esteem

Procedia PDF Downloads 152

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 82

Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

Procedia PDF Downloads 178

Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

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Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

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Authors: Deng Zengming, Wang Mingjiang

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As 3D video is explored as a hot research topic in the last few decades, free-viewpoint TV (FTV) is no doubt a promising field for its better visual experience and incomparable interactivity. View synthesis is obviously a crucial technology for FTV; it enables to render images in unlimited numbers of virtual viewpoints with the information from limited numbers of reference view. In this paper, a novel hybrid synthesis framework is proposed and blending priority is explored. In contrast to the commonly used View Synthesis Reference Software (VSRS), the presented synthesis process is driven in consideration of the temporal correlation of image sequences. The temporal correlations will be exploited to produce fine synthesis results even near the foreground boundaries. As for the blending priority, this scheme proposed that one of the two reference views is selected to be the main reference view based on the distance between the reference views and virtual view, another view is chosen as the auxiliary viewpoint, just assist to fill the hole pixel with the help of background information. Significant improvement of the proposed approach over the state-of –the-art pixel-based virtual view synthesis method is presented, the results of the experiments show that subjective gains can be observed, and objective PSNR average gains range from 0.5 to 1.3 dB, while SSIM average gains range from 0.01 to 0.05.

Keywords: fusion method, Gaussian mixture model, hybrid framework, view synthesis

Procedia PDF Downloads 250

Authors: Hortènsia Curell, Ana Fernández-Montraveta

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This paper presents the creation, development, and analysis of a corpus designed to study the presence of attitude markers and author’s stance in research articles in two different areas of linguistics (theoretical linguistics and sociolinguistics). These two disciplines are expected to behave differently in this respect, given the disparity in their discursive conventions. Attitude markers in this work are understood as the linguistic elements (adjectives, nouns and verbs) used to convey the writer's stance towards the content presented in the article, and are crucial in understanding writer-reader interaction and the writer's position. These attitude markers are divided into three broad classes: assessment, significance, and emotion. In addition to them, we also consider first-person singular and plural pronouns and possessives, modal verbs, and passive constructions, which are other linguistic elements expressing the author’s stance. The corpus, Corpus of Attitude in Academic Writing (CAAW), comprises a collection of 21 articles, collected from six journals indexed in JCR. These articles were originally written in English by a single native-speaker author from the UK or USA and were published between 2022 and 2023. The total number of words in the corpus is approximately 222,400, with 106,422 from theoretical linguistics (Lingua, Linguistic Inquiry and Journal of Linguistics) and 116,022 from sociolinguistics journals (International Journal of the Sociology of Language, Language in Society and Journal of Sociolinguistics). Together with the corpus, we present the tool created for the creation and storage of the corpus, along with a tool for automatic annotation. The steps followed in the compilation of the corpus are as follows. First, the articles were selected according to the parameters explained above. Second, they were downloaded and converted to txt format. Finally, examples, direct quotes, section titles and references were eliminated, since they do not involve the author’s stance. The resulting texts were the input for the annotation of the linguistic features related to stance. As for the annotation, two articles (one from each subdiscipline) were annotated manually by the two researchers. An existing list was used as a baseline, and other attitude markers were identified, together with the other elements mentioned above. Once a consensus was reached, the rest of articles were annotated automatically using the tool created for this purpose. The annotated corpus will serve as a resource for scholars working in discourse analysis (both in linguistics and communication) and related fields, since it offers new insights into the expression of attitude. The tools created for the compilation and annotation of the corpus will be useful to study author’s attitude and stance in articles from any academic discipline: new data can be uploaded and the list of markers can be enlarged. Finally, the tool can be expanded to other languages, which will allow cross-linguistic studies of author’s stance.

