Search results for: multimedia retrieval

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

Abstract:

Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

Procedia PDF Downloads 254

Authors: Kinda Alsamara

Abstract:

Foreign language education is a complex endeavor that often presents educators with a range of challenges and difficulties. This study shed light on the specific challenges encountered in the context of teaching Arabic as a foreign language at the Australian National University (ANU). Drawing from real-world experiences and insights, we explore the multifaceted nature of these challenges and discuss strategies that educators have employed to address them. The challenges in teaching the Arabic language encompass various dimensions, including linguistic intricacies, cultural nuances, and diverse learner backgrounds. The complex Arabic script, grammatical structures, and pronunciation patterns pose unique obstacles for learners. Moreover, the cultural context embedded within the language demands a nuanced understanding of cultural norms and practices. The diverse backgrounds of learners further contribute to the challenge of tailoring instruction to meet individual needs and proficiency levels. This study also underscores the importance of technology in tackling these challenges. Technological tools and platforms offer innovative solutions to enhance language acquisition and engagement. Online resources, interactive applications, and multimedia content can provide learners with immersive experiences, aiding in overcoming barriers posed by traditional teaching methods. Furthermore, this study addresses the role of instructors in mitigating challenges. Educators often find themselves adapting teaching approaches to accommodate different learning styles, abilities, and motivations. Establishing a supportive learning environment and fostering a sense of community can contribute significantly to overcoming challenges related to learner diversity. In conclusion, this study provides a comprehensive overview of the challenges faced in teaching Arabic as a foreign language at ANU. By recognizing these challenges and embracing technological and pedagogical advancements, educators can create more effective and engaging learning experiences for students pursuing Arabic language proficiency.

Keywords: Arabic, Arabic online, blended learning, teaching and learning, Arabic language, educational aids, technology

Procedia PDF Downloads 37

Authors: Tamara Bastianello, Rachele Ferrari, Marinella Majorano

Abstract:

The adoption of the syllabic approach in preschool programmes could support and reinforce meta-phonological awareness and literacy skills in children. The introduction of a meta-phonological intervention in preschool could facilitate the transition to primary school, especially for children with learning fragilities. In the present contribution, we want to investigate the efficacy of "Simo-syl" intervention in enhancing emergent literacy skills in children (especially for reading). Simo-syl is a 12 weeks multimedia programme developed for children to improve their language and communication skills and later literacy development in preschool. During the intervention, Simo-syl, an invented character, leads children in a series of meta-phonological games. Forty-six Italian preschool children (i.e., the Simo-syl group) participated in the programme; seventeen preschool children (i.e., the control group) did not participate in the intervention. Children in the two groups were between 4;10 and 5;9 years. They were assessed on their vocabulary, morpho-syntactical, meta-phonological, phonological, and phono-articulatory skills twice: 1) at the beginning of the last year of the preschool through standardised paper-based assessment tools and 2) one week after the intervention. All children in the Simo-syl group took part in the meta-phonological programme based on the syllabic approach. The intervention lasted 12 weeks (three activities per week; week 1: activities focused on syllable blending and spelling and a first approach to the written code; weeks 2-11: activities focused on syllables recognition; week 12: activities focused on vowels recognition). Very few children (Simo-syl group = 21, control group = 9) were tested again (post-test) one week after the intervention. Before starting the intervention programme, the Simo-syl and the control groups had similar meta-phonological, phonological, lexical skills (all ps > .05). One week after the intervention, a significant difference emerged between the two groups in their meta-phonological skills (syllable blending, p = .029; syllable spelling, p = .032), in their vowel recognition ability (p = .032) and their word reading skills (p = .05). An ANOVA confirmed the effect of the group membership on the developmental growth for the word reading task (F (1,28) = 6.83, p = .014, ηp2 = .196). Taking part in the Simo-syl intervention has a positive effect on the ability to read in preschool children.

