Search results for: evolved search queries

Authors: Muhammedamin Hussen Saad, Geoffrey Haagler, Onno Omta, Gerben Van Der Velde

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Unfolding chaos and persistent disruptions pose threats to companies’ performance especially in vulnerable settings of SME’s particularly in developing countries. Attention for resilience research in the academic world has increased considerably during the last decade looking at the number of papers published. As we are interested in adding to the understanding of the foundation and development of the concept of resilience, we focus especially on structuring the literature of business resilience in those vulnerable settings. A well-structured systematic search & review procedure was deployed. First, we defined key search terms and applied these to multiple databases (Scopus, Web of Science, Google Scholar, Emerald, and Science Direct). To make our literature search more encompassing, we augmented with co-citation, reference checking including hand searching techniques. The paper offers (1) an overview of SMEs resilience literature from 2000 up to March 2017 comprising 88 articles, and (2) special attention, within that overview, to developing countries. This review concludes that resilience literature is very much diverse in definitions and its measurements, and is inconclusive about its influencing factors. Furthermore, resilience literature is based predominantly on research in the developed world. On the bases of how the concept resilience emerges from the literature we describe distinct features of resilience, give options to extend the theoretical bases of research into resilience and describe concrete ideas for further research.

Keywords: business resilience, systematic review, SMEs, developing countries

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Diego Alejandro Espíndola-Fernández, Ana María Posada-Cano, Dagnóvar Aristizábal-Ocampo, Jaime Alberto Gallo-Villegas

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Background: With the increase in life expectancy, aging has been subject of frequent research, and therefore multiple strategies have been proposed to quantify the advance of the years based on the known physiology of human senescence. For several decades, attempts have been made to characterize these changes through the concept of biological age, which aims to integrate, in a measure of time, structural or functional variation through biomarkers in comparison with simple chronological age. The objective of this scoping review is to deepen the updated concept of measuring biological age composed of biomarkers in the general population and to summarize recent evidence to identify gaps and priorities for future research. Methods: A scoping review was conducted according to the five-phase methodology developed by Arksey and O'Malley through a search of five bibliographic databases to February 2021. Original articles were included with no time or language limit that described the biological age composed of at least two biomarkers in those over 18 years of age. Results: 674 articles were identified, of which 105 were evaluated for eligibility and 65 were included with information on the measurement of biological age composed of biomarkers. Articles from 1974 of 15 nationalities were found, most observational studies, in which clinical or paraclinical biomarkers were used, and 11 different methods described for the calculation of the composite biological age were informed. The outcomes reported were the relationship with the same measured biomarkers, specified risk factors, comorbidities, physical or cognitive functionality, and mortality. Conclusions: The concept of biological age composed of biomarkers has evolved since the 1970s and multiple methods of its quantification have been described through the combination of different clinical and paraclinical variables from observational studies. Future research should consider the population characteristics, and the choice of biomarkers against the proposed outcomes to improve the understanding of aging variables to direct effective strategies for a proper approach.

Keywords: biological age, biological aging, aging, senescence, biomarker

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Authors: Nasa'i Muhammad Gwadabe

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This study seeks to find the extent to which the old Islamophobic prejudice was tilted towards a more negative direction in the United States following the 9/11 terrorist attacks. It is hypothesized that, the 9/11 attacks in the United States reshaped the old Islamophobic prejudice through the reinforcement of a strong social identity construction of Muslims as “out-group”. The “social identity” and “discourse representation” theories are used as framework for analysis. To test the hypothesis, two categories were created: the prejudice (out-group) and the tolerance (in-group) categories. The Prejudice (out-group) against Muslims category was coded to include six attributes: (Terrorist, Threat, Women's Rights violation, Undemocratic, Backward and Intolerant); while the tolerance (In-group) for Muslims category was also coded to include six attributes: (Peaceful, civilized, educated, partners trustworthy and honest). Data are generated from the archives of three American newspapers: The Los Angeles Times, New York Times and USA Today using specific search terms and specific date range; from 9/11/1996 to 9/11/2006, that is five years before and five years after the 9/11. An aggregate of 20595 articles were generated from the search of the three newspapers throughout the search periods. Conclusively, for both pre and post 9/11 periods, the articles generated under the category of prejudice (out-group) against Muslims revealed a higher frequency, against that of tolerance (in-group) for them, which is lesser. Finally, The comparison between the pre and post 9/11 periods showed that, the increased Prejudice (out-group) against Muslims was most influenced through libeling them as terrorist, which signaled a skyrocketed increase from pre to post 9/11.

