Search results for: identify skills

Authors: Ntloyalefu Justinah, Fumane Khanare

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English learning has been found as one of the prevalent areas of difficulty for Deaf learners. However, studies conducted indicated that this challenge experienced by Deaf learners is an upsetting concern globally as is blamed and hampered by various reasons such as the way English is taught at schools, lack of teachers ' skills and knowledge, therefore, impact negatively on their academic performance. Despite any difficulty in English learning, this language is considered nowadays as the key tool to an educational and occupational career especially in Lesotho. This paper, therefore, intends to contribute to the existing literature by providing the views of Lesotho English teachers, which focuses on how effectively Universal design for learning can be implemented to enhance the academic performance of Deaf learners in context of the English language classroom. The purpose of this study sought to explore the use of universal design for learning (UDL) to support Deaf learners in Lesotho Secondary schools. The present study is informed by interpretative paradigm and situated within a qualitative research approach. Ten participating English teachers from two inclusive schools were purposefully selected and telephonically interviewed to generate data for this study. The data were thematically analysed. The findings indicated that even though UDL is identified as highly proficient and promotes flexibility in teaching methods teachers reflect limited knowledge of the UDL approach. The findings further showed that UDL ensures education for all learners, including marginalised groups, such as learners with disabilities through different teaching strategies. This means that the findings signify the effective use of UDL for the better performance of the English language by Deaf learners (DLs). This aligns with literature that shows mobilizing English teachers as assets help DLs to be engaged and have control in their communities by defining and solving problems using their resources and connections to other networks for asset and exchange. The study, therefore, concludes that teachers acknowledge that even though they assume to be knowledgeable about the definition of UDL, they have a limited practice of the approach, thus they need to be equipped with some techniques and skills to apply for supporting the performance of DLs by using UDL approach in their English teaching. The researchers recommend the awareness of UDL principles by the ministry of Education and Training and teachers training Universities, as well as teachers training colleges, for them to include it in their curricula so that teachers could be properly trained on how to apply it in their teaching effectively

Keywords: deaf learners, Lesotho, support learning, universal design for learning

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Lam Pham, Peter Hubber, Russell Tytler

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Students’ conceptual understandings of chemistry concepts/phenomena involve capability to coordinate across the three levels of Johnston’s triangle model. This triplet model is based on reasoning about chemical phenomena across macro, sub-micro and symbolic levels. In chemistry education, there is a need for further examining inquiry-based approaches that enhance students’ conceptual learning and problem solving skills. This research adopted a directed inquiry pedagogy based on students constructing and coordinating representations, to investigate senior school students’ capabilities to flexibly move across Johnston’ levels when learning dilution and molar concentration concepts. The participants comprise 50 grade 11 and 20 grade 10 students and 4 chemistry teachers who were selected from 4 secondary schools located in metropolitan Melbourne, Victoria. This research into classroom practices used ethnographic methodology, involved teachers working collaboratively with the research team to develop representational activities and lesson sequences in the instruction of a unit on solution chemistry. The representational activities included challenges (Representational Challenges-RCs) that used ‘representational tools’ to assist students to move across Johnson’s three levels for dilution phenomena. In this report, the ‘representational tool’ called ‘cross and portion’ model was developed and used in teaching and learning the molar concentration concept. Students’ conceptual understanding and problem solving skills when learning with this model are analysed through group case studies of year 10 and 11 chemistry students. In learning dilution concepts, students in both group case studies actively conducted a practical experiment, used their own language and visualisation skills to represent dilution phenomena at macroscopic level (RC1). At the sub-microscopic level, students generated and negotiated representations of the chemical interactions between solute and solvent underpinning the dilution process. At the symbolic level, students demonstrated their understandings about dilution concepts by drawing chemical structures and performing mathematical calculations. When learning molar concentration with a ‘cross and portion’ model (RC2), students coordinated across visual and symbolic representational forms and Johnson’s levels to construct representations. The analysis showed that in RC1, Year 10 students needed more ‘scaffolding’ in inducing to representations to explicit the form and function of sub-microscopic representations. In RC2, Year 11 students showed clarity in using visual representations (drawings) to link to mathematics to solve representational challenges about molar concentration. In contrast, year 10 students struggled to get match up the two systems, symbolic system of mole per litre (‘cross and portion’) and visual representation (drawing). These conceptual problems do not lie in the students’ mathematical calculation capability but rather in students’ capability to align visual representations with the symbolic mathematical formulations. This research also found that students in both group case studies were able to coordinate representations when probed about the use of ‘cross and portion’ model (in RC2) to demonstrate molar concentration of diluted solutions (in RC1). Students mostly succeeded in constructing ‘cross and portion’ models to represent the reduction of molar concentration of the concentration gradients. In conclusion, this research demonstrated how the strategic introduction and coordination of chemical representations across modes and across the macro, sub-micro and symbolic levels, supported student reasoning and problem solving in chemistry.