Keywords: intervention programme, literacy skills, meta-phonological skills, syllabic approach

Procedia PDF Downloads 137

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

Procedia PDF Downloads 298

Authors: Cristian Soitu, Alexander Feuerborn, Cyril Deroy, Alfonso Castrejon-Pita, Peter R. Cook, Edmond J. Walsh

Abstract:

Microfluidics now stands as an academically mature technology after a quarter of a century research activities have delivered a vast array of proof of concepts for many biological workflows. However, translation to industry remains poor, with only a handful of notable exceptions – e.g. digital PCR, DNA sequencing – mainly because of biocompatibility issues, limited range of readouts supported or complex operation required. This technology exploits the domination of interfacial forces over gravitational ones at the microscale, replacing solid walls with fluid ones as building blocks for cell micro-environments. By employing only materials used by biologists for decades, the system is shown to be biocompatible, and easy to manufacture and operate. The method consists in displacing a continuous fluid layer into a pattern of isolated chambers overlaid with an immiscible liquid to prevent evaporation. The resulting fluid arrangements can be arrays of micro-chambers with rectangular footprint, which use the maximum surface area available, or structures with irregular patterns. Pliant, self-healing fluid walls confine volumes as small as 1 nl. Such fluidic structures can be reconfigured during the assays, giving the platform an unprecedented level of flexibility. Common workflows in cell biology are demonstrated – e.g. cell growth and retrieval, cloning, cryopreservation, fixation and immunolabeling, CRISPR-Cas9 gene editing, and proof-of-concept drug tests. This fluid-shaping technology is shown to have potential for high-throughput cell- and organism-based assays. The ability to make and reconfigure on-demand microfluidic circuits on standard Petri dishes should find many applications in biology, and yield more relevant phenotypic and genotypic responses when compared to standard microfluidic assays.

Keywords: fluid walls, micro-chambers, reconfigurable, freestyle

Procedia PDF Downloads 167

Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

Abstract:

Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

Procedia PDF Downloads 234

Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

Abstract:

In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

Procedia PDF Downloads 200

Authors: Vishal Raj, Noorhan Abbas

Abstract:

Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

Procedia PDF Downloads 70

Authors: Covadonga Rodrigo, Felipe Alvarez Arrieta, Ana Garcia Serrano

Abstract:

Mobile augmented reality technologies have become very popular in the last years in the educational field. Researchers have studied how these technologies improve the engagement of the student and better understanding of the process of learning. But few studies have been made regarding the accessibility of these new technologies applied to digital humanities. The goal of our research is to develop an accessible mobile application with embedded augmented reality main characters of the art work and gamification events accompanied by multi-sensorial activities. The mobile app conducts a learning itinerary around the artistic work, driving the user experience in and out the museum. The learning design follows the inquiry-based methodology and social learning conducted through interaction with social networks. As for the software application, it’s being user-centered designed, following the universal design for learning (UDL) principles to assure the best level of accessibility for all. The mobile augmented reality application starts recognizing a marker from a masterpiece of a museum using the camera of the mobile device. The augmented reality information (history, author, 3D images, audio, quizzes) is shown through virtual main characters that come out from the art work. To comply with the UDL principles, we use a version of the technology acceptance model (TAM) to study the easiness of use and perception of usefulness, extended by the authors with specific indicators for measuring accessibility issues. Following a rapid prototype method for development, the first app has been recently produced, fulfilling the EN 301549 standard and W3C accessibility guidelines for mobile development. A TAM-based web questionnaire with 214 participants with different kinds of disabilities was previously conducted to gather information and feedback on user preferences from the artistic work on the Museo del Prado, the level of acceptance of technology innovations and the easiness of use of mobile elements. Preliminary results show that people with disabilities felt very comfortable while using mobile apps and internet connection. The augmented reality elements seem to offer an added value highly engaging and motivating for the students.

Keywords: H.5.1 (multimedia information systems), artificial, augmented and virtual realities, evaluation/methodology

Procedia PDF Downloads 104

Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

Abstract:

Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

Procedia PDF Downloads 178

Authors: Jinghui Wang, Minjie Xing

Abstract:

