Search results for: user data security

Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

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Authors: Lucy Horrobin, Rebecca Fores

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Background: Muay Thai is an increasingly popular combat sport worldwide. Further academic research in the sport will contribute to its professional development. This research sought to produce normative data in relation to the physical and physiological characteristics of professional Muay Thai boxers, as, currently no such data exists. The ultimate aim being to inform appropriate training programs and to facilitate coaching. Methods: N = 9 professional, adult, male Muay Thai boxers were assessed for the following anthropometric, physical and physiological characteristics, using validated methods of assessment: body fat, hamstring flexibility, maximal dynamic upper body strength, lower limb peak power, upper body muscular endurance and aerobic capacity. Raw data scores were analysed for mean, range and SD and where applicable were expressed relative to body mass (BM). Results: Results showed similar characteristics to those found in other combat sports. Low percentages of body fat (mean±SD) 8.54 ± 1.16 allow for optimal power to weight ratios. Highly developed aerobic capacity (mean ±SD) 61.56 ± 5.13 ml.min.kg facilitate recovery and power maintenance throughout bouts. Lower limb peak power output values of (mean ± SD) 12.60 ± 2.09 W/kg indicate that Muay Thai boxers are amongst the most powerful of combat sport athletes. However, maximal dynamic upper body strength scores of (mean±SD) 1.14 kg/kg ± 0.18 were in only the 60th percentile of normative data for the general population and muscular endurance scores (mean±SD) 31.55 ± 11.95 and flexibility scores (mean±SD) 19.55 ± 11.89 cm expressed wide standard deviation. These results might suggest that these characteristics are insignificant in Muay Thai or under-developed, perhaps due to deficient training programs. Implications: This research provides the first normative data of physical and physiological characteristics of Muay Thai boxers. The findings of this study would aid trainers and coaches when designing effective evidence-based training programs. Furthermore, it provides a foundation for further research relating to physiology in Muay Thai. Areas of further study could be determining the physiological demands of a full rules bout and the effects of evidence-based training programs on performance.

Keywords: fitness testing, Muay Thai, physiology, strength and conditioning

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Authors: Maria Bonolo Mathevula

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Background: Children are important members of communities playing major role in the future of any given country (Pera, Fails, Gelsomini, &Garzotto, 2018). Visual Perceptual Skills (VPSs) in children are important health aspect of early childhood development through the Foundation Phases in school. Subsequently, children should undergo visual screening before commencement of schooling for early diagnosis ofVPSs anomalies because the primary role of VPSs is to capacitate children with academic performance in general. Aim : The aim of this study was to determine the anomalies of visual VPSs amongst school children in Foundation Phase. The study’s objectives were to determine the prevalence of VPSs anomalies amongst school children in Foundation Phase; Determine the relationship between children’s academic and VPSs anomalies; and to investigate the relationship between VPSs anomalies and refractive error. Methodology: This study was a mixed method whereby triangulated qualitative (interviews) and quantitative (questionnaire and clinical data) was used. This was, therefore, descriptive by nature. The study’s target population was school children in Foundation Phase. The study followed purposive sampling method. School children in Foundation Phase were purposively sampled to form part of this study provided their parents have given a signed the consent. Data was collected by the use of standardized interviews; questionnaire; clinical data card, and TVPS standard data card. Results: Although the study is still ongoing, the preliminary study outcome based on data collected from one of the Foundation Phases have suggested the following:While VPSs anomalies is not prevalent, it, however, have indirect relationship with children’s academic performance in Foundation phase; Notably, VPSs anomalies and refractive error are directly related since majority of children with refractive error, specifically compound hyperopic astigmatism, failed most subtests of TVPS standard tests. Conclusion: Based on the study’s preliminary findings, it was clear that optometrists still have a lot to do in as far as researching on VPSs is concerned. Furthermore, the researcher recommends that optometrist, as the primary healthcare professionals, should also conduct the school-readiness pre-assessment on children before commencement of their grades in Foundation phase.

