Search results for: personnel information

Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

Procedia PDF Downloads 102

Authors: Nazira B. Boldurukova

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The main aim of this article is to give the information about life and social and diplomatic work of Zhou Enlai, to prove his identity in his impact to the history of the world; to show his place in the organization of internal and foreign policy and in the peaceful international relationships of China with other countries.

Keywords: China, foreign policy of China, identity, politician, diplomacy, Zhou Enlai

Procedia PDF Downloads 554

Authors: Abduladim Maitieg, Kevin Lynch, Mark Johnson

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The goal of the Libyan Environmental General Authority (EGA) and National Oil Corporation (Department of Health, Safety & Environment) during the last 5 years has been to adopt a common approach to coastal and marine spatial planning. Protection and planning of the coastal zone is a significant for Libya, due to the length of coast and, the high rate of oil export, and spills’ potential negative impacts on coastal and marine habitats. Coastal resource scenarios constitute an important tool for exploring the long-term and short-term consequences of oil spill impact and available response options that would provide an integrated perspective on mitigation. To investigate that, this paper reviews the Misratah coastal parameters to present the physical and human controls and attributes of coastal habitats as the first step in understanding how they may be damaged by an oil spill. This paper also investigates costal resources, providing a better understanding of the resources and factors that impact the integrity of the ecosystem. Therefore, the study described the potential spatial distribution of oil spill risk and the coastal resources value, and also created spatial maps of coastal resources and their vulnerability to oil spills along the coast. This study proposes an analysis of coastal resources condition at a local level in the Misratah region of the Mediterranean Sea, considering the implementation of coastal and marine spatial planning over time as an indication of the will to manage urban development. Oil spill contamination analysis and their impact on the coastal resources depend on (1) oil spill sequence, (2) oil spill location, (3) oil spill movement near the coastal area. The resulting maps show natural, socio-economic activity, environmental resources along of the coast, and oil spill location. Moreover, the study provides significant geodatabase information which is required for coastal sensitivity index mapping and coastal management studies. The outcome of study provides the information necessary to set an Environmental Sensitivity Index (ESI) for the Misratah shoreline, which can be used for management of coastal resources and setting boundaries for each coastal sensitivity sectors, as well as to help planners measure the impact of oil spills on coastal resources. Geographic Information System (GIS) tools were used in order to store and illustrate the spatial convergence of existing socio-economic activities such as fishing, tourism, and the salt industry, and ecosystem components such as sea turtle nesting area, Sabkha habitats, and migratory birds feeding sites. These geodatabases help planners investigate the vulnerability of coastal resources to an oil spill.

Keywords: coastal and marine spatial planning advancement training, GIS mapping, human uses, ecosystem components, Misratah coast, Libyan, oil spill

Procedia PDF Downloads 364

Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

Procedia PDF Downloads 162

Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

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Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

Procedia PDF Downloads 541

Authors: Madison Meyer

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Dermatological conditions are one of the most viewed medical subjects on the social media platform TikTok, resulting in the rise of several prominent American board-certified dermatologists as influencers. Notably, dermatology is one of the least diverse specialties. This cross-sectional study aimed to assess individuals’ preferences related to race, gender, and sexual identity of doctors in terms of dermatology-related information on TikTok and which group posts more reliable information. This study qualitatively and quantitatively evaluated the racial, gender, and sexual diversity of the top 55 dermatologist influencers on TikTok based on their follower count. The DISCERN tool was used to determine the reliability of consumer health content based on a score ranging from 1-5. Among the top 55 dermatologist influencers, African American (54,241.60) and Latinx (6,696) groups had the lowest mean number of followers compared to Caucasian (1,046,298.50) and Asian (1,403,393.50) physicians. Latinx and African American dermatologists had the highest DISCERN scores of 2 and 1.9, respectively. None of the physicians identified as a different gender or as LGBTQIA+ in any racial category. There is a considerable lack of minority dermatologist influencers on TikTok, especially Latinx, African American, and LGBTQIA+ physicians. The lack of diversity in the dermatology specialty can lead to inequitable care and health outcomes for racial/ethnic, gender, and sexual minority patient populations. This study’s findings also suggest Latinx and African American dermatologists post more reliable content compared with their Caucasian and Asian counterparts.