Keywords: in-group, Islam, Islamophobia, Muslims, out-group, prejudice, terrorism, the 9/11 and tolerance

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Sandisiwe Mangali, Graeme Bradley

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Genome is complete set of the organism's hereditary information encoded as either deoxyribonucleic acid or ribonucleic acid in most viruses. The three different types of genomes are nuclear, mitochondrial and the plastid genome and their sequences which are uncovered by genome sequencing are known as an archive for all genetic information and enable researchers to understand the composition of a genome, regulation of gene expression and also provide information on how the whole genome works. These sequences enable researchers to explore the population structure, genetic variations, and recent demographic events in threatened species. Particularly, genome sequencing refers to a process of figuring out the exact arrangement of the basic nucleotide bases of a genome and the process through which all the afore-mentioned genomes are sequenced is referred to as whole or complete genome sequencing. Gelidium pristoides is South African endemic Rhodophyta species which has been harvested in the Eastern Cape since the 1950s for its high economic value which is one motivation for its sequencing. Its endemism further motivates its sequencing for conservation biology as endemic species are more vulnerable to anthropogenic activities endangering a species. As sequencing, mapping and annotating the Gelidium pristoides genome is the aim of this study. To accomplish this aim, the genomic DNA was extracted and quantified using the Nucleospin Plank Kit, Qubit 2.0 and Nanodrop. Thereafter, the Ion Plus Fragment Library was used for preparation of a 600bp library which was then sequenced through the Ion S5 sequencing platform for two runs. The produced reads were then quality-controlled and assembled through the SPAdes assembler with default parameters and the genome assembly was quality assessed through the QUAST software. From this assembly, the plastid and the mitochondrial genomes were then sampled out using Gelidiales organellar genomes as search queries and ordered according to them using the Geneious software. The Qubit and the Nanodrop instruments revealed an A260/A280 and A230/A260 values of 1.81 and 1.52 respectively. A total of 30792074 reads were obtained and produced a total of 94140 contigs with resulted into a sequence length of 217.06 Mbp with N50 value of 3072 bp and GC content of 41.72%. A total length of 179281bp and 25734 bp was obtained for plastid and mitochondrial respectively. Genomic data allows a clear understanding of the genomic constituent of an organism and is valuable as foundation information for studies of individual genes and resolving the evolutionary relationships between organisms including Rhodophytes and other seaweeds.

Keywords: Gelidium pristoides, genome, genome sequencing and assembly, Ion S5 sequencing platform

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Mohamed Karodia

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Accountancy as a subject is one of the sciences that for many years has been perceived as a difficult subject to study and teach. Yet, it continuously attracts scholars graduating from school and entering Higher Education Institutions as a subject of choice and career. The teaching and learning of this subject have not been easy and has evolved and progressed over the past few decades however students still find it difficult to study and this has resulted in poor student achievement. In search of solutions, this study has considered the effect and efficacy that study skills have on the performance of Accountancy students and in particular students studying Second Year Diploma in Accountancy at the University of Johannesburg. These students appear to have a lack of appropriate study skills and as a result of these impacts on their performance in the courses, they are studying. This study also focuses on strategies to enhance Second Year Diploma Accountancy students’ academic performance. A literature review was conducted to investigate what scholarly literature suggests about study skills, in general, and in particular for Accountancy to be successful. In order to determine what study skills Second Year Accountancy students are applying when they learn and why they are failing the Accountancy examinations and formal class tests, the study adopted the quantitative research method. A questionnaire addressing various aspects of study skills, studying accountancy and studying, in general, was provided to 800 students studying Second Year Diploma in Accountancy at the University of Johannesburg’s Soweto Campus. The quantitative data collected were analyzed using descriptive statistics in the form of proportions, frequencies, means, and standard deviations, t-tests to compare differences between two groups as well as correlations between variables. Based on the findings of this study, it is recommended that students are provided with courses in time management, procrastination, reading, note taking and writing, test preparation techniques as well as study attitude. Lecturers spend more time teaching students how to study in general as well as accountancy specifically preferably at the first-year level before proceeding to the second year. It is also recommended that the University implements a study skills course to assist the students with studying.