Keywords: foundation phase, visual perceptual skills, school children, refractive error

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Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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Authors: Victor Prevost, Solene Landerneau, Michel Duhamel, Joel Sternheimer, Olivier Gallet, Pedro Ferrandiz, Marwa Mokni

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The search for homologous proteins is one of the ongoing challenges in biology and bioinformatics. Traditionally, a pair of proteins is thought to be homologous when they originate from the same ancestral protein. In such a case, their sequences share similarities, and advanced scientific research effort is spent to investigate this question. On this basis, we propose the Protein-Wave Alignment Tool (”P-WAT”) developed within the framework of the France Relance 2030 plan. Our work takes into consideration the mass-related wave aspect of protein biosynthesis, by associating specific frequencies to each amino acid according to its mass. Amino acids are then regrouped within their mass category. This way, our algorithm produces specific alignments in addition to those obtained with a common amino acid coding system. For this purpose, we develop the ”P-WAT” original algorithm, able to address large protein databases, with different attributes such as species, protein names, etc. that allow us to align user’s requests with a set of specific protein sequences. The primary intent of this algorithm is to achieve efficient alignments, in this specific conceptual frame, by minimizing execution costs and information loss. Our algorithm identifies sequence similarities by searching for matches of sub-sequences of different sizes, referred to as primers. Our algorithm relies on Boolean operations upon a dot plot matrix to identify primer amino acids common to both proteins which are likely to be part of a significant alignment of peptides. From those primers, dynamic programming-like traceback operations generate alignments and alignment scores based on an adjusted PAM250 matrix.

Keywords: protein, alignment, homologous, Genodic

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Authors: Tesfaye Fenta Boka, Niu Zhendong

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Recommender systems play a crucial role in connecting individuals with the items they require, as is particularly evident in the rapid growth of online grocery shopping platforms. These systems predominantly rely on user-centered recommendations, where items are suggested based on individual preferences, garnering considerable attention and adoption. However, our focus lies on the item-centered recommendation task within the grocery shopping context. In the reverse next item period recommendation (RNPR) task, we are presented with a specific item and challenged to identify potential users who are likely to consume it in the upcoming period. Despite the ever-expanding inventory of products on online grocery platforms, the cold start item problem persists, posing a substantial hurdle in delivering personalized and accurate recommendations for new or niche grocery items. To address this challenge, we propose a Graph Neural Network (GNN)-based approach. By capitalizing on the inherent relationships among grocery items and leveraging users' historical interactions, our model aims to provide reliable and context-aware recommendations for cold-start items. This integration of GNN technology holds the promise of enhancing recommendation accuracy and catering to users' individual preferences. This research contributes to the advancement of personalized recommendations in the online grocery shopping domain. By harnessing the potential of GNNs and exploring item-centered recommendation strategies, we aim to improve the overall shopping experience and satisfaction of users on these platforms.

Keywords: recommender systems, cold start item recommendations, online grocery shopping platforms, graph neural networks

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Authors: Chiung-Hui Chen

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Diagram and drawing are important ways to communicate and the reproduce of architectural design, Due to the development of information and communication technology, the professional thinking of architecture and interior design are also change rapidly. In development process of design, diagram always play very important role. This study is based on diagram theories, observe and record interaction between man and objects, objects and space, and space and time in a modern nuclear family. Construct a method for diagram to systematically and visualized describe the space plan of a modern nuclear family toward a intelligent design, to assist designer to retrieve information and check/review event pattern of past and present.

Keywords: digital diagram, information model, context aware, data analysis

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Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

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Authors: Robert Gilliland

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In any organization, a potential issue can arise and become a problem when management deviates from the standard norms set in the system development process of an IT system and the policies that pertain to it. In these instances, cybersecurity is a big challenge that organizations have to face in safeguarding the data that they generate and use. When a new idea, task, or process begins, specific standards must be followed, along with the policies and procedures that ensure the safeguard of data in the information system within the company. A good IT Strategy and Policy should have individuals who are in charge of overseeing the design, development, implementation, and auditing of these policies. Auditors are people who check to make sure that the issue conforms with the plan that is in place. Management has the ability through the role of the manager to potentially abuse power is given and to direct specific ideas, events, projects, and outcomes that are contrary to the vision or goals of the company.