Keywords: dermatology, social media, sexual and gender minorities, racial minorities, skin of color, tiktok

Procedia PDF Downloads 79

Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

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Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

Procedia PDF Downloads 136

Authors: Professor Jo Angouri, Polina Mesinioti, Chris Turner

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In order for a group of ad-hoc professional to perform as a team, a shared understanding of the problem at hand and an agreed action plan are necessary components. This is particularly significant in complex, time sensitive professional settings such as in trauma emergencies. In this context, team briefings prior to the patient arrival (pre-briefings) constitute a critical event for the performance of the team; they provide the necessary space for co-constructing a shared understanding of the situation through summarising information available to the team: yet the act of summarising is widely assumed in medical practice but not systematically researched. In the vast teamwork literature, terms such as ‘shared mental model’, ‘mental space’ and ‘cognate labelling’ are used extensively, and loosely, to denote the outcome of the summarising process, but how exactly this is done interactionally remains under researched. This paper reports on the forms and functions of pre-briefings in a major trauma centre in the UK. Taking an interactional approach, we draw on 30 simulated and real-life trauma emergencies (15 from each dataset) and zoom in on the use of pre-briefings, which we consider focal points in the management of trauma emergencies. We show how ad hoc teams negotiate sharedness of future orientation through summarising, synthesising information, and establishing common understanding of the situation. We illustrate the role, characteristics, and structure of pre-briefing sequences that have been evaluated as ‘efficient’ in our data and the impact (in)effective pre-briefings have on teamwork. Our work shows that the key roles in the event own the act of summarising and we problematise the implications for leadership in trauma emergencies. We close the paper with a model for pre-briefing and provide recommendations for clinical practice, arguing that effective pre-briefing practice is teachable.

Keywords: summarising, medical emergencies, interaction analysis, shared/mental models

Procedia PDF Downloads 96

Authors: Nwamaka Patricia Ibeme, Musa Zakari

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E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

Procedia PDF Downloads 71

Authors: Rahimah Akbar, Abdullah Al-Hashemi, Hanan Taqi, Taiba Sadeq

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As technology continues to develop, teaching curriculums in both schools and universities have begun adopting a more computer/digital based approach to the transmission of knowledge and information, as opposed to the more old-fashioned use of textbooks. This gives rise to the question: Are there any differences in learning from a digital source over learning from a printed source, as in from a textbook? More specifically, which medium of information results in better long-term retention? A review of the confounding factors implicated in understanding the relationship between learning from the two different mediums was done. Alongside this, a 4-week cohort study involving 76 1st year English Language female students was performed, whereby the participants were divided into 2 groups. Group A studied material from a paper source (referred to as the Print Medium), and Group B studied material from a digital source (Digital Medium). The dependent variables were grading of memory recall indexed by a 4 point grading system, and total frequency of item repetition. The study was facilitated by advanced computer software called Super Memo. Results showed that, contrary to prevailing evidence, the Digital Medium group showed no statistically significant differences in terms of the shift from Remember (Episodic) to Know (Semantic) when all confounding factors were accounted for. The shift from Random Guess and Familiar to Remember occurred faster in the Digital Medium than it did in the Print Medium.

Keywords: digital medium, print medium, long-term memory recall, episodic memory, semantic memory, super memo, forgetting index, frequency of repetitions, total time spent

Procedia PDF Downloads 291

Authors: Hsuan Yu Lai, Hsuan Hsuan Chang

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The consumer decision process steps through problems by weighing evidence, examining alternatives, and choosing a decision path. Currently, the COVID 19 made the tourism industry encounter a huge challenge and suffer the biggest amount of economic loss. It would be very important to reexamine the decision-making process model, especially after the pandemic, and consider the differences among different generations. The tourism industry has been significantly impacted by the global outbreak of COVID-19, but as the pandemic subsides, the sector is recovering. This study addresses the scarcity of research on travel decision-making patterns among generations in Taiwan. Specifically targeting individuals who frequently traveled abroad before the pandemic, the study explores differences in decision-making at different stages post-outbreak. So this study investigates differences in travel decision-making among individuals from different generations during/after the COVID-19 pandemic and examines the moderating effects of social media usage and individuals' perception of health risks. The study hypotheses are “there are significant differences in the decision-making process including travel motivation, information searching preferences, and criteria for decision-making” and that social-media usage and health-risk perception would moderate the results of the previous study hypothesis. The X, Y, and Z generations are defined and categorized based on a literature review. The survey collected data including their social-economic background, travel behaviors, motivations, considerations for destinations, travel information searching preferences, and decision-making criteria before/after the pandemic based on the reviews of previous studies. Data from 656 online questionnaires were collected between January to May 2023 and from Taiwanese travel consumers who used to travel at least one time abroad before Covid-19. SPSS is used to analyze the data with One-Way ANOVA and Two-Way ANOVA. The analysis includes demand perception, information gathering, alternative comparison, purchase behavior, and post-travel experience sharing. Social media influence and perception of health risks are examined as moderating factors. The findings show that before the pandemic, the Y Generation preferred natural environments, while the X Generation favored historical and cultural sites compared to the Z Generation. However, after the outbreak, the Z Generation displayed a significant preference for entertainment activities. This study contributes to understanding changes in travel decision-making patterns following COVID-19 and the influence of social media and health risks. The findings have practical implications for the tourism industry.

