Search results for: learning and teaching with technology
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14323

Search results for: learning and teaching with technology

6433 Supports for Student Learning Program: Exploring the Educational Terrain of Newcomer and Refugee Students in Canada

Authors: Edward Shizha, Edward Makwarimba

Abstract:

This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.

Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness

Procedia PDF Downloads 51
6432 Surgical Applied Anatomy: Alive and Kicking

Authors: Jake Hindmarch, Edward Farley, Norman Eizenberg, Mark Midwinter

Abstract:

There is a need to bring the anatomical knowledge of medical students up to the standards required by surgical specialties. Contention exists amongst anatomists, clinicians, and surgeons about the standard of anatomical knowledge medical students need. The aim of this study was to explore the standards which the Royal Australasian College of Surgeons are applying knowledge of anatomy. Furthermore, to align medical school teaching to what the surgical profession requires from graduates.: The 2018 volume of the ANZ Journal of Surgery was narrowed down to 254 articles by applying the search term “Anatomy”. The main topic was then extracted from each paper. The content of the paper was assessed for ‘novel description’ or ‘application’ of anatomical knowledge’ and classified accordingly. The majority of papers with an anatomical focus was from the general surgery specialty, which focused on surgical techniques, outcomes and management. Vascular surgery had the highest percentage of papers with a novel description and application of anatomy. Cardiothoracic and paediatric surgery had no papers with a novel description of anatomy. Finally, a novel application of anatomy was the main focus of each speciality. Firstly, a high proportion of novel applications and descriptions of anatomy are in general surgery. Secondly, vascular surgery had the largest proportion of novel application and description of anatomy, namely due to the rise of therapeutic imaging and endovascular techniques. Finally, all disciplines demonstrated a trend towards having a higher proportion of novel application of anatomical knowledge

Keywords: anatomical knowledge, anatomy, surgery, novel anatomy

Procedia PDF Downloads 106
6431 Plasma Chemical Gasification of Solid Fuel with Mineral Mass Processing

Authors: V. E. Messerle, O. A. Lavrichshev, A. B. Ustimenko

Abstract:

Currently and in the foreseeable future (up to 2100), the global economy is oriented to the use of organic fuel, mostly, solid fuels, the share of which constitutes 40% in the generation of electric power. Therefore, the development of technologies for their effective and environmentally friendly application represents a priority problem nowadays. This work presents the results of thermodynamic and experimental investigations of plasma technology for processing of low-grade coals. The use of this technology for producing target products (synthesis gas, hydrogen, technical carbon, and valuable components of mineral mass of coals) meets the modern environmental and economic requirements applied to basic industrial sectors. The plasma technology of coal processing for the production of synthesis gas from the coal organic mass (COM) and valuable components from coal mineral mass (CMM) is highly promising. Its essence is heating the coal dust by reducing electric arc plasma to the complete gasification temperature, when the COM converts into synthesis gas, free from particles of ash, nitrogen oxides and sulfur. At the same time, oxides of the CMM are reduced by the carbon residue, producing valuable components, such as technical silicon, ferrosilicon, aluminum and carbon silicon, as well as microelements of rare metals, such as uranium, molybdenum, vanadium, titanium. Thermodynamic analysis of the process was made using a versatile computation program TERRA. Calculations were carried out in the temperature range 300 - 4000 K and a pressure of 0.1 MPa. Bituminous coal with the ash content of 40% and the heating value 16,632 kJ/kg was taken for the investigation. The gaseous phase of coal processing products includes, basically, a synthesis gas with a concentration of up to 99 vol.% at 1500 K. CMM components completely converts from the condensed phase into the gaseous phase at a temperature above 2600 K. At temperatures above 3000 K, the gaseous phase includes, basically, Si, Al, Ca, Fe, Na, and compounds of SiO, SiH, AlH, and SiS. The latter compounds dissociate into relevant elements with increasing temperature. Complex coal conversion for the production of synthesis gas from COM and valuable components from CMM was investigated using a versatile experimental plant the main element of which was plug and flow plasma reactor. The material and thermal balances helped to find the integral indicators for the process. Plasma-steam gasification of the low-grade coal with CMM processing gave the synthesis gas yield 95.2%, the carbon gasification 92.3%, and coal desulfurization 95.2%. The reduced material of the CMM was found in the slag in the form of ferrosilicon as well as silicon and iron carbides. The maximum reduction of the CMM oxides was observed in the slag from the walls of the plasma reactor in the areas with maximum temperatures, reaching 47%. The thusly produced synthesis gas can be used for synthesis of methanol, or as a high-calorific reducing gas instead of blast-furnace coke as well as power gas for thermal power plants. Reduced material of CMM can be used in metallurgy.

