Search results for: mutual recognition

Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

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Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: Ilana Margalith, Yaron Niv

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One of the most important factors of professional health treatment is teamwork, in which each discipline contributes its expert knowledge, thus ensuring quality and a high standard of care as well as efficient communication (one of the International Patient Safety Goals). However, in most countries, students are educated separately by each health discipline. They are exposed to teamwork only during their clinical experience, which in some cases is short and skill-oriented. In addition, health organizations in most countries are hierarchical and although changes have occurred in the hierarchy of the medical system, there are still disciplines that underrate the unique contributions of other health professionals, thus, young graduates of health professions develop and base their perception of their peers from other disciplines on insufficient knowledge. In order to establish a wide-ranging perception among nursing students as to the contribution of different health professionals to the health of their patients, students at the Clalit Nursing Academy, Rabin Campus (Dina), Israel, participated in an interdisciplinary clinical discussion with students from several different professions, other than nursing, who were completing their clinical experience at Rabin Medical Center in medicine, health psychology, social work, audiology, physiotherapy and occupational therapy. The discussion was led by a medical-surgical nursing instructor. Their tutors received in advance, a case report enabling them to prepare the students as to how to present their professional theories and interventions regarding the case. Mutual stimulation and acknowledgment of the unique contribution of each part of the team enriched the nursing students' understanding as to how their own nursing interventions could be integrated into the entire process towards a safe and speedy recovery of the patient.

Keywords: health professions' students, interdisciplinary clinical discussion, nursing education, patient safety

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Authors: Fatten F. Elkomy

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The Syrian refugees are the largest refugee population since World War II. Mostly, children, these individuals were exposed to intense traumatic events in their homeland, throughout their journey, and during settlement in foreign lands. Art is a universal language to express feelings and tough human experiences. It is also a medium for healing and promoting creativity and resilience. Literature review was conducted to examine the use of art to facilitate psychiatric interviews, diagnosis, and therapy with traumatized children. Results show a severe impact of childhood trauma on the increased risk for abuse, neglect, and psychiatric disorders. Clinicians must recognize, evaluated and provide help for these children. In conclusion, drawings are used to tell a story, reflect deep emotions, and create a meaningful self-recognition and determination. Participants will understand art therapy using the expressive therapies continuum framework to evaluate drawings and to promote healing for refugee children.

Keywords: art therapy, children drawings, Syrian refugees, trauma in childhood

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Authors: Azusa Katsumata

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Several universities in Japan have introduced activities aimed at the mutual enlightenment of a diversity of people in career education. However, several programs emphasize on delivering results, and on practicing the prepared materials as planned. Few programs focus on unexpected failures and setbacks. This way of learning is important in career education so that classmates can help each other, overcome difficulties, draw out each other’s strengths, and learn from them. Seijo University in Tokyo offered excursion focusing Various Problems of Society, as second year career education course, Students will learn about contraception, infertility, homeless people, LGBT, and they will discuss based on the excursion. This paper aims to study the ‘learning platform’ created by a series of processes such as the excursion, the discussion, and the presentation. In this course, students looked back on their lives and imagined the future in concrete terms, performing tasks in groups. The students came across a range of values through lectures and conversations, thereby developing feelings of self-efficacy. We conducted a questionnaire to measure the development of career in class. From the results of the questionnaire, we can see, in the example of this class, that students respected diversity and understood the importance of uncertainty and discontinuity. Whereas the students developed career awareness, they actually did not come across that scene and would do so only in the future when it became necessary. In this class, students consciously considered social problems, but did not develop the practical skills necessary to deal with these. This is appropriate for one of project, but we need to consider how this can be incorporated into future courses. University constitutes only a single period in life-long career formation. Thus, further research may be indicated to determine whether the positive effects of career education at university continue to contribute to individual careers going forward.

Keywords: career education of university, excursion, learning platform, problems of society

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Authors: G. Ramya

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Value engineering is a systematic approach, widely used to optimize the design or process or product in the designing stage. It used to achieve the client's obligation by increasing the functionality and attain the targeted cost in the cost planning. Value engineering effectiveness and benefits decrease along with the progress of the project since the change in the scope of the work and design will account for more cost all along the lifecycle of the project. Integrating the value engineering with other project management activities will promote cost minimization, client satisfaction, and ensure early completion of the project in time. Previous research studies suggested that value engineering can integrate with other project delivery activities, but research studies unable to frame a model that collaborates the project management activities with the job plan of value engineering approach. I analyzed various project management activities and their synergy between each other. The project management activities and processes like a)risk analysis b)lifecycle cost analysis c)lean construction d)facility management e)Building information modelling f)Contract administration, collaborated, and project delivery model planned along with the RIBA plan of work. The key outcome of the research is a value-driven project delivery model, which will succeed in dealing with the economic impact, constraints and conflicts arise due to the COVID-19 outbreak in the Indian construction sector. Benefits associated with the structured framework is construction project delivery that ensures early contractor involvement, mutual risk sharing, and reviving the project with a cost overrun and delay back on track ,are discussed. Keywords: Value-driven project delivery model, Integration, RIBA plan of work Themes: Design Economics