The increasing number of international students for doctoral education has brought vitality and diversity to the educational environment in China, and at the same time constituted a new challenge to the English teaching in the higher education as the majority of international students come from developing countries where English is not their first language. To make their contribution to knowledge development and technical innovation, these international doctoral students need to present their research work in English, locally and globally. This study reports an exploratory study with an emphasis on the cognition and construction of academic discourse in the multicultural context. The present study aims to explore ways to better prepare them for international academic exchange in English. Voluntarily, all international doctoral students (n = 81) from 35 countries enrolled in the English Course: Speaking and Writing as a New Scientist, participated in the study. Two research questions were raised: 1) What did these doctoral students say about their cognition and construction of English academic discourses? 2) How did they manage to develop their productive skills in a multicultural context? To answer the research questions, data were collected from self-reports, in-depth interviews, and video-recorded class observations. The major findings of the study suggest that the participants to varying degrees benefitted from the cognition and construction of English academic discourse in the multicultural context. Specifically, 1) The cognition and construction of meta-discourse allowed them to construct their own academic discourses in English; 2) In the light of Swales’ CARS Model, they became sensitive to the “moves” involved in the published papers closely related to their study, and learned to use them in their English academic discourses; 3) Multimodality-driven presentation (multimedia modes) enabled these doctoral student to have their voice heard for technical innovation purposes; 4) Speaking as a new scientist, every doctoral student felt happy and able to serve as an intercultural mediator in the multicultural context, bridging the gap between their home culture and the global culture; and most importantly, 5) most of the participants reported developing an English discourse community among international doctoral students, becoming resourceful and productive in the multicultural context. It is concluded that the cognition and construction of academic discourse in the multicultural context proves to be conducive to the productivity and intercultural citizenship education of international doctoral students.

Keywords: academic discourse, international doctoral students, meta-discourse, multicultural context

Procedia PDF Downloads 362

Authors: Hsin Lee, Hsuan Lee

Abstract:

Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

Procedia PDF Downloads 46

Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

Abstract:

Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

Procedia PDF Downloads 156

Authors: C. Vogeler

Abstract:

Change processes such as individualization and digitalization have an impact on higher education. Graduates are expected to cooperate in creative work processes in their professional life. During their studies, they need to be prepared accordingly. This includes modern learning scenarios that integrate the benefits of digital media. Therefore, design thinking and blended learning have been combined in the project-based seminar conception introduced here. The presented seminar conception has been realized and evaluated with students of information sciences since September 2017. Within the seminar, the students learn to work on a project. They apply the methods in a problem-based learning scenario. Task of the case study is to arrange a conference on the topic gaming in libraries. In order to collaborative develop creative possibilities of realization within the group of students the design thinking method has been chosen. Design thinking is a method, used to create user-centric, problem-solving and need-driven innovation through creative collaboration in multidisciplinary teams. Central characteristics are the openness of this approach to work results and the visualization of ideas. This approach is now also accepted in the field of higher education. Especially in problem-based learning scenarios, the method offers clearly defined process steps for creative ideas and their realization. The creative process can be supported by digital media, such as search engines and tools for the documentation of brainstorming, creation of mind maps, project management etc. Because the students have to do two-thirds of the workload in their private study, design thinking has been combined with a blended learning approach. This supports students’ preparation and follow-up of the joint work in workshops (flipped classroom scenario) as well as the communication and collaboration during the entire project work phase. For this purpose, learning materials are provided on a Moodle-based learning platform as well as various tools that supported the design thinking process as described above. In this paper, the seminar conception with a combination of design thinking and blended learning is described and the potentials and limitations of the chosen strategy for the development of a course with a multimedia approach in higher education are reflected.

Keywords: blended learning, design thinking, digital media tools and methods, flipped classroom

Procedia PDF Downloads 170

Authors: Chang Yu Chuan

Abstract:

Background and Aim: Pressure sore is not only the consequence of any gradual damage of the skin leading to tissue defects but also an important indicator of clinical care. If hospitalized patients develop pressure sores without proper care, it would result in delayed healing, wound infection, increase patient physical pain, prolonged hospital stay and even death, which would have a negative impact on the quality of care and also increase nursing manpower and medical costs. This project is aimed at decreasing the incidence of pressure sore in one ward of internal medicine. Our data showed 53 cases (0.61%) of pressure sore in 2015, which exceeded the average (0.5%) of Taiwan Clinical Performance Indicator (TCPI) for medical centers. The purpose of this project is to reduce the incidence rate of pressure sore in the ward. After data collection and analysis from January to December 2016, the reasons of developing pressure sore were found: 1. Lack of knowledge to prevent pressure among nursing staffs; 2. No relevant courses about preventing pressure ulcers and pressure wound care being held in this unit; 3. Low complete rate of pressure sore care education that family members should receive from nursing staffs; 4. Decompression equipment is not enough; 5. Lack of standard procedures for body-turning and positioning care. After team members brainstorming, several strategies were proposed, including holding in-service education, pressure sore care seed training, purchasing decompression mattress and memory pillows, designing more elements of health education tools, such as health education pamphlet, posters and multimedia films of body-turning and positioning demonstration, formulation and promotion of standard operating procedures. In this way, nursing staffs can understand the body-turning and positioning guidelines for pressure sore prevention and enhance the quality of care. After the implementation of this project, the pressure sore density significantly decreased from 0.61%(53 cases) to 0.45%(28 cases) in this ward. The project shows good results and good example for nurses working at the ward and helps to enhance quality of care.

