Search results for: remote application

Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

Procedia PDF Downloads 102

Authors: Yaser Miaji, Mohammed Aloryani

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The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 565

Authors: Berhanu Terfa, Nengcheng C.

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The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

Procedia PDF Downloads 286

Authors: Amina Naidja, Zedira Khammar, Ines Soltani

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This study investigates the impact of urban development on the urban heat island (UHI) effect in the semi-arid Aures region of Algeria, integrating remote sensing data with statistical analysis and community surveys to examine the interconnected environmental and social dynamics. Using Landsat 8 satellite imagery, temporal variations in the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and land use/land cover (LULC) changes are analyzed to understand patterns of urbanization and environmental transformation. These environmental metrics are correlated with land surface temperature (LST) data derived from remote sensing to quantify the UHI effect. To incorporate the social dimension, a structured questionnaire survey is conducted among residents in selected urban areas. The survey assesses community perceptions of urban heat, its impacts on daily life, health concerns, and coping strategies. Statistical analysis is employed to analyze survey responses, identifying correlations between demographic factors, socioeconomic status, and perceived heat stress. Preliminary findings reveal significant correlations between built-up areas (NDBI) and higher LST, indicating the contribution of urbanization to local warming. Conversely, areas with higher vegetation cover (NDVI) exhibit lower LST, highlighting the cooling effect of green spaces. Social survey results provide insights into how UHI affects different demographic groups, with vulnerable populations experiencing greater heat-related challenges. By integrating remote sensing analysis with statistical modeling and community surveys, this study offers a comprehensive understanding of the environmental and social implications of urban development in semi-arid climates. The findings contribute to evidence-based urban planning strategies that prioritize environmental sustainability and social well-being. Future research should focus on policy recommendations and community engagement initiatives to mitigate UHI impacts and promote climate-resilient urban development.

Keywords: urban heat island, remote sensing, social analysis, NDVI, NDBI, LST, community perception

Procedia PDF Downloads 41

Authors: Rui Liu, Klaus Greve

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The navigation information is a kind of dynamic geographic information, and the navigation information system is a kind of special geographic information system. At present, there are many researches on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing is not deeply applied into the research of navigation information service. And the imperfection of navigation target coordination and navigation information sharing mechanism under certain navigation tasks has greatly affected the reliability and scientificity of navigation service such as path planning. Considering this, the project intends to study the multi-source information fusion and multi-objective united navigation information interaction mechanism: first of all, investigate the actual needs of navigation users in different areas, and establish the preliminary navigation information classification and importance level model; and then analyze the characteristics of the remote sensing and GIS vector data, and design the fusion algorithm from the aspect of improving the positioning accuracy and extracting the navigation environment data. At last, the project intends to analyze the feature of navigation information of the land, sea and air navigation targets, and design the united navigation data standard and navigation information sharing model under certain navigation tasks, and establish a test navigation system for united navigation simulation experiment. The aim of this study is to explore the theory of united navigation service and optimize the navigation information service model, which will lay the theory and technology foundation for the united navigation of land, sea and air targets.

Keywords: information fusion, united navigation, dynamic path planning, navigation information visualization

Procedia PDF Downloads 288

Authors: Muhammad Shahzad Shifa, Amna Shifa, Muhammad Omar, Aamir Shahzad, Rahmat Ali Khan

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Many applications of remote sensing to vegetation and crop response depend on spectral properties of individual leaves and plants. Vegetation indices are usually determined to estimate crop biophysical parameters like crop canopies and crop leaf area indices with the help of remote sensing. Cotton crops assessment is performed with the help of vegetative indices. Remotely sensed images from an optical multispectral radiometer MSR5 are used in this study. The interpretation is based on the fact that different materials reflect and absorb light differently at different wavelengths. Non-normalized and normalized forms of these datasets are analyzed using two complementary data mining algorithms; K-means and K-nearest neighbor (KNN). Our analysis shows that the use of normalized reflectance data and vegetative indices are suitable for an automated assessment and decision making.