Keywords: gasification, mineral mass, organic mass, plasma, processing, solid fuel, synthesis gas, valuable components

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6430 Aerial Photogrammetry-Based Techniques to Rebuild the 30-Years Landform Changes of a Landslide-Dominated Watershed in Taiwan

Authors: Yichin Chen

Abstract:

Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.

Keywords: aerial photogrammetry, landslide, landform change, Taiwan

Procedia PDF Downloads 145
6429 Information Technology Service Management System Measurement Using ISO20000-1 and ISO15504-8

Authors: Imam Asrowardi, Septafiansyah Dwi Putra, Eko Subyantoro

Abstract:

Process assessments can improve IT service management system (IT SMS) processes but the assessment method is not always transparent. This paper outlines a project to develop a solution- mediated process assessment tool to enable transparent and objective SMS process assessment. Using the international standards for SMS and process assessment, the tool is being developed following the International standard approach in collaboration and evaluate by expert judgment from committee members and ITSM practitioners.

Keywords: SMS, tools evaluation, ITIL, ISO service

Procedia PDF Downloads 464
6428 Paraplegic Dimensions of Asymmetric Warfare: A Strategic Analysis for Resilience Policy Plan

Authors: Sehrish Qayyum

Abstract:

In this age of constant technology, asymmetrical warfare could not be won. Attuned psychometric study confirms that screaming sometimes is more productive than active retaliation against strong adversaries. Asymmetric warfare is a game of nerves and thoughts with least vigorous participation for large anticipated losses. It creates the condition of paraplegia with partial but permanent immobility, which effects the core warfare operations, being screams rather than active retaliation. When one’s own power is doubted, it gives power to one’s own doubt to ruin all planning either done with superlative cost-benefit analysis. Strategically calculated estimation of asymmetric warfare since the early WWI to WWII, WWII-to Cold War, and then to the current era in three chronological periods exposits that courage makes nations win the battle of warriors to battle of comrades. Asymmetric warfare has been most difficult to fight and survive due to unexpectedness and being lethal despite preparations. Thoughts before action may be the best-assumed strategy to mix Regional Security Complex Theory and OODA loop to develop the Paraplegic Resilience Policy Plan (PRPP) to win asymmetric warfare. PRPP may serve to control and halt the ongoing wave of terrorism, guerilla warfare, and insurgencies, etc. PRPP, along with a strategic work plan, is based on psychometric analysis to deal with any possible war condition and tactic to save millions of innocent lives such that lost in Christchurch New Zealand in 2019, November 2015 Paris attacks, and Berlin market attacks in 2016, etc. Getting tangled into self-imposed epistemic dilemmas results in regret that becomes the only option of performance. It is a descriptive psychometric analysis of war conditions with generic application of probability tests to find the best possible options and conditions to develop PRPP for any adverse condition possible so far. Innovation in technology begets innovation in planning and action-plan to serve as a rheostat approach to deal with asymmetric warfare.

Keywords: asymmetric warfare, psychometric analysis, PRPP, security

Procedia PDF Downloads 123
6427 On ‘Freaks’ and the Feminine in Margaret Atwood’s ‘Lusus Naturae’

Authors: Shahd Alshammari

Abstract:

This paper considers one of Margaret Atwood’s short stories ‘Lusus Naturae'. Through a critical lens that makes use of Julia Kristeva’s work on Powers of Horror and abjection, this paper suggests that the monstrous girl is the disabled woman, the abject in society. The monster is used as a metaphor for the unknown, the misunderstood, and the ‘different’ woman. Culturally Relevant Teaching (CRT) is a pedagogy that calls for making course material accessible and relevant to students. Through the study of literary texts, we are able to help create agency inside and outside the classroom. Stories are a necessary part of establishing connections across borders and boundaries. Stories are meant to raise awareness both inside and outside the classroom. The discussion is equally important, and the text is meant to facilitate relevant questions that the students need to consider when it comes to identity. Questions to consider are: what does it mean to be a ‘girl’ today, and what implications and consequences are at hand when you fail to perform this gendered identity? Gender is sometimes a fatal bond in the Middle East, and even more so, is the disability. In the case of our unnamed protagonist, she undergoes a process of un-becoming, a non-linear process of growing up. In a sense, it is a counter-Bildungsroman. The reading of this text emphasizes that a non-linear narrative is sometimes necessary for the female protagonist’s self-awareness and development. Discussion in class facilitates this sense of agency and questioning of gender and disability.