Keywords: cross and portion, dilution, Johnston's triangle, molar concentration, representations

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Authors: Sulemana Saibu, Moses Ikpeme

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Background: The severity of the COVID-19 pandemic, brought on by the SARS-CoV-2 coronavirus, has been unprecedented since the 1918 influenza pandemic. SARS-CoV-2 cases of CNS and peripheral nervous system disease, including neurodegenerative disorders and chronic immune-mediated diseases, may be anticipated based on knowledge of past coronaviruses, particularly those that caused the severe acute respiratory syndrome and Middle East respiratory syndrome outbreaks. Although respiratory symptoms are the most common clinical presentation, neurological symptoms are becoming increasingly recognized, raising concerns about their potential role in causing Parkinson's disease, Multiple sclerosis, and Narcolepsy. This systematic review aims to summarize the current evidence by exploring the association between COVID-19 infection and how it may overlap with etiological mechanisms resulting in Narcolepsy, Parkinson's disease, and Multiple sclerosis. Methods: A systematic search was conducted using electronic databases ((PubMed/MedLine, Embase, PsycINFO, ScieLO, Web of Science, ProQuest (Biotechnology, Virology, and AIDS), Scopus, and CINAHL)) to identify studies published between January 2020 and December 2022 that investigated the association between COVID-19 and Parkinson's disease, multiple sclerosis, and Narcolepsy. Per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review was performed and reported. Study quality was assessed using the Critical Appraisal Skills Programme Checklist and the Joanna Briggs Institute Critical appraisal tools. Results: A total of 21 studies out of 1025 met the inclusion criteria, including 8 studies reporting Parkinson's disease, 11 on multiple sclerosis, and 2 on Narcolepsy. In COVID-19 individuals compared to the general population, Narcolepsy, Parkinson's disease, and multiple sclerosis were shown to have a higher incidence. The findings imply that COVID-19 may worsen the signs or induce multiple sclerosis and Parkinson's disease and may raise the risk of developing Narcolepsy. Further research is required to confirm these connections because the available data is insufficient. Conclusion: According to the existing data, COVID-19 may raise the risk of Narcolepsy and have a causative relationship with Parkinson's disease, multiple sclerosis, and other diseases. More study is required to confirm these correlations and pinpoint probable mechanisms behind these interactions. Clinicians should be aware of how COVID-19 may affect various neurological illnesses and should treat patients who are affected accordingly.

Keywords: COVID-19, parkinson’s disease, multiple sclerosis, narcolepsy, neurological disorders, sars-cov-2, neurodegenerative disorders, chronic immune-mediated diseases

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Authors: Abdul Manan

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The necessity for efficient and cost-effective energy storage devices to intelligently store the inconsistent energy output from modern renewable energy sources is peaked today. The scientific community is struggling to identify the appropriate material system for energy storage applications. Countless contributions by researchers worldwide have now helped us identify the possible snags and limitations associated with each material/method. Energy storage has attracted great attention for its use in portable electronic devices military field. Different devices, such as dielectric capacitors, supercapacitors, and batteries, are used for energy storage. Of these, dielectric capacitors have high energy output, a long life cycle, fast charging and discharging capabilities, work at high temperatures, and excellent fatigue resistance. The energy storage characteristics have been studied to be highly affected by various factors, such as grain size, optimized compositions, grain orientation, energy band gap, processing techniques, defect engineering, core-shell formation, interface engineering, electronegativity difference, the addition of additives, density, secondary phases, the difference of Pmax-Pr, sample thickness, area of the electrode, testing frequency, and AC/DC conditions. The data regarding these parameters/factors are scattered in the literature, and the aim of this study is to gather the data into a single paper that will be beneficial for new researchers in the field of interest. Furthermore, control over and optimizing these parameters will lead to enhancing the energy storage properties.

Keywords: strategies, ceramics, energy storage, capacitors

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Authors: Pandurang Balwant, Ashutosh Mishra, Jyothi V., Abhay Soni, Padmakar C., Rafat Quamar, Ramesh J.