Keywords: value-driven project delivery model, Integration, RIBA

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Authors: Takwiir Tahriim Khan, Tausif Khalid, Mohammad Redwan Ahamed, Md Soebur Rahman

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The mutual connection in joints has a significant impact on the safe and cost-effective design of steel structures. Generally, the end plates are welded at the end of the beam and columns are bolted with the end plates. Thus, the moment will be transferred at the interface, which is a critical segment at the connection. 3-D Finite Element Models (FEM) has been developed using ABAQUS 2017 software to predict the yield capacity of the end plate connections. The parameters used in this study are the depth, width, and thickness of the end plate, dimensions of the bolt, sectional and material properties of beams and columns. The influence width, depth, and thicknesses of the end plate connection on yield capacity were investigated through parametric studies. The results showed that, for increasing plate thickness from 0.3 inch to 0.8 inch by an increment of 0.1 inch the yield capacity increased by 2.85% on average, for decreasing the end plate depth from 13 inch to 11 inch the yield capacity increased by 25.4 %, and for decreasing the end plate width from 6.5 inch to 5.75 inch the yield capacity increased by 35.4%. Variation in yield capacity was also found by changing the beam and column section. Besides, the numerical results showed a good agreement with published experimental literature with an average variation of less than 8.3 % in yield capacity. So the study allows for a more effective combination of beam, column, and end plate dimensions.

Keywords: steel beam-column joints, finite element analysis, yield moment capacity, parametric study, ABAQUS, bolted joints, flush end plates, moment vs rotation curves

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Authors: Sara Namdarian, Hafez Salleh

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This paper scrutinizes the circumstances of the application of Augmented Reality (AR) technology to enhance the adaptability of architecture classrooms in private Malaysian university classrooms. This study aims to indicate the constraints of mono-functional classrooms in comparison to the potentials of multi-functional classrooms derived from AR application through an exploratory mixed method strategy. This paper expects to contribute towards recognition of suitable AR techniques which can be applied in the development of Adaptive-AR-Classroom-Systems (AARCS) in architecture classrooms. The findings, derived from the analysis, show current classrooms have limited functional spaces, and concludes that AR application can be used in design classrooms to provide a variety of visuals and virtual objects that are required in conducting architecture projects in higher educational centers.

Keywords: design activity, space enhancement, design education, architectural design augmented reality

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Authors: Weiyao Zhu, Qian Qi, Ming Yue, Dongxu Ma

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Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interference of the fractures. In regard to the fractured horizontal wells, the free gas was found to majorly contribute to the productivity, while the contribution of the desorption increased with the increased pressure differences.

Keywords: multi-scale, fracture network, composite model, productivity

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Zahra Karimian, Effat Merghati Khoei, Raziyeh Maasoumi

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Background: Women's sexual well-being is center of focus in the field of sexology. Study of sexual behavior and investigating its predictors is important in women's health promotion. Objectives: This study aimed to explore the components of sexual behaviors and their possible associations with the women's demographic. Methods: A National Sexual Behavior Assessment Questionnaire was administered to 500 women ages 15 to 45 who referred to the public health centers seeking for health care services. The associations with demographic were examined. Results: From all participant, 31.8% of women obtain high score in the sexual capacity 21.2% in sexual motivation and 0.2% in sexual function. In sexual script component, 86.2% of women were holding traditional beliefs toward sexual behaviors; the majority (91.5%) of women believed in mutual and relational sexuality, 83.4% believed in androcentricity (male-dominated sexuality). Pearson correlation test showed significant positive correlations between sexual capacity, motivation, function and sexual script (p < 0.05). Regression model showed that sexual capacity is associated with women's education, age of her spouse. Sexual function and sexual motivation were significantly associated with the age of subjects' spouses. Conclusion: In this study, lower score was found in sexual performance while women were scored higher in the sexual capacity and motivation. We argue that these lower score in sexual performance more likely is due to the level of participants' religiosity and formation of their sexuality through an androcentric culture. Women's level of education and the spouse age appear to be predicting factors in the scores the subjects gained. We suggest that gender-specific and culturally sensitive sexuality education should be focus of women's health programs in Iran.