Keywords: disability, gender, literature, pedagogy

Procedia PDF Downloads 643
6426 Financial Inclusion as Twig of Internally Generated Revenue From Entrepreneurial Venture: A University Funding Alternate

Authors: Anifowose Oluwafemi Dele, Ngah Rohana, Hasni Abdulahi

Abstract:

The economic crisis, which resulted in university funding cuts with an astronomically devastating impact on teaching and research around the world. Sequel to this, Nigerian universities are in disarray due to insufficient government funding and are under pressure to discover new financial streams of Internally Generated Revenue (IGR) to disentangle finance-related teething problems and most tangible means of outsourcing finance inclusively for the creation of more entrepreneurial ventures through the possibilities of prudent IGR management. To the best of our knowledge, one way to address this still-unknown or underappreciated cog is through the strategic use of IGR and the outsourcing of financing for the launch of entrepreneurial ventures. As a result, it is critical to investigate and evaluate financial inclusion through prudently managed IGR to achieve greater financial inclusion for more long-term entrepreneurial ventures. Justifying the need to look inward and devise mechanisms for strong instruments internal fund raising and managing cash inflows to benefit university entrepreneurial ventures to increase the University's IGR for the benefit of the university and its stakeholders. The paper concludes that University Managers must fully accept the use of genuine means of boosting IGR through financial inclusion of in-house funds to aggressively established IGR boosting and the creation of entrepreneurial ventures that could serve as an alternative to inadequate government funding.

Keywords: government funding, university managers, financial inclusion, entrepreneurial venture

Procedia PDF Downloads 65
6425 Application of Vector Representation for Revealing the Richness of Meaning of Facial Expressions

Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

Abstract:

Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

Procedia PDF Downloads 170
6424 Social Enterprise Concept in Sustaining Agro-Industry Development in Indonesia: Case Study of Yourgood Social Business

Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

Abstract:

Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: agro-industry, small medium enterprises, empowerment, design thinking, AHP, business model canvas, social business

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6423 Design and Implementation of A 10-bit SAR ADC with A Programmable Reference

Authors: Hasmayadi Abdul Majid, Yuzman Yusoff, Noor Shelida Salleh

Abstract:

This paper presents the development of a single-ended 38.5 kS/s 10-bit programmable reference SAR ADC which is realized in MIMOS’s 0.35 µm CMOS process. The design uses a resistive DAC, a dynamic comparator with pre-amplifier and a SAR digital logic to create 10 effective bits ADC. A programmable reference circuitry allows the ADC to operate with different input range from 0.6 V to 2.1 V. A single ended 38.5 kS/s 10-bit programmable reference SAR ADC was proposed and implemented in a 0.35 µm CMOS technology and consumed less than 7.5 mW power with a 3 V supply.

Keywords: successive approximation register analog-to-digital converter, SAR ADC, resistive DAC, programmable reference

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6422 Systematic Review of Current Best Practice in the Diagnosis and Treatment of Obsessive Compulsive Disorder

Authors: Zahra R. Almansoor

Abstract:

Background: Selective serotonin reuptake inhibitors (SSRI’s) and cognitive behavioural therapy (CBT) are the main treatment methods used for patients with obsessive compulsive disorder (OCD) under the National Institute of Health and Care Excellence (NICE) guidelines. Yet many patients are left with residual symptoms or remit, so several other therapeutic approaches have been explored. Objective: The objective was to systematically review the available literature regarding the treatment efficacy of current and potential approaches and diagnostic strategies. Method: First, studies were examined concerning diagnosis, prognosis, and influencing factors. Then, one reviewer conducted a systematic search of six databases using stringent search terms. Results of studies exploring the efficacy of treatment interventions were analysed and compared separately for adults and children. This review was limited to randomised controlled trials (RCT’s) conducted from 2016 onwards, and an improved Y-BOCS (Yale- Brown obsessive compulsive scale) score was the primary outcome measure. Results: Technology-based interventions including internet-based cognitive behavioural therapy (iCBT) were deemed as potentially effective. Discrepancy remains about the benefits of SSRI use past one year, but potential medication adjuncts include amantadine. Treatments such as association splitting and family and mindfulness strategies also have future potential. Conclusion: A range of potential therapies exist, either as treatment adjuncts to current interventions or as sole therapies. To further improve efficacy, it may be necessary to remodel the current NICE stepped-care model, especially regarding the potential use of lower intensity, cheaper treatments, including iCBT. Although many interventions show promise, further research is warranted to confirm this.