Keywords: body-turning and positioning, incidence density, nursing, pressure sore

Procedia PDF Downloads 245

Authors: Denise Levy, Anna Lucia C. H. Villavicencio

Abstract:

Food irradiation is a processing and preservation technique to eliminate insects and parasites and reduce disease-causing microorganisms. Moreover, the process helps to inhibit sprouting and delay ripening, extending fresh fruits and vegetables shelf-life. Nevertheless, most Brazilian consumers seem to misunderstand the difference between irradiated food and radioactive food and the general public has major concerns about the negative health effects and environmental contamination. Society´s judgment and decision making are directly linked to perceived benefits and risks. The web-based project entitled ‘Scientific information about food irradiation: Internet as a tool to approach science and society’ was created by the Nuclear and Energetic Research Institute (IPEN), in order to offer an interdisciplinary approach to science education, integrating economic, ethical, social and political aspects of food irradiation. This project takes into account that, misinformation and unfounded preconceived ideas impact heavily on the acceptance of irradiated food and purchase intention by the Brazilian consumer. Taking advantage of the potential value of the Internet to enhance communication and education among general public, a research study was carried out regarding the possibilities and trends of Information and Communication Technologies among the Brazilian population. The content includes concepts, definitions and Frequently Asked Questions (FAQ) about processes, safety, advantages, limitations and the possibilities of food irradiation, including health issues, as well as its impacts on the environment. The project counts on eight self-instructional interactive web courses, situating scientific content in relevant social contexts in order to encourage self-learning and further reflections. Communication is a must to improve public understanding of science. The use of information technology for quality scientific divulgation shall contribute greatly to provide information throughout the country, spreading information to as many people as possible, minimizing geographic distances and stimulating communication and development.

Keywords: food irradiation, multimedia learning tools, nuclear science, society and education

Procedia PDF Downloads 222

Authors: Nooraisah Katmon, Hartini Jaafar, Hazianti Abdul Halim, Jessnor Elmy Mat Jizat

Abstract:

Our study empirically examines the effect of student activities on Facebook and religion on academic performance. We extend prior research in this area in a number of ways. First, given the paucity of the research in this area particularly from the Asian context, we provide the evidence from developing country like Malaysia. Second, our sample drawn from Sultan Idris Education University in Malaysia, where graduates from these universities are unique since they are expected to be able to work in both education and industry environment, and presumed to play significant roles in shaping the development of future student’s intellectual at the Malaysian secondary school and Malaysian economy in general. Third, we control for religiosity aspect when examining the association between Facebook and academic performance, something that has been predominantly neglected by the prior studies. Fourth, unlike prior studies that circulating around the Christian sphere in measuring religiosity, we provide evidence from the Islamic perspective where the act of worships and practices are much more comprehensive rather than the Christian counterparts. Fifth, we examine whether Facebook activities and religiosity are complementary or substitutive each other in improving student’s academic performance. Our sample comprise of 60 undergraduates. Our result exhibit that students with high number of friends on facebook and frequent engagement on facebook activities, such as sharing links, send message, posting photo, tagging video as well as spending long hours on facebook generally are associated with lower academic performance. Our results also reported that student’s engagement in religious activities promotes better academic performance. When we examine the potential interaction effect between facebook and religiosity, our result revealed that religiosity is effective in reducing student’s interest on facebook, hence lead to better academic achievement. In other words, religious student will be less interested in joining activities on facebook and make them more perform than their counterparts. Our findings from this study should be able to assist the university management in shaping university policies and curriculum to regulate and manage student’s activities in order to enhance overall student’s quality. Moreover, the findings from this study are also of use to the policy maker such as Malaysian Communication and Multimedia Commissions to regulate the policy on the student’s access and activities on facebook.