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The sea water intrusion in the coastal aquifers has become one of the major environmental concerns. Although, it is a natural phenomenon but, it can be induced with anthropogenic activities like excessive exploitation of groundwater, seacoast mining, etc. The geological and hydrogeological conditions including groundwater heads and groundwater pumping pattern in the coastal areas also influence the magnitude of seawater intrusion. However, this problem can be remediated by taking some preventive measures like rainwater harvesting and artificial recharge. The present study is an attempt to identify suitable sites for rainwater harvesting in salt intrusion affected area near coastal aquifer of Jafrabad town, Amreli district, Gujrat, India. The physico-chemical water quality results show that out of 25 groundwater samples collected from the study area most of samples were found to contain high concentration of Total Dissolved Solids (TDS) with major fractions of Na and Cl ions. The Cl/HCO3 ratio was also found greater than 1 which indicates the salt water contamination in the study area. The geophysical survey was conducted at nine sites within the study area to explore the extent of contamination of sea water. From the inverted resistivity sections, low resistivity zone (<3 Ohm m) associated with seawater contamination were demarcated in North block pit and south block pit of NCJW mines, Mitiyala village Lotpur and Lunsapur village at the depth of 33 m, 12 m, 40 m, 37 m, 24 m respectively. Geospatial techniques in combination of Analytical Hierarchy Process (AHP) considering hydrogeological factors, geographical features, drainage pattern, water quality and geophysical results for the study area were exploited to identify potential zones for the Rainwater Harvesting. Rainwater harvesting suitability model was developed in ArcGIS 10.1 software and Rainwater harvesting suitability map for the study area was generated. AHP in combination of the weighted overlay analysis is an appropriate method to identify rainwater harvesting potential zones. The suitability map can be further utilized as a guidance map for the development of rainwater harvesting infrastructures in the study area for either artificial groundwater recharge facilities or for direct use of harvested rainwater.

Keywords: analytical hierarchy process, groundwater quality, rainwater harvesting, seawater intrusion

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Authors: Esther Pearl Palmer

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Driven by the increased pressure on Higher Education Institutions (HEIs) to produce work-ready graduates for the modern world of work, this study reflects on triad teaching and learning practices to increase student engagement and employability. In the South African higher education context, the employability of graduates is imperative in strengthening the country’s economy and in increasing competitiveness. Within this context, the field of Human Resource Management (HRM) calls for innovative methods and approaches to teaching and learning and assessing the skills and competencies of graduates to render them employable. Digital competency in Human Resource Information Systems (HRIS) is an important component and prerequisite for employment in HRM. The purpose of this research is to reflect on the subject HRIS developed by lecturers at the Central University of Technology, Free State (CUT), with the intention to actively engage students in real-world learning activities and increase their employability. The Enrichment Triad Model (ETM) was used as theoretical framework to develop the subject as it supports a triad teaching and learning approach to education. It is, furthermore, an inter-structured model that supports collaboration between industry, academics and students. The study follows a mixed-method approach to reflect on the learning experiences of the industry, academics and students in the subject field over the past three years. This paper is a work in progress and seeks to broaden the scope of extant studies about student engagement in work-related learning to increase employability. Based on the ETM as theoretical framework and pedagogical practice, this paper proposes that following a triad teaching and learning approach will increase work-related skills of students. Findings from the study show that students, academics and industry alike regard educational opportunities that incorporate active learning experiences with the world of work enhances student engagement in learning and renders them more employable.

Keywords: digital competence, enriched triad model, human resource information systems, student engagement, triad pedagogy.

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Authors: Kari Bjorn

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Team learning has been studied and modeled as double loop model and its variations. Also, metacognition has been suggested as a concept to describe the nature of team learning to be more than a simple sum of individual learning of the team members. Team learning has a positive correlation with both individual motivation of its members, as well as the collective factors within the team. Team learning of previously very independent members of two teaching teams is analyzed. Applied Science Universities are training future professionals with ever more diversified and multidisciplinary skills. The size of the units of teaching and learning are increasingly larger for several reasons. First, multi-disciplinary skill development requires more active learning and richer learning environments and learning experiences. This occurs on students teams. Secondly, teaching of multidisciplinary skills requires a multidisciplinary and team-based teaching from the teachers as well. Team formation phases have been identifies and widely accepted. Team role stress has been analyzed in project teams. Projects typically have a well-defined goal and organization. This paper explores team stress of two teacher teams in a parallel running two course units in engineering education. The first is an Industrial Automation Technology and the second is Development of Medical Devices. The courses have a separate student group, and they are in different campuses. Both are run in parallel within 8 week time. Both of them are taught by a group of four teachers with several years of teaching experience, but individually. The team role stress scale items - the survey is done to both teaching groups at the beginning of the course and at the end of the course. The inventory of questions covers the factors of ambiguity, conflict, quantitative role overload and qualitative role overload. Some comparison to the study on project teams can be drawn. Team development stage of the two teaching groups is different. Relating the team role stress factors to the development stage of the group can reveal the potential of management actions to promote team building and to understand the maturity of functional and well-established teams. Mature teams indicate higher job satisfaction and deliver higher performance. Especially, teaching teams who deliver highly intangible results of learning outcome are sensitive to issues in the job satisfaction and team conflicts. Because team teaching is increasing, the paper provides a review of the relevant theories and initial comparative and longitudinal results of the team role stress factors applied to teaching teams.