Keywords: sexual behaviors, women, health, Iran

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Authors: B. G. Abiona, E. O. Fakoya, D. O. Alabi

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Influence of leadership roles on agricultural employees’ job satisfaction was studied. Data were from 68 randomly selected respondents. Major leadership roles include supervision of employees work (x̄=3.67), leaders were goal oriented (x̄=3.39), dissemination of information among the employees (x̄=3.35). Major employees’ satisfaction was: Employees work together with their colleagues (x̄=3.54) and also interact freely with their colleagues (x̄=3.51). Major challenges affecting employees job satisfaction were inadequate funding (x̄=3.30), irregular leave bonus (x̄=3.29), climate and weather condition (x̄=3.08) and inadequate incentive (x̄=3.02). Regression analysis showed a positive significant coefficient (P<0.05) exist between religion (p<0.05), educational status(p<0.05), year of service(p<0.05), leadership roles (p<0.005), challenges faced by respondents(P<0.05), and employees’ job satisfaction. For adequate leadership role, organization should pay attention to disbursement of training funds, availability of adequate incentive and leadership recognition.

Keywords: leadership roles, agricultural employees’, job satisfaction, institute, Nigeria

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Shiva Subhedar, Abhishek Jain, Shivin Mittal

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Icons are not merely decorative elements in enterprise applications but very often used because of their many advantages such as compactness, visual appeal, etc. Despite these potential advantages, icons often cause usability problems when they are designed without consideration for their many potential downsides. The aim of the current study was to examine the effect of articulatory distance – the distance between the physical appearance of an interface element and what it actually means. In other words, will the subject find the association of the function and its appearance on the interface natural or is the icon difficult for them to associate with its function. We have calculated response time and quality of identification by varying icon concreteness, the context of usage and subject experience in the enterprise context. The subjects were asked to associate icons (prepared for study purpose) with given function options in context and out of context mode. Response time and their selection were recorded for analysis.

Keywords: HCI, icons, icon concreteness, icon recognition

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Tahereh Habibi

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The Oligocene carbonates are widespread along Fars Province, Zagros Basin, SW Iran. Distribution of planktonic and larger benthic foraminfera, stratal patterns and facies architecture are used as a tool to define microfacies and foraminiferal associations of these strata at Kavar Section. The presence of Nummulites spp. indicated the age of the sequence as Rupelian-Chattian (Nummulites vascus-Nummulites fichteli and Archaias asmaricus/hensoni-Miogypsinoides complanatus assemblage zones). The paleoenvironmental setting is interpreted as a homoclinal ramp environment according to the recognition of eight microfacies types. Four foraminiferal associations are recognized in the investigated ramp setting. They represent a salinity of 34-40 to 50 psu and higher than 50 psu in more restricted conditions. The depth ranges from 200 m as evidenced by the presence of planktonic foraminifera and to less than 30m in the more restricted inner ramp environment. Warm tropical and subtropical water with temperature of 18-25° C is proposed.

Keywords: foraminiferal associations, microfacies, oligocene, paleoecology

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Authors: Smriti Gour, Neelam Pandey

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The objective of this study was to describe and analyse the mutual relationship between the coping mechanisms used by the families of a child with Autism Spectrum Disorder (ASD) and family dynamics and the effect sibling interactions have on the dynamics and coping mechanisms in an urban setup. In-depth interviews were conducted for 25 families, with 4 members each in the Delhi NCR area in India. The families who were interviewed had a younger child who had received a diagnosis of ASD between the ages of 5-12. The in-depth questionnaires contained open-ended questions and the interviews were conducted separately for the mother, father and the typically developing sibling. The key findings of the study suggested that lack of communication was a common factor in most families (n=19) leading to other difficulties like stress and relationship dysfunction. It also fostered a fallacious perception of the relationship dynamics in the family in most of the interviewed families and changed depending on the family member being interviewed. In families where the typically developing elder sibling had a good relationship with the autistic child, the family dynamics were found to be more stable, and the overall family well-being was better maintained. The coping mechanisms employed by the families were also more positive and tended to work better if the typically developing sibling maintained a positive and interactive relationship with the parents and the autistic child. The type of coping mechanisms had a major impact on the relationship between the parents and in dictating the dynamics of the family of the child with ASD. Spirituality, professional help, family support and household help emerged to be the most effective coping mechanisms for the families, with spirituality emerging to be the most positive and effective coping mechanism in the families interviewed.