Keywords: facebook, religiosity, academic performance, effect of student activities

Procedia PDF Downloads 287

Authors: Tamara Vagg, Cathy Shortt, Claire Hickey, Joseph A. Eustace, Barry J. Plant, Sabin Tabirca

Abstract:

Introduction: Paper-based patient passports have been used advantageously for older patients, patients with diabetes, and patients with learning difficulties. However, these passports can experience issues with data security, patients forgetting to bring the passport, patients being over encumbered, and uncertainty with who is responsible for entering and managing data in this passport. These issues could be resolved by transferring the paper-based system to a convenient platform such as a smartphone application (app). Background: Life expectancy for some Cystic Fibrosis (CF) patients are rising and as such new complications and procedures are predicted. Subsequently, there is a need for education and management interventions that can benefit CF adults. This research proposes a CF patient passport to record basic medical information through a smartphone app which will allow CF adults access to their basic medical information. Aim: To provide CF patients with their basic medical information via mobile multimedia so that they can receive care when traveling abroad or between CF centres. Moreover, by recording their basic medical information, CF patients may become more aware of their own condition and more active in their health care. Methods: This app is designed by a CF multidisciplinary team to be a lightweight reflection of a hospital patient file. The passport app is created using PhoneGap so that it can be deployed for both Android and iOS devices. Data entered into the app is encrypted and stored locally only. The app is password protected and includes the ability to set reminders and a graph to visualise weight and lung function over time. The app is introduced to seven participants as part of a stress test. The participants are asked to test the performance and usability of the app and report any issues identified. Results: Feedback and suggestions received via this testing include the ability to reorder the list of clinical appointments via date, an open format of recording dates (in the event specifics are unknown), and a drop down menu for data which is difficult to enter (such as bugs found in mucus). The app is found to be usable and accessible and is now being prepared for a pilot study with adult CF patients. Conclusions: It is anticipated that such an app will be beneficial to CF adult patients when travelling abroad and between CF centres.

Keywords: Cystic Fibrosis, digital patient passport, mHealth, self management

Procedia PDF Downloads 222

Authors: A. Kalizhanova, T. Shelestova

Abstract:

Teacher professional development (TPD) in Kazakhstan has followed a fairly standard format for centuries, with teachers learning new information from a lecturer and being tested using multiple-choice questions. In the online world, self-access courses have become increasingly popular. Due to their extensive multimedia content, peer-reviewed assignments, adaptable class times, and instruction from top university faculty from across the world, massive open online courses (MOOCs) have found a home in Kazakhstan's system for lifelong learning. Recent studies indicate the limited use of connectivism-based tools such as discussion forums by Kazakhstani pre-service and in-service English teachers, whose professional interests are limited to obtaining certificates rather than enhancing their teaching abilities and exchanging knowledge with colleagues. This paper highlights the significance of connectivism-based tools and instruments, such as MOOCs, for the continuous professional development of pre- and in-service English teachers, facilitators' roles, and their strategies for enhancing trainees' conceptual knowledge within the MOOCs' curriculum and online learning skills. Reviewing the most pertinent papers on Connectivism Theory, facilitators' function in TPD, and connectivism-based tools, such as MOOCs, a code extraction method was utilized. Three experts, former active participants in a series of projects initiated across Kazakhstan to improve the efficacy of MOOCs, evaluated the excerpts and selected the most appropriate ones to propose the matrix of teacher professional competencies that can be acquired through MOOCs. In this paper, we'll look at some of the strategies employed by course instructors to boost their students' English skills and knowledge of course material, both inside and outside of the MOOC platform. Participants' interactive learning contributed to their language and subject conceptual knowledge and prepared them for peer-reviewed assignments in the MOOCs, and this approach of small group interaction was given to highlight the outcomes of participants' interactive learning. Both formal and informal continuing education institutions can use the findings of this study to support teachers in gaining experience with MOOCs and creating their own online courses.

Keywords: connectivism-based tools, teacher professional development, massive open online courses, facilitators, Kazakhstani context

Procedia PDF Downloads 43

Authors: Sohini Manna, Jong Woo Kim, Oleg Shpyrko, Eric E. Fullerton

Abstract:

CVD techniques have emerged as a promising approach in the formation of a broad range of nanostructured materials. The realization of many practical applications will require efficient and economical synthesis techniques that preferably avoid the need for templates or costly single-crystal substrates and also afford process adaptability. Towards this end, we have developed a single-step route for the reduction-type synthesis of nanostructured Ni materials using a thermal CVD method. By tuning the CVD growth parameters, we can synthesize morphologically dissimilar nanostructures including single-crystal cubes and Au nanostructures which form atop untreated amorphous SiO2||Si substrates. An understanding of the new properties that emerge in these nanostructures materials and their relationship to function will lead to for a broad range of magnetostrictive devices as well as other catalysis, fuel cell, sensor, and battery applications based on high-surface-area transition-metal nanostructures. We use coherent X-ray diffraction imaging technique to obtain 3-D image and strain maps of individual nanocrystals. Coherent x-ray diffractive imaging (CXDI) is a technique that provides the overall shape of a nanostructure and the lattice distortion based on the combination of highly brilliant coherent x-ray sources and phase retrieval algorithm. We observe a fine interplay of reduction of surface energy vs internal stress, which plays an important role in the morphology of nano-crystals. The strain distribution is influenced by the metal-substrate interface and metal-air interface, which arise due to differences in their thermal expansion. We find the lattice strain at the surface of the octahedral gold nanocrystal agrees well with the predictions of the Young-Laplace equation quantitatively, but exhibits a discrepancy near the nanocrystal-substrate interface resulting from the interface. The strain in the bottom side of the Ni nanocube, which is contacted on the substrate surface is compressive. This is caused by dissimilar thermal expansion coefficients between Ni nanocube and Si substrate. Research at UCSD support by NSF DMR Award # 1411335.

Keywords: CVD, nanostructures, strain, CXRD

Procedia PDF Downloads 369

Authors: Gul Rahim Rahimi

Abstract:

The IoT-based soil moisture monitoring system for indoor plants is designed to address the challenges of maintaining optimal moisture levels in soil for plant growth and health. The system utilizes sensor technology to collect real-time data on soil moisture levels, which is then processed and analyzed using machine learning algorithms. This allows for accurate and timely monitoring of soil moisture levels, ensuring plants receive the appropriate amount of water to thrive. The main objectives of the system are twofold: to keep plants fresh and healthy by preventing water deficiency and to provide users with comprehensive insights into the water content of the soil on a daily and hourly basis. By monitoring soil moisture levels, users can identify patterns and trends in water consumption, allowing for more informed decision-making regarding watering schedules and plant care. The scope of the system extends to the agriculture industry, where it can be utilized to minimize the efforts required by farmers to monitor soil moisture levels manually. By automating the process of soil moisture monitoring, farmers can optimize water usage, improve crop yields, and reduce the risk of plant diseases associated with over or under-watering. Key technologies employed in the system include the Capacitive Soil Moisture Sensor V1.2 for accurate soil moisture measurement, the Node MCU ESP8266-12E Board for data transmission and communication, and the Arduino framework for programming and development. Additionally, machine learning algorithms are utilized to analyze the collected data and provide actionable insights. Cloud storage is utilized to store and manage the data collected from multiple sensors, allowing for easy access and retrieval of information. Overall, the IoT-based soil moisture monitoring system offers a scalable and efficient solution for indoor plant care, with potential applications in agriculture and beyond. By harnessing the power of IoT and machine learning, the system empowers users to make informed decisions about plant watering, leading to healthier and more vibrant indoor environments.

Keywords: IoT-based, soil moisture monitoring, indoor plants, water management

Procedia PDF Downloads 22

Authors: Mohaya Farzin, Parvin Babaei, Mohammad Rostampour

Abstract:

Ghrelin plays a considerable role in important neurological effects related to food intake and energy homeostasis. As was found, regular physical activity may make available significant improvements to cognitive functions in various behavioral situations. Anxiety is one of the main concerns of the modern world, affecting millions of individuals’ health. There are contradictory results regarding ghrelin's effects on anxiety-like behavior, and the plasma level of this peptide is increased during physical activity. Here we aimed to evaluate the coincident effects of exogenous ghrelin and aerobic exercise on anxiety-like behavior and passive avoidance memory in Wistar rats. Forty-five male Wistar rats (250 ± 20 g) were divided into 9 groups (n=5) and received intra-hippocampal injections of 3.0 nmol ghrelin and performed aerobic exercise training for 8 weeks. Control groups received the same volume of saline and diazepam as negative and positive control groups, respectively. Learning and memory were estimated using a shuttle box apparatus, and anxiety-like behavior was recorded by an elevated plus-maze test (EPM). Data were analyzed by ANOVA test, and p<0.05 was considered significant. Our findings showed that the combined effect of ghrelin and aerobic exercise improves the acquisition, consolidation, and retrieval of passive avoidance memory in Wistar rats. Furthermore, it is supposed that the ghrelin receiving group spent less time in open arms and fewer open arms entries compared with the control group (p<0.05). However, exercising Wistar rats spent more time in the open arm zone in comparison with the control group (p<0.05). The exercise + Ghrelin administration established reduced anxiety (p<0.05). The results of this study demonstrate that aerobic exercise contributes to an increase in the endogenous production of ghrelin, and physical activity alleviates anxiety-related behaviors induced by intra-hippocampal injection of ghrelin. In general, exercise and ghrelin can reduce anxiety and improve memory.