Keywords: engineering education, stress, team role, team teaching

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Authors: Tanuj Joshi

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Smart transportation is fast emerging as a solution to modern cities’ approach mobility issues, delayed emergency response rate and high congestion on streets. Present day scenario with Google Maps, Waze, Yelp etc. demonstrates how information and communications technologies controls the intelligent transportation system. This intangible and invisible infrastructure is largely guided by the big data analytics. On the other side, the exponential increase in Indian urban population has intensified the demand for better services and infrastructure to satisfy the transportation needs of its citizens. No doubt, India’s huge internet usage is looked as an important resource to guide to achieve this. However, with a projected number of over 40 billion objects connected to the Internet by 2025, the need for systems to handle massive volume of data (big data) also arises. This research paper attempts to identify the ways of exploiting the big data variables which will aid commuters on Indian tracks. This study explores real life inputs by conducting survey and interviews to identify which gaps need to be targeted to better satisfy the customers. Several experts at Mumbai Metropolitan Region Development Authority (MMRDA), Mumbai Metro and Brihanmumbai Electric Supply and Transport (BEST) were interviewed regarding the Information Technology (IT) systems currently in use. The interviews give relevant insights and requirements into the workings of public transportation systems whereas the survey investigates the macro situation.

Keywords: smart transportation, mobility issue, Mumbai transportation, big data, data analysis

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

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Authors: Bruna Azzari Puga, Richard Roe, Andre Pagani de Souza

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abstract outlines a proposed study to examine how and to what extent interactive, experiential, learner centered methodology develops learning of basic civic and democratic competencies among young children. It stems from the Literacy and Law course taught at Georgetown University Law Center in Washington, DC, since 1998. Law students, trained in best literacy practices and legal cases affecting literacy development, read “law related” children’s books and engage in interactive and extension activities with emerging readers. The law students write a monthly journal describing their experiences and a final paper: a conventional paper or a children’s book illuminating some aspect of literacy and law. This proposal is based on the recent adaptation of Literacy and Law to Brazil at Mackenzie Presbyterian University in São Paulo in three forms: first, a course similar to the US model, often conducted jointly online with Brazilian and US law students; second, a similar course that combines readings of children’s literature with activity based learning, with law students from a satellite Mackenzie campus, for young children from a vulnerable community near the city; and third, a course taught by law students at the main Mackenzie campus for 4th grade students at the Mackenzie elementary school, that is wholly activity and discourse based. The workings and outcomes of these courses are well documented by photographs, reports, lesson plans, and law student journals. The authors, faculty who teach the above courses at Mackenzie and Georgetown, observe that literacy, broadly defined as cognitive and expressive development through reading and discourse-based activities, can be influential in developing democratic civic skills, identifiable by explicit civic competencies. For example, children experience justice in the classroom through cooperation, creativity, diversity, fairness, systemic thinking, and appreciation for rules and their purposes. Moreover, the learning of civic skills as well as the literacy skills is enhanced through interactive, learner centered practices in which the learners experience literacy and civic development. This study will develop rubrics for individual and classroom teaching and supervision by examining 1) the children’s books and students diaries of participating law students and 2) the collection of photos and videos of classroom activities, and 3) faculty and supervisor observations and reports. These rubrics, and the lesson plans and activities which are employed to advance the higher levels of performance outcomes, will be useful in training and supervision and in further replication and promotion of this form of teaching and learning. Examples of outcomes include helping, cooperating and participating; appreciation of viewpoint diversity; knowledge and utilization of democratic processes, including due process, advocacy, individual and shared decision making, consensus building, and voting; establishing and valuing appropriate rules and a reasoned approach to conflict resolution. In conclusion, further development and replication of the learner centered literacy and law practices outlined here can lead to improved qualities of democratic teaching and learning supporting mutual respect, positivity, deep learning, and the common good – foundation qualities of a sustainable world.

Keywords: democracy, law, learner-centered, literacy

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Authors: Juha Kettunen

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The purpose of this study is to develop a framework for the assessment of research and development projects. The assessment map is developed in this study based on the strategy map of the balanced scorecard approach. The assessment map is applied in a project that aims to reduce the inequality and risk of exclusion of young people from disadvantaged social groups. The assessment map denotes that not only funding but also necessary skills and qualifications should be carefully assessed in the implementation of the project plans so as to achieve the objectives of projects and the desired impact. The results of this study are useful for those who want to develop the implementation of the Erasmus+ Programme and the project teams of research and development projects.

