Search results for: text processing

Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

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While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

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Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

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Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

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Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: Miroslav Dumbrovsky, Lucie Larisova

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The infiltration characteristic of the soil surface is one of the major factors that determines the potential soil degradation risk. The physical, chemical and biological characteristic of soil is changed by the processing of soil. The infiltration soil ability has an important role in soil and water conservation. The subject of the contribution is the evaluation of the influence of the conventional tillage and reduced tillage technology on soil surface crusting processing and infiltration properties of the soil in the North Bohemia region. Field experimental work at the area was carried out in the years 2013-2016 on Cambisol district medium-heavy clayey soil. The research was conducted on sloping erosion-endangered blocks of compacted arable land. The areas were chosen each year in the way that one of the experimental areas was handled by conventional tillage technologies and the other by reduced tillage technologies. Intact soil samples were taken into Kopecký´s cylinders in the three landscape positions, at a depth of 10 cm (representing topsoil) and 30 cm (representing subsoil). The cumulative infiltration was measured using a mini-disc infiltrometer near the consumption points. The Zhang method (1997), which provides an estimate of the unsaturated hydraulic conductivity K(h), was used for the evaluation of the infiltration tests of the mini-disc infiltrometer. The soil profile processed by conventional tillage showed a higher degree of compaction and soil crusting processing. The bulk density was between 1.10–1.67 g.cm⁻³, compared to the land processed by the reduced tillage technology, where the values were between 0.80–1.29 g.cm⁻³. Unsaturated hydraulic conductivity values were about one-third higher within the reduced tillage technology soil processing.

Keywords: soil crusting processing, unsaturated hydraulic conductivity, cumulative infiltration, bulk density, porosity

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Authors: Mingshu Liu, Laura Santamaria, Xavier Carmaniu Mainadé

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As one of the sectors most affected by the COVID-19 pandemic, tourism is facing challenges in revitalizing the industry. But at the same time, it would be a good opportunity to take advantage of digital communication as an effective tool for tourism promotion. Our proposal aims to verify the linguistic operations on online platforms in China. The research is carried out based on the theory of Eco-traductology put forward by Gengshen Hu, whose contribution focuses on the translator's adaptation to the ecosystem environment and the three elaborated parameters (linguistic, cultural and communicative). We also relate it to Even-Zohar's and Toury's theoretical postulates on the Polysystem to elaborate on interdisciplinary methodology. Such a methodology allows us to analyze personal treatments and phraseology in the target text. As for the corpus, we adopt the official Spanish-language website of Turismo de España as the source text and the postings on the two major social networks in China, Weibo and Wechat, in 2019. Through qualitative analysis, we conclude that, in the tourism advertising campaign on Chinese social networks, chengyu (Chinese phraseology) and honorific titles are used very frequently.

Keywords: digital communication, eco-traductology, polysystem theory, tourism advertising

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Authors: Eish Sharma

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Literature around Mathematics education suggests that democratic attitudes can be strengthened through teaching and learning Mathematics. Furthermore, connections between critical education and Mathematics education are observed in the light of critical pedagogy to locate Critical Mathematics Education (CME) as the theoretical framework. Critical pedagogy applied to Mathematics education is identified as one of the key themes subsumed under Critical Mathematics Education. Through the application of critical pedagogy in mathematics, unequal power relations and social injustice can be identified, analyzed, and challenged. The research question is: have educational policies in India viewed the role of critical pedagogy applied to mathematics education (i.e., critical mathematics education) to ensure social justice as an educational aim? The National Curriculum Framework (NCF), 2005 upholds education for democracy and the role of mathematics education in facilitating the same. More than this, NCF 2005 rests on Critical Pedagogy Framework and it recommends that critical pedagogy must be practiced in all dimensions of school education. NCF 2005 visualizes critical pedagogy for social sciences as well as sciences, stating that the science curriculum, including mathematics, must be used as an “instrument for achieving social change to reduce the divide based on economic class, gender, caste, religion, and the region”. Furthermore, the implementation of NCF 2005 led to a reform in the syllabus and textbooks in school mathematics at the national level, and critical pedagogy was applied to mathematics textbooks at the primary level. This intervention led to ethnomathematics and critical mathematics education in the school curriculum in India for the first time at the national level. In October 2022, the Ministry of Education launched the National Curriculum Framework for Foundational Stage (NCF-FS), developed in light of the National Education Policy, 2020, for children in the three to eight years age group. I want to find out whether critical pedagogy-based education and critical pedagogy-based mathematics education are carried forward in NCF 2022. To find this, an argument analysis of specific sections of the National Curriculum Framework 2022 document needs to be executed. Des Gasper suggests two tables: The first table contains four columns, namely, text component, comments on meanings, possible reformulation of the same text, and identified conclusions and assumptions (both stated and unstated). This table is for understanding the components and meanings of the text and is based on Scriven’s model for understanding the components and meanings of words in the text. The second table contains four columns i.e., claim identified, given data, warrant, and stated qualifier/rebuttal. This table is for describing the structure of the argument, how and how well the components fit together and is called ‘George Table diagram based on Toulmin-Bunn Model’.