Keywords: accountancy, skills, strategies, study

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Mahdi Taheri Asl

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Using a variety of strategies to read text plays an important role to make students strategic independent, strategic, and metacognitive readers. Given the importance of comprehension instruction (CI), it is essential to support the fostering comprehension skills at elementary age students, particularly those who struggle with or dislike reading. One of the main components of CI is activating metacognitive skills, which double function of elementary students. Thus, it’s important to evaluate the implemented comprehension interventions to inform reading specialist and teachers. There has been limited review research in the area of CI, so the conduction review research is required. The purpose of this review is to examine the effectiveness of metacognitive reading strategies in a regular classroom environment with elementary aged students. We develop five inclusion criteria to identify researches relevant to our research. First, the article had to be published in a peer-reviewed journal from 2000 to 2023. second, the study had to include participants in elementary school it could include of special education students. Third, the intervention needed to be involved with metacognitive strategies. Fourth, the articles had to use experimental or quasi experimental design. The last one needed to include measurement of reading performance in pre and post intervention. We used computer data-based site like Eric, PsychoINFO, and google scholar to search for articles that met these criteria. we used the following search terms: comprehension instruction, meta cognitive strategies, and elementary school. The next step was to do an ancestral search that get in reviewing the relevant studies cited in the articles that were found in the database search. We identified 30studies in the initial searches. After coding agreement, we synthesized 13 with respect to the participant, setting, research design, dependent variables, measures, the intervention used by instructors, and general outcomes. The finding show metacognitive strategies were effective to empower student’s comprehension skills. It also showed that linguistic instruction will be effective if got mixed with metacognitive strategies. The research provides a useful view into reading intervention. Despite the positive effect of metacognitive instruction on students’ comprehension skills, it is not widely used in classroom.

Keywords: comprehension instruction, metacogntion, metacognitive skills, reading intervention

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Authors: Hazim Abdulsada

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The inspection of underneath vehicle system has been given significant attention by governments after the threat of terrorism become more prevalent. New technologies such as mobile robots and computer vision are led to have more secure environment. This paper proposed that a mobile robot like Aria robot can be used to search and inspect the bombs under parking a lot vehicle. This robot is using fuzzy logic and subsumption algorithms to control the robot that movies underneath the vehicle. An OpenCV library and laser Hokuyo are added to Aria robot to complete the experiment for under vehicle inspection. This experiment was conducted at the indoor environment to demonstrate the efficiency of our methods to search objects and control the robot movements under vehicle. We got excellent results not only by controlling the robot movement but also inspecting object by the robot camera at same time. This success allowed us to know the requirement to construct a new cost effective robot with more functionality.

Keywords: fuzzy logic, mobile robots, Opencv, subsumption, under vehicle inspection

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Authors: Feras Hanandeh, Izzat Alsmadi, Muhammad M. Kwafha

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Prefix trees or tries are data structures that are used to store data or index of data. The goal is to be able to store and retrieve data by executing queries in quick and reliable manners. In principle, the structure of the trie depends on having letters in nodes at the different levels to point to the actual words in the leafs. However, the exact structure of the trie may vary based on several aspects. In this paper, we evaluated different structures for building tries. Using datasets of words of different sizes, we evaluated the different forms of trie structures. Results showed that some characteristics may impact significantly, positively or negatively, the size and the performance of the trie. We investigated different forms and structures for the trie. Results showed that using an array of pointers in each level to represent the different alphabet letters is the best choice.

Keywords: data structures, indexing, tree structure, trie, information retrieval

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Authors: Lican Guzmán, José Manuel Lattus, Mariana Cervetto, Mauricio Calderón

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Today the estimation of effects produced by climate change in high Andean wetland environments is confronted by big challenges. This study provides a way to an analysis by remote sensing how some Ambiental aspects have evolved on the Maricunga salt flat in the last 30 years, divided into the summer and winter seasons, and if global warming is conditioning these changes. The first step to achieve this goal was the recompilation of geological, hydrological, and morphometric antecedents to ensure an adequate contextualization of its environmental parameters. After this, software processing and analysis of Landsat 5,7 and 8 satellite imagery was required to get the vegetation, water, surface temperature, and soil moisture indexes (NDVI, NDWI, LST, and SMI) in order to see how their spatial-temporal conditions have evolved in the area of study during recent decades. Results show a tendency of regular increase in surface temperature and disponibility of water during both seasons but with slight drought periods during summer. Soil moisture factor behaves as a constant during the dry season and with a tendency to increase during wintertime. Vegetation analysis shows an areal and quality increase of its surface sustained through time that is consistent with the increase of water supply and temperature in the basin mentioned before. Roughly, the effects of climate change can be described as positive for the Maricunga salt flat; however, the lack of exact correlation in dates of the imagery available to remote sensing analysis could be a factor for misleading in the interpretation of results.