Keywords: non-formal learning, youth work, social inclusion, innovation

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Authors: M. Rutkowski, J. Cwiklak, M. Grzegorzewski, M. Adamski

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All class A Airplanes have to be equipped with Mod. S transponder for ATC surveillance purposes. This technology was designed to provide a robust and dependable solution to localize, identify and exchange data with the airplane. The purpose of this paper is to analyze potential hazards that are a result of lack of any security or encryption on a design level. Secondary Surveillance Radars rely on an active response from an airplane. SSR radar installation is broadcasting a directional interrogation signal to the planes in range on 1030MHz frequency with DPSK modulation. If the interrogation is correctly received by the transponder located on the plane, a proper answer is sent on 1090MHz with PPM modulation containing plane’s SQUAWK, barometric altitude, GPS coordinates and 24bit unique address code. This technology does not use any kind of encryption. All of the specifications from the previous chapter can be found easily on the internet. Since there is no encryption or security measure to ensure the credibility of the sender and message, it is highly hazardous to use such technology to ensure the safety of the air traffic. The only thing that identifies the airplane is the 24-bit unique address. Most of the planes have been sniffed by aviation enthusiasts and cataloged in web databases. In the moment of writing this article, The PoFung Technologies has announced that they are planning to release all band SDR transceiver – this device would be more than enough to build your own Mod. S Transponder. With fake transponder, a potential terrorist can identify as a different airplane. By replacing the transponder in a poorly controlled airspace, hijackers can enter another airspace identifying themselves as another plane and land in the desired area.

Keywords: flight safety, hijack, mod S transponder, security analysis

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Authors: Humara Bano, Nyla Anjum

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Disability in any form has great impact not only for the person facing it but also for its family members too. This effect may be so severe that may lead to mal adjustment of any member of the family in society as well. This impact has also been multiplied due to negative attitudes of the society, unawareness about the needs of special needs and no legislation for the parents of children with special needs. As a result not only the separations among the parents have been reported but also the normal siblings in the home are also badly affected in their daily lives. The situation is more challenging when more than one child with disability is present in the family. The main objectives of this paper are to unfold the relationship of variety of disabilities (hearing, visual or physical impairment, mental retardation, speech impairment) in i) developing depression in home setting, ii) social exclusion, iii) anxiety and aggression and iv) development of insecure feelings among family members of the persons with disabilities, as well as, v) to identify coping strategies to manage the special needs by family members too. To reach on conclusion about fifty families (having any sort of disability in their homes) have been interviewed on basis of convenient sampling. Correlation, ANOVA and different analysis have been used to identify the relationship of disability in developing depression among family members in line of above mentioned problems. Results revealed that depression due to disability among families is a common phenomenon and adversely have affected their lives in daily routines as well as in following their life achievements. Coping with the situation and recommending various remedies by parents is the positive reflection of this study too that can help to families in managing their mental health.

Keywords: depression, anxiety and aggression, social exclusion, parents of children with special needs

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Yen Yen Tan, Lynn Lam, Cynthia Lam, Angela Koh, Edwin Seng

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Entrepreneurial education plays a crucial role in nurturing future innovators and change-makers. Over time, significant progress has been made in refining instructional approaches to develop the necessary skills among learners effectively. Two highly valuable frameworks, Kearney's "4 Principles of Entrepreneurial Pedagogy" and Bloom's "Three Domains of Learning," serve as guiding principles in entrepreneurial education. Kearney's principles align with experiential and student-centric learning, which are crucial for cultivating an entrepreneurial mindset. The potential synergies between these frameworks hold great promise for enhancing entrepreneurial acumen among students. However, despite this potential, their integration remains largely unexplored. This study aims to bridge this gap by building upon the Business Essentials through Action (BETA) module and investigating its contributions to nurturing the entrepreneurial mindset. This study employs a quasi-experimental mixed-methods approach, combining quantitative and qualitative elements to ensure comprehensive and insightful data. A cohort of 235 students participated, with 118 enrolled in the BETA module and 117 in a traditional curriculum. Their Personal Entrepreneurial Competencies (PECs) were assessed before admission (pre-Y1) and one year into the course (post-Y1) using a comprehensive 55-item PEC questionnaire, enabling measurement of critical traits such as opportunity-seeking, persistence, and risk-taking. Rigorous computations of individual entrepreneurial competencies and overall PEC scores were performed, including a correction factor to mitigate potential self-assessment bias. The orchestration of Kearney's principles and Bloom's domains within the BETA module necessitates a granular examination. Here, qualitative revelations surface, courtesy of structured interviews aligned with contemporary research methodologies. These interviews act as a portal, ushering us into the transformative journey undertaken by students. Meanwhile, the study pivots to explore the BETA module's influence on students' entrepreneurial competencies from the vantage point of faculty members. A symphony of insights emanates from intimate focus group discussions featuring six dedicated lecturers, who share their perceptions, experiences, and reflective narratives, illuminating the profound impact of pedagogical practices embedded within the BETA module. Preliminary findings from ongoing data analysis indicate promising results, showcasing a substantial improvement in entrepreneurial skills among students participating in the BETA module. This study promises not only to elevate students' entrepreneurial competencies but also to illuminate the broader canvas of applicability for Kearney's principles and Bloom's domains. The dynamic interplay of quantitative analyses, proffering precise competency metrics, and qualitative revelations, delving into the nuanced narratives of transformative journeys, engenders a holistic understanding of this educational endeavour. Through a rigorous quasi-experimental mixed-methods approach, this research aims to establish the BETA module's effectiveness in fostering entrepreneurial acumen among students at Singapore Polytechnic, thereby contributing valuable insights to the broader discourse on educational methodologies.