Keywords: strategic policy, policy management, new policy, strategic planning

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Clyde Haruzivi, Olusegun Oyebade Ikusika, Thando Conference Mpendulo

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Feed scarcity, increasing demand for animal products due to the growing human population, competition for conventional feed resources for humans and animal production, and ever-increasing prices of these feed resources are major constraints to the livestock industry in Sub-Saharan Africa. As a result, the industry is suffering immensely as the cost of production is high, hence the reduced returns. Most affected are the communal and resource-limited farmers who cannot afford the cost of conventional feed resources to supplement feeds, especially in arid and semi-arid areas where the available feed resources are not adequate for maintenance and production. This has tasked researchers and animal scientists to focus on the potential of non-conventional feed resources (NCFRs). Non-conventional feed resources could fill the gap through reduced competition, cost of feed, increased supply, increased profits, and independency as farmers will be utilizing locally available feed resources. Identifying available non-conventional feed resources is vital as it creates possibilities for novel feed industries and markets and implements methods of using these feedstuffs to improve livestock production and livelihoods in Sub-Saharan Africa. Hence, this research work analyses the progress, challenges, and prospects of some non-conventional feed resources in Sub-Saharan Africa.

Keywords: non-conventional, feed resources, livestock production, food security, Sub-Saharan

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Authors: Hao-Jun Hong, Jung-Tang Huang

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The world is gradually becoming an aging society, and with the lack of laboring forces, this phenomenon is affecting the nation’s economy growth. Although nursing centers are booming in recent years, the lack of medical resources are yet to be resolved, thus creating an innovative wearable medical device could be a vital solution. This research is focused on the design and development of a wearable device which obtains a more precise heart failure measurement than products on the market. The method used by the device is based on the sensor fusion and big data algorithm. From the test result, the modified structure of wearable device can significantly decrease the MA (Motion Artifact) and provide users a more cozy and accurate physical monitor experience.

Keywords: big data, heart failure, motion artifact, sensor fusion, wearable medical device

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Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Mohd Iskandar Illyas Tan, Zuhra Junaida Mohamad Husny, Farawahida Mohd Yusof

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The potentials of Muslim-friendly hospitality services bring huge opportunities to operators (hoteliers, tourist guides, and travel agents), especially among the Muslim countries. In order to provide guidelines that facilitate the operations among these operators, standards and manuals have been developing by the authorities. Among the challenges is the applicability and complexity of the standard to be adopted in the real world. Mobile digital technology can be implemented to overcome those challenges. A prototype has been developed to help operators and authorities to assess their readiness in complying with MS2610:2015. This study analyzes the of mobile digital technology characteristics that are suitable for the user in conducting sharia’ compliant hospitality audit. A focus group study was conducted in the state of Penang, Malaysia that involves operators (hoteliers, tourist guide, and travel agents) as well as agencies (Islamic Tourism Center, Penang Islamic Affairs Department, Malaysian Standard) that involved directly in the implementation of the certification. Both groups were given the 3 weeks to test and provide feedback on the usability of the mobile applications in order to conduct an audit on their readiness towards the Muslim-friendly hospitality services standard developed by the Malaysian Standard. The feedbacks were analyzed and the overall results show that three criteria (ease of use, completeness and fast to complete) show the highest responses among both groups for the mobile application. This study provides the evidence that the mobile application development has huge potentials to be implemented by the Muslim-friendly hospitality services operator and agencies.

Keywords: hospitality, innovation, audit, compliance, mobile application

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Authors: Liu Yi Hui, Chun-Liang Lai, Jhang Yu Cih, He You Jing, Chiu Fan-Yun, Lin Yu Fang

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For universities offering long-term care education, the inclusion of adulting learning and practices in professional courses as appropriate based on holistic design and evaluation could improve talent empowerment by leveraging social capital. Moreover, it could make the courses and materials used in long-term care education responsive to real-life needs. A mixed research method was used in the research design. A quantitative study was also conducted using a questionnaire survey, and the data were analyzed by SPSS 22.0 Chinese version. The qualitative data included students’ learning files (learning reflection notes, course reports, and experience records).