Keywords: academic writing, attitude, corpus, english

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Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

Procedia PDF Downloads 324

Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Han Xiao

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The development of nanomedicines has recently achieved several breakthroughs in the field of cancer treatment; however, the biocompatibility and targeted burst release of these medications remain a limitation, which leads to serious side effects and significantly narrows the scope of their applications. The self-assembly of intermediate filament protein (IFP) peptides was triggered by a hydrophobic cation drug 7-amino actinomycin D (7-AAD) to synthesize pH-activatable nanoparticles (NPs) that could simultaneously locate tumors and produce antitumor effects. The designed IFP peptide included a target peptide (arginine–glycine–aspartate), a negatively charged region, and an α-helix sequence. It also possessed the ability to encapsulate 7-AAD molecules through the formation of hydrogen bonds and hydrophobic interactions by a one-step method. 7-AAD molecules with excellent near-infrared fluorescence properties could be target delivered into tumor cells by NPs and released immediately in the acidic environments of tumors and endosome/lysosomes, ultimately inducing cytotoxicity by arresting the tumor cell cycle with inserted DNA. It is noteworthy that the IFP/7-AAD NPs tail vein injection approach demonstrated not only high tumor-targeted imaging potential, but also strong antitumor therapeutic effects in vivo. The proposed strategy may be used in the delivery of cationic antitumor drugs for precise imaging and cancer therapy.

Keywords: 7-amino actinomycin D, intermediate filament protein, nanoparticle, tumor image

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Authors: Nikita Bharadia, Vikas Gupta, Sushant Koshy

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Mobile phone applications (“apps”) have generated substantial interest among marketers and researchers because of the developments in the smartphone technology and the availability of affordable phones to a large number of consumers. Apps are enabling brands to engage with consumers at any time and any place. This study utilizes a pre-test/post-test experimental design to determine if apps can have a persuasive impact on the consumer attitude towards the brand and her purchase intention. The study also tests the impact of informational vs. interactive style of apps on categories with high and low level of involvement. The results show that for high involvement brands, consumers have a predetermined brand image and apps that satisfy consumer needs through an interactive interface can increase purchase intention. For low involvement brands, while informational apps do not create substantial engagement, interactive apps can increase consumer focus on the brand and establish personal connect with the consumers. This has a positive impact in the attitude towards the brand. These results suggest that understanding how to maximize the consumer interaction with mobile phone apps will be a key topic of future research. This research indicates that managers need to evaluate the how apps can solve consumer needs before investing resources towards digital marketing campaign for their brands, following the global trend to capitalize on the digital platforms.

Keywords: App execution style, high and low involvement categories, mobile marketing, smartphone applications

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Authors: Vrajesh Chokshi

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In last three decades, the global economy is substantially changed. Today, we are living in highly inter-connected world. The global markets are more open and consumers are well informed about products and services. The information technology revolution has broken all barriers in global business. The E-commerce has given opportunities of global trades to corporate. The IT is extensively used in almost all industries. After liberalization in 1992, the Indian economy is also significantly changed. The IT (information technology) and ITES (IT enable services) are extensively used in supply chain management. In India, previously car rental service business was dominated by local organization and operated through local contact. This industry is very lucrative and to catch this opportunity, many new corporate have ventured into e-commerce car rental service business in India. As the market is very competitive, branding is also very important part of marketing strategy. Now, the E-commerce portals those are in car rental business in India have realized the importance of the same and have started usage of all types of communication channel to promote their brand in different Indian markets. At consumer side, the awareness is also being considerably increased due to marketing communication campaign run by these companies. This paper aims to understand effectiveness of branding strategies in car rental business in India and also tries to identify unique promotional strategies to consolidate brand image of this business in different Indian markets.

Keywords: branding strategies, car rental business, CRM (customer relationship management), ITES (information technology enabled services)

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Authors: E. E. S. Uy, T. Noda, K. Nakai, J. R. Dungca

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Cyclic threshold shear strain is the cyclic shear strain amplitude that serves as the indicator of the development of pore water pressure. The parameter can be obtained by performing either cyclic triaxial test, shaking table test, cyclic simple shear or resonant column. In a cyclic triaxial test, other researchers install measuring devices in close proximity of the soil to measure the parameter. In this study, an attempt was made to estimate the cyclic threshold shear strain parameter using full-field measurement technique. The technique uses a camera to monitor and measure the movement of the soil. For this study, the technique was incorporated in a strain-controlled consolidated undrained cyclic triaxial test. Calibration of the camera was first performed to ensure that the camera can properly measure the deformation under cyclic loading. Its capacity to measure deformation was also investigated using a cylindrical rubber dummy. Two-dimensional image processing was implemented. Lucas and Kanade optical flow algorithm was applied to track the movement of the soil particles. Results from the full-field measurement technique were compared with the results from the linear variable displacement transducer. A range of values was determined from the estimation. This was due to the nonhomogeneous deformation of the soil observed during the cyclic loading. The minimum values were in the order of 10-2% in some areas of the specimen.