Keywords: entrepreneurial education, experiential learning, pedagogical frameworks, innovative competencies

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Authors: Asma Ammar, Nabiha Bouafia , Asma BenCheikh, Mohamed Mahjoub, Olfa Ezzi, Wadiaa Bannour, Radhia Helali, Mansour Njah

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Background: The objective of the present study was to identify factors associated with vaccination against Hepatitis B virus (HBV) among healthcare workers (HWs) in the University Hospital Center (UHC) Farhat Hached Sousse, Tunisia. Methods: We conducted a descriptive cross-sectional study all licensed physicians (n= 206) and a representative sample of paramedical staff (n= 372) exercising at UHC Hached Sousse (Tunisia) during two months (January and February 2014). Data were collected using a self-administered and pre-tested questionnaire, which composed by 21 questions. In order to determinate factors associated with vaccination against hepatitis B among HWs, this questionnaire was based on the Health Belief Model, one of the most classical behavior theories. Logistic regression with the stepwise method of Hosmer and Lemeshow was used to identify the determinants of the use of vaccination against HBV. Results: The response rates were 79.8%. Fifty two percent believe that HBV is frequent in our healthcare units and 60.6% consider it a severe infection. The prevalence of HWs vaccination was 39%, 95% CI [34.49%; 43.5%]. In multivariate analysis, determinants of the use of vaccination against HBV among HWs were young age (p=10-4), male gender (p = 0. 006), high or very high importance accorded to health (p = 0.035), perception membership in a risk group for HBV infection (p = 0.038) and very favorable or favorable opinion about vaccination against HVB (p=10-4). Conclusion: The results of our study should be considered in any strategy for preventing VHB infection in HWs. In the mean time, coverage with standard vaccines should be improved also by supplying complete information on the risks of VHB infection and on the safety and efficacy of vaccination.

Keywords: Hepatitis B virus, healthcare workers, prevalence, vaccination

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

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Authors: Ranis Cheng

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Corporate identity is an asset of a company that is unique, valuable and provides a source of competitive advantage. This research taking a holistic view to explore all dimensions of corporate identity and influence of each on customers’ shopping experience in the fast fashion retail sector in the U.K. Unfortunately these issues have not been explored sufficiently in the extant literature, especially in the area of the identity gap. To date, there is still a lack of empirical research on corporate identity, especially in the retail sector despite the importance of the concept to all organisations. Furthermore, although customer group is one of the essential audiences of organisations and the importance of customers in corporate identity management cannot be ignored, to date limited studies have been conducted in order to understand how customers interpret and perceive corporate identity (perceived identity). Therefore, this research investigates customers’ perceptions of corporate identity in the fast fashion retail sector. 1) To explore customers’ perceptions of fast fashion retailers’ corporate identities; 2) To uncover the important constructs of corporate identity which contribute to the U.K. fast fashion retail sector. 40 semi-structured interviews with the fast fashion consumers have been carried out to identify their perceptions of fast fashion retailers' corporate identities. Secondary research on retailers' websites and press releases have been evaluated to identify their desired corporate identities. The findings have revealed that there are significant gaps between how fast fashion retailers present their identities and how their consumers perceive them. This has posed customers' negative perceptions towards the retailers and their shopping experience as a whole. This study has studied how the corporate identity constructs could be applied in the fashion context and has helped retailers to shed lights on how to minimise the gap between desired and perceived identity.