Keywords: global warming, geology, SIG, Atacama Desert, Salar de Maricunga, environmental geology, NDVI, SMI, LST, NDWI, Landsat

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Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis

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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Keywords: nowcasting, search data, Google Trends, official statistics

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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Authors: Neha Adsul, Rohit Shah

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Background: The global history of nursing is exclusively a history of deep contradictions as it seeks to negotiate inclusion in an already gendered world. Although a powerful 'clinical gaze exists, nurses have toiled to re-negotiate and subvert the 'medical gaze' by practicing the 'therapeutic gaze' to tether back 'care into nursing practice.' This helps address the duality of the 'body' and 'mind' wherein the patient is not just limited to being an object of medical inquiry. Nevertheless, there has been a consistent effort to fit 'nursing' into being an art or an emerging science over the years. Especially with advances in hospital-based techno-centric medical practices, the boundaries between technology and nursing practices are becoming more blurred as the technical process becomes synonymous with nursing, eroding the essence of nursing care. Aim: This paper examines the history of nursing and offers insights into how gendered relations and the ideological belief of 'nursing as gendered work' have propagated to the subjugation of the nursing profession. It further aims to provide insights into the patriarchally imbibed techno-centrism that negates the gendered caregiving which lies at the crux of a nurse's work. Method: A literature search was carried out using Google Scholar, Web of Science and PubMed databases. Search words included: technology and nursing, medical technology and nursing, history of nursing, sociology and nursing and nursing care. The history of nursing is presented in a discussion that weaves together the historical events of the 'Birth of the Clinic' and the shift from 'bed-side medicine' to 'hospital-based medicine' that legitimizes exploitation of the bodies of patients to the 'medical gaze while the emergence of nursing as acquiescent to instrumental, technical, positivist and dominant views of medicine. The resultant power asymmetries, wherein in contemporary nursing, the constant struggle of nurses to juggle between being the physicians "operational right arm" to harboring that subjective understanding of the patients to refrain from de-humanizing nursing-care. Findings: The nursing profession suffers from being rendered invisible due to gendered relations having patrifocal societal roots. This perpetuates a notion rooted in the idea that emphasizes empiricism and has resulted in theoretical and epistemological fragmentation of the understanding of body and mind as separate entities. Nurses operate within this structure while constantly being at the brink of being pushed beyond the legitimate professional boundaries while being labeled as being 'unscientific' as the work does not always corroborate and align with the existing dominant positivist lines of inquiries. Conclusion: When understood in this broader context of how nursing as a practice has evolved over the years, it provides a particularly crucial testbed for understanding contemporary gender relations. Not because nurses like to live in a gendered work trap but because the gendered relations at work are written in a covert narcissistic patriarchal milieu that fails to recognize the value of intangible yet utmost necessary 'caring work in nursing. This research urges and calls for preserving and revering the humane aspect of nursing care alongside the emerging tech-savvy expectations from nursing work.

Keywords: nursing history, technocentric, power relations, scientific duality

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Authors: Panas Gerasimos, Kotidou Varvara, Halkiopoulos Constantinos, Gkintoni Evgenia

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As a result of growing technology and briefing by the internet, users resort to the internet and subsequently to the opinion of an expert. In many cases, they take control of their health in their hand and make a decision without the contribution of a doctor. According to that, this essay intends to analyze the confidence of searching health issues on the internet. For the fulfillment of this study, there has been a survey among doctors in order to find out the reasons a patient uses the internet about their health problems and the consequences that health information could lead by searching on the internet, as well. Specifically, the results regarding the research of the users demonstrate: a) the majority of users make use of the internet about health issues once or twice a month, b) individuals that possess chronic disease make health search on the internet more frequently, c) the most important topics that the majority of users usually search are pathological, dietary issues and the search of issues that are associated with doctors and hospitals. However, it observed that topic search varies depending on the users’ age, d) the most common sources of information concern the direct contact with doctors, as there is a huge preference from the majority of users over the use of the electronic form for their briefing and e) it has been observed that there is large lack of knowledge about e-health services. From the doctor's point of view, the following conclusions occur: a) almost all doctors use the internet as their main source of information, b) the internet has great influence over doctors’ relationship with the patients, c) in many cases a patient first makes a visit to the internet and then to the doctor, d) the internet significantly has a psychological impact on patients in order to for them to reach a decision, e) the most important reason users choose the internet instead of the health professional is economic, f) the negative consequence that emerges is inaccurate information, g) and the positive consequences are about the possibility of online contact with the doctor and contributes to the easy comprehension of the doctor, as well. Generally, it’s observed from both sides that the use of the internet in health issues is intense, which declares that the new means the doctors have at their disposal, produce the conditions for radical changes in the way of providing services and in the doctor-patient relationship.