Keywords: cyclic loading, cyclic threshold shear strain, full-field measurement, optical flow

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

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In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

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Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

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Authors: Tadele Tesfaw, Ajit Pal Singh, Abebaw Mekonnen Gezahegn

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. Research on welding of materials like steel is still critical and ongoing. Welding input parameters play a very significant role in determining the quality of a weld joint. The metal active gas (MAG) welding parameters are the most important factors affecting the quality, productivity and cost of welding in many industrial operations. The aim of this study is to investigate the optimization process parameters for metal active gas welding for 60x60x5mm dead mild steel plate work-piece using Taguchi method to formulate the statistical experimental design using semi-automatic welding machine. An experimental study was conducted at Bishoftu Automotive Industry, Bishoftu, Ethiopia. This study presents the influence of four welding parameters (control factors) like welding voltage (volt), welding current (ampere), wire speed (m/min.), and gas (CO2) flow rate (lit./min.) with three different levels for variability in the welding hardness. The objective functions have been chosen in relation to parameters of MAG welding i.e., welding hardness in final products. Nine experimental runs based on an L9 orthogonal array Taguchi method were performed. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the welding characteristics of dead mild steel plate and used in order to obtain optimum levels for every input parameter at 95% confidence level. The optimal parameters setting was found is welding voltage at 22 volts, welding current at 125 ampere, wire speed at 2.15 m/min and gas flow rate at 19 l/min by using the Taguchi experimental design method within the constraints of the production process. Finally, six conformations welding have been carried out to compare the existing values; the predicated values with the experimental values confirm its effectiveness in the analysis of welding hardness (quality) in final products. It is found that welding current has a major influence on the quality of welded joints. Experimental result for optimum setting gave a better hardness of welding condition than initial setting. This study is valuable for different material and thickness variation of welding plate for Ethiopian industries.

Keywords: Weld quality, metal active gas welding, dead mild steel plate, orthogonal array, analysis of variance, Taguchi method

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Antonia Stanojević, Agnes Akkerman

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In contemporary society, economically active people typically spend most of their waking hours doing their job. Having that in mind, this research examines how socialization at the workplace shapes political preferences. Innovatively, it examines, in particular, the possible relationship between employees’ voice suppression by the employer and the formation of their political preferences. Since the employer is perceived as an authority figure, their behavior might induce spillovers to attitudes about political authorities and authoritarian governance. Therefore, a positive effect of suppression of voice by employers on employees' preference for authoritarian governance is expected. Furthermore, this relation is expected to be mediated by two mechanisms: system justification and power distance. Namely, it is expected that suppression of voice would create a power distance organizational climate and increase employees’ acceptance of unequal distribution of power, as well as evoke attempts of oppression rationalization through system justification. The hypotheses will be tested on the data gathered within the first wave of Work and Politics Dataset 2017 (N=6000), which allows for a wide range of demographic and psychological control variables. Although a cross-sectional analysis to be used at this point does not allow for causal inferences, the confirmation of expected relationships would encourage and justify further longitudinal research on the same panel dataset, in order to get a clearer image of the causal relationship between employers' suppression of voice and workers' political preferences.

Keywords: authoritarian values, political preferences, power distance, system justification, voice suppression

Procedia PDF Downloads 269

Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

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Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

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Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 141

Authors: Marco Castagna

Abstract:

Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.