Keywords: autism spectrum disorder, coping mechanism, family dynamics, parental relationships, siblings

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Authors: Eric Chabrol, Sidonia B.G. Eckle, Renate de Boer, James McCluskey, Jamie Rossjohn, Mirjam H.M. Heemskerk, Stephanie Gras

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αβ and γδ T-cells are disparate T-cell lineages that, via their use of either αβ or γδ T-cell antigen receptors (TCRs) respectively, can respond to distinct antigens. Here we characterise a new population of human T-cells, term δβ T-cells, that express TCRs comprising a TCR-δ variable gene fused to a Joining-α/Constant-α domain, paired with an array of TCR-β chains. We characterised the cellular, functional, biophysical and structural characteristic feature of this new T-cells population that reveal some new insight into TCR diversity. We provide molecular bases of how δβ T-cells can recognise viral peptide presented by Human Leukocyte Antigen (HLA) molecule. Our findings highlight how components from αβ and γδTCR gene loci can recombine to confer antigen specificity thus expanding our understanding of T-cell biology and TCR diversity.

Keywords: new delta-beta TCR, HLA, viral peptide, structural immunology

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Authors: Dinh Ha, Tran, Chung-Ruey Yen

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This study explored the morphological characteristics and effects of pollination methods on fruit set and characteristics in four red pitaya (Hylocereus spp.) clones. The distinctive morphological recognition and classification among pitaya clones were confirmed by the stem, flower and fruit features. The fruit production season was indicated from the beginning of May to the end of August, the beginning of September with 6-7 flowering cycles per year. The floral stage took from 15-19 days and fruit duration spent 30–32 days. VN White, fully self-compatible, obtained high fruit set rates (80.0-90.5 %) in all pollination treatments and the maximum fruit weight (402.6 g) in hand self- and (403.4 g) in open-pollination. Chaozhou 5 was partially self-compatible while Orejona and F11 were completely self-incompatible. Hand cross-pollination increased significantly fruit set (95.8; 88.4 and 90.2 %) and fruit weight (374.2; 281.8 and 416.3 g) in Chaozhou 5, Orejona, and F11, respectively. TSS contents were not much influenced by pollination methods.

Keywords: Hylocereus spp., morphology, floral phenology, pollination requirement

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Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Jekaterina Novikova, Leon Watts

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In the emerging world of human-robot interaction, people and robots will interact socially in real-world situations. This paper presents the results of an experimental study probing the interaction between situational context and emotional body language in robots. 34 people rated video clips of robots performing expressive behaviours in different situational contexts both for emotional expressivity on Valence-Arousal-Dominance dimensions and by selecting a specific emotional term from a list of suggestions. Results showed that a contextual information enhanced a recognition of emotional body language of a robot, although it did not override emotional signals provided by robot expressions. Results are discussed in terms of design guidelines on how an emotional body language of a robot can be used by roboticists developing social robots.

Keywords: social robotics, non-verbal communication, situational context, artificial emotions, body language

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Authors: Yangwon Hyun

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Nowadays, business settings are becoming increasingly multilingual and multicultural under the conditions of globalization. When people from different linguistic and cultural background interact, their divergent cultural conceptualizations may result in communicative problems. Even though intercultural business communication between Thais and South Koreans has become increasingly significant along with the development of international trade relations, there have been very few attempts to conduct research on interactional problems in that context. Based on a Cultural Linguistics perspective, this study analyzes Thai cultural conceptualizations that underly interactional problems with Koreans at Korean business organizations where were located in Thailand. The data was gathered through in-depth interviews with ten Korean and ten Thai employees as well as through six months of field observations. The results indicate that there are three cultural pragmatic schemas that underly problems of interaction between the two groups; (1) the schema of kreng-jai as a communicative strategy of withholding one’s intentions in order to not hurt another’s emotion, (2) the schema of mai-pen-rai as a linguistic strategy of inducing interlocutors to not be concerned about substantial matters so as to avoid confrontations, and (3) the schema of jai-yen as a linguistic expression used for persuading interlocutors to maintain a calm state of mind in order to avoid conflicts. The linguistic behaviors of Thai employees in relation to these three cultural schemas had led to misunderstandings and interpersonal conflicts with Korean supervisors and co-workers. These interactional problems were caused not only because Koreans were unfamiliar with Thai cultural conceptualizations, but also because these conceptualizations were incompatible with goal-oriented Korean business discourse. The findings of this study can enhance mutual understandings between Thai and Korean employees. Thus, it contributes to the promotion of smooth intercultural communication in the workplace.