Keywords: family and group treatment, mindfulness strategies, novel treatment approaches, standard treatment, technology-based interventions

Procedia PDF Downloads 108
6421 HTML5 Online Learning Application with Offline Web, Location Based, Animated Web, Multithread, and Real-Time Features

Authors: Sheetal R. Jadhwani, Daisy Sang, Chang-Shyh Peng

Abstract:

Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.

Keywords: HTML5, web worker, canvas, web socket

Procedia PDF Downloads 287
6420 Review of Vehicle to Grid Applications in Recent Years

Authors: Afsane Amiri

Abstract:

Electric Vehicle (EV) technology is expected to take a major share in the light-vehicle market in the coming decades. Charging of EVs will put an extra burden on the distribution grid and in some cases adjustments will need to be made. In this paper a review of different plug-in and vehicle to grid (V2G) capable vehicles are given along with their power electronics topologies. The economic implication of charging the vehicle or sending power back to the utility is described in brief.

Keywords: energy storage system, battery unit, cost, optimal sizing, plug-in electric vehicles (PEVs), smart grid

Procedia PDF Downloads 587
6419 The Development of Open Access in Latin America and Caribbean: Mapping National and International Policies and Scientific Publications of the Region

Authors: Simone Belli, Sergio Minniti, Valeria Santoro

Abstract:

ICTs and technology transfer can benefit and move a country forward in economic and social development. However, ICT and access to the Internet have been inequitably distributed in most developing countries. In terms of science production and dissemination, this divide articulates itself also through the inequitable distribution of access to scientific knowledge and networks, which results in the exclusion of developing countries from the center of science. Developing countries are on the fringe of Science and Technology (S&T) production due not only to low investment in research but also to the difficulties to access international scholarly literature. In this respect, Open access (OA) initiatives and knowledge infrastructure represent key elements for both producing significant changes in scholarly communication and reducing the problems of developing countries. The spreading of the OA movement in the region, exemplified by the growth of regional and national initiatives, such as the creation of OA institutional repositories (e.g. SciELO and Redalyc) and the establishing of supportive governmental policies, provides evidence of the significant role that OA is playing in reducing the scientific gap between Latin American countries and improving their participation in the so-called ‘global knowledge commons’. In this paper, we map OA publications in Latin America and observe how Latin American countries are moving forward and becoming a leading force in widening access to knowledge. Our analysis, developed as part of the H2020 EULAC Focus research project, is based on mixed methods and consists mainly of a bibliometric analysis of OA publications indexed in the most important scientific databases (Web of Science and Scopus) and OA regional repositories, as well as the qualitative analysis of documents related to the main OA initiatives in Latin America. Through our analysis, we aim at reflecting critically on what policies, international standards, and best practices might be adapted to incorporate OA worldwide and improve the infrastructure of the global knowledge commons.

Keywords: open access, LAC countries, scientific publications, bibliometric analysis

Procedia PDF Downloads 196
6418 Design and Implementation of Remote Control Application for Elderly People Who Live Alone

Authors: Cristina Nieves Perdomo Delgado

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The study consists of the design and use of an application for cell phones called “Me Cuido” that consists of remote control of elderly people who live alone with their families. The objective of the study is to analyze the usability of the application by 40-year-olds using the Questionnaire for User Interaction Satisfaction (QUIS) method. The results highlight that the application has a design adapted to the elderly and that it is easy to use and understand.

Keywords: design, assistive technology, elderly people, independence

Procedia PDF Downloads 233
6417 Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

Procedia PDF Downloads 207
6416 Low-Power Digital Filters Design Using a Bypassing Technique

Authors: Thiago Brito Bezerra

Abstract:

This paper presents a novel approach to reduce power consumption of digital filters based on dynamic bypassing of partial products in their multipliers. The bypassing elements incorporated into the multiplier hardware eliminate redundant signal transitions, which appear within the carry-save adders when the partial product is zero. This technique reduces the power consumption by around 20%. The circuit implementation was made using the AMS 0.18 um technology. The bypassing technique applied to the circuits is outlined.

Keywords: digital filter, low-power, bypassing technique, low-pass filter

Procedia PDF Downloads 365
6415 Integrating a Six Thinking Hats Approach Into the Prewriting Stage of Argumentative Writing In English as a Foreign Language: A Chinese Case Study of Generating Ideas in Action

Authors: Mei Lin, Chang Liu

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Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.

Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education

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6414 Proposed Anticipating Learning Classifier System for Cloud Intrusion Detection (ALCS-CID)

Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

Procedia PDF Downloads 460
6413 Corporate Social Responsibility in Indian Apparel Industry

Authors: Archana Gandhi

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Indian apparel manufacturers see several benefits of Corporate Social Responsibility (CSR). At the same time, they clearly face steep challenges in its implementation. From the perspective of the participants, the challenges tend to outweigh the benefits. The short-term expenses, misperceptions about the financial benefits of CSR and the additional burden of implementing CSR-related policies and activities tend to overshadow perceptions of the long-term benefits. CSR activities currently seen in the Indian apparel industry are primarily people focused, society-focused or environment-focused. However, most CSR activities focus on employee welfare, including teaching employees about health and safety awareness, creating opportunities for community building, and providing general education to employees. Employee retention is very high in socially responsible Indian firms as compared to non-CSR firms, largely because CSR plays a crucial role in overall employee satisfaction, which translates to worker loyalty and low turnover. Employee retention and commitment are not the​ only potential benefits of CSR in the Indian apparel industry. CSR can also enhance a company’s image. Although it is a long-term benefit, being socially responsible can build a company’s social reputation and help it to gain others’ trust. Buyers do not hesitate to do business with these companies, since it is difficult to find socially responsible firms in India.

Keywords: corporate social responsibility, apparel industry, workers, improve work life

Procedia PDF Downloads 350
6412 Data Disorders in Healthcare Organizations: Symptoms, Diagnoses, and Treatments

Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

Procedia PDF Downloads 420
6411 People Management, Knowledge Sharing and Intermediary Variables

Authors: Nizar Mansour, Chiha Gaha, Emna Gara

Abstract:

The present research investigates the relationship among HRM practices, knowledge sharing behavior and a certain number of intermediary variables in the context of Tunisian knowledge-intensive firms. Results suggest that five HR practices influence either directly or indirectly the knowledge sharing behavior through enhancing the value of human capital and fostering a learning-oriented organizational climate. Results have strong theoretical implications for both the fields of knowledge management and strategic human resource management. Managerial implications are also derived.

Keywords: human capital, knowledge intensive firms, knowledge sharing, organizational climate, Tunisia

Procedia PDF Downloads 321
6410 Nuclear Energy: The Reorientations of the French Public Perception

Authors: Aurélia Jandot

Abstract:

With the oil and economic crises which began in the 1970’s, it has progressively appeared necessary to convince the French “general public“ that a use of new energy sources was essential. In this field, nuclear energy represented the future and concentrated lots of hopes. However, the discourse about nuclear energy has progressively seen negative arguments growing in the French media. The gradual changes in the perception of nuclear energy will be studied here through the arguments given in the main French weekly newsmagazines, which had a great impact on the readers, thus on the “general public“, from the 1970’s to the end of the 1980’s. Indeed, to understand better these changes will be taken into account the major international events, the reorientations of the French domestic policy, and the evolutions of the nuclear technology. As this represents a considerable amount of copies and thus of information, will be selected here the main articles which emphasize the “mental images“ aiming to direct the thought of the readers, and which have led the public awareness and acceptance to evolve. From the 1970’s to the end of the 1980’s, two dichotomous trends are in confrontation : one is promoting the perception of the nuclear energy, the other is discrediting it. Moreover, these two trends are organized in two axes. The first axis is about the engineerings evolutions, such as the main French media represent them, with its approximations, its exaggerations, its fictions sometimes. Is added the will to make accessible to the “general public“ some concepts which are quite difficult to understand for the largest number. The second axis rests on the way the major accidents of the period are approached, including those of Three Mile Island and Chernobyl. Thanks to these accidents and because of the international relations evolutions, the ecologist movements and their impacts have progressively grown, with evident consequences on the public perception of nuclear energy and on the way the successive governments can implement new power plants in France. Then, in both cases, over the period considered, the language has changed, as the perceptible objectives of the communication, allowing to discern the deepest intentions of the newsmagazines editing. This is all these changes that will be emphasized, over a period where the nuclear energy technology, to there a field for specialists, bearing mystery and secret, has become a social issue seemingly open to all.