Keywords: critical mathematics education, critical pedagogy, social justice, etnomathematics

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Authors: Mh. D Tammam Ayoubi

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The Old Testament has been translated into many languages, including Arabic. There have been consecutive translations of it since Islamic antiquity. The Rabbinic translation, which rendered the Hebrew text into Arabic without a linguistic medium, appeared later. It was followed by several Orthodox and Jesuit trials, including the Protestant translation. Those two translations were chosen to study the book of Proverbs, which is classified as one of the books of Wisdom; something that distances it from being either symbolical or historical and makes the translation the subject of the translator's ideology starting from the incorporated cultural element be it Jewish, Aramaic or Islamist (Mu'tazila) of the first translation, or through the choice of the equivalent signs of origin, and the neutralization of the Rabbinic, Arabic, and Greek element of the second translation. The various Protestant translation of different authors has contributed to the multiplicity of the term of reference, mostly Christian, in contrast with the single reference of one author, which carries multiple conflicting cultural facades when it comes to the Rabbinic translation. This has led to a change in the origin through the inclusion of those various verbal or interpretative elements in the book of Proverbs, which will be examined in the verses through a comparative study with the original Hebrew text or the cultural terms or references.

Keywords: rabbinic and protestant translations, book of proverbs, hebrew, protestant translation

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Authors: Amaal Almigal

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Technology has been argued to offer distinct advantages and benefits for teaching children with autism spectrum disorder (ASD) to communicate. One aspect of this technology is augmentative and alternative communication (AAC) systems such as picture exchange or speech generation devices. Whilst there has been significant progress in teaching these children to request their wants and needs with AAC, there remains a need for developing technologies that can really make a difference in teaching them to ask questions. iPad-based AAC can be effective for communication. However, the effectiveness of this type of AAC in teaching children to ask questions needs to be examined. Thus, in order to examine the effectiveness of iPad-based AAC in teaching children with ASD to ask questions, This research will test whether iPad leads to more learning than a traditional approach picture and text cards does. Two groups of children who use AAC will be taught to ask ‘What is it?’ questions. With the first group, low-tech AAC picture and text cards will be used, while an iPad-based AAC application called Proloquo2Go will be used with the second group. Interviews with teachers and parents will be conducted before and after the experiment. The children’s perspectives will also be considered. The initial outcomes of this research indicate that iPad can be an effective tool to help children with autism to ask questions.

Keywords: autism, communication, information, iPad, pictures, requesting

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Authors: Zafar Ali

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The aim of this research is to highlight problems that are faced by women at the hands of men. Males in Pakistani society have power and use this power for the exploitation of women. Further, the purpose of the study is to make societies like Pakistan and especially the young generation, aware and enable them to resist such issues, and the role of discourse in this regard is to minimize its political and social repercussions. The study finds out different discursive techniques and manipulative language used in the short story to construct gender identity. The study also investigates socio-economic roles in the construction of gender identity. This study has been completed with the help of Critical Discourse Analysis (CDA) principles. CDA principles have been applied to the text of the selected short story Saleema from Daniyal Mueenuddin’s collection In Other Rooms, Other Wonders. Related passages, structures, expressions, and text are analyzed from the point of view of CDA, especially Norman Fairclough’s CDA approach. It was found from the analysis that women have no identity of their own in patriarchal societies like Pakistan. Further, it was found women are mistreated, and they have a very limited and defined role in Pakistan. They cannot go beyond the limit defined to them by men.

Keywords: gender issues, resourceful groups, CDA, exploitation

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: Van Chung Nguyen

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The purpose of this study is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, market, distributions channel

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

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Authors: Mamdouh Omran, Timo Fabritius

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A growing interest in microwave heating has emerged recently. Many researchers have begun to pay attention to microwave energy as an alternative technique for processing various primary and secondary raw materials. Compared to conventional methods, microwave processing offers several advantages, such as selective heating, rapid heating, and volumetric heating. The present study gives a summary on our recent works related to the use of microwave energy for the recovery of valuable metals from primary and secondary raw materials. The research is mainly focusing on: Application of microwave for the recovery and recycling of metals from different metallurgical industries wastes (i.e. electric arc furnace (EAF) dust, blast furnace (BF), basic oxygen furnace (BOF) sludge). Application of microwave for upgrading and recovery of valuable metals from primary raw materials (i.e. iron ore). The results indicated that microwave heating is a promising and effective technique for processing primary and secondary steelmaking wastes. After microwave treatment of iron ore for 60 s and 900 W, about a 28.30% increase in grindability.Wet high intensity magnetic separation (WHIMS) indicated that the magnetic separation increased from 34% to 98% after microwave treatment for 90 s and 900 W. In the case of EAF dust, after microwave processing at 1100 W for 20 min, Zinc removal from 64 % to ~ 97 %, depending on mixture ratio and treatment time.

Keywords: dielectric properties, microwave heating, raw materials, secondary raw materials

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Authors: Alexandra-Monica Toma

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Internet memes are an element of computer mediated communication and an important part of online culture that combines text and image in order to generate meaning. This term coined by Richard Dawkings refers to more than a mere way to briefly communicate ideas or emotions, thus naming a complex and an intensely perpetuated phenomenon in the virtual environment. This paper approaches memes as a cultural artefact and a virtual trope that mirrors societal concerns and issues, and analyses the pragmatics of their use. Memes have to be analysed in series, usually relating to some image macros, which is proof of the interplay between imitation and creativity in the memes’ writing process. We believe that their potential to become viral relates to three key elements: adaptation to context, reference to a successful meme series, and humour (jokes, irony, sarcasm), with various pragmatic functions. The study also uses the concept of multimodality and stresses how the memes’ text interacts with the image, discussing three types of relations: symmetry, amplification, and contradiction. Moreover, the paper proves that memes could be employed as speech acts with illocutionary force, when the interaction between text and image is enriched through the connection to a specific situation. The features mentioned above are analysed in a corpus that consists of memes related to the COVID-19 pandemic. This corpus shows them to be highly adaptable to context, which helps build the feeling of connection and belonging in an otherwise tremendously fragmented world. Some of them are created based on well-known image macros, and their humour results from an intricate dialogue between texts and contexts. Memes created in relation to the COVID-19 pandemic can be considered speech acts and are often used as such, as proven in the paper. Consequently, this paper tackles the key features of memes, makes a thorough analysis of the memes sociocultural, linguistic, and situational context, and emphasizes their intertextuality, with special accent on their illocutionary potential.

Keywords: context, memes, multimodality, speech acts

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Authors: Homa Ghave, Parmis Shahmaleki

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This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

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Authors: Yili Chen, Jixiang Fu, Zhihua Liu, Zhicheng Zhang, Rongmao Li, Nan Fu, Yaoqin Xie

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Retinal prothesis is designed to help the blind to get some sight.It is made up of internal part and external part.In external part ,there is made up of camera, image processing, and RF transmitter.In internal part, there is RF receiver, implant chip,micro-electrode.The image got from the camera should be processed by suitable stragies to corresponds to stimulus the electrode.Nowadays, the number of the micro-electrode is hundreds and we don’t know the mechanism how the elctrode stimulus the optic nerve, an easy way to the hypothesis is that the pixel in the image is correspondence to the electrode.So it is a question how to get the important information of the image captured from the picture.There are many strategies to experimented to get the most important information as soon as possible, due to the real time system.ROI is a useful algorithem to extract the region of the interest.Our paper will explain the details of the orinciples and functions of the ROI.And based on this, we simplified the ROI algrithem,and used it in outside image prcessing DSP system of the retinal prothesis.Results show that our image processing stratiges is suitable for real-time retinal prothesis and can cut redundant information and help useful information to express in the low-size image.

Keywords: image processing, region of interest, saliency map, low-size image, useful information express, cut redundant information in image

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Authors: Samane Sharifi Monfared, Lavdie Rada

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Nowadays, autonomous vehicles are developing rapidly toward facilitating human car driving. One of the main issues is road lane detection for a suitable guidance direction and car accident prevention. This paper aims to improve and optimize road line detection based on a combination of camera calibration, the Hough transform, and Canny edge detection. The video processing is implemented using the Open CV library with the novelty of having a scale able region masking. The aim of the study is to introduce automatic road lane detection techniques with the user’s minimum manual intervention.

Keywords: hough transform, canny edge detection, optimisation, scaleable masking, camera calibration, improving the quality of image, image processing, video processing

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Rishabh Beri, Sahil Shah

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We have applied a range of filters and processing in order to extract out the various features of the football game, like the field lines of a football field. Another important aspect was the detection of the players in the field and tagging them according to their teams distinguished by their jersey colours. This extracted information combined about the players and field helped us to create a virtual field that consists of the playing field and the players mapped to their locations in it.

Keywords: Detect, Football, Players, Virtual

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Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

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Authors: Luis Enrique Bautista-Hinojosa, Luis A. Herrera, Cristian Arriaga-Canon

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Text should be written in the third person. Please avoid using "I" “my” or the pronoun "one". It is best to say "It is believed..." rather than "I believe..." or "One believes...".

Keywords: transcriptomics, co-expression, cancer, biomarkers

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Authors: Ouafa Sakka, Henri Barki, Louise Cote

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Uncertainty and equivocality are defined in the information processing literature as two task characteristics that require different information processing responses from managers. As uncertainty often stems from a lack of information, addressing it is thought to require the collection of additional data. On the other hand, as equivocality stems from ambiguity and a lack of understanding of the task at hand, addressing it is thought to require rich communication between those involved. Past research has provided weak to moderate empirical support to these hypotheses. The present study contributes to this literature by defining uncertainty and equivocality at the project level and investigating their moderating effects on the association between several project information processing constructs and project performance. The information processing constructs considered are the amount of information collected by the project team, and the richness and frequency of formal communications among the team members to discuss the project’s follow-up reports. Data on 93 information system development (ISD) project managers was collected in a questionnaire survey and analyzed it via the Fisher Test for correlation differences. The results indicate that the highest project performance levels were observed in projects characterized by high uncertainty and low equivocality in which project managers were provided with detailed and updated information on project costs and schedules. In addition, our findings show that information about user needs and technical aspects of the project is less useful to managing projects where uncertainty and equivocality are high. Further, while the strongest positive effect of interactive use of follow-up reports on performance occurred in projects where both uncertainty and equivocality levels were high, its weakest effect occurred when both of these were low.

Keywords: uncertainty, equivocality, information processing model, management control systems, project control, interactive use, diagnostic use, information system development

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Natia Kvachakidze

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Translating fiction is a complicated and multidimensional issue. However, studying and analyzing literary translations is not less challenging. This becomes even more complex due to the existence of several alternative translations of one and the same literary work. However, this also makes the research process more interesting at the same time. The aim of the given work is to distinguish major obstacles and challenges translators come across while working on Ernest Hemingway’s short fiction, as well as to analyze certain peculiarities and characteristic features of some existing Georgian translations of the writer’s work (especially in the context of various alternative versions of some well-known short stories). Consequently, the focus is on studying how close these translations come to the form and the context of the original text in order to see if the linguistic and stylistic characteristics of the original author are preserved. Moreover, it is interesting not only to study the relevance of each translation to the original text but also to present a comparative analysis of some major peculiarities of the given translations, which are naturally characterized by certain strengths and weaknesses. The latter is at times inevitable, but in certain cases, there is room for improvement. The given work also attempts to humbly suggest certain ways of possible improvements of some translation inadequacies, as this can provide even more opportunities for deeper and detailed studies in the future.

Keywords: Hemingway, short fiction, translation, Georgian

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Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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

Abstract:

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

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

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

Abstract:

Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Zarmina Gillani, Nuzhat Huma, Aysha Sameen, Mulazim Hussain Bukhari

Abstract:

Whey is an excellent food ingredient owing to its high nutritive value and its functional properties. However, composition of whey varies depending on composition of milk, processing conditions, processing method, and its whey protein content. The aim of this study was to prepare a whey powder from raw whey and to determine the influence of different processing temperatures (160 and 180 °C) on the physicochemical, functional properties during storage of 180 days and on whey protein denaturation. Results have shown that temperature significantly (P < 0.05) affects the pH, acidity, non-protein nitrogen (NPN), protein total soluble solids, fat and lactose contents. Significantly (p < 0.05) higher foaming capacity (FC), foam stability (FS), whey protein nitrogen index (WPNI), and a lower turbidity and solubility index (SI) were observed in whey powder processed at 160 °C compared to whey powder processed at 180 °C. During storage of 180 days, slow but progressive changes were noticed on the physicochemical and functional properties of whey powder. Reverse phase-HPLC analysis revealed a significant (P < 0.05) effect of temperature on whey protein contents. Denaturation of β-Lactoglobulin is followed by α-lacalbumin, casein glycomacropeptide (CMP/GMP), and bovine serum albumin (BSA).

Keywords: whey powder, temperature, denaturation, reverse phase, HPLC

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

Abstract:

Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: Elyta Widyaningrum

Abstract:

The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

Procedia PDF Downloads 368