Keywords: consumer decision-making, generation study, health risk perception, post-pandemic era, social media

Procedia PDF Downloads 61

Authors: Wambugu Naftaly, Ruisheng Wang, Zhijun Wang

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Models based on convolutional neural networks (CNNs), in conjunction with Transformer, have excelled in semantic segmentation, a fundamental task for intelligent Earth observation using remote sensing (RS) imagery. Nonetheless, tokenization in the Transformer model undermines object structures and neglects inner-patch local information, whereas CNNs are unable to simulate global semantics due to limitations inherent in their convolutional local properties. The integration of the two methodologies facilitates effective global-local feature aggregation and interactions, potentially enhancing segmentation results. Inspired by the merits of CNNs and Transformers, we introduce a layer-level feature aggregation network (LLFA-Net) to address semantic segmentation of fine-resolution remote sensing (FRRS) images for land cover classification. The simple yet efficient system employs a transposed unit that hierarchically utilizes dense high-level semantics and sufficient spatial information from various encoder layers through a layer-level feature aggregation module (LLFAM) and models global contexts using structured Transformer blocks. Furthermore, the decoder aggregates resultant features to generate rich semantic representation. Extensive experiments on two public land cover datasets demonstrate that our proposed framework exhibits competitive performance relative to the most recent frameworks in semantic segmentation.

Keywords: land cover mapping, semantic segmentation, remote sensing, vision transformer networks, deep learning

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Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

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The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

Procedia PDF Downloads 122

Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

Procedia PDF Downloads 127

Authors: Joseph Ampratwum, Yaw Nyadu Offei, Afua Ntoaduro, Frank Twum

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The use of computer assistive technology has captured the attention of individuals with visual impairment. Children with visual impairments who are tactual learners have one unique need which is quite different from all other disability groups. They depend on the use of computer assistive technology for reading, writing, receiving information and sending information as well. The objective of the study was to assess students’ competencies in the use of computer assistive technology at Akropong School for the Blind in Ghana. This became necessary because little research has been conducted to document the competencies and challenges in the use of computer among students with visual impairments in Africa. A case study design with a mixed research strategy was adopted for the study. A purposive sampling technique was used to sample 35 students from Akropong School for the Blind in the eastern region of Ghana. The researcher gathered both quantitative and qualitative data to measure students’ competencies in keyboarding skills and Job Access with Speech (JAWS), as well as the other challenges. The findings indicated that comparatively students’ competency in keyboard skills was higher than JAWS application use. Thus students had reached higher stages in the conscious competencies matrix in the former than the latter. It was generally noted that challenges limiting effective use of students’ competencies in computer assistive technology in the School were more personal than external influences. This was because most of the challenges were due to the individual response to the training and familiarity in developing their competencies in using computer assistive technology. Base on this it was recommended that efforts should be made to stock up the laboratory with additional computers. Directly in line with the first recommendation, it was further suggested that more practice time should be created for the students to maximize computer use. Also Licensed JAWS must be acquired by the school to advance students’ competence in using computer assistive technology.

Keywords: computer assistive technology, job access with speech, keyboard, visual impairment

Procedia PDF Downloads 345

Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

Procedia PDF Downloads 173

Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

Procedia PDF Downloads 387

Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

Procedia PDF Downloads 424

Authors: Babar Rasheed

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The organizations are in continuous effort to increase their yield and to retain their associates, employees. Technology is considered an integral part of attaining apposite work practices, work environment, and employee engagement. Unconsciously, these advanced practices like work from home, personalized intra-network are disturbing employee work-life balance which ultimately increases psychological pressure on employees. The smart work practice is to develop business models and organizational practices with enhanced employee engagement, minimum trouncing of organization resources with persistent revenue and positive addition in global societies. Need of smart work practices comes from increasing employee turnover rate, global economic recession, unnecessary job pressure, increasing contingent workforce and advancement in technologies. Current practices are not enough elastic to tackle global changing work environment and organizational competitions. Current practices are causing many reciprocal problems among employee and organization mechanically. There is conscious understanding among business sectors smart work practices that will deal with new century challenges with addressing the concerns of relevant issues. It is aimed in this paper to endorse customized and smart work practice tools along knowledge framework to manage the growing concerns of employee engagement, use of technology, orgaization concerns and challenges for the business. This includes a Smart Management Information System to address necessary concerns of employees and combine with a framework to extract the best possible ways to allocate companies resources and re-align only required efforts to adopt the best possible strategy for controlling potential risks.

Keywords: employees engagement, management information system, psychological pressure, current and future HR practices

Procedia PDF Downloads 186

Authors: Carolina Aparicio-Fernández, Alejandro Vilar Abad, Mar Cañada Soriano, Jose-Luis Vivancos

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The building sector is responsible for 40% of the total energy consumption in the European Union (EU). Thus, implementation of strategies for quantifying and reducing buildings energy consumption is indispensable for reaching the EU’s carbon neutrality and energy efficiency goals. Each Member State has transposed the European Directives according to its own peculiarities: existing technical legislation, constructive solutions, climatic zones, etc. Therefore, in accordance with the Energy Performance of Buildings Directive, Member States have developed different Energy Performance Certificate schemes, using proposed energy simulation software-tool for each national or regional area. Energy Performance Certificates provide a powerful and comprehensive information to predict, analyze and improve the energy demand of new and existing buildings. Energy simulation software and databases allow a better understanding of the current constructive reality of the European building stock. However, Energy Performance Certificates still have to face several issues to consider them as a reliable and global source of information since different calculation tools are used that do not allow the connection between them. In this document, TRNSYS (TRaNsient System Simulation program) software is used to calculate the energy demand of a building, and it is compared with the energy labeling obtained with Spanish Official software-tools. We demonstrate the possibility of using not official software-tools to calculate the Energy Performance Certificate. Thus, this approach could be used throughout the EU and compare the results in all possible cases proposed by the EU Member States. To implement the simulations, an isolated single-family house with different construction solutions is considered. The results are obtained for every climatic zone of the Spanish Technical Building Code.

Keywords: energy demand, energy performance certificate EPBD, trnsys, buildings

Procedia PDF Downloads 128

Authors: R. Barros, J. Azevedo, P. Padrão, M. Gregório, I. Pádua, C. Almeida, C. Rodrigues, P. Fontes, A. Coelho

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Recent evidence shows a positive association between nutritional literacy and healthy eating. Traditional nutrition education strategies for childhood obesity prevention have shown weak effect. The Nutriscience project aims to create and evaluate an innovative and multidisciplinary strategy for promoting effective and accessible nutritional information to children, their families, and educators. Nutriscience is a one-year prospective follow-up evaluation study including pre-school children (3-5 y), who attend national schools’ network (29). The project is structured around a web-based intervention, using an on-line interactive platform, and focus on increasing fruit and vegetable consumption, and reducing sugar and salt intake. The platform acts as a social network where educational materials, games, and nutritional challenges are proposed in a gamification approach that promotes family and community social ties. A nutrition Massive Online Open Course is developed for educators, and a national healthy culinary contest will be promoted on TV channel. A parental self-reported questionnaire assessing sociodemographic and nutritional literacy (knowledge, attitudes, skills) is administered (baseline and end of the intervention). We expect that results on nutritional literacy from the presented strategy intervention will give us important information about the best practices for health intervention with kindergarten families. This intervention program using a digital interactive platform could be an educational tool easily adapted and disseminated for childhood obesity prevention.

Keywords: childhood obesity, educational tool, nutritional literacy, web-based intervention

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Authors: Olalekan Sunday Alabi, Titus Adeyemi Alonge, Olumuyiwa Idowu Ojo

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Agricultural land suitability analysis and mapping play an imperative role for sustainable utilization of scarce physical land resources. The objective of this study was to prepare spatial database of physical land resources for irrigated agriculture and to assess land suitability for irrigation and developing suitable area map of the study area. The study was conducted at Kampe-Omi irrigation scheme located at Yagba West Local Government Area of Kogi State, Nigeria. Temperature and rainfall data of the study area were collected for 10 consecutive years (2005-2014). Geographic Information System (GIS) techniques were used to develop irrigation land suitability map of the study area. Attribute parameters such as the slope, soil properties, topography of the study area were used for the analysis. The available data were arranged, proximity analysis of Arc-GIS was made, and this resulted into five mapping units. The final agricultural land suitability map of the study area was derived after overlay analysis. Based on soil composition, slope, soil properties and topography, it was concluded that; Kampe-Omi has rich sandy loam soil, which is viable for agricultural purpose, the soil composition is made up of 60% sand and 40% loam. The land-use pattern map of Kampe-Omi has vegetal area and water-bodies covering 55.6% and 19.3% of the total assessed area respectively. The landform of Kampe-Omi is made up of 41.2% lowlands, 37.5% normal lands and 21.3% highlands. Kampe-Omi is adequately suitable for agricultural purpose while an extra of 20.2% of the area is highly suitable for agricultural purpose making 72.6% while 18.7% of the area is slightly suitable.

Keywords: remote sensing, GIS, Kampe–Omi, land suitability, mapping

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Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

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Authors: Victoria L. Chester, Usha Kuruganti

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The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Natinee Thanajaro

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In the past few decades, international research on the country of origin of products has garnered significant interest, particularly in investigating the effects of consumers’ evaluation and perception. As globalization and market competition rise, international firms are seeking ways to control their labour costs and minimise taxes. Many products are outsourced and manufactured in countries with cheap labour. Consequently, the proliferation of ‘bi-national’ products has increased, raising important questions related to consumers’ perception. Moreover, the rapid growth in emerging markets, especially in Asia, has made these countries attractive options for international brands. Therefore, studying the country of origin allows firms and researchers to understand how customers perceive such information regarding the country of manufacture and the country of the brand. This study aims to investigate the influence of the country of manufacture (COM) and country of brand (COB) on Thai consumers’ perception of the brand. In addition, it embraces a different perspective on brand experience as a moderating factor. A sample of 403 Thai respondents was collected through face-to-face survey questionnaires in central Bangkok. This research employs an experiment using a factorial design to test the hypotheses. SPSS statistics software was adopted to analyse and validate the reliability of the testing of the constructs and model hypotheses. The results of this research show that the respondents positively respond to the COB more than the COM, and brand experience plays a moderating role in this research. This research provides a significant contribution to the existing literature and managerial practicality by using multi-dimensional information on the country and analyses the relationships between these dimensions.

Keywords: brand experience, country of brand, country of manufacture, purchase intention

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Authors: Salim Yaren, Nergis Canturk

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Signatures are signs that are handwritten by person in order to confirm values such as information, amount, meaning, time and undertaking that bear on a document. It is understood that the signature of a document and the accuracy of the information on the signature is accepted and approved. Forged signatures are formed by forger without knowing and seeing original signature of person that forger will imitate and as a result of his/her effort for hiding typical characteristics of his/her own signatures. Forged signatures are often signed by starting with the initials of the first and last name or persons of the persons whose fake signature will be signed. The similarities in the signatures are completely random. Within the scope of the study, forged signatures are collected from 100 people both their original signatures and forged signatures signed referring to 5 imaginary people. These signatures are compared for 14 signature analyzing criteria by 2 signature analyzing experts except the researcher. 1 numbered analyzing expert who is 9 year experience in his/her field evaluated signatures of 39 (39%) people right and of 25 (25%) people wrong and he /she made any evaluations for signatures of 36 (36%) people. 2 numbered analyzing expert who is 16 year experienced in his/her field evaluated signatures of 49 (49%) people right and 28 (28%) people wrong and he /she made any evaluations for signatures of 23 (23%) people. Forged signatures that are signed by 24 (24%) people are matched by two analyzing experts properly, forged signatures that are signed by 8 (8%) people are matched wrongfully and made up signatures that are signed by 12 (12%) people couldn't be decided by both analyzing experts. Signatures analyzing is a subjective topic so that analyzing and comparisons take form according to education, knowledge and experience of the expert. Consequently, due to the fact that 39% success is achieved by analyzing expert who has 9 year professional experience and 49% success is achieved by analyzing expert who has 16 year professional experience, it is seen that success rate is directly proportionate to knowledge and experience of the expert.

Keywords: forensic signature, forensic signature analysis, signature analysis criteria, forged signature

Procedia PDF Downloads 125

Authors: Sofia Sehli, Zainab El Ouafi, Casey Eddington, Soumaya Jbara, Kasambula Arthur Shem, Islam El Jaddaoui, Ayorinde Afolayan, Olaitan I. Awe, Allissa Dillman, Hassan Ghazal

Abstract:

The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually.

Keywords: metagenomics, shotgun metagenomic sequence analysis, COVID-19, pipeline, bioinformatics

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Authors: A. Bhatt, C. Bassi, H. Farragher, J. Musk

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Background: All medicines placed on the EU market are legally required to be accompanied by labeling and package leaflet, which provide comprehensive information, enabling its safe and appropriate use. Mock-ups with results of assessments using a target patient group must be submitted for a marketing authorisation application. Consumers need confidence in non-prescription, OTC medicines in order to manage their minor ailments and umbrella brands assist purchasing decisions by assisting easy identification within a particular therapeutic area. A number of regulatory agencies have risk management tools and guidelines to assist in developing umbrella brands for OTC medicines, however assessment and decision making is subjective and inconsistent. This study presents an evaluation in the UK following the US FDA warning concerning methaemoglobinaemia following 21 reported cases (11 children under 2 years) caused by OTC oral analgesics containing benzocaine. METHODS: A standard face to face, 25 structured task based user interview testing methodology using a standard questionnaire and rating scale in consumers aged 15-91 years, was conducted independently between June and October 2015 in their homes. Whether individuals could discriminate between the labelling, safety information and warnings on cartons and PILs between 3 different OTC medicines packs with the same umbrella name was evaluated. Each pack was presented with differing information hierarchy using, different coloured cartons, containing the 3 different active ingredients, benzocaine (oromucosal spray) and two lozenges containing 2, 4, dichlorobenzyl alcohol, amylmetacresol and hexylresorcinol respectively (for the symptomatic relief of sore throat pain). The test was designed to determine whether warnings on the carton and leaflet were prominent, accessible to alert users that one product contained benzocaine, risk of methaemoglobinaemia, and refer to the leaflet for the signs of the condition and what to do should this occur. Results: Two consumers did not locate the warnings on the side of the pack, eventually found them on the back and two suggestions to further improve accessibility of the methaemoglobinaemia warning. Using a gold pack design for the oromucosal spray, all consumers could differentiate between the 3 drugs, minimum age particulars, pharmaceutical form and the risk factor methaemoglobinaemia. The warnings for benzocaine were deemed to be clear or very clear; appearance of the 3 packs were either very well differentiated or quite well differentiated. The PIL test passed on all criteria. All consumers could use the product correctly, identify risk factors ensuring the critical information necessary for the safe use was legible and easily accessible so that confusion and errors were minimised. Conclusion: Patients with known methaemoglobinaemia are likely to be vigilant in checking for benzocaine containing products, despite similar umbrella brand names across a range of active ingredients. Despite these findings, the package design and spray format were not deemed to be sufficient to mitigate potential safety risks associated with differences in target populations and contraindications when submitted to the Regulatory Agency. Although risk management tools are increasingly being used by agencies to assist in providing objective assurance of package safety, further transparency, reduction in subjectivity and proportionate risk should be demonstrated.

Keywords: labelling, OTC, risk, user testing

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Authors: Marpaleni

Abstract:

The intergovernmental Panel on Climate Change (IPCC) declared in 2007 that global warming and climate change are not just a series of events caused by nature, but rather caused by human behaviour. Thus, to reduce the impact of human activities on climate change it is required to have information about how people respond to the environmental issues and what constraints they face. However, information on these and other phenomena remains largely missing, or not fully integrated within the existing data systems. The proposed study is aimed at filling the gap in this knowledge by focusing on Environmentally Friendly Behaviour (EFB) of the people of Indonesia, by taking the province of South Sumatera as a case of study. EFB is defined as any activity in which people engage to improve the conditions of the natural resources and/or to diminish the impact of their behaviour on the environment. This activity is measured in terms of consumption in five areas at the household level, namely housing, energy, water usage, recycling and transportation. By adopting the Indonesia’s Environmentally Friendly Behaviour conducted by Statistics Indonesia in 2013, this study aims to precisely identify one’s orientation towards EFB based on socio demographic characteristics such as: age, income, occupation, location, education, gender and family size. The results of this research will be useful to precisely identify what support people require to strengthen their EFB, to help identify specific constraints that different actors and groups face and to uncover a more holistic understanding of EFB in relation to particular demographic and socio-economics contexts. As the empirical data are examined from the national data sample framework, which will continue to be collected, it can be used to forecast and monitor the future of EFB.

Keywords: environmentally friendly behavior, demographic, South Sumatera, Indonesia

Procedia PDF Downloads 286