Keywords: adult learning, community empowerment, social capital, mixed research

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Authors: Arazan Jane V., Badiang, Ronesito Jr. R., Clavesillas Cristine Joy H., Belleza Saramie S.

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This study examined the coaching style among the PE Teachers in terms of Autonomy, Supportive style, and Controlling Style. On the other hand, gives opportunities to an athlete to be independent, task-oriented, and acknowledge their feelings and perspective of each individual. A controlling coaching style is also portrayed by the rises and falls over an athlete's training development; when this variance is identified, it might harm training. The selection of the respondents of the study will use a random sample of High School PE teachers of the Division of Davao del Norte with a total of 78 High School PE teachers, which can be broken down into 70 High School PE Teachers for Quantitative data for the survey questionnaire and 8 PE Teachers for Qualitative data (IDI). In the quantitative phase, a set of survey questionnaires will be used to gather data from the participants—the extent of the Implementation Questionnaire. The tool will be a researcher-made questionnaire based on the Coaching Styles of selected High School PE teachers of Davao Del Norte. In the qualitative phase, an interview guide questionnaire will be used. Focus group discussions will be conducted to determine themes and patterns or participants' experiences and insights. The researchers conclude that the degree of coaching style among PE Teachers from the Division of Davao del Norte is high, as seen by the findings of this study, and that coaching style among these teachers is highly noticeable.

Keywords: supportive autonomy style, controlling style, live experiences, exemplified

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Authors: Chih-Hsing Lin, Wen-Ching Chen, Chih-Ting Kuo, Gang-Neng Sung, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

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This paper proposes a cellular-based structure health monitoring device (HMD) for temporary bridge monitoring without the requirement of power line and internet service. The proposed HMD includes sensor node, power module, cellular gateway, and rechargeable batteries. The purpose of HMD focuses on short-term collection of civil infrastructure information. It achieves the features of low cost by using three 1-axis accelerometers with data synchronization problem being solved. Furthermore, instead of using data acquisition system (DAQ) sensed data is transmitted to Host through cellular gateway. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 50.5% cost saving with high sensitivity 2000mv/g. In addition to fit different monitoring environments, the proposed system can be easily replaced and/or extended with different PCB boards, such as communication interfaces and sensors, to adapt to various applications. Therefore, with using the proposed device, the real-time diagnosis system for civil infrastructure damage monitoring can be conducted effectively.

Keywords: cellular-based structural health monitoring, cost-effective 1-axis accelerometers, short-term monitoring, structural engineering

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Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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Authors: Bibek Sapkota, Michael Burton, Krishna Prasad Timsina

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This paper presents a discrete choice experiment (DCE)-based analysis of farmers' preferences for rice variety attributes involving 540 farmers from the Terai region of Nepal clustered into East, Mid, and Western Terai regions. Findings reveal that farmers prioritize grain yield, finer grain types, drought tolerance, and shorter crop duration when selecting rice varieties, with subtle gender-based differences observed. However, breeding programs have predominantly emphasized grain yield and crop duration, possibly neglecting other vital traits. Furthermore, the research reveals a concerning decline in the yield trends of both released and registered rice varieties. Notably, the limited availability of recommended rainfed varieties, despite strong farmer preferences for drought tolerance, underscores the imperative of bridging this gap to ensure food security. This study provides insights into the multifaceted nature of farmer preferences and calls for a more holistic approach to varietal development that aligns with farmers' needs and the evolving challenges of rice farming in the Terai region of Nepal.