Keywords: cognitive models, health marketing, e-health, psychological factors, digital marketing, e-health services

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Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

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Authors: Haluk Eren, Mucahit Karaduman

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This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, three-dimensional, smart city, scholarly search, semantic

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Authors: Geetu Gahlawat, Manisha Singh

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In the recent years, the concept of media literacy is being extended from its traditional focus on print and audio-visual media to encompass the internet and other new media within academic and policy discourses. This article throws revolves around three significant queries which are to be dealt by the academia, general public and the policy-makers: What is media literacy? How is it changing? And what is the significance of media literacy? At the beginning of the article, the definition 'media literacy' is the ability to access, analyse, evaluate and create messages across a variety of contexts are given and then this is further being tested in connection with the internet and other information and communication technologies.Having advocated this skills-based approach to media literacy in relation to the internet, the article identifies some outstanding issues for new media literacy crucial to any policy of promoting media literacy among the population. The outcome is better understanding of media literacy and also the impact of ICT on media literacy by the public as well as media literate people.

Keywords: media literacy, ICT, internet, education

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

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Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer

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Authors: Jason Digalakis, John Cotronis

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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

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Authors: Heiko Jessen, Laura Tanus, Slobodan Ruzicic

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Objectives: The efficacy of Stribild®, an integrase strand transfer inhibitor (INSTI) -based STR, has been evaluated in randomized clinical trials and it has demonstrated durable capability in terms of achieving sustained suppression of HIV-1 RNA-levels. However, differences in monitoring frequency, existing selection bias and profile of patients enrolled in the trials, may all result in divergent efficacy of this regimen in routine clinical settings. The aim of this study was to assess the virologic outcomes, safety and tolerability profile of Stribild® in a routine clinical setting. Methods: This was a retrospective monocentric analysis on HIV-1-infected patients, who started with or were switched to Stribild®. Virological failure (VF) was defined as confirmed HIV-RNA>50 copies/ml. The minimum time of follow-up was 24 weeks. The percentage of patients remaining free of therapeutic failure was estimated using the time-to-loss-of-virologic-response (TLOVR) algorithm, by intent-to-treat analysis. Results: We analyzed the data of 197 patients (56 ART-naïve and 141 treatment-experienced patients), who fulfilled the inclusion criteria. Majority (95.9%) of patients were male. The median time of HIV-infection at baseline was 2 months in treatment-naïve and 70 months in treatment-experienced patients. Median time [IQR] under ART in treatment-experienced patients was 37 months. Among the treatment-experienced patients 27.0% had already been treated with a regimen consisting of two NRTIs and one INSTI, whereas 18.4% of them experienced a VF. The median time [IQR] of virological suppression prior to therapy with Stribild® in the treatment-experienced patients was 10 months [0-27]. At the end of follow-up (median 33 months), 87.3% (95% CI, 83.5-91.2) of treatment-naïve and 80.3% (95% CI, 75.8-84.8) of treatment-experienced patients remained free of therapeutic failure. Considering only treatment-experienced patients with baseline VL<50 copies/ml, 83.0% (95% CI, 78.5-87.5) remained free of therapeutic failure. A total of 17 patients stopped treatment with Stribild®, 5.4% (3/56) of them were treatment-naïve and 9.9% (14/141) were treatment-experienced patients. The Stribild® therapy was discontinued in 2 (1.0%) because of VF, loss to follow-up in 4 (2.0%), and drug-drug interactions in 2 (1.0%) patients. Adverse events were in 7 (3.6%) patients the reason to switch from therapy with Stribild® and further 2 (1.0%) patients decided personally to switch. The most frequently observed adverse events were gastrointestinal side effects (20.0%), headache (8%), rash events (7%) and dizziness (6%). In two patients we observed an emergence of novel resistances in integrase-gene. The N155H evolved in one patient and resulted in VF. In another patient S119R evolved either during or shortly upon switch from therapy with Stribild®. In one further patient with VF two novel mutations in the RT-gene were observed when compared to historical genotypic test result (V106I/M and M184V), whereby it is not clear whether they evolved during or already before the switch to Stribild®. Conclusions: Effectiveness of Stribild® for treatment-naïve patients was consistent with data obtained in clinical trials. The safety and tolerability profile as well as resistance development confirmed clinical efficacy of Stribild® in a daily practice setting.