Keywords: corporate identity, fast fashion, fashion retailing, identity gap

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Iman Jabbar

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Within the scope of professionalism and in order to compete with the modern world, teachers, are expected to develop their teaching skills and activities in addition to their professional knowledge. At the college level, the teacher should be able to face classroom challenges through his engagement with the learning situation to understand the students and their needs. In our field of TESOL, the role of the English teacher is no longer restricted to teaching English texts, but rather he should endeavor to enhance the students’ skills such as communication and critical analysis. Within the literature of professionalism, there are certain strategies and tools that an English teacher should adopt to develop his competence and performance. Reflective practice, which is an exploratory process, is one of these strategies. Another strategy contributing to classroom development is motivation. It is crucial in students’ learning as it affects the quality of learning English in the classroom in addition to determining success or failure as well as language achievement. This is a qualitative study grounded on interpretive perspectives of teachers and students regarding the process of professional development. This study aims at (a) understanding how teachers at the college level conceptualize reflective practice and motivation inside EFL classroom, and (b) exploring the methods and strategies that they implement to practice reflection and motivation. This study and is based on two questions: 1. How do EFL teachers perceive and view reflection and motivation in relation to their teaching and professional development? 2. How can reflective practice and motivation be developed into practical strategies and actions in EFL teachers’ professional context? The study is organized into two parts, theoretical and practical. The theoretical part reviews the literature on the concept of reflective practice and motivation in relation to professional development through providing certain definitions, theoretical models, and strategies. The practical part draws on the theoretical one, however; it is the core of the study since it deals with two issues. It involves the research design, methodology, and methods of data collection, sampling, and data analysis. It ends up with an overall discussion of findings and the researcher's reflections on the investigated topic. In terms of significance, the study is intended to contribute to the field of TESOL at the academic level through the selection of the topic and investigating it from theoretical and practical perspectives. Professional development is the path that leads to enhancing the quality of teaching English as a foreign or second language in a way that suits the modern trends of globalization and advanced technology.

Keywords: professional development, motivation, reflection, learning

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Authors: Jamal Gaber Abdalla

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In business promotion and advertising, language is used intentionally to create a powerful influence over people and their behavior. In commercial and marketing activities, the choice of language to convey specific messages with the intention of influencing people is pragmatically important. Design and visual content in promotional and advertising texts also have a great persuasive impact on consumers. It is the functional combination of design, language and visual content that helps people to identify a product or service and remember it. Translating promotional and advertising texts between structurally and culturally different languages, such as English and Arabic, usually involves pragmatic/functional shifts that decide the quality of translation. This study explores some of these shifts in translating promotional and advertising texts between English and Arabic and their implications for translation quality. The study is based on a contrastive analysis of data collected from real samples of English-Arabic translations of promotional and advertising texts. The samples cover different promotional and advertising text types and different business domains. The aim is to identify the most recurrent translation shifts and most used translation approaches/strategies that achieve quality in view of the functional nature of promotional and advertising texts and target language culture conventions. The study shows that linguistic shifts and visual shifts are recurrent in English-Arabic translations of promotional and advertising texts. The study also shows that the most commonly used translation approaches/strategies are functional translation, domestication, communicative translation.

Keywords: advertising, Arabic, English, functional translation, promotion

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Authors: Gabriel Michel

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The aim of our research is to find solutions for adapting university teaching to today's students and companies. To achieve this, we have tried to change the posture and behavior of those involved in the learning situation by promoting other skills. There is a gap between the expectations and functioning of students and university teaching. At the same time, the business world needs employees who are obviously competent and proficient in technology, but who are also imaginative, flexible, able to communicate, learn on their own and work in groups. These skills are rarely developed as a goal at university. The flipped classroom has been one solution. Thanks to digital tools such as Moodle, for example, but the model behind them is still centered on teachers and classic learning scenarios: it makes course materials available without really involving them and encouraging them to cooperate. It's against this backdrop that we've conducted action research to explore the possibility of changing the way we learn (rather than teach) by changing the posture of both the classic student and the teacher. We hypothesized that a tool we developed would encourage autonomy, the possibility of progressing at one's own pace, collaboration and learning using all available resources(other students, course materials, those on the web and the teacher/facilitator). Experimentation with this tool was carried out with around thirty German and French first-year students at the Université de Lorraine in Metz (France). The projected changesin the groups' learning situations were as follows: - use the flipped classroom approach but with a few traditional presentations by the teacher (materials having been put on a server) and lots of collective case solving, - engage students in their learning by inviting them to set themselves a primary objective from the outset, e.g. “Assimilating 90% of the course”, and secondary objectives (like a to-do list) such as “create a new case study for Tuesday”, - encourage students to take control of their learning (knowing at all times where they stand and how far they still have to go), - develop cooperation: the tool should encourage group work, the search for common solutions and the exchange of the best solutions with other groups. Those who have advanced much faster than the others, or who already have expertise in a subject, can become tutors for the others. A student can also present a case study he or she has developed, for example, or share materials found on the web or produced by the group, as well as evaluating the productions of others, - etc… A questionnaire and analysis of assessment results showed that the test group made considerable progress compared with a similar control group. These results confirmed our hypotheses. Obviously, this tool is only effective if the organization of teaching is adapted and if teachers are willing to change the way they work.