Keywords: cotton, condition assessment, KNN algorithm, clustering, MSR5, vegetation indices

Procedia PDF Downloads 333

Authors: A. Akın, H. Çoban

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This study was carried out to determine the effects of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR + Boric Acid (BA), 1/6 CTR + BA, 1/9 CTR + BA applications on yield and yield components of four years old Alphonse Lavallee grape variety (Vitis vinifera L.) grown on grafted 110 Paulsen rootstock in Konya province in Turkey in the vegetation period in 2015. According to the results, the highest maturity index 21.46 with 1/9 CTR application; the highest grape juice yields 736.67 ml with 1/3 CTR + BA application; the highest L* color value 32.07 with 1/9 CTR application; the highest a* color value 1.74 with 1/9 CTR application; the highest b* color value 3.72 with 1/9 CTR application were obtained. The effects of applications on grape fresh yield, cluster weight and berry weight were not found statistically significant.

Keywords: alphonse lavallee grape cultivar, different cluster tip reduction (1/3, 1/6, 1/9), foliar boric acid application, yield, quality

Procedia PDF Downloads 280

Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

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With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

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Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

Procedia PDF Downloads 36

Authors: Diamant Irene, Shklarnik Batya

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In on to its widespread effects on health and economic issues, Covid-19 shook the work and employment world. Among the prominent changes during the pandemic is the work-from-home trend, complete or partial, as part of social distancing. In fact, these changes accelerated an existing tendency of work flexibility already underway before the pandemic. Technology and means of advanced communications led to a re-assessment of “place of work” as a physical space in which work takes place. Today workers can remotely carry out meetings, manage projects, work in groups, and different research studies point to the fact that this type of work has no adverse effect on productivity. However, from the worker’s perspective, despite numerous advantages associated with work from home, such as convenience, flexibility, and autonomy, various drawbacks have been identified such as loneliness, reduction of commitment, home-work boundary erosion, all risk factors relating to the quality of life and burnout. Thus, a real need has arisen in exploring differences in work-from-home experiences and understanding the relationship between psychological characteristics and the prevalence of burnout. This understanding may be of significant value to organizations considering a future hybrid work model combining in-office and remote working. Based on Hobfoll’s Theory of Conservation of Resources, we hypothesized that burnout would mainly be found among workers whose physical remoteness from the workplace threatens or hinders their ability to retain significant individual resources. In the present study, we compared fully remote and partially remote workers (hybrid work), and we examined psychological characteristics and their connection to the formation of burnout. Based on the conceptualization of Place Attachment as the cognitive-emotional bond of an individual to a meaningful place and the need to maintain closeness to it, we assumed that individuals characterized with Place Attachment to the workplace would suffer more from burnout when working from home. We also assumed that extrovert individuals, characterized by the need of social interaction at the workplace and individuals with segmentationpreference – a need for separation between different life domains, would suffer more from burnout, especially among fully remote workers relative to partially remote workers. 194 workers, of which 111 worked from home in full and 83 worked partially from home, aged 19-53, from different sectors, were tested using an online questionnaire through social media. The results of the study supported our assumptions. The repercussions of these findings are discussed, relating to future occupational experience, with an emphasis on suitable occupational adjustment according to the psychological characteristics and needs of workers.

Keywords: working from home, burnout, place attachment, extraversion, segmentation preference, Covid-19

Procedia PDF Downloads 190

Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

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The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

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Authors: Stuart Bradley, Mathew Legg, Lilyan Panton

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Ultrasonic remote sensing is a useful tool for assessing the interior structure of complex targets. For these methods, significantly enhanced spatial resolution is obtained if the pulse is coded, for example using a linearly changing frequency during the pulse duration. Such pulses have a time-dependent spectral structure. Interpretation of the backscatter from targets is, therefore, complicated if the scattering is frequency-dependent. While analytic models are well established for steady sinusoidal excitations applied to simple shapes such as spheres, such models do not generally exist for temporally evolving excitations. Therefore, models are developed in the current paper for handling such signals so that the properties of the targets can be quantitatively evaluated while maintaining very high spatial resolution. Laboratory measurements on simple shapes are used to confirm the validity of the models.

Keywords: linear FM chirp, time-dependent acoustic scattering, ultrasonic remote sensing, ultrasonic scattering

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Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben

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Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.

Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning

Procedia PDF Downloads 172

Authors: Tuisem Shimrah

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One general agreement on climate change is that its causes may be local but the effects are global. Indigenous people are subscribed to “low-carbon” traditional ways of life and as such they have contributed little to causes of climate change. On the contrary they are the most adversely affected by climate change due to their dependence on surrounding rich biological wealth as a source of their livelihood, health care, entertainment and cultural activities This paper deals with the results of the investigation of various adaptation strategies adopted to combat climate change by traditional community. The result shows effective ways of application of traditional knowledge and wisdom applied by Tangkhul traditional community at local and community level in remote areas in Northeast India. Four adaptation measures are being presented in this paper.

Keywords: adaptation, climate change, Northeast India, Tangkhul, traditional community

Procedia PDF Downloads 278

Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

Procedia PDF Downloads 106

Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

Procedia PDF Downloads 127

Authors: Sandhya Armoogum

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In distributed systems and in open systems such as the Internet, often mobile code has to run on unknown and potentially hostile hosts. Mobile code such as a mobile agent is vulnerable when executing on remote hosts. The mobile agent may be subjected to various attacks such as tampering, inspection, and replay attack by a malicious host. Much research has been done to provide solutions for various security problems, such as authentication of mobile agent and hosts, integrity and confidentiality of the data carried by the mobile agent. Many of such proposed solutions in literature are not suitable for open systems whereby the mobile code arrives and executes on a host which is not known and trusted by the mobile agent owner. In this paper, we propose the adoption of the reference monitor by hosts in an open system for providing trust and security for mobile code execution. A secure protocol for the distribution of the reference monitor entity is described. This reference monitor entity on the remote host may also provide several security services such as authentication and integrity to the mobile code.

Keywords: security, mobile agents, reference monitor, trust

Procedia PDF Downloads 440

Authors: Hassam Muazzam

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This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

Procedia PDF Downloads 409

Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: Basit Aftab, Zhichao Wang, Feng Zhongke

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Land Use and Land Cover Change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the spatiotemporal dynamics of land use and land cover (LULC) across a three-decade period (1992–2022) in a district area. The goal is to support sustainable land management and urban planning by utilizing the combination of remote sensing, GIS data, and observations from Landsat satellites 5 and 8 to provide precise predictions of the trajectory of urban sprawl. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the Random Forest method with Multilayer Perceptron (MLP) and Markov Chain analysis. To predict the dynamics of LULC change for the year 2035, a hybrid technique based on multilayer Perceptron and Markov Chain Model Analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. The study also discovered that between 1998 and 2023, the built-up area increased by 468 km² as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will be increased by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. It provides valuable insights for policymakers, land managers, and researchers to support sustainable land use planning, conservation efforts, and climate change mitigation strategies.

Keywords: land use land cover, Markov chain model, multi-layer perceptron, random forest, sustainable land, remote sensing.

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Authors: Mohamed Sarrab, Hadj Bourdoucen

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Mobile applications are verified to check the correctness or evaluated to check the performance with respect to specific security properties such as availability, integrity, and confidentiality. Where they are made available to the end users of the mobile application is achievable only to a limited degree using software engineering static verification techniques. The more sensitive the information, such as credit card data, personal medical information or personal emails being processed by mobile application, the more important it is to ensure the confidentiality of this information. Monitoring non-trusted mobile application during execution in an environment where sensitive information is present is difficult and unnerving. The paper addresses the issue of monitoring and controlling the flow of confidential information during non-trusted mobile application execution. The approach concentrates on providing a dynamic and usable information security solution by interacting with the mobile users during the run-time of mobile application in response to information flow events.