Keywords: attestation, meaning, reader, text

Procedia PDF Downloads 237

Authors: Zhehao Zhang

Abstract:

Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Sundara Subramanian Karuppasamy, Che Hua Yang

Abstract:

In this work, the laser ultrasound technique has been used for analyzing and imaging the inner defects in metal blocks. To detect the defects in blocks, traditionally the researchers used piezoelectric transducers for the generation and reception of ultrasonic signals. These transducers can be configured into the sparse and phased array. But these two configurations have their drawbacks including the requirement of many transducers, time-consuming calculations, limited bandwidth, and provide confined image resolution. Here, we focus on the non-contact method for generating and receiving the ultrasound to examine the inner defects in aluminum blocks. A Q-switched pulsed laser has been used for the generation and the reception is done by using Laser Doppler Vibrometer (LDV). Based on the Doppler effect, LDV provides a rapid and high spatial resolution way for sensing ultrasonic waves. From the LDV, a series of scanning points are selected which serves as the phased array elements. The side-drilled hole of 10 mm diameter with a depth of 25 mm has been introduced and the defect is interrogated by the linear array of scanning points obtained from the LDV. With the aid of the Synthetic Aperture Focusing Technique (SAFT) algorithm, based on the time-shifting principle the inspected images are generated from the A-scan data acquired from the 1-D linear phased array elements. Thus the defect can be precisely detected with good resolution.

Keywords: laser ultrasonics, linear phased array, nondestructive testing, synthetic aperture focusing technique, ultrasonic imaging

Procedia PDF Downloads 134

Authors: Foad Vashahi, Shahnaz Rezaei, Jeekeun Lee

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Large Eddy Simulation (LES) was performed on a dual counter rotating axial swirler in a confined rectangular configuration. Grids were constructed based on a primary Reynolds Averaged Navier-Stokes (RANS) simulation and then were refined based on the Kolmogorov length scale. Water as cold flow condition was applied and results were compared via Particle Image Velocimetry (PIV) experimental results. The focus was to investigate the flow behavior within the region before the flare and very close to the exit of the swirler. This region contributes to a highly unsteady flow behavior and requires great attention to enhancing the flame stability in gas turbine combustor and swirl burners. The PVC formation within the central core flow is strongly related to the peaks of pressure or axial velocity spectrum and up to two distinct peaks at the swirler mouth could be observed. Here, spectra analysis in iso-thermal condition inside the swirler where the inner swirler dominates the flow, showed a higher potential of instabilities with three to four distinct peaks where moving forward to the exit of swirler the number of peaks is decreased. In addition to this, the central axis corresponds to no peaks of instabilities while further away in the radial direction, several peaks exist.

Keywords: axial counter rotating swirler, large eddy simulation (LES), precessing vortex core (PVC), power spectral density (PSD)

Procedia PDF Downloads 280

Authors: Francia Martinez

Abstract:

This study documents and demonstrates the profound impact of the high status of American English and culture in Colombian commercial landscape due to the globalization and commodification of English. It also documents and describes how Colombian advertisers make use of various language and visual mechanisms in the commercial linguistic landscape to convey messages, create an image with which the target audience can identify, and build a relationship with that target audience. The data (in the form of pictures) were collected in different cities in Colombia and were classified and organized into different categories for the reliability and validity of the analysis. The research questions were: do the ubiquity and high status of American English and culture play a major role in the Colombian commercial linguistic landscape? If so, how?, what roles do national and local culture and language (Spanish) play in the commercial linguistic landscape?, and what different linguistic and visual strategies do Colombian advertisers employ to reach their target audience? Based on data analysis and results, American and local culture and icons play a major role when Colombian advertisers create and design their commercial logos and ads to get consumers’ attention and establish a rapport with them in a successful way. In order to achieve their objectives, Colombian advertisers rely on creative linguistic and visual techniques in their ads, such as puns, humor, irony, comparisons, metaphors, mocking, exaggeration, parody, personification, sarcasm, satire, allusion, onomatopoeias, and imitation (copycat or cloning).

Keywords: Colombian ads, linguistic landscape, rhetorical devices, sociolinguistics

Procedia PDF Downloads 310

Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

Procedia PDF Downloads 216