Keywords: anxiety, ghrelin, aerobic exercise, learning, passive avoidance memory

Procedia PDF Downloads 98

Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

Abstract:

The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: electric propulsion, mass gauging, propellant, PVT, xenon

Procedia PDF Downloads 321

Authors: Ghazal Faraj, Andras Micsik

Abstract:

The CIDOC Conceptual Reference Model (CRM) is an extensible ontology that provides integrated access to heterogeneous and digital datasets. The CIDOC-CRM offers a “semantic glue” intended to promote accessibility to several diverse and dispersed sources of cultural heritage data. That is achieved by providing a formal structure for the implicit and explicit concepts and their relationships in the cultural heritage field. The COURAGE (“Cultural Opposition – Understanding the CultuRal HeritAGE of Dissent in the Former Socialist Countries”) project aimed to explore methods about socialist-era cultural resistance during 1950-1990 and planned to serve as a basis for further narratives and digital humanities (DH) research. This project highlights the diversity of flourished alternative cultural scenes in Eastern Europe before 1989. Moreover, the dataset of COURAGE is an online RDF-based registry that consists of historical people, organizations, collections, and featured items. For increasing the inter-links between different datasets and retrieving more relevant data from various data silos, a shared federated ontology for reconciled data is needed. As a first step towards these goals, a full understanding of the CIDOC CRM ontology (target ontology), as well as the COURAGE dataset, was required to start the work. Subsequently, the queries toward the ontology were determined, and a table of equivalent properties from COURAGE and CIDOC CRM was created. The structural diagrams that clarify the mapping process and construct queries are on progress to map person, organization, and collection entities to the ontology. Through mapping the COURAGE dataset to CIDOC-CRM ontology, the dataset will have a common ontological foundation with several other datasets. Therefore, the expected results are: 1) retrieving more detailed data about existing entities, 2) retrieving new entities’ data, 3) aligning COURAGE dataset to a standard vocabulary, 4) running distributed SPARQL queries over several CIDOC-CRM datasets and testing the potentials of distributed query answering using SPARQL. The next plan is to map CIDOC-CRM to other upper-level ontologies or large datasets (e.g., DBpedia, Wikidata), and address similar questions on a wide variety of knowledge bases.

Keywords: CIDOC CRM, cultural heritage data, COURAGE dataset, ontology alignment

Procedia PDF Downloads 120

Authors: Yun Chen, Qihang Liu, Catherine Ticehurst, Chandrama Sarker, Fazlul Karim, Dave Penton, Ashmita Sengupta

Abstract:

The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect with water. The ICESAT-2 track generates multiple VSs as it crosses the different water bodies. The difficulties are particularly pronounced in large river basins where there are many tributaries and meanders often adjacent to each other. One challenge is to split photon segments along a beam to accurately partition them to extract only the true representative water height for individual elements. As far as we can establish, there is no automated procedure to make this distinction. Earlier studies have relied on human intervention or river masks. Both approaches are unsatisfactory solutions where the number of intersections is large, and river width/extent changes over time. We describe here an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparison with river water level observations at 10 different stations on 37 different dates along the Lower Murray River, Australia. The congruence is very high and without detectable bias. In addition, we compared different outlier removal methods on the mean WSE calculation at VSs post the auto-segmentation process. All four outlier removal methods perform almost equally well with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189m) and MAE (0.130–0.142m). Overall, the auto-segmentation method developed here is an effective and efficient approach to deriving accurate mean WSE at river VSs. It provides a much better way of facilitating the application of ICESAT-2 ATL13 altimetry to rivers compared to previously reported studies. Therefore, the findings of our study will make a significant contribution towards the retrieval of hydraulic parameters, such as water surface slope along the river, water depth at cross sections, and river channel bathymetry for calculating flow velocity and discharge from remotely sensed imagery at large spatial scales.