Keywords: ART, HIV, integrase inhibitor, stribild

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Authors: Anu S. Nair, V. Anantha Subramanian

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This paper presents a surface development and fairing technique combining the features of a modern computer-aided design tool namely the Non-Uniform Rational Basis Spline (NURBS) with an algorithm to obtain a rapidly faired hull form. Some of the older series based designs give sectional area distribution such as in the Wageningen-Lap Series. Others such as the FORMDATA give more comprehensive offset data points. Nevertheless, this basic data still requires fairing to obtain an acceptable faired hull form. This method uses the input of sectional area distribution as an example and arrives at the faired form. Characteristic section shapes define any general ship hull form in the entrance, parallel mid-body and run regions. The method defines a minimum of control points at each section and using the Golden search method or the bisection method; the section shape converges to the one with the prescribed sectional area with a minimized error in the area fit. The section shapes combine into evolving the faired surface by NURBS and typically takes 20 iterations. The advantage of the method is that it is fast, robust and evolves the faired hull form through minimal iterations. The curvature criterion check for the hull lines shows the evolution of the smooth faired surface. The method is applicable to hull form from any parent series and the evolved form can be evaluated for hydrodynamic performance as is done in more modern design practice. The method can handle complex shape such as that of the bulbous bow. Surface patches developed fit together at their common boundaries with curvature continuity and fairness check. The development is coded in MATLAB and the example illustrates the development of the method. The most important advantage is quick time, the rapid iterative fairing of the hull form.

Keywords: computer-aided design, methodical series, NURBS, ship design

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Authors: O. Lasaga

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Defining professional objectives and the search for work are some of the greatest stress factors for final year university students and recent graduates. To manage correctly the stress brought about by the uncertainty, confusion and frustration this process often generates, a course to control stress based on mindfulness has been designed and taught. This course provides tools based on relaxation, mindfulness and meditation that enable students to address personal and professional challenges in the transition to the job market, eliminating or easing the anxiety involved. The course is extremely practical and experiential, combining theory classes and practical classes of relaxation, meditation and mindfulness, group dynamics, reflection, application protocols and session integration. The evaluation of the courses highlighted on the one hand the high degree of satisfaction and, on the other, the usefulness for the students in becoming aware of stressful situations and how these affect them and learning new coping techniques that enable them to reach their goals more easily and with greater satisfaction and well-being.

Keywords: employability, meditation, mindfulness, relaxation techniques, stress

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Authors: Rachel Goh, Alexander McNab, Brent Alsop, David O'Hare

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In a busy airport, the decision whether to take passengers aside and search their luggage for dangerous items can have important consequences. If an officer fails to search and stop a bag containing a dangerous object, a life-threatening incident might occur. But stopping a bag unnecessarily means that the officer might lose time searching the bag and face an angry passenger. Passengers’ bags, however, are often cluttered with personal belongings of varying shapes and sizes. It can be difficult to determine what is dangerous or not, especially if the decisions must be made quickly in cases of busy flight schedules. Additionally, the decision to search bags is often made with input from the surrounding officers on duty. This scenario raises several questions: 1) Past findings suggest that humans are more reliant on an automated aid when under time pressure in a visual search task, but does this translate to human-human reliance? 2) Are humans more likely to agree with another person if the person is assumed to be an expert or a novice in these ambiguous situations? In the present study, forty-one participants performed a simulated luggage-screening task. They were partnered with an advisor of two different statuses (expert vs. novice), but of equal accuracy (90% correct). Participants made two choices each trial: their first choice with no advisor input, and their second choice after advisor input. The second choice was made within either 2 seconds or 8 seconds; failure to do so resulted in a long time-out period. Under the 2-second time pressure, participants were more likely to disagree with their own first choice and agree with the expert advisor, regardless of whether the expert was right or wrong, but especially when the expert suggested that the bag was safe. The findings indicate a tendency for people to assume less responsibility for their decisions and defer to their partner, especially when a quick decision is required. This over-reliance on others’ opinions might have negative consequences in real life, particularly when relying on fallible human judgments. More awareness is needed regarding how a stressful environment may influence reliance on other’s opinions, and how better techniques are needed to make the best decisions under high stress and time pressure.

Keywords: advisors, decision-making, time pressure, trust

Procedia PDF Downloads 151