Keywords: mobile application, run-time verification, usable security, direct information flow

Procedia PDF Downloads 381

Authors: Carina Emminger, Umut D. Cakmak, Evrim Burkut, Rene Preuer, Ingrid Graz, Zoltan Major

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Damping accompanies us daily in everyday life and is used to protect (e.g., in shoes) and make our life more comfortable (damping of unwanted motion) and calm (noise reduction). In general, damping is the absorption of energy which is either stored in the material (vibration isolation systems) or changed into heat (vibration absorbers). In case of the last, the damping mechanism can be split in active, passive, as well as semi-active (a combination of active and passive). Active damping is required to enable an almost perfect damping over the whole application range and is used, for instance, in sport cars. In contrast, passive damping is a response of the material due to external loading. Consequently, the material composition has a huge influence on the damping behavior. For elastomers, the material behavior is inherent viscoelastic, temperature, and frequency dependent. However, passive damping is not adjustable during application. Therefore, it is of importance to understand the fundamental viscoelastic behavior and the dissipation capability due to external loading. The objective of this work is to assess the limitation and applicability of viscoelastic material damping for applications in which currently coil-over shock absorbers are utilized. Coil-over shock absorbers are usually made of various mechanical parts and incorporate fluids within the damper. These shock absorbers are well-known and studied in the industry, and when needed, they can be easily adjusted during their product lifetime. In contrary, dampers made of – ideally – a single material are more resource efficient, have an easier serviceability, and are easier manufactured. However, they lack of adaptability and adjustability in service. Therefore, a case study with a remote-controlled sport car was conducted. The original shock absorbers were redesigned, and the spring-dashpot system was replaced by both an elastomer and a thermoplastic-elastomer, respectively. Here, five different formulations of elastomers were used, including a pure and an iron-particle filled thermoplastic poly(urethan) (TPU) and blends of two different poly(dimethyl siloxane) (PDMS). In addition, the TPUs were investigated as full and hollow dampers to investigate the difference between solid and structured material. To get comparative results each material formulation was comprehensively characterized, by monotonic uniaxial compression tests, dynamic thermomechanical analysis (DTMA), and rebound resilience. Moreover, the new material-based shock absorbers were compared with spring-dashpot shock absorbers. The shock absorbers were analyzed under monotonic and cyclic loading. In addition, an impact loading was applied on the remote-controlled car to measure the damping properties in operation. A servo-hydraulic high-speed linear actuator was utilized to apply the loads. The acceleration of the car and the displacement of specific measurement points were recorded while testing by a sensor and high-speed camera, respectively. The results prove that elastomers are suitable in damping applications, but they are temperature and frequency dependent. This is a limitation in applicability of viscous material damper. Feasible fields of application may be in the case of micromobility, like bicycles, e-scooters, and e-skateboards. Furthermore, the viscous material damping could be used to increase the inherent damping of a whole structure, e.g., in bicycle-frames.

Keywords: damper structures, material damping, PDMS, TPU

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Authors: Norshazmira Mat Azmi, Sayidal El Fatimah Masnan, Shatirah Akib

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More than 70% of the Earth is covered by oceans, which are considered to possess boundless renewable energy, such as tidal energy, tidal current energy, wave energy, thermal energy, and chemical energy. The hybrid system help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The concept of hybridizing renewable energy is to meet the desired system requirements, with the lowest value of the energy cost. This paper propose a hybrid power generation system suitable for remote area application and highlight the impact of surface waves on turbine design and performance, and the importance of understanding the site-specific wave conditions.

Keywords: marine current energy, tidal turbines, wave turbine, renewable energy, surface waves, hydraulic flume experiments, instantaneous wave phase

Procedia PDF Downloads 408

Authors: Jansirani Natarajan, Mickael Antoinne Joseph

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The COVID-19 pandemic has interrupted face-to-face education and forced universities into an emergency remote teaching curriculum over a short duration. This abrupt transition in the Spring 2020 semester left both faculty and students without proper preparation for continuing higher education in an online environment. Online learning took place in different formats, including fully synchronous, fully asynchronous, and blended in our university through the e-learning platform MOODLE. Studies have shown that students’ engagement, is a critical factor for optimal online teaching. Very few studies have assessed online engagement with ERT during the COVID-19 pandemic. Purpose: Therefore, this study, sought to understand how the sudden transition to emergency remote teaching impacted nursing students’ engagement with online courses in a Middle Eastern public university. Method: A cross-sectional descriptive research design was adopted in this study. Data were collected through a self-reported online survey using Dixon’s online students’ engagement questionnaire from a sample of 177 nursing students after the ERT learning semester. Results The maximum possible engagement score was 95, and the maximum scores in the domains of skills engagement, emotional engagement, participation engagement, and performance engagement were 30, 25, 30, and 10 respectively. Dixson (2010) noted that a mean item score of ≥3.5 (total score of ≥66.5) represents a highly engaged student. The majority of the participants were females (71.8%) and 84.2% were regular BSN students. Most of them (32.2%) were second-year students and 52% had a CGPA between 2 and 3. Most participants (56.5%) had low engagement scores with ERT learning during the COVID lockdown. Among the four engagement domains, 78% had low engagement scores for the participation domain. There was no significant association found between the engagement and the demographic characteristics of the participants. Conclusion The findings supported the importance of engaging students in all four categories skill, emotional, performance, and participation. Based on the results, training sessions were organized for faculty on various strategies for engaging nursing students in all domains by using the facilities available in the MOODLE (online e-learning platform). It added value as a dashboard of information regarding ERT for the administrators and nurse educators to introduce numerous active learning strategies to improve the quality of teaching and learning of nursing students in the University.

Keywords: engagement, perception, emergency remote learning, COVID-19

Procedia PDF Downloads 63

Authors: K. Tunde Olagunju, C. Scott Allen, Freek Van Der Meer

Abstract:

Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization are only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two (2) operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the hydrocarbon spectral slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven (7) different hydrocarbon oils (crude and refined oil) taken on ten (10) different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon-substrate combination, Sentinel-2, WorldView-3

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Authors: Ramandeep Kaur, Kamaljit Kaur

Abstract:

In recent years, the technology of the remote sensing is growing rapidly. Image enhancement is one of most commonly used of image processing operations. Noise reduction plays very important role in digital image processing and various technologies have been located ahead to reduce the noise of the remote sensing images. The noise reduction using wavelet coefficients based on Orthogonal Matching Pursuit (OMP) has less consequences on the edges than available methods but this is not as establish in edge preservation techniques. So in this paper we provide a new technique minimum patch based noise reduction OMP which reduce the noise from an image and used edge preservation patch which preserve the edges of the image and presents the superior results than existing OMP technique. Experimental results show that the proposed minimum patch approach outperforms over existing techniques.

Keywords: image denoising, minimum patch, OMP, WCOMP

Procedia PDF Downloads 389

Authors: Betzabet García-Mendoza, Rocío Abascal-Mena

Abstract:

Breast and cervical cancer are among the leading causes of death of women in Mexico. The mortality rate for these diseases is alarming, even though there have been many campaigns for making people self-aware of the importance of conducting gynecological studies for a timely prevention and detection, these have not been enough. This paper presents a mobile application for organizing and controlling gynecological studies in order to help and boost women to take care of their bodies and health. The process of analyzing and designing the mobile application is presented, along with all the steps carried out by following a user-centered design methodology.

Keywords: breast cancer, cervical cancer, gynecological mobile application, paper prototyping, storyboard, women health

Procedia PDF Downloads 309

Authors: Shubhakar K., Nachamma S., Judy T., Jacob S. C., Melvin Lee, Kenneth Lo

Abstract:

In recent years, technological advancements have ushered in a new era of education characterized by the integration of technology-enabled devices and online tools. The cyber-physical learning environment (CPLE) is a prime example of this evolution, merging remote cyber participants with in-class learners through immersive technology, interactive digital whiteboards, and online communication platforms like Zoom and MS Teams. This approach transforms the teaching and learning experience into a more seamless, immersive, and inclusive one. This paper outlines the design principles and key features of CPLE that support both teaching and group-based activities. We also explore the key characteristics and potential impact of such environments on educational practices. By analyzing user feedback, we evaluate how technology enhances teaching and learning in a cyber-physical setting, its impact on learning outcomes, user-friendliness, and areas for further enhancement to optimize the teaching and learning environment.

Keywords: cyber-physical class, hybrid teaching, online learning, remote learning, technology enabled learning

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Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang

Abstract:

Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.

Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)

Procedia PDF Downloads 329