Keywords: lidar sensor, virtual station, cross section, mean water surface elevation, beam/track segmentation

Procedia PDF Downloads 35

Authors: Arafan Traore, Teiji Watanabe

Abstract:

Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

Procedia PDF Downloads 216

Authors: Mohamed H. Khalil

Abstract:

Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

Procedia PDF Downloads 62

Authors: Abisha Isaac Mohanlal

Abstract:

Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

Procedia PDF Downloads 198

Authors: Rhaetian Bern D. Azaula

Abstract:

The Philippines' indigenous population, estimated to be 10%-20%, is protected by the Indigenous Peoples Rights Act (IPRA), passed in 1997. However, due to their isolation and limited access to basic services such as health education or needs for health assistance, the law's implementation remains a challenge. As traditional medicine continues to play a significant role in society as the prevention and treatment of some illnesses, it is still customary and widely used to use plants in both traditional and modern ways; however, commercially prepared drugs are progressively advanced as time goes by. Therefore, the purpose of this quantitative study is to investigate the indigenous community at Barangay Magsikap General Nakar, Quezon, and analyze the factors that affect the respondent’s preferences in an indigenous community and reasons for patronizing traditional and commercially prepared medicines and proposes updated health education strategies and instructional materials. Slovin's formula was utilized to reduce the total population representation, followed by stratified sampling for proportional allocation of respondents. The study selects respondents (1) from an Indigenous Community in Barangay Magsikap, General Nakar, Quezon, (2) aged 60 and above, and (3) who are willing to participate. The researcher utilized a checklist-based questionnaire with a Tagalog version, and a Likert Scale was utilized to assess the respondent's choices on selected items. The researcher obtained informed consent from the indigenous community's regional and local office, the chieftain of the tribe, and the respondents, ensuring confidentiality in the collection and retrieval of data. The study revealed that respondents aged 60-69, males with no formal education, are unemployed and have no income source. They prefer traditional medicines due to their affordability, availability, and cultural practices but lack safe preparation, dosages, and contraindications of used medicines. Commercially prepared medications are acknowledged, but respondents are not fully aware of proper administration instructions and dosage labels. Recommendations include disseminating approved herbal medicines and ensuring proper preparation, indications, and contraindications.

Keywords: traditional medicine, commercially prepared medicine, indigenous community, elderly adult

Procedia PDF Downloads 45

Authors: K. W. Lee, C. M. Choi, H. C. Tsang, W. K. Fong, Y. K. Cheng, L. Y. Chan, C. K. Yuen, P. W. Lau, Y. L. To, K. C. Chow

Abstract:

QR (Quick Response) Code is a matrix barcode. It enables users to open websites, photos and other information with mobile devices by just snapping the code. In usual Long Term Oxygen Therapy arrangement, piles of LTOT related information like leaflets from different oxygen service providers are given to patients to choose an appropriate plan according to their needs. If these printed materials are transformed into electronic format (QR Code), it would be more environmentally-friendly. More importantly, electronic materials including LTOT equipment operation and dyspnoea relieving techniques also empower patients in long-term disease management. The objective to this study is to investigate the effect of QR code in patient education on new LTOT users. This study was carried out in medical wards of North District Hospital. Adult patients and relatives who followed commands, were able to use smartphones with internet services and required LTOT arrangement on hospital discharge were recruited. In LTOT arrangement, apart from the usual LTOT education booklets which included patients’ personal information (e.g. oxygen titration and six-minute walk test results etc.), extra leaflets consisted of 1. QR codes of LTOT plans from different oxygen service providers, 2. Education materials of dyspnoea management and 3. Instructions on LTOT equipment operation were given. Upon completion of LTOT arrangement, a questionnaire about the use of QR code on patient education was filled in by patients or relatives. A total of 10 new LTOT users were recruited from November 2017 to January 2018. Initially, 70% of them did not know anything about the QR code, but all of them understood its operation after a simple demonstration. 70% of them agreed that it was convenient to use (20% strongly agree, 40% agree, 10% somewhat agree). 80% of them agreed that QR code could facilitate the retrieval of more LTOT related information (10% strongly agree, 70% agree) while 90% agreed that we should continue delivering QR code leaflets to new LTOT users in the future (30% strongly agree, 40% agree, 20% somewhat agree). It is proven that QR code is a convenient and environmentally-friendly tool to deliver information. It is also relatively easy to be introduced to new users. It has received welcoming feedbacks from current users.

Keywords: long-term oxygen therapy, physiotherapy, patient education, QR code

Procedia PDF Downloads 124