Keywords: breeders’ preferences, discrete choice experiment, farmers’ preferences, rice variety attributes

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Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: Seyed Vahid Kamal Alavi

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Italy has experienced a notable quantity and impact of disasters due to natural hazards and technological accidents caused by diverse risk sources on its physical, technological, and human/sociological infrastructures during past decade. This study discusses the frequency and impacts of the most three physical devastating natural hazards in Italy for the period 2000–2013. The approach examines the reliability of a range of open source WebGIS techniques versus a proposed multi-hazard risk management methodology. Spatial and attribute data which include USGS publically available hazard data and thirteen years Munich RE recorded data for Italy with different severities have been processed, visualized in a GIS (Geographic Information System) framework. Comparison of results from the study showed that the multi-hazard risk maps generated using open source techniques do not provide a reliable system to analyze the infrastructures losses in respect to national risk sources while they can be adopted for general international risk management purposes. Additionally, this study establishes the possibility to critically examine and calibrate different integrated techniques in evaluating what better protection measures can be taken in an area.

Keywords: multi-hazard risk mapping, risk management, GIS, Italy

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Authors: Peter Boyes, Sarah Sharples, Paul Tennent, Gary Priestnall, Jeremy Morley

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Significant long-term investment projects can involve complex decisions. These are often described as capital projects, and the factors that contribute to their complexity include budgets, motivating reasons for investment, stakeholder involvement, interdependent projects, and the delivery phases required. The complexity of these projects often requires management groups to be established involving stakeholder representatives; these teams are inherently multidisciplinary. This study uses two university campus capital projects as case studies for this type of management group. Due to the interaction of projects with wider campus infrastructure and users, decisions are made at varying spatial granularity throughout the project lifespan. This spatial-related context brings complexity to the group decisions. Sensemaking is the process used to achieve group situational awareness of a complex situation, enabling the team to arrive at a consensus and make a decision. The purpose of this study is to understand the role of people and data in the complex spatial related long-term decision and sensemaking processes. The paper aims to identify and present issues experienced in practical settings of these types of decision. A series of exploratory semi-structured interviews with members of the two projects elicit an understanding of their operation. From two stages of thematic analysis, inductive and deductive, emergent themes are identified around the group structure, the data usage, and the decision making within these groups. When data were made available to the group, there were commonly issues with the perception of veracity and validity of the data presented; this impacted the ability of group to reach consensus and, therefore, for decisions to be made. Similarly, there were different responses to forecasted or modelled data, shaped by the experience and occupation of the individuals within the multidisciplinary management group. This paper provides an understanding of further support required for team sensemaking and decision making in complex capital projects. The paper also discusses the barriers found to effective decision making in this setting and suggests opportunities to develop decision support systems in this team strategic decision-making process. Recommendations are made for further research into the sensemaking and decision-making process of this complex spatial-related setting.

Keywords: decision making, decisions under uncertainty, real decisions, sensemaking, spatial, team decision making

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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Authors: Morteza Khorrami

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The idea of final triumph of peace and justice on evil force, conflict and global spread of the religious faith, the full deployment of human values, constitute a utopia and the ideal society is discussed by many of religions. Thus, mankind has always been waiting for a savior and has received good tidings for coming of Great Savior at the end of Time. Of course, various persons were introduced as the Promised Saviors by different religions, but all of the religions share in this fact that the future of humanity is very bright and promising and the future will belong to the righteous and justice. In this article which is written with a descriptive and analytic method, the author tries to show the vision of global justice at the end of time. The opinion of various religions such as Judaism, Christianity, Zoroastrianism, Islam and even idolatry about the great savior as well as the justice status in his era in the world will be discussed. Also the viewpoint of Muslims and specially Shiites, which is explained clearly in their scripts, will be depicted. Current human responsibility towards this golden era will be discussed, too. Based on paper findings, religious doctrine promises that a heaven person and sacred character will come as a reformer of the world. In his era, humanity will be saved from tyranny, oppression and inequality, and the earth will be filled with peace, security, justice, and equity. Moreover promoting justice, truth and spreading religion in the world, economic, scientific, political and moral development will be happened.