Keywords: business context, cultural conceptualizations, cultural linguistics, intercultural communication, thai culture

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Authors: Jean-Pierre Lomaliza, Kwang-Seok Moon, Hanhoon Park

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It is well-known that Ramer Douglas Peucker (RDP) algorithm greatly depends on the method of choosing starting points. Therefore, this paper focuses on finding such starting points that will optimize the results of RDP algorithm. Specifically, this paper proposes a curve approximation algorithm that finds flat points, called essential points, of an input curve, divides the curve into corner-like sub-curves using the essential points, and applies the RDP algorithm to the sub-curves. The number of essential points play a role on optimizing the approximation results by balancing the degree of shape information loss and the amount of data reduction. Through experiments with curves of various types and complexities of shape, we compared the performance of the proposed algorithm with three other methods, i.e., the RDP algorithm itself and its variants. As a result, the proposed algorithm outperformed the others in term of maintaining the original shapes of the input curve, which is important in various applications like pattern recognition.

Keywords: curve approximation, essential point, RDP algorithm

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Authors: Kevin Wongleedee

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This research paper was aimed to examine the reasons associated with hotel employees’ loyalty. This was a case study of 200 hotel employees in Bangkok, Thailand. The population of this study included all hotel employees who were working in Bangkok during January to March, 2014. Based on 200 respondents who answered the questionnaire, the data were complied by using SPSS. Mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of importance was 4.40, with 0.7585 of standard deviation. Moreover, the mean average can be used to rank the level of importance from each factor as follows: 1) salary, service charge cut, and benefits, 2) career development and possible advancement, 3) freedom of working, thinking, and ability to use my initiative, 4) training opportunities, 5) social involvement and positive environment, 6) fair treatment in the workplace and fair evaluation of job performance, and 7) personal satisfaction, participation, and recognition.

Keywords: hotel employees, loyalty, reasons, case study

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Authors: Jian Xu, Xiaochun Yun, Yongzheng Zhang, Yafei Sang, Zhenyu Cheng

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Network attack prevention is a critical research area of information security. Network attack would be oppressed if attribution techniques are capable to trace back to the attackers after the hacking event. Therefore attributing these attacks to a particular identification becomes one of the important tasks when analysts attempt to differentiate and profile the attacker behind a piece of attack trace. To assist analysts in expose attackers behind the scenes, this paper researches on the connections between attribution traces and proposes probabilistic relevance based attribution patterns. This method facilitates the evaluation of the plausibility relevance between different traceable identifications. Furthermore, through analyzing the connections among traces, it could confirm the existence probability of a certain organization as well as discover its affinitive partners by the means of drawing relevance matrix from attribution traces.

Keywords: attribution trace, probabilistic relevance, network attack, attacker identification

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

Abstract:

Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Threera Intarareaung

Abstract:

This research aims to study guidelines of organizing the Wat Sai Museum of Local Boats, of Ruam Sai Pattana Community 789, Kradangnga sub-district, Bang Khon Tee district, Samut Songkram province. The procedures are to seek for potentials and problems within the community to properly organize the said museum. The research contains methodology of qualitative by studying from the population from Ruam Sai Pattana 789, a community that located within the area of the museum. The sample contains 40 persons. The procedures are in-depth interview, observation, focus group by discussing ideas, problems and the importance of the museum. After that, the information received is synthesized and analyzed. The result finds that the local temple requires setting up the boat museum. However, there are several factors that limit the possibility which are the museum manager, resources, exhibition and service and knowledge management. These factors reflect mutual potentials and problems that lead us to seek the best solutions to set up the local boat museum. In conclusion, there are 4 issues regarding the management. First, the knowledge management should be conducted to indicate the purposes of the museum. Second, exhibition and service should be categorized. In addition, the serviced should be assisted by local guides. Third, the museum should employ staffs to correspond to other entities such as related authorities. Fourth is regarding location and condition of the building. This is considered as a major factor that needs discussion from different parties. However, the condition of the existing resource is proper. All the information is collected by field trip and interview the locals and person of interest. Therefore, the idea is inconsistent with the community’s requirement that can proceed to real practice.

Keywords: museum, boat museum, heritage tourism, conservation lifestyle

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

Abstract:

Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

Abstract:

We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride

Procedia PDF Downloads 450

Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

Abstract:

The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

Procedia PDF Downloads 127