Keywords: pedagogy, cooperation, university, learning environment

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Authors: Raluca Popescu, Diana Costinel, Elisabeta-Irina Geana, Oana-Romina Botoran, Roxana-Elena Ionete, Yazan Falah Jadee 'Alabedallat, Mihai Botu

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Walnut production is high in Romania, different varieties being cultivated dependent on high yield, disease resistance or quality of produce. Walnuts have a highly nutritional composition, the kernels containing essential fatty acids, where the unsaturated fraction is higher than in other types of nuts, quinones, tannins, minerals. Walnut consumption can lower the cholesterol, improve the arterial function and reduce inflammation. The purpose of this study is to determine and compare the composition of walnuts of indigenous and international varieties all grown in Romania, in order to identify high-quality indigenous varieties. Oil has been extracted from the nuts of 34 varieties, the fatty acids composition and IV (iodine value) being afterwards measured by NMR. Furthermore, δ13C of the extracted oil had been measured by IRMS to find specific isotopic fingerprints that can be used in authenticating the varieties. Chemometrics had been applied to the data in order to identify similarities and differences between the varieties. The total saturated fatty acids content (SFA) varied between n.d. and 23% molar, oleic acid between 17 and 35%, linoleic acid between 38 and 59%, linolenic acid between 8 and 14%, corresponding to iodine values (IV - total amount of unsaturation) ranging from 100 to 135. The varieties separated in four groups according to the fatty acids composition, each group containing an international variety, making possible the classification of the indigenous ones. At both ends of the unsaturation spectrum, international varieties had been found.

Keywords: δ13C-IRMS, fatty acids composition, 1H-NMR, walnut varieties

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Pradeep Kumar Sahoo

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Facilitating writing skill among the young techies seems a bit challenging. Various factors may owe to this difficulty. Inappropriate syllabus, inadequate infrastructure, to some extent, untrained faculty members and above all the background of learners may be treated as the components that make the process challenging. In order to convert/create/prepare writing skill friendly, the focused items will have to be different from the classroom the present day traditional classroom situation. This paper focuses on the multiple contemporary strategies for approaching a wide range of typical problems that the writers face in a specific technical university of Odisha.

Keywords: background of learners, classroom friendly approach, inappropriate syllabus, traditional classroom situation

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Authors: S. Rostampour Yasouri, M. Ghane, M. Doudi

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Leptospirosis is one of the most significant infectious and zoonotic diseases along with global spreading. This disease is causative agent of economoic losses and human fatalities in various countries, including Northern provinces of Iran. The aim of this research is to identify and compare the rapid diagnostic techniques of pathogenic leptospiras, considering the multifacetedness of the disease from a clinical manifestation and premature death of patients. In the spring and summer of 2020-2022, 25 fecal samples were collected from suspected leptospirosis patients and 25 Fecal samples from mice residing in the rice fields and factories in Tonekabon city. Samples were prepared by centrifugation and passing through membrane filters. Culture technique was used in liquid and solid EMJH media during one month of incubation at 30°C. Then, the media were examined microscopically. DNA extraction was conducted by extraction Kit. Diagnosis of leptospiras was enforced by PCR and Real time PCR (SYBR Green) techniques using lipL32 specific primer. Out of the patients, 11 samples (44%) and 8 samples (32%) were determined to be pathogenic Leptospira by Real time PCR and PCR technique, respectively. Out of the mice, 9 Samples (36%) and 3 samples (12%) were determined to be pathogenic Leptospira by the mentioned techniques, respectively. Although the culture technique is considered to be the gold standard technique, but due to the slow growth of pathogenic Leptospira and lack of colony formation of some species, it is not a fast technique. Real time PCR allowed rapid diagnosis with much higher accuracy compared to PCR because PCR could not completely identify samples with lower microbial load.

Keywords: culture, pathogenic leptospiras, PCR, real time PCR

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Nassim Salmi

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This study aimed to identify the administrative, social, cultural, economic and psychological challenges facing the nursing s ector in the Tebessa Algeria. It also seeks to identify whether there are differences between the opinions of managers in public and private hospitals about these challenges. To achieve the objectives of the study, the descriptive analytical method was adopted. The study also used the questionnaire as a tool for collecting the necessary data and information, which was applied to a sample of directors of public and private hospitals in the Tebessa, which amounted to (114) individuals. The study reached a set of results, including: that there are no statistically significant differences between the opinions of managers in public and private hospitals about the administrative, social, cultural, economic and psychological challenges facing the nursing sector in the Tebessa . The results also showed agreement between the views of managers in private public hospitals that the most important administrative challenges are the lack of training programs that affect the efficiency and performance of nursing work, and that the most important social and cultural challenges are the hospital’s failure to provide suitable nurseries for Saudi female nurses, and that the most important economic challenges are the lack of Availability of medical equipment and devices, and the most important psychological challenge is the tense relationship between the administration and the hospital's nursing staff. The study recommended focusing on the importance of rehabilitation and training together, activating the role of training in the ministry and making it compulsory and a condition of renewal for practicing and continuing the nursing profession, and providing the social and economic needs of the nursing staff.

Keywords: postoperative care, gynecology, nursing documentation, database

Procedia PDF Downloads 88