Keywords: future of humanity, global justice, islam, religions

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Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

Abstract:

In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

Procedia PDF Downloads 114

Authors: Jason Maffia, Maria D’urso, Robert Crupi, Margaret Cartmell

Abstract:

The emotional aspects of traumatic events such as workplace violence are often ignored, causing low productivity, disillusionment, and resentment within an organization. As a result, if workplace violence, particularly in healthcare settings, is not adequately addressed, it will become a phenomenon, undermining the peace and stability among the active communities while also posing a risk to the population's health and well-being. This review intends to identify the risk factors and the implications of workplace violence in healthcare settings and highlight the collaborative efforts needed in sustaining control and prevention measures against workplace violence. It is essential that health care organizations are prepared physically and emotionally for traumatic situations. This study explores the theoretical nature of addressing work-related violence in healthcare settings as well as traumatic stress reactivity and the context within which reactions occur and recovery takes place. Cognitive, social, and organizational influences on response are identified and used to tentatively offer explanations for identifying security risks, development, and implementation of de-escalation teams, CISM programs and training staff in violence prevention are among strategies hospitals are employing to keep workers and patients safe. General conclusion regarding the implications for intervention effectiveness and design are discussed.

Keywords: healthcare settings, stress reactions, traumatic events, workplace violence

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Authors: Mohamed Abdalla Saleem, Hana Ellafi

Abstract:

The study area is located in the eastern part of the Sirt Basin, in the Sarir-Hameimat arm of the basin, south of Amal High. The area covers the northern part of the Hamemat Trough and the Rakb High. All of these tectonic elements are part of the major and common tectonics that were created when the old Sirt Arch collapsed, and most of them are trending NW-SE. This study has been conducted to investigate the subsurface structures and the sedimentology characterization of the area and attempt to define its development tectonically and stratigraphically. About 7600 land gravity measurements, 22500 gridded magnetic data, and petrographic core data from some wells were used to investigate the subsurface structural features both vertically and laterally. A third-order separation of the regional trends from the original Bouguer gravity data has been chosen. The residual gravity map reveals a significant number of high anomalies distributed in the area, separated by a group of thick sediment centers. The reduction to the pole magnetic map also shows nearly the same major trends and anomalies in the area. Applying the further interpretation filters reveals that these high anomalies are sourced from different depth levels; some are deep-rooted, and others are intruded igneous bodies within the sediment layers. The petrographic sedimentology study for some wells in the area confirmed the presence of these igneous bodies and defined their composition as most likely to be gabbro hosted by marine shale layers. Depth investigation of these anomalies by the average depth spectrum shows that the average basement depth is about 7.7 km, while the top of the intrusions is about 2.65 km, and some near-surface magnetic sources are about 1.86 km. The depth values of the magnetic anomalies and their location were estimated specifically using the 3D Euler deconvolution technique. The obtained results suggest that the maximum depth of the sources is about 4938m. The total horizontal gradient of the magnetic data shows that the trends are mostly extending NW-SE, others are NE-SW, and a third group has an N-S extension. This variety in trend direction shows that the area experienced different tectonic regimes throughout its geological history.

Keywords: sirt basin, tectonics, gravity, magnetic

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Authors: Zeyad Abdelmageid, Xianbin Wang

Abstract:

Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

Procedia PDF Downloads 101

Authors: Elnur Abbasov

Abstract:

Energy security and climate change comprise some of the most important concerns facing humankind today and probably in the future if they are not addressed appropriately. In order to stabilize the global climate, there is the need for the world to lessen its use of fossil energy, which requires enhancement of current energy efficiency as well as the development of novel energy sources, such as energy obtained from renewable sources. There is no doubt that the steady transition towards a solar-based economy is likely to result in the development of completely new sectors, behaviours, and jobs that are pro-environmental. Azerbaijan Republic as the largest nation state in the South Caucasus Region has the potential for using and developing the renewable sources of energy in order to support the environmental challenge resolution associated with the climate change, improving the environmental situation in the country. Solar PV comprises one of the direct usages of solar energy. In this paper, sustainable PV usage scenario in residential houses was introduced to reduce negative environmental effects of land use, water consumption, air pollution etc. It was recommended by an author that, PV systems can be part of function and design of residential building components: such as roofs, walls, windows.

Keywords: energy efficiency, environmentally friendly, photovoltaic engineering, sustainable energy usage scenario

Procedia PDF Downloads 231