Keywords: social issues, public acceptance, mediatization, discourse changes

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6409 High Resolution Satellite Imagery and Lidar Data for Object-Based Tree Species Classification in Quebec, Canada

Authors: Bilel Chalghaf, Mathieu Varin

Abstract:

Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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6408 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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6407 Global Solar Irradiance: Data Imputation to Analyze Complementarity Studies of Energy in Colombia

Authors: Jeisson A. Estrella, Laura C. Herrera, Cristian A. Arenas

Abstract:

The Colombian electricity sector has been transforming through the insertion of new energy sources to generate electricity, one of them being solar energy, which is being promoted by companies interested in photovoltaic technology. The study of this technology is important for electricity generation in general and for the planning of the sector from the perspective of energy complementarity. Precisely in this last approach is where the project is located; we are interested in answering the concerns about the reliability of the electrical system when climatic phenomena such as El Niño occur or in defining whether it is viable to replace or expand thermoelectric plants. Reliability of the electrical system when climatic phenomena such as El Niño occur, or to define whether it is viable to replace or expand thermoelectric plants with renewable electricity generation systems. In this regard, some difficulties related to the basic information on renewable energy sources from measured data must first be solved, as these come from automatic weather stations. Basic information on renewable energy sources from measured data, since these come from automatic weather stations administered by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) and, in the range of study (2005-2019), have significant amounts of missing data. For this reason, the overall objective of the project is to complete the global solar irradiance datasets to obtain time series to develop energy complementarity analyses in a subsequent project. Global solar irradiance data sets to obtain time series that will allow the elaboration of energy complementarity analyses in the following project. The filling of the databases will be done through numerical and statistical methods, which are basic techniques for undergraduate students in technical areas who are starting out as researchers technical areas who are starting out as researchers.

Keywords: time series, global solar irradiance, imputed data, energy complementarity

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6406 Makhraj Recognition Using Convolutional Neural Network

Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

Abstract:

This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

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6405 Decoding Socio-Cultural Trends in Indian Urban Youth Using Ogilvy 3E Model

Authors: Falguni Vasavada, Pradyumna Malladi

Abstract:

The research focuses on studying the ecosystem of the youth using Ogilvy's 3E model, Ethnography and Thematic Analysis. It has been found that urban Indian youth today is an honest generation, hungry for success, living life by the moment, fiercely independent, are open about sex, sexuality and embrace individual differences. Technology and social media dominate their life. However, they are also phobic about commitments, often drifting along life and engage in unsubstantiated brave-talk.

Keywords: ethnography, youth, culture, track, buyer behavior

Procedia PDF Downloads 347
6404 Wet Processing of Algae for Protein and Carbohydrate Recovery as Co-Product of Algal Oil

Authors: Sahil Kumar, Rajaram Ghadge, Ramesh Bhujade

Abstract:

Historically, lipid extraction from dried algal biomass remained a focus area of the algal research. It has been realized over the past few years that the lipid-centric approach and conversion technologies that require dry algal biomass have several challenges. Algal culture in cultivation systems contains more than 99% water, with algal concentrations of just a few hundred milligrams per liter ( < 0.05 wt%), which makes harvesting and drying energy intensive. Drying the algal biomass followed by extraction also entails the loss of water and nutrients. In view of these challenges, focus has shifted toward developing processes that will enable oil production from wet algal biomass without drying. Hydrothermal liquefaction (HTL), an emerging technology, is a thermo-chemical conversion process that converts wet biomass to oil and gas using water as a solvent at high temperature and high pressure. HTL processes wet algal slurry containing more than 80% water and significantly reduces the adverse cost impact owing to drying the algal biomass. HTL, being inherently feedstock agnostic, i.e., can convert carbohydrates and proteins also to fuels and recovers water and nutrients. It is most effective with low-lipid (10--30%) algal biomass, and bio-crude yield is two to four times higher than the lipid content in the feedstock. In the early 2010s, research remained focused on increasing the oil yield by optimizing the process conditions of HTL. However, various techno-economic studies showed that simply converting algal biomass to only oil does not make economic sense, particularly in view of low crude oil prices. Making the best use of every component of algae is a key for economic viability of algal to oil process. On investigation of HTL reactions at the molecular level, it has been observed that sequential HTL has the potential to recover value-added products along with biocrude and improve the overall economics of the process. This potential of sequential HTL makes it a most promising technology for converting wet waste to wealth. In this presentation, we will share our experience on the techno-economic and engineering aspects of sequential HTL for conversion of algal biomass to algal bio-oil and co-products.

Keywords: algae, biomass, lipid, protein

Procedia PDF Downloads 201