Search results for: minority forms of information processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15711

Search results for: minority forms of information processing

15351 Grammatical Forms and Functions in Selected Political Interviews of Nigerian Presidential Aspirants in 2015 General Election

Authors: Temitope Abiodun Balogun

Abstract:

Political interviews are one of the ways by which political office-seekers in Nigeria sell themselves to the electorates. Extant studies have examined the discourse of political interviews from conversational, philosophical, rhetorical, stylistic and pragmatic perspectives with insufficient attention paid to grammatical forms and communicative intentions of the interviews granted by the two presidential aspirants in the 2015 Nigerian general election. This study fills this scholarly gap to unmask their grammatical forms and communicative styles, intention and credibility. The paper adopts Halliday’s Systemic Functional Grammar, specifically interpersonal function coupled with Searle’s Model of Speech Acts Theory as a theoretical framework. A total of six interviews granted by the two presidential aspirants in media serve as the source of data. It is discovered that, in most cases, politicians’ communicative intention is to “pull-down” their political opponents. While declarative and interrogatives are simple, direct and straightforward, the intention is to condemn, lambast and castigate their opponents. This communicative style does not allow the general populace to decipher the political manifestoes of the political aspirants and the party they represent. The paper recommends that before Nigeria can boast of any sustainable growth and development, there is the need for her political office-seekers to adopt effective communication strategies and styles to unveil their intention and manifestoes so that electorates can evaluate their performance after their tenure of office.

Keywords: general election, grammatical forms and function, political interviews, presidential aspirants

Procedia PDF Downloads 142
15350 The Need for Automation in the Domestic Food Processing Sector and its Impact

Authors: Shantam Gupta

Abstract:

The objective of this study is to address the critical need for automation in the domestic food processing sector and study its impact. Food is the one of the most basic physiological needs essential for the survival of a living being. Some of them have the capacity to prepare their own food (like most plants) and henceforth are designated as primary food producers; those who depend on these primary food producers for food form the primary consumers’ class (herbivores). Some of the organisms relying on the primary food are the secondary food consumers (carnivores). There is a third class of consumers called tertiary food consumers/apex food consumers that feed on both the primary and secondary food consumers. Humans form an essential part of the apex predators and are generally at the top of the food chain. But still further disintegration of the food habits of the modern human i.e. Homo sapiens, reveals that humans depend on other individuals for preparing their own food. The old notion of eating raw/brute food is long gone and food processing has become very trenchant in lives of modern human. This has led to an increase in dependence on other individuals for ‘processing’ the food before it can be actually consumed by the modern human. This has led to a further shift of humans in the classification of food chain of consumers. The effects of the shifts shall be systematically investigated in this paper. The processing of food has a direct impact on the economy of the individual (consumer). Also most individuals depend on other processing individuals for the preparation of food. This dependency leads to establishment of a vital link of dependency in the food web which when altered can adversely affect the food web and can have dire consequences on the health of the individual. This study investigates the challenges arising out due to this dependency and the impact of food processing on the economy of the individual. A comparison of Industrial food processing and processing at domestic platforms (households and restaurants) has been made to provide an idea about the present scenario of automation in the food processing sector. A lot of time and energy is also consumed while processing food at home for consumption. The high frequency of consumption of meals (greater than 2 times a day) makes it even more laborious. Through the medium of this study a pressing need for development of an automatic cooking machine is proposed with a mission to reduce the inter-dependency & human effort of individuals required for the preparation of food (by automation of the food preparation process) and make them more self-reliant The impact of development of this product has also further been profoundly discussed. Assumption used: The individuals those who process food also consume the food that they produce. (They are also termed as ‘independent’ or ‘self-reliant’ modern human beings.)

Keywords: automation, food processing, impact on economy, processing individual

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15349 Development of a Tesla Music Coil from Signal Processing

Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

Abstract:

This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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15348 Synthesis and Characterisation of Bi-Substituted Magnetite Nanoparticles by Mechanochemical Processing (MCP)

Authors: Morteza Mohri Esfahani, Amir S. H. Rozatian, Morteza Mozaffari

Abstract:

Single phase magnetite nanoparticles and Bi-substituted ones were prepared by mechanochemical processing (MCP). The effects of Bi-substitution on the structural and magnetic properties of the nanoparticles were studied by X-ray Diffraction (XRD) and magnetometry techniques, respectively. The XRD results showed that all samples have spinel phase and by increasing Bi content, the main diffraction peaks were shifted to higher angles, which means the lattice parameter decreases from 0.843 to 0.838 nm and then increases to 0.841 nm. Also, the results revealed that increasing Bi content lead to a decrease in saturation magnetization (Ms) from 74.9 to 48.8 emu/g and an increase in coercivity (Hc) from 96.8 to 137.1 Oe.

Keywords: bi-substituted magnetite nanoparticles, mechanochemical processing, X-ray diffraction, magnetism

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15347 Online Prediction of Nonlinear Signal Processing Problems Based Kernel Adaptive Filtering

Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

Procedia PDF Downloads 381
15346 Efficient Pre-Processing of Single-Cell Assay for Transposase Accessible Chromatin with High-Throughput Sequencing Data

Authors: Fan Gao, Lior Pachter

Abstract:

The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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15345 Resource Framework Descriptors for Interestingness in Data

Authors: C. B. Abhilash, Kavi Mahesh

Abstract:

Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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15344 The Patterns of Cross-Sentence: An Event-Related Potential Study of Mathematical Word Problem

Authors: Tien-Ching Yao, Ching-Ching Lu

Abstract:

Understanding human language processing is one of the main challenges of current cognitive neuroscience. The aims of the present study were to use a sentence decision task combined with event-related potentials to investigate the psychological reality of "cross-sentence patterns." Therefore, we take the math word problems the experimental materials and use the ERPs' P600 component to verify. In this study, the experimental material consisted of 200 math word problems with three different conditions were used ( multiplication word problems、division word problems type 1、division word problems type 2 ). Eighteen Mandarin native speakers participated in the ERPs study (14 of whom were female). The result of the grand average waveforms suggests a later posterior positivity at around 500ms - 900ms. These findings were tested statistically using repeated measures ANOVAs at the component caused by the stimulus type of different questions. Results suggest that three conditions present significant (P < 0.05) on the Mean Amplitude, Latency, and Peak Amplitude. The result showed the characteristic timing and posterior scalp distribution of a P600 effect. We interpreted these characteristic responses as the psychological reality of "cross-sentence patterns." These results provide insights into the sentence processing issues in linguistic theory and psycholinguistic models of language processing and advance our understanding of how people make sense of information during language comprehension.

Keywords: language processing, sentence comprehension, event-related potentials, cross-sentence patterns

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15343 Probing Language Models for Multiple Linguistic Information

Authors: Bowen Ding, Yihao Kuang

Abstract:

In recent years, large-scale pre-trained language models have achieved state-of-the-art performance on a variety of natural language processing tasks. The word vectors produced by these language models can be viewed as dense encoded presentations of natural language that in text form. However, it is unknown how much linguistic information is encoded and how. In this paper, we construct several corresponding probing tasks for multiple linguistic information to clarify the encoding capabilities of different language models and performed a visual display. We firstly obtain word presentations in vector form from different language models, including BERT, ELMo, RoBERTa and GPT. Classifiers with a small scale of parameters and unsupervised tasks are then applied on these word vectors to discriminate their capability to encode corresponding linguistic information. The constructed probe tasks contain both semantic and syntactic aspects. The semantic aspect includes the ability of the model to understand semantic entities such as numbers, time, and characters, and the grammatical aspect includes the ability of the language model to understand grammatical structures such as dependency relationships and reference relationships. We also compare encoding capabilities of different layers in the same language model to infer how linguistic information is encoded in the model.

Keywords: language models, probing task, text presentation, linguistic information

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15342 Capacity Enhancement for Agricultural Workers in Mangosteen Product

Authors: Cholpassorn Sitthiwarongchai, Chutikarn Sriviboon

Abstract:

The two primary objectives of this research were (1) to examine the current knowledge and actual circumstance of agricultural workers about mangosteen product processing; and (2) to analyze and evaluate ways to develop capacity of mangosteen product processing. The population of this study was 15,125 people who work in the agricultural sector, in this context, mangosteen production, in the eastern part of Thailand that included Chantaburi Province, Rayong Province, Trad Province and Pracheenburi Province. The sample size based on Yamane’s calculation with 95% reliability was therefore 392 samples. Mixed method was employed included questionnaire and focus group discussion with Connoisseurship Model used in order to collect quantitative and qualitative data. Key informants were used in the focus group including agricultural business owners, academic people in agro food processing, local academics, local community development staff, OTOP subcommittee, and representatives of agro processing industry professional organizations. The study found that the majority of the respondents agreed with a high level (in five-rating scale) towards most of variables of knowledge management in agro food processing. The result of the current knowledge and actual circumstance of agricultural human resource in an arena of mangosteen product processing revealed that mostly, the respondents agreed at a high level to establish 7 variables. The guideline to developing the body of knowledge in order to enhance the capacity of the agricultural workers in mangosteen product processing was delivered in the focus group discussion. The discussion finally contributed to an idea to produce manuals for mangosteen product processing methods, with 4 products chosen: (1) mangosteen soap, (2) mangosteen juice, (3) mangosteen toffee, and (4) mangosteen preserves or jam.

Keywords: capacity enhancement, agricultural workers, mangosteen product processing, marketing management

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15341 Nursing Documentation of Patients' Information at Selected Primary Health Care Facilities in Limpopo Province, South Africa: Implications for Professional Practice

Authors: Maria Sonto Maputle, Rhulani C. Shihundla, Rachel T. Lebese

Abstract:

Background: Patients’ information must be complete and accurately documented in order to foster quality and continuity of care. The multidisciplinary health care members use patients’ documentation to communicate about health status, preventive health services, treatment, planning and delivery of care. The purpose of this study was to determine the practice of nursing documentation of patients’ information at selected Primary Health Care (PHC) facilities in Vhembe District, Limpopo Province, South Africa. Methods: The research approach adopted was qualitative while exploratory and descriptive design was used. The study was conducted at selected PHC facilities. Population included twelve professional nurses. Non-probability purposive sampling method was used to sample professional nurses who were willing to participate in the study. The criteria included participants’ whose daily work and activities, involved creating, keeping and updating nursing documentation of patients’ information. Qualitative data collection was through unstructured in-depth interviews until no new information emerged. Data were analysed through open–coding of, Tesch’s eight steps method. Results: Following data analysis, it was found that professional nurses’ had knowledge deficit related to insufficient training on updates and rendering multiple services daily had negative impact on accurate documentation of patients’ information. Conclusion: The study recommended standardization of registers, books and forms used at PHC facilities, and reorganization of PHC services into open day system.

Keywords: documentation, knowledge, patient care, patient’s information, training

Procedia PDF Downloads 172
15340 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm

Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

Abstract:

Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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15339 Road Condition Monitoring Using Built-in Vehicle Technology Data, Drones, and Deep Learning

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

Abstract:

Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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15338 Information Communication Technology in Early Childhood Education: An Assessment of the Quality of ICT in the New Mega Primary Schools in Ondo State, Southwestern Nigeria

Authors: Oluyemi Christianah Ojo

Abstract:

This study seeks to investigate the quality of ICT provided in the new Caring Heart schools in Ondo State, Nigeria. The population for the study was all caring Heart Mega Schools in Ondo State, Nigeria. Research questions were generated; two instruments CCCMS and TQCUC were used to elicit information from the schools and the teachers. The study adopts descriptive survey approach. The studies revealed and concluded that ICT components were available and adequate in these schools, Charts showing ICT components and other forms of computer devices used as instructional materials were available but were not adequate; teachers teaching computer studies are competent in the delivery of instructions and in handling computer gadgets in the laboratory. The study recommended the provision of steady electricity, uninterrupted internet facilities and provision of adequate ICT components and charts for effective teaching delivery and learning.

Keywords: facilities, information communication technology, mega primary school, primary education

Procedia PDF Downloads 279
15337 The Resistance Reader Program Based on Image Processing

Authors: Janpen Srijan, Nahathai Tanmang, Thanit Purathanang, Anun Dowchern, Saksit Summart, Seangduan Kampimpa

Abstract:

This paper presents the resistance reader program based on image processing by using MATLAB. The proposed program is divided into six parts; the first part is the web camera; the second part is a watt selection before shooting the resistor; the third part is a part of finding the position of the color on the mid-point of resistor; the fourth part is a part of identifying color code of the resistor; the fifth part is a part of taking the number of values for each color for resistance calculation and the last part is a part of displaying result of resistance value. The experimental result of the resistance reader program based on image processing was able to display the resistance value of resistor. The accuracy of proposed program is 85 percent for 1 watt resistor. It has 15 percent of reading error because a problem with the color code of some resistor was too bright.

Keywords: resistance reader program, image processing, resistor, MATLAB

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15336 Developments in corporate governance and economic growth in Sub Saharan Africa

Authors: Martha Matashu

Abstract:

This study examined corporate governance and economic growth trends in Sub Saharan African (SSA) countries. The need for corporate governance arise from the fact that the day to day running of the business is done by management who in accordance with the neoclassical theory and agency theory have inborn tendencies to use the resources of the company to their advantage. This prevails against a background where the endogenous economic growth theory hold the assumption that economic growth is an outcome of the overall performance of all companies within an economy. This suggest that corporate governance at firm level determine economic growth through its impact on the overall performance. Nevertheless, insight into literature suggest that efforts to promote corporate governance in countries across SSA since the 1980s to date have not yet yielded desired outcomes. The board responsibilities, shareholder rights, disclosure and transparency, protection of minority shareholder, and liability of directors were thus used as proxies of corporate governance because these are believed to be mechanisms that are believed to enhance company performance their effect on enhancing accountability and transparency. Using panel data techniques, corporate governance and economic growth data for 29 SSA countries from the period of 2008 to 2019 was analysed. The findings revealed declining economic growth trend despite an increase in corporate governance aspects such as director liability, shareholders’ rights, and protection of minority shareholder in SSA countries. These findings are in contradiction to the popularly held theoretical principles of economic growth and corporate governance. The study reached the conclusion thata nonlinearrelationship exists between corporate governance and economic growth within the selectedSSA countries during the period under investigation. This study thus recommends that measures should be taken to create conditions for corporate governance that would bolster significant positive contributions to economic growth in the region.

Keywords: corporate governance, economic growth, sub saharan Africa, agency theory, endogenous theory

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15335 Efficient Filtering of Graph Based Data Using Graph Partitioning

Authors: Nileshkumar Vaishnav, Aditya Tatu

Abstract:

An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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15334 An Examination of Economic Evaluation Approaches in Mental Health Promotion Initiatives Targeted at Black and Asian Minority Ethnic Communities in the UK: A Critical Discourse Analysis

Authors: Phillipa Denise Peart

Abstract:

Black Asian and Minority Ethnic (BAME) people are more at risk of developing mental health disorders because they are more exposed to unfavorable social, economic, and environmental circumstances. These include housing, education, employment, community development, stigma, and discrimination. However, the majority of BAME mental health intervention studies focus on treatment with therapeutically effective drugs and use basic economic methods to evaluate their effectiveness; as a result, little is invested in the economic assessment of psychosocial interventions in BAME mental health. The UK government’s austerity programme and reduced funds for mental health services, has increased the need for the evaluation and assessment of initiatives to focus on value for money. The No Health without Mental Health policy (2011) provides practice guidance to practitioners, but there is little or no mention of the need to provide mental health initiatives targeted at BAME communities that are effective in terms of their impact and the cost-effectiveness. This, therefore, appears to contradict with and is at odds with the wider political discourse, which suggests there should be an increasing focus on health economic evaluation. As a consequence, it could be argued that whilst such policies provide direction to organisations to provide mental health services to the BAME community, by not requesting effective governance, assurance, and evaluation processes, they are merely paying lip service to address these problems and not helping advance knowledge and practice through evidence-based approaches. As a result, BAME communities suffer due to lack of efficient resources that can aid in the recovery process. This research study explores the mental health initiatives targeted at BAME communities, and analyses the techniques used when examining the cost effectiveness of mental health initiatives for BAME mental health communities. Using critical discourse analysis as an approach and method, mental health services will be selected as case studies, and their evaluations will be examined, alongside the political drivers that frame, shape, and direct their work. In doing so, it will analyse what the mental health policies initiatives are, how the initiatives are directed and demonstrate how economic models of evaluation are used in mental health programmes and how the value for money impacts and outcomes are articulated by mental health programme staff. It is anticipated that this study will further our understanding in order to provide adequate mental health resources and will deliver creative, supportive research to ensure evaluation is effective for the government to provide and maintain high quality and efficient mental health initiatives targeted at BAME communities.

Keywords: black, Asian and ethnic minority, economic models, mental health, health policy

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15333 COVID_ICU_BERT: A Fine-Tuned Language Model for COVID-19 Intensive Care Unit Clinical Notes

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

Abstract:

Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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15332 Variation in the Morphology of Soft Palate

Authors: Hema Lattupalli

Abstract:

Introduction: The palate forms a partition between the oral cavity and nasal cavity. The palate is made up of two parts hard palate and soft palate. The Hard palate forms the anterior part of the palate, the soft palate forms a movable muscular fold covered by mucous membrane that is suspended from the posterior border of a hard palate. Aim and Objectives: Soft palate morphological variations have a great paucity in the literature. It’s also believed that the soft palate has no such important anatomical variations. There is a variable presentation of the soft palate morphology in the lateral cephalograms. The aim of this study is to identify the velar morphology. Materials and Methods: 100 normal subjects between the age group of 20 – 35 were taken for the study. Method: Lateral Cephalogram (radiologic study). Results: Different shapes of the soft palate were observed in the lateral cephalograms. The morphology of soft palate was classified into six types 1.Leaf like (50 cases) most common type, 2.Straight line (20 cases), 3.S shaped (4 cases) very rare, 4.Butt like (10 cases), 5. Rat tail (6 cases), 6. Hook shaped (10 cases). Conclusion: This classification helps us to understand the better diversity of the velar morphology in mid-sagittal plane. These findings help us to understand the etiology of OSAS.

Keywords: soft palate, cephalometric radiographs, morphology, cleft palate, obstructive sleep apnoea syndrome

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15331 Reduction of Speckle Noise in Echocardiographic Images: A Survey

Authors: Fathi Kallel, Saida Khachira, Mohamed Ben Slima, Ahmed Ben Hamida

Abstract:

Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures.

Keywords: medical image processing, ultrasound images, Speckle noise, image enhancement, speckle filtering, segmentation, snakes

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15330 Structural Investigation of the GAF Domain Protein BPSL2418 from Burkholderia pseudomallei

Authors: Mona G. Alharbi

Abstract:

A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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15329 The Internet of Things Ecosystem: Survey of the Current Landscape, Identity Relationship Management, Multifactor Authentication Mechanisms, and Underlying Protocols

Authors: Nazli W. Hardy

Abstract:

A critical component in the Internet of Things (IoT) ecosystem is the need for secure and appropriate transmission, processing, and storage of the data. Our current forms of authentication, and identity and access management do not suffice because they are not designed to service cohesive, integrated, interconnected devices, and service applications. The seemingly endless opportunities of IoT are in fact circumscribed on multiple levels by concerns such as trust, privacy, security, loss of control, and related issues. This paper considers multi-factor authentication (MFA) mechanisms and cohesive identity relationship management (IRM) standards. It also surveys messaging protocols that are appropriate for the IoT ecosystem.

Keywords: identity relation management, multifactor authentication, protocols, survey of internet of things ecosystem

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15328 Recognition of Objects in a Maritime Environment Using a Combination of Pre- and Post-Processing of the Polynomial Fit Method

Authors: R. R. Hordijk, O. J. G. Somsen

Abstract:

Traditionally, radar systems are the eyes and ears of a ship. However, these systems have their drawbacks and nowadays they are extended with systems that work with video and photos. Processing of data from these videos and photos is however very labour-intensive and efforts are being made to automate this process. A major problem when trying to recognize objects in water is that the 'background' is not homogeneous so that traditional image recognition technics do not work well. Main question is, can a method be developed which automate this recognition process. There are a large number of parameters involved to facilitate the identification of objects on such images. One is varying the resolution. In this research, the resolution of some images has been reduced to the extreme value of 1% of the original to reduce clutter before the polynomial fit (pre-processing). It turned out that the searched object was clearly recognizable as its grey value was well above the average. Another approach is to take two images of the same scene shortly after each other and compare the result. Because the water (waves) fluctuates much faster than an object floating in the water one can expect that the object is the only stable item in the two images. Both these methods (pre-processing and comparing two images of the same scene) delivered useful results. Though it is too early to conclude that with these methods all image problems can be solved they are certainly worthwhile for further research.

Keywords: image processing, image recognition, polynomial fit, water

Procedia PDF Downloads 517
15327 Role of mHealth in Effective Response to Disaster

Authors: Mohammad H. Yarmohamadian, Reza Safdari, Nahid Tavakoli

Abstract:

In recent years, many countries have suffered various natural disasters. Disaster response continues to face the challenges in health care sector in all countries. Information and communication management is a significant challenge in disaster scene. During the last decades, rapid advances in information technology have led to manage information effectively and improve communication in health care setting. Information technology is a vital solution for effective response to disasters and emergencies so that if an efficient ICT-based health information system is available, it will be highly valuable in such situation. Of that, mobile technology represents a nearly computing technology infrastructure that is accessible, convenient, inexpensive and easy to use. Most projects have not yet reached the deployment stage, but evaluation exercises show that mHealth should allow faster processing and transport of patients, improved accuracy of triage and better monitoring of unattended patients at a disaster scene. Since there is a high prevalence of cell phones among world population, it is expected the health care providers and managers to take measures for applying this technology for improvement patient safety and public health in disasters. At present there are challenges in the utilization of mhealth in disasters such as lack of structural and financial issues in our country. In this paper we will discuss about benefits and challenges of mhealth technology in disaster setting considering connectivity, usability, intelligibility, communication and teaching for implementing this technology for disaster response.

Keywords: information technology, mhealth, disaster, effective response

Procedia PDF Downloads 422
15326 Social Innovation, Change and the Future of Resilient Communities in Tokyo

Authors: Heide Imai

Abstract:

The paper will introduce and discuss specific examples of urban practices which take place within the dynamic urban landscape of contemporary Tokyo. The rising interest and importance of derelict places as resilient and creative clusters will be analysed, before relating this to the rediscovery of small urban niches and the emergence of different forms of social entrepreneurs. Secondly, two different case study areas will be introduced before discussing different forms of hybrid lifestyles, social micro scale enterprises and social innovations, understanding the concept of ‘small places of resilience’ as zones of human interaction, desire and care in which spontaneous practices take place.

Keywords: entrepreneurship, social innovation, Tokyo, urban regeneration

Procedia PDF Downloads 460
15325 Co-Operation in Hungarian Agriculture

Authors: Eszter Hamza

Abstract:

The competitiveness of economic operators is based on interoperability, which is relatively low in Hungary. The development of co-operation is high priority in Common Agricultural Policy 2014-2020. The aim of the paper to assess co-operations in Hungarian agriculture, estimate the economic outputs and benefits of co-operations, based on statistical data processing and literature. Further objective is to explore the potential of agricultural co-operation with the help of interviews and questionnaire survey. The research seeks to answer questions as to what fundamental factors play role in the development of co-operation, and what are the motivations of the actors and the key success factors and pitfalls. The results were analysed using econometric methods. In Hungarian agriculture we can find several forms of co-operation: cooperatives, producer groups (PG) and producer organizations (PO), machinery cooperatives, integrator companies, product boards and interbranch organisations. Despite the several appearance of the agricultural co-operation, their economic weight is significantly lower in Hungary than in western European countries. Considering the agricultural importance, the integrator companies represent the most weight among the co-operations forms. Hungarian farmers linked to co-operations or organizations mostly in relation to procurement and sales. Less than 30 percent of surveyed farmers are members of a producer organization or cooperative. The trust level is low among farmers. The main obstacle to the development of formalized co-operation, is producers' risk aversion and the black economy in agriculture. Producers often prefer informal co-operation instead of long-term contractual relationships. The Hungarian agricultural co-operations are characterized by non-dynamic development, but slow qualitative change. For the future, one breakout point could be the association of producer groups and organizations, which in addition to the benefits of market concentration, in the dissemination of knowledge, advisory network operation and innovation can act more effectively.

Keywords: agriculture, co-operation, producer organisation, trust level

Procedia PDF Downloads 378
15324 Simplified Equations for Rigidity and Lateral Deflection for Reinforced Concrete Cantilever Shear Walls

Authors: Anas M. Fares

Abstract:

Reinforced concrete shear walls are the most frequently used forms of lateral resisting structural elements. These walls may take many forms due to their functions and locations in the building. In Palestine, the most lateral resisting forces construction forms is the cantilever shear walls system. It is thus of prime importance to study the rigidity of these walls. The virtual work theorem is used to derive the total lateral deflection of cantilever shear walls due to flexural and shear deformation. The case of neglecting the shear deformation in the walls is also studied, and it is found that the wall height to length aspect ratio (H/B) plays a major role in calculating the lateral deflection and the rigidity of such walls. When the H/B is more than or equal to 3.7, the shear deformation may be neglected from the calculation of the lateral deflection. Moreover, the walls with the same material properties, same lateral load value, and same aspect ratio, shall have the same of both the lateral deflection and the rigidity. Finally, an equation to calculate the total rigidity and total deflection of such walls is derived by using the virtual work theorem for a cantilever beam.

Keywords: cantilever shear walls, flexural deformation, lateral deflection, lateral loads, reinforced concrete shear walls, rigidity, shear deformation, virtual work theorem

Procedia PDF Downloads 204
15323 Uptake and Determinants of Rabies Pre-exposure Prophylaxis among At-Risk Travelers

Authors: Florian Lienert, Peter Costa, Caroline Aurensan, Elaine Melander

Abstract:

Introduction: Rabies pre-exposure prophylaxis (PrEP) can be given before travel and simplifies post-exposure prophylaxis (PEP). We studied the knowledge about rabies, the uptake of PrEP, and reasons for deciding for or against PrEP in at-risk travelers. We also examined how healthcare professionals (HCPs) counsel on rabies prevention. Methods: On behalf of Bavarian Nordic, Ipsos MORI conducted two online surveys in the USA. Fieldwork from February 24th to April 23rd, 2021, 689 participants aged 18-85 years, visited one of 91 endemic rabies countries in the past 3 years for at least one week, involved in at least 1 of 7 at-risk activities, heard of rabies, positive towards vaccination and chose to take part (surveyed travelers). Secondly, 76 HCPs, with responsibility for advising/ making decisions about vaccination requirements for their patients, personally recommend or prescribe vaccines for rabies, positive towards vaccination and chose to take part (surveyed HCPs). Results: A minority (36%) of surveyed travelers classified rabies as a life-threatening disease. A third of surveyed HCPs (37%) did not discuss rabies vaccination with at-risk travelers, 18% discussed only PEP, 23% only PrEP and 22% both. A minority (21%) of surveyed travelers reported having received rabies vaccination since they were 18. Among those participants (n=145), the most common reasons for deciding to get PrEP were for their own peace of mind (35%) and following an HCP recommendation (32%). Of those who decided not to receive the rabies vaccine (n=319), the most common reasons were that they did not think their risk of rabies was sufficient (23%) and that the HCP did not suggest it (23%). Conclusions: The survey demonstrated knowledge gaps around rabies and low PrEP coverage among surveyed travelers. It also highlighted the role of HCP recommendations and showed that most HCPs did not discuss PrEP with at-risk travelers.

Keywords: rabies, pre-exposure prophylaxis, travel, travel health, post-travel care, rabies treatment, vaccine, post-exposure, prophylaxis, at-risk, education, PrEP, PEP

Procedia PDF Downloads 169
15322 Crop Classification using Unmanned Aerial Vehicle Images

Authors: Iqra Yaseen

Abstract:

One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

Procedia